**Table 5.**

*Original Sample Cell Data Before Normalisation.*



**Table 6.**

*Sample Cell Data After Normalisation.*

In this study, the cell dataset has the attributes of a 3D feature shape, where each patient has a list of cell inputs. This gives it a general 3D shape consisting of (Patients x No of Cells x Cell Parameters x 1). However, as each patient has a different number of cells, this results in a non-uniform dataset shape of (104 patients x χ cells x 144 Cell Parameters x 1)*,* whereχ denotes the patient dependent number of cells in the dataset which ranges from 991 cell inputs to 10720 cell inputs.

Two strategies were evaluated to assess for the best approach of ensuring data conformity. The first method involves keeping the model and parameters constant. A dataset (Complete Cell Data) of "ghost cells" with value 0 were appended to the data to ensure regular shape of (107 x 10720 x 144). Alternatively, a dataset (Random Sampled Cell Data) with cells that were sampled randomly are pegged to the patient with the least number of markers to create a shape of (107 x 991 x 10720) (**Table 7**). Random sampled cell data are also employed for the training and evaluation of the DL model in this study. Following evaluation, no difference in the accuracy between both sets of data were observed. However, it was found that the smaller dataset required a smaller DL network that requires less computational power.

#### **2.2 Feature engineering**

In retrospect, there is no definitive answer when selecting a DL model. However, there is a wide array of models including the basic dense layers or CNN that could be applied. In view of multi-dimensional datasets, CNN is the most versatile in its ability to accommodate multi-dimensionality and has a strong community of research & development from Academics to Corporations. Despite so, CNN may be unsuitable for a non-imaging problem, as most CNN research is based on imaging problems where many of its tools such as max pooling may only work for spatial data. However, if harnessed correctly, CNN offers a highly flexible and advanced architecture that works for many types of data.

To understand the limitations of CNN on non-imaging dataset, it is essential to understand the fundamental difference between a spatial and non-spatial data. In spatial data like an image, a data point in one position is highly related to its surrounding pixels. Whereas for purely numerical data, one data point may not be related to its surrounding data points. It could instead be related to another data that is located at a different position, or more succinctly, is position independent.

#### *2.2.1 Model selection and parameters*

Most CNN tools assume that data points are position dependent. In this study, we looked at the dataset at hand to select a suitable CNN model and to adapt a powerful CNN tool called *Pooling Layer* to the non-spatial data. To select a suitable model that best fits the dataset and problem at hand, one should consider the general dimensions of the dataset which dictates the type of CNN to be used as listed in **Table 8**. For models that involve interaction with the environment, agent-based


**Table 7.**

*Overview of Cell Data Size of Both Approaches.*

*Approaches for Handling Immunopathological and Clinical Data Using Deep Learning… DOI: http://dx.doi.org/10.5772/intechopen.96342*


**Table 8.**

*Overview of Different Data Dimension and Suitable CNN Type.*


#### **Table 9.**

*Overview of Objective Function of Different Problems.*

models may be used. Furthermore, one should consider if the problem is a prediction or classification problem and if additional correlational features are necessary. As for a complex problem, the use of a deeper model may be more appropriate. Nevertheless, using a deeper model could lead to additional problems that require new architecture to overcome. Lastly, the objective of the problem and if it is a scalar prediction or classification problem must also be deduced (**Table 9**).

In this study, 2D CNN is used as the dataset is 3D and image-like. The problem type is a prediction model thus a plain 2D CNN with no agent-based is used. Given that the problem is complex, a Wide Residual Neural Network (WRN) identity mapping may help with modelling its complexity. Lastly, as this is a scalar prediction problem, the model should end with 1 sigmoid function and mean absolute error (MAE) objective function (**Table 9**).

The model selection process must be carefully chosen as it dictates the basis of the model and its result. To illustrate, an early stage proof-of-concept of application of DL on this dataset, a categorical approach was taken, where the patients were split into categories based on their survival rate in years. In designing it this way, the aim was to apply categorisation as the objective function [38]. However, this approach introduced an unintended consequence, a fixed error of the range of each category that could not be rid of regardless of how accurate the model is. This was because of framing a scalar problem as a categorical problem. Even though the resulting model achieved an accuracy of 90% [38], it did not show the in-built error of the prediction that was hidden by the range of each category.

Pooling layers progressively achieve spatial invariance by reducing the resolution of the feature maps, which reduces the number of parameters and computation in the network. This presents one with the ability to create a much deeper network with limited computational cost and overfitting. In a pooling layer, a simple function could be applied. The two conventional functions available are [1] maximization function, which find the maximum value of the region as a representation, and [2] average pooling function that aims to find an average representation of the region, where *p* is the resultant value of the pooling operation (**Figure 3**).

#### **Figure 3.**

*Pooling Layer Computation & Representation- Pooling provides a form of abstraction of our data by downsampling an input representation. There are two common rules for downsampling. Max-Pooling- which picks the input with the largest value. Average-Pooling – which averages out the input in the region. This prevents overfitting by reducing noise in the data, also to reduce computational cost by reducing the number of parameters to learn. In the figure, a 4 x 4 matrix with 16 parameters is down-sampled to a 2 x 2 matrix of 4 parameters.*

However, conventional form of a rectangular pooling layer is not applicable in datasets with only vertical relations. Pooling is mainly done in the context where all data in a 2D array are spatial, where any integers within the array size are related spatially. Such techniques help to compact representations, which could greatly influence the model's performance. With regards to this study, a 2D non-spatial cell dataset, each row has a different unit such as size (mm) or standard deviations. Pooling together variables of different types would result in an invalid representation. Thus, a different form of a pooling layer for non-spatial data could be created instead. Such rectangular pooling seeks to pool between data of the same type to create a representative value of the region, while reducing data noise, and the parameter size of the network.

Furthermore, the operation of the study aims to take a sample of group of nine cell markers of the BC dataset and to obtain the maximum value of each set. A graphical representation of the operation of max rectangular pooling layer (RPL) is shown in **Figure 4**.

*Approaches for Handling Immunopathological and Clinical Data Using Deep Learning… DOI: http://dx.doi.org/10.5772/intechopen.96342*

#### **Figure 4.**

*Max Rectangular Pooling Layer Operation Representation – This shows a sample of how Rectangular Pooling Layer affects our input dataset. With a rectangular pool matrix, we ensure that non-related columns are not pooled together, unlike in a conventional square pooling layer. The transformation is a smaller dataset, with no loss in representation. This reduction in data size, results in faster learning generalisation and computation of the model.*

In another experiment comparing a plain vanilla 2D CNN with RPL of 9 x 1 dimension and a conventional square pooling layer (SPL) of 3 x 3 dimension, it showed both having the same max function (**Table 10**). Comparing the training record of both pooling shapes, the RPL generalised at a much faster rate, of about 500 epochs ahead of SPL to achieve the same MAE. The former also achieved a lower MAE at the end of the training. In the context of a large dataset and DL network, using RPL in a non-spatial 2D dataset could achieve significant reduction in computational time.

#### *2.2.2 Validation and evaluation*

#### *2.2.2.1 Validation*

In the context of medical dataset, one common hampering factor is having a small dataset. This results in a validation process that is not robust enough as there may be an uneven distribution of data across the dataset. Traditional holdout validation is not rigorous enough to negate this effect and may result in an unfair representation of the efficacy of the model. This could be overcome with the use of K-Fold cross validation (K-cv), which is done by splitting the dataset by *k* iteratively holding out the sections of the data and evaluating the model with an average prediction error of all *k* evaluations (**Figure 5**).


**Table 10.** *Result of Rectangular Pooling Layer (RPL) vs. Square Pooling Layer (SQL).*

**Figure 5.**

*K - Fold Cross Validation – By splitting our dataset into k folds, we can evaluate our model across the entire dataset independently. This is especially critical for small datasets (as is the case in medical context).*

K-cv provides a more robust way of validating a model by validating a model with the entire data set. A study by Rodriguez et al. confirmed that K-cv reduces variance in prediction error and recommends implementing a K-cv whenever computationally possible [39]. In this study, the BC dataset was split into four groups of 23 patients and the standard deviation σ of each group is evaluated. It was discovered that the σ across all four groups was 8.43 months, which is a substantial amount in its ability to misrepresent the efficacy of the dataset.

#### *2.2.2.2 Evaluation*

The evaluation step acts as a feedback loop to the development of the CNN model. An iterative approach must be taken to analyse these results from a DL and a medical point of view to understand how further improvements could be made to the CNN model. Firstly, a model was built to evaluate clinical dataset followed by another model to evaluate the cell dataset. In an experiment with 107 patients, an adaptation of Dense ResNet [40] to the clinical data was used. A 2D CNN Wide Residual Network (WRN) [41] was also adapted for the cell data (**Figure 6**). A benchmark was developed on the dataset as a starting point for comparison, as this was a greenfield application. A simple vanilla dense network was used as a starting point to benchmark the results for the clinical dataset containing patients' information such as age, ethnicity, and tumour size. For the immunopathological dataset, we use a benchmark CNN model from the imaging domain as our starting point. MobileNet50 V2 [42] was chosen for the starting benchmark for

#### **Figure 6.**

*Proposed Network Layout – Two independent model first learn representation from their respective dataset, which will have their weights combined together to create a unified model to create a single prediction from both datasets.*

*Approaches for Handling Immunopathological and Clinical Data Using Deep Learning… DOI: http://dx.doi.org/10.5772/intechopen.96342*

immunopathological dataset due to its accuracy, and training speed secondary to its small size (**Table 11**).

A sample k-fold training record as shown in **Figure 7**, shows the overfitting tendencies as the training error is minimised, but the validation error is not minimised. This could be attributed to the unsuitability of the models in the imaging domain without adaptation, which emphasises the importance of using the framework to adapt available CNN models to specific needs. In this study, a more suitable model was developed to clean up, augment, and enhance our dataset following the steps of the framework.

As shown in **Table 12**, the clinical dataset results were augmented from ±15.69 to ±8.24 by the immunopathological data from mIHC/IF with two additional information: number of stromal immune cells and cancer cells of each patients quantitated from the cell dataset. The results were subsequently normalised and iteratively developed to form a new Dense Neural Network based on the ResNet architecture that was better suited to the dataset. With regards to the cell dataset, the results


**Table 11.**

*Benchmark Results for Both Dataset.*

#### **Figure 7.**

*Training History of MobileNet V2 – Benchmarking using a conventional general CNN model. Without adapting the model from imaging domain to our specific use case, we see a tendency to overfit by the divergence decreasing training error (Blue line) and the constant validation error (red line). This shows that there is no generalisation in the model, which serves as a good starting point, and a reminder of the need to adapt CNN to our specific use case.*


#### **Table 12.**

*Result for Both Dataset and Unified Model Using Adapted Models which factored in immunopathological data from mIHC/IF.*


**Table 13.**

*MAE of dataset of Cut-Off Survival Rate.*

were normalised to develop a more suitable CNN using WRN with RPL. Significant improvements in both the cell and clinical dataset were seen, which is appended with immunopathological data. The results were further improved by including a threshold based on the patients' survival rate.

A filter of patients with lower survival rate was experimented where the dataset was split with an arbitrary cut-off of ≥12 months, ≥16 months, and ≥ 20 months. Evaluating using the same unified model, **Table 13** showed the following MAE on 5-fold K-cv for each cut-off*,* where comparison of the combined clinical dataset and cell dataset were made after applying cut-off filter. The clinical dataset augmented with the stroma and tumour count from the cell dataset is also reflected in **Table 13** for reference. The increased in cut-off threshold meant that the model had a smaller dataset. Therefore, an increased in MAE of the model was expected, which was in line with the results shown in **Table 13**.

#### **3. Limitations**

Some limitations of this study should be noted. Firstly, this study uses a small dataset, which meant that the results could be less robust and of a lower confidence level. Although, this was minimised with the use of k-fold cross validation, more advanced techniques such as semi-supervised learning could be explored to augment the dataset. Secondly, there is currently no medical evidence to support using a cut-off to segregate patients as a valid approach. The approach used in this study is solely from a DL standpoint and therefore requires more medical based research to prove its validity. Moreover, given the novelty of the proposed framework, there is currently limited literature to support its application in other medical domains.

#### **4. Conclusions**

The adaptation of DL technology with the use of mIHC in the analysis of complex data is in the upcoming alternative approach of analysis in the field of immunopatholgy. However, given its novelty, further studies are needed to optimised the framework to enable application in varies medical field. Nevertheless, the framework proposed in this chapter serves to provide a starting foundation for application in clinical studies.

#### **Author contributions**

Conceptualization and design, Y. Chua and J. Yeong; literature review, S. Goh and Y. Chua; writing-original draft, S. Goh and Y. Chua; intellectual input and

*Approaches for Handling Immunopathological and Clinical Data Using Deep Learning… DOI: http://dx.doi.org/10.5772/intechopen.96342*

critical review, J. Lee, J. Yeong and Y. Cai.; writing-review and final editing, S. Goh and J. Lee. All authors have read and agreed to the published version of the manuscript.

### **Author details**

Siting Goh1 , Yueda Chua4 , Justina Lee3 , Joe Yeong1,2,3\* and Yiyu Cai4

1 Division of Pathology, Singapore General Hospital, Singapore

2 Duke-NUS Medical School, Singapore

3 Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A\*STAR), Singapore

4 Nanyang Technological University (NTU), Singapore

\*Address all correspondence to: yeongps@imcb.a-star.edu.sg

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section 4 Liquid Biopsy

#### **Chapter 7**

## Liquid Biopsy: A New Diagnostic Strategy and Not Only for Lung Cancer?

*Stefania Scarpino and Umberto Malapelle*

#### **Abstract**

Targeted molecular therapies have significantly improved the therapeutic management of advanced lung cancer. The possibility of detecting lung cancer at an early stage is surely an important event in order to improve patient survival. Liquid biopsy has recently demonstrated its clinical utility in advanced non-small cell lung cancer (NSCLC) as a possible alternative to tissue biopsy for non-invasive evaluation of specific genomic alterations, thus providing prognostic and predictive information when the tissue is difficult to find or the material is not sufficient for the numerous investigations to be carried out. Several biosources from liquid biopsy, including free circulating tumor DNA (ctDNA) and RNA (ctRNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs), have been extensively studied for their potential role in the diagnosis of lung cancer. This chapter proposes an overview of the circulating biomarkers assessed for the detention and monitoring of disease evolution with a particular focus on cell-free DNA, on the techniques developed to perform the evaluation and on the results of the most recent studies. The text will analyze in greater depth the liquid biopsy applied to the clinical practice of the management of NSCLC.

**Keywords:** liquid biopsy, NSCLC, cfDNA, ctDNA, biomarkers

#### **1. Introduction**

In the era of precision medicine, the management of cancer patients has dramatically changed. An increasing number of prognostic and predictive biomarkers are being implemented in order to ensure the best treatment option for advanced stage cancer patients and pathologists have learned to refine their reports [1]. To date, the analysis epidermal growth factor receptor (EGFR) gene mutations, anaplastic lymphoma kinase (ALK), and ROS 1 proto-oncogene (ROS1) rearrangements and schedules the state of death-ligand 1 (PD-L1) is capital for clinical decision making [2, 3]. In addition to these biomarkers, other activating mutations harbored by other clinically relevant genes are under investigation in clinical trials. However, despite the rapid development of this field in terms of discovered predictive biomarkers and platforms, tissue still remains an issue. To date, tissue samples represent the "gold standard" starting material to obtain nucleic acids (DNA and RNA) for molecular purposes and the only matherial available for morphological diagnosis and molecular analisys is often represented by paucicellular samples

(cytological speciments or small tissue histological biopsies) [4]. However, a not negligible percentage, about 30%, of advanced stage NSCLC patients, cannot be tested because tissue sample is not adequate both for anatomo pathological revision and for molecular analysis [5]. In addition, even in high expertise centers, the percentage of inadequate molecular results, in particular when small tissue samples are adopted, may be significant [6]. In this setting, and in order to avoid to leave patients behind, liquid biopsy represents a valid option as a rapid, noninvasive and accurate clinical option. Several biosources from liquid biopsy, including free circulating DNA (cfDNA) and RNA (cfRNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs), can be isolated. While each of these modalities has the potential to provide new diagnostic information and their exploration is highly encouraged, ctDNA certainly represents the most mature example of the survey on liquid biopsy in clinical practice for lung cancer patients. Therefore, this chapter will mainly focus on the clinical value of the free circulating tumor DNA (ctDNA), a small fraction of cfDNA extracted from plasma samples and we will review the available data that suggest the role of liquid biopsy in the management of NSCLC.

To date, Food and Drug Administration (FDA) has approved the analysis of ctDNA in two different NSCLC patients settings: naïve advanced stage NSCLC (basal setting), when tissue is not available or inadequate for molecular analysis of the Epidermal Growth Factor Receptor (EGFR) in order to select patients for first or second generation EGFR tyrosine kinase inhibitor (TKI) administration; acquisition of somatic resistance mechanism after first or second EGFR TKI administration (resistance setting), in order to detect the EGFR exon 20 p.T790M resistance point mutation and select patients for third generation EGFR TKIs [7].

Here we will report the potential of liquid biopsy to help manage NSCLC throughout all stages: cancer screening, minimal residual disease detection to guide adjuvant treatment, early detection of relapse, systemic treatment initiation and monitoring of response (targeted or immune therapy), and resistance genotyping. Moreover, we will also carefully analyze each step of the pre-analytical management of liquid biopsy specimen, (sample collection, ctDNA extraction, and molecular analysis) and the advantages and disadvantages found in the use of liquid biopsy respect the adoption of gold standard tissue sample in the context of clinical practice.

#### **2. Liquid biopsy: definition**

The term liquid biopsy refers to the use of biological fluids as a surrogate for neoplastic tissue to obtain information useful for diagnostic, prognostic purposes or to predict the response to therapy with specific anticancer drugs. In the biological fluids (blood, urine, saliva, cerebrospinal fluid, pleural effusions, ascites or cytology specimen-derived supernatant [8–10] of tumor patients are contained cell-free DNA (cfDNA), circulating tumor DNA (ctDNA)circulating tumor cells, circulating RNA, microRNAs (miRNA), platelets and exosomes, which can be a valuable source of information about molecular assessment of cancer. Analysis of ctDNA contained in the free circulating DNA (cfDNA) that can be isolated from peripheral blood, represents to date the main liquid biopsy approach employed in clinical practice. In healthy patients, cfDNA is released in low quantity from normal cells during cellular turnover and is represented by small DNA fragments (150–200 base pairs). On the otherwise cancer patients show an increased levels of cfDNA [11, 12] with a consistent release of ctDNA generally represented, by more small fragment, with sizes ranging from 90 to 150 base pairs [13]. The amount of ctDNA is variable

*Liquid Biopsy: A New Diagnostic Strategy and Not Only for Lung Cancer? DOI: http://dx.doi.org/10.5772/intechopen.94838*

in cancer patients, ranging from less than 0.1% to more than 90% [11, 12]. The cf./ ctDNA ratio can depends on the time of sample collection and clinical condition of the patient and is influenced by total tumor burden, location and extent of metastases, proliferation rate, apoptotic potential and genome instability [14]. ctDNA can enter the bloodstream through two different mechanisms: by a passive mechanism derived from apoptosis and necrosis or by an active mechanism derived from a spontaneous release of DNA fragment from primary tumor tissues or from circulating tumor cells or tumor-associated macrophages [15, 16].

#### **2.1 Liquid biopsy versus traditional biopsy**

The new College of American Pathologists (CAP), International Association for the Study of Lung Cancer (IASLC)/Association for Molecular Pathology (AMP) guideline for molecular testing of patients with NSCLC, although did not recommend the performance of molecular analysis when tissue is available, they strongly suggest liquid biopsy in those cases where tissue sample is not adequate to perform molecular analysis [17] In fact, a significant subgroup of patients cannot undergo a biopsy or rebiopsy for several reasons such as unsuitable clinical conditions or an unfavorable tumor site such as bone or central nervous system or multiple small pulmonary nodules that are not safely amenable to biopsy [18].

Let us see what are the advantages and disadvantages of using liquid biopsy. Liquid biopsy shows several advantages over that traditional biopsy:


The International Association for the Study of Lung Cancer (IASLC) established in a statement paper the guideline when considering to adopt liquid biopsy samples for molecular analysis [7].

#### **3. What are the methods for ctDNA analysis? Pre-analytical consideration: from blood collection to ctDNA**

CtDNA can be extracted from various biological fluids. However, the procedures more standardized in clinical practice concern isolation of ctDNA from peripheral blood. ctDNA can be isolated from serum or plasma. Several studies compare cfDNA levels in plasma and serum samples and have shown significantly higher cfDNA concentrations in serum [25, 26] but shown that the use of plasma is preferable to serum. In the latter, in fact, the coagulation process causes the release of genomic DNA deriving from leukocytes and leads to a contamination of germline DNA that causes a ctDNA dilution.

Isolation and enrichment of ctDNA is a great challenge given the high degree of cfDNA fragmentation and its low concentration in the bloodstream to the extent of a few ng/ml, of which the ctDNA is alone a fraction [15]. Several factors affect the quality and quantity of ctDNA including: the burden of disease, the rate of release of the ctDNA in the bloodstream and the levels of DNA released by non- transformed cells. Therefore, for these reasons the pre-analytical phase must be carefully checked. to achieve superior quality results.

#### **3.1 Sample collection**

A first problem that can affect the quality of the sample is constituted from hemolysis that can occur during phlebotomy. It is necessary, therefore, that blood sampling is carried out by highly qualified personnel.

The sample can be collected in standard EDTA tubes or using tubes containing special fixatives, capable of stabilizing the blood and the cfDNA for several days. If the sampling is carried out using standard tubes, one important factor must be taken into account. cfDNA has a short half-life, estimated at around 2.5 hours therefore tubes can be stored before plasma isolation for a maximum of 3 hours at room temperature (**Figure 1**). Several studies have shown that after three hours of sampling, the wild-type cfDNA concentration could increase due to lysis of hematological cells thus reduce the relative percentage of tumor-specific ctDNA [27]. The storage of blood at a temperature of 4°C it does not prevent leukocyte lysis. Operators dealing with blood collection, handling, and eventual shipping should be cognizant of these time constraints. Blood should never be frozen before plasma extraction.

#### **3.2 Extraction, quantification and storage of cfDNA**

There are many methods for extracting cfDNA, which include both the use of commercial kits and protocols developed by laboratories.

*Liquid Biopsy: A New Diagnostic Strategy and Not Only for Lung Cancer? DOI: http://dx.doi.org/10.5772/intechopen.94838*

#### **Figure 1.**

*Incidence of time withdrawn in the managment of liquid biopsy specimen. The figure shows the comparison between electhropherograms performed by nanofluidic platform Tapestation 4200, (Agilent, Santa Clara, California, USA) on a sample immediately and after 1 h processed to isolate cfDNA respect time of withdrawn. In the left profile, ctDNA peak of 180–200 bp is inspected; on the right profile the peak is not detected.*

The extraction method must be very reliable and must generate as much possible DNA of the sample under examination. For the extraction and purification of cfDNA from plasma they are now available various commercial kits dedicated to this specific use. These kits are generally based on the use of columns equipped with silica membranes in association with a vacuum pump, or on the use of magnetic balls for the capture of nucleic acids.

Once extracted, the cfDNA must undergo quantification in order to optimize the amplification process and to know if the subsequent molecular analyzes may be possible starting from the cfDNA extract [28].

Optimal storage of cfDNA is very important as it allows its use also a time to carry out further molecular investigations, The process takes adequate equipment, including −20° C/ -80° C freezers, devices graphic temperature control, acoustic alarm systems, quality controls of the biological material stored [28].

#### **4. Analytical methods for detecting ctDNA**

Until recently, the available technology was not sensitive enough to detect ctDNA and use it in a meaningful way but in recent years highly sensitive bloodbased assays have been developed to test cfDNA at very low concentrations for most genomic abnormalities and advances in pre-analytical processes and purification methods have enabled the capture, amplification and sequencing of ctDNA to be successful. A good molecular ctDNA test should retain an acceptable concordance to molecular testing in the tumor tissue. However, even with the increased sensitivity, a negative result from ctDNA analisys is not sufficient to exclude the potential existence of a driver alteration; therefore, in these circumstances tissue analysis should be performed.

The methods currently used to detect or measure ctDNA are numerous and can be divided into two categories: polymerase chain reaction (PCR)-based techniques and next-generation sequencing (NGS) technologies.

#### **4.1 Polymerase chain reaction (PCR)-based techniques**

Within the PCR-based techniques are included real time PCR, digital PCR (dPCR), droplet digital PCR (ddPCR), peptide nucleid acid (PNA) clamp-based PCR assay (Taqman assay), beads, emulsions, amplification and magnetics

(BEAMing). PCR-based approaches, can detect mutations in cfDNA at allele frequencies of 0.01% or lower. Although there are numerous platforms currently for ctDNA evaluation, the gold standards in pcr-based technologies are basically quantitative PCR (qPCR) and digital PCR.

#### *4.1.1 PCR real time*

PCR-based tests generally have faster response times and are less expensive, but can typically evaluate only one or a few specific mutations at a time. The analysis of point mutations or small insertions/deletions on ctDNA it can be often conducted through the use of Real Time technologies PCR, often modified to increase the sensitivity of the test. There are commercially available ctDNA kits based on different amplification technology (e.g. Refractory Mutation System ARMS/SCORPION) which detect mutations against EGFR exons 19, 20 and 21. These kits allow the co-amplification of one or more mutated alleles and of an endogenous control gene. The analysis with these kits allows to detect low percentages of mutated allele in the presence of high amounts of wild-type genomic DNA and can reach an even lower limit of detection (LOD) 0.5%. The main limitation related to the adoption of this approach is related to the annealing step where probes may not able to target corresponding genomic region (**Figure 2**).

#### *4.1.2 Digital PCR (dPCR)*

Digital PCR (dPCR) is a next-generation evolution of PCR of which there are two technological platforms: "digital droplet PCR - ddPCR" and "BEAMing dPCR" (Beam, Emulsion, Amplification, Magnetics).

Both methods, utilize emulsion technology to quantify the amount of mutant cfDNA in patient plasma and are based on the limiting dilution of DNA with a distribution of the sample in thousands of homogeneous "droplets" in an oil–water


#### **Figure 2.**

*Visual inspection of p.T790M EGFR acquired resistance mutations by using NGS system. The figure shows the manual count of aligned reads generated by Golden helix genome browse 1.1.2 (Golden helix genome browse Inc). In the red box is reported a polymorphism in the genomic region near p.T790M base change (blue box). Although the presence of this polymorphic alteration, NGS platform is able to p.T790M resistance mutation while RT-qPCR based approaches report a false negative result.*

#### *Liquid Biopsy: A New Diagnostic Strategy and Not Only for Lung Cancer? DOI: http://dx.doi.org/10.5772/intechopen.94838*

emulsion. These characteristics are of great importance in the context of the analysis of ctDNA, where it is necessary to search for and amplify rare molecules of tumor DNA in the presence of a large excess of wildtype germline DNA.

In fact, the breakdown of the sample into droplets has the function of reduce competition between mutated tumor DNA and wild-type DNA increasing the specificity and sensitivity of the analysis.

Both of these experimental approach is very useful for the identification of rare variants since only a small concentration of template is required for the analysis.

The sensibility and the specificity of the tests with ddPCR and BEAMing dPCR are, respectively 0.1% and 0.01%.

Several studies have compared multiple platforms for detecting EGFR mutations in plasma ctDNA. In one study, two non-digital platforms (cobas®EGFR mutation test and therascreen EGFR amplification refractory mutation system test) and two digital platforms (Droplet Digital PCR and BEAMing digital PCR) were compared in their ability to identify sensitizing mutations and the results support the potential use of both platforms in a clinical development program [29].

The limit of these technologies is that of their limited ability to detect complex genomic alterations and perform multiplex testing.

#### **4.2 NGS in liquid biopsy**

In contrast to PCR-based methods, NGS is a fascinating technology able to analyze different biomarkers for different patients, simultaneously [30] and detect rare and previously uncharacterized alterations. NGS are capable of detection of mutations, indels, copy number variations and genomic rearrangements such as oncogenic fusions. Another advantage of an NGS approach is the possibility to quantify the amount of DNA that brings a particular alteration.

This technology, based on massive and parallel sequencing, ensures a high sequencing throughput, by generating from hundreds of thousands to millions of sequences (reads) [30]. To overcome the limitations of ctDNA, next generation sequencing (NGS) may be a viable option. The use of NGS for liquid biopsy requires changes to the protocols normally used for blood and tissue analysis. Operational protocols dedicated to liquid biopsy.

Different NGS platforms are commercially available and validated on liquid biopsy samples [31]. Among these, Illumina (San Diego, California) platform adopts a sequencing-by-synthesis chemistry able to identify DNA bases, while introducing them into a nucleic acid strand, by adopting a system of fluorescently labeled nucleotides; Ion Torrent (ThermoFisher Scientifics, Waltham, Massachusetts) platform adopts a sequencing-by-synthesis chemistry able to identify DNA bases, while introducing them into a nucleic acid strand, by adopting a semiconductor system useful to measure a change in pH due to the release of an H+ ion [32]. Important differences exist between these various platforms with respect to the number of genomic alterations included in a single panel, the ability to multiplex these assays, the turnaround time of the test, and its ability to detect complex genomic alterations.

Different NGS gene panels have been adopted for ctDNA analysis and numerous studies have been carried out in recent years to validate concordance to molecular testing in the tumor tissue. A higher sensitivity and specificity was obtained by Reckampet al by using a short footprint mutation enrichment NGS assay to analyze ctDNA samples extracted from plasma of NSCLC patients [8]. On the overall, taking into account the results obtained on matched tissue samples, a sensitivity of 93, 100, and 87% for EGFR exon 20 p.T790M, EGFR exon 21 p.L858R, and EGFR exon 19 deletions, was reached. The specificity, for the same mutations was 94, 100, and 96% [8]. In the experience of Paweletz et al. a high sensitivity (86% and 79%) and specificity (100% and 100%) was obtained by using a targeted NGS approach on NSCLC patients for EGFR and KRAS mutations [33]. Another valid approach is represented by the use of narrow gene panels. In the experience of the Predictive Molecular Pathology Laboratory at the University of Naples Federico II a custom, narrow NGS gene panel (named SiRe®), that cover 568 clinical relevant mutations in six genes (EGFR, KRAS, BRAF, NRAS, KIT and PDGFRA), was routinely employed for both tissue and liquid biopsy testing [34, 35]. In the validation study on different tumor types, a sensitivity of 90.5% and a specificity of 100% was reached by comparing results obtained on ctDNA extracted from serum and plasma with those obtained on matched tissue samples. In addition, this panel may be useful to detect EGFR and KRAS actionable mutations in basal setting NSCLC patients [35].

Ultra-sensitive NGS techniques dedicated to analysis have been developed of the ctDNA. The characterizing element of Cancer custom profiling deep sequencing (Capp-Seq), its is a selector that identifies different classes of somatic mutations with sensitivity and specificity greater than 90%. Similar results in terms of sensitivity and specificity were achieved with Tagged-amplicon deep sequencing (Tam-Seq) and Safe-Sequencing techniques System (Safe-SeqS).

What was once a limitation of ngs technology, the turnaround time is now acceptable for clinical management — approximately 13 days — and costs have been significantly reduced [36]. Also the difficulty of analyzing the numerous information deriving from the multigene panels has also been overcome since a variety of publically available and proprietary bioinformatics tools have been developed to assist in these calculations.

#### **4.3 New emerging technologies to the study of liquid biopsy**

Several studies today aim to overcome the current limits of sensitivity for liquid biopsy, to support extensive research and clinics applications. Although for the evaluation of the ctDNA the gold standards are basically quantitative PCR (qPCR), digital PCR and NGS to these have been added many technologies such as whole genome sequencing (WGS) [37], Rare Ep iAlleles by Melt qPCR (DREAMing) [38] and bidirectional pyrophosphorolysis activated polymerization (bi-PAP).

Moreover, of great interest in biomedicine applied to the study of liquid biopsy are the PCR-free methods [39]. Several articles have been published dealing with PCR-free methods for the detection of point mutations [40]. These methods applied alternative isothermal-amplification methods whitch do not require thermal cycling to avoid heating and cooling steps. About the smetods include those based on nucleic acid sequences polymerization (NASBA), loop-mediated amplification (LAMP, helicase-dependent amplification (HAD), rolling - circle amplification (RCA), recombinase-polymerase amplification (RPA) and multi-displacement amplification (MDA), isothermal displacement of the circular filament polymerization (ICSPD).

Among these methods of sure interest is surface plasmon resonance imaging (SPR-I). This tecnology are able to detected Attomolar concentrations of target genomic DNA, demonstrating the ultra-sensitivity of the new method [39].

Thanks to these new ultra-sensitive technologies, several authors are pushing towards new horizons. In some studies differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for noninvasive genomic analysis of cancer. Mouliere et al. [13] argue that cfDNA fragment size analysis improved the discrimination between samples from patients with cancer and those from healthy individuals.

All these technologies are now supported by different platforms and have already been approved for clinical use [41]. However, the lack of standardization limit the clinical implementation for most of these methodologies.

### **5. Liquid biopsy in clinical practice**

There are two main scenarios in which the liquid biopsy might confer an advantage to NSCLC advanced patients:at initial molecular profiling and at progression during targeted therapy. To date, Food and Drug Administration (FDA) has approved the analysis of ctDNA extracted from plasma samples in two different patient settings: in treatment naïve advanced stage NSCLC (basal setting), when tissue is not available or inadequate for molecular purposes, for the Epidermal Growth Factor Receptor (EGFR) gene assessment in order to select patients for first or second generation EGFR tyrosine kinase inhibitor (TKI) treatments and in advanced stage NSCLC resistant to a first or second EGFR TKI (resistance setting), in order to detect the EGFR exon 20 p.T790M resistance point mutation and select patients for third generation EGFR TKIs [7].

#### **5.1 Tumor molecular profiling of naïve patients (basal setting)**

Liquid biopsy should be taken into consideration at the time of initial diagnosis in all patients who need tumor molecular profiling, but:


In clinical practice, liquid biopsy is currently mainly used for analysis of mutational status of the epidermal growth factor receptor (EGFR) in advanced NSCLC patients. Several studies and meta-analyzes [42, 43] have evaluated the diagnostic accuracy of ctDNA analysis for the identification of the most frequent activating mutations of the EGFR gene (deletions of exon 19, L858R of exon 21) in patients naïve with advanced NSCLC proving a good specificity greater than 90%. Sensitivity results instead be lower, with fluctuations between 50% and 80% depending on the technology used. On the basis of these evidences the evaluation of the mutational status of the EGFR gene on liquid biopsy is currently recommended as a possible alternative to analysis on tumor tissue.

A positive finding of an actionable mutation in ctDNA, if using a validated assay, is sufficient to initiate targeted treatment. However, a negative result it cannot be trusted and it should be followed up with a secondary test or conventional tumor testing. A negative result can be negative for several factors. The amounts

#### *Pathology - From Classics to Innovations*

of DNA into peripheral circulation of patients with indolent slow-growing tumors is often insufficient for detection and these patient may be at more risk of a false negative compared to patients with a more disseminated cancer. Therefore, it is imperative that operators are aware of the possibility of a false negative result from the liquid biopsy.

For this reason the liquid biopsy at diagnosis is far from being able to replace the traditional analysis of the tissue which therefore remains the standard goal in patient's diagnosis.

#### *5.1.1 Other oncogenic drivers in NSCLC have been detected in ctDNA isolated from plasma*

In addition to EGFR mutations a wide range of potentially actionable alterations are of particular interest clinically and are detectable in patients with NSCLC, including ROS1, fibroblast growth factor receptor 3 (FGFR3), and neurotrophic receptor tyrosine kinase (NTRK) rearrangements and ALK, MEK, AKT, BRAF, HER2, MEK1/2, NRAS, KRAS mutations and MET receptor tyrosine kinase mutations and amplification. All of these abnormalities have been detected in ctDNA isolated from plasma and could therefore be used for screening naive patients.

As regards the study of rearrangements, which is carried out at the ctRNA level, some technical difficulties may arise due to the low stability of the circulating plasma RNA which easily undergoes degradation. The most commonly used techniques to identified ALK at the time of diagnosis, are qPCR and digital PCR or next-generation sequencing (NGS) approaches [44, 45].

The sensitivity of the techniques for studying this alteration is less high than those that can normally be used on the tissue (e.g., immunohistochemistry or Fluorescent in situ Hybridization (FISH).

#### *5.1.2 The liquid biopsy in other fluids*

Although plasma is the most widely used fluid sample for liquid biopsy, other samples are available such as urine, sputum, cerebrospinal fluid or pleural effusion as a source of ctDNA.

Sputum is an important source of nucleic acids and different studies investigated EGFR status in NSCLC patients. Wu et al. [46] identified a high concordance between sputum and tissue samples (74%). In a recent study it has been identified the potential role as a diagnostic biomarker for NSCLC of P16INK4 gene promoter methylation in both bronchoalveolar lavage (BAL) and sputum [47]. A recent study showed that sensitivity of EGFR mutation detection in the urine is comparable to that found in the plasma of the same patient [48] and concordance of mutations in the driver gene may increase when compared to plasma alone to combination of plasma, urine and sputum [49].

The ability to use ctDNA obtained from cerebrospinal fluid (CSF) to study genetic alterations and monitor response to treatment is very important as brain metastases are difficult to reach.

#### **5.2 Monitoring therapeutic resistance**

Resistance inevitably arises in almost all patients undergoing treatment for metastatic disease [50]. The ability to detect the presence of multiple resistance mechanisms is critical. Acquired resistance to therapy is often driven by presence of one or more tumor subclones that harbor resistance alterations [51]. These

#### *Liquid Biopsy: A New Diagnostic Strategy and Not Only for Lung Cancer? DOI: http://dx.doi.org/10.5772/intechopen.94838*

subclones drive disease progression and may reside in the same tumor lesion or in different metastatic lesions [52]. Therefore, a standard tumor biopsy of a single lesion at the time of disease progression may fail to capture resistance mechanisms present in tumor cells outside of the biopsied region [53]. This is where the liquid biopsy comes into play overcomes the limit of tumor heterogeneity.

p.T790M gatekeeper resistance identification in liquid biopsy is currently employed as a first diagnostic approach in all patients with EGFR-positive advanced NSCLC in progression after EGFR-TKI treatment. However, due to the risk of "false negatives" associated with such method, all patients in whom the mutational analysis on ctDNA results "negative" and even the initial sensitizing mutation is not detected must be subjected to test tumor tissue taken by re-biopsy, in order to define the best therapeutic strategy. However before proceeding with the tissue biopsy, it would be advisable to repeat liquid biopsy. In the absence of such a mutation, the test should be considered non-informative as the sample contains no sufficient ctDNA. In this regard, multiple studies, and a recent meta-analysis, have clearly highlighted as the site of metastases cancer significantly affects the diagnostic accuracy of the mutation analysis of the EGFR gene performed on ctDNA. The sensitivity of that method in determining both activating and p.T790M mutation can in fact vary from 80% in presence of extra-thoracic metastases at 50% in the presence of exclusively intra-thoracic localizations [28]. In order to increase the chances of success of the liquid biopsy, the test should be performed at the time of obvious progression of disease, when the probability that the tumor DNA is released into the circulation is higher.

Liquid biopsy is also utilized to detected additional coexisting resistance alterations, such as MET amplification that predicts decreased benefit from subsequent therapy with third-generation EGFR inhibitors and EGFR p.C797S mutation following therapy with the third-generation EGFR inhibitor osimertinib [52].

#### **6. How should the results of liquid biopsy be reported? The reporting**

European Society of Pathology Task Force on Quality Assurance in Molecular Pathology and the Royal College of Pathologists published standards of molecular diagnostics reporting [54].

Reporting is an integral part of the diagnostic procedure and should contain the following information: patient identifiers, specimen type, assay methodology and the platform used including sensitivity and limit of detection, date of collection of the material used for the analysis and date of arrival of the sample in the laboratory that performs the analysis, methods of conservation of the sample investigated mutations, results of the test, data interpretation and an overall evaluation of the analysis specifying whether a detected alteration is clinically relevant.

The report must be completed on a predetermined form, dated and signed by the service manager.

#### **7. Emerging application and future direction of liquid biopsy**

Liquid biopsy is a rapidly growing field in oncology and ctDNA analysis is considered to be very promising as a biomarker for early stage detection, identification and monitoring of minimal residual disease (MRD), immuno-oncology, assessment of treatment response, and monitoring tumor evolution. Currently, several trials are ongoing in this field.

#### **7.1 Potential applications in early stage NSCLC: screening**

Detection of lung cancer at an earlier stage of disease, potentially susceptible of curative resection, can be critical to improve patients survival. Current screening and diagnostic tests, such as computed tomography (CT) scans and cytological/histological analyzes could be supplemented by the specificity of cfDNA [55]. The evaluation of genomic anomalies, including specific mutations, in cfDNA could offer a promising, non-invasive approach for the early diagnosis of lung cancer, considering the high specificity of these related tumors alterations. A limitation is due to the low frequency of some mutations and the fact that the mutant cfDNA can be obscured by an excess of background wild-type DNA. However, highly sensitive approaches have been developed to analyze low-level mutants cfDNA, including NGS-based options.

Many studies have focused on assessing the quantities of cfDNA. In a study carried out on smoking patients it was shown that the concentration in cfDNA, of the human telomerase reverse transcription (hTERT) gene was eight times higher in lung cancer patients than in controls and correlate with a strong risk factor for the development of lung cancer [56]. In other studies it has been shown that a greater amount of cfDNA during surgery correlates with a worse prognosis at 5 years survival, selecting a more aggressive disease [57]. Using a very sensitive quantitative test [57] it was demonstrated the possibility of discriminate between healthy subjects and NSCLC patients by measuring the quantities of cfDNA [58, 59]. cfDNA were significantly higher in NSCLC patients compared to healthy controls.

Methylation is an early and frequent epigenetic alteration that can be detected in cfDNA, including in plasma [60, 61]. Epigenetic modifications, regulate the expression of a large number of genes involved in malignant transformation and carcinogenesis. DNA alterations in methylation occur early in carcinogenesis and are remarkably more stable than other potentials diagnostic biomarkers.

Several studies have evaluated the methylation levels of single or panels of tumor suppressor genes in plasma or serum from lung cancer patients. Several genes have been found to be differentially methylated in cfDNA between patients with lung cancer and controls including MGMT, p16, RASSF1A, DAPK, RAR-β, DCLK1, SHOX2 and septin9 [62, 63]. In a recent study, a methylation panel of six genes showed a sensitivity of 72% for the detection of stage Ia NSCLC [64].

However though, methylation changes can also occur in the DNA of peritumor normal tissue which can therefore interfere with the analysis of tumor DNA generating a false positive result [65]. Considering together the fact that ctDNA is absent or very low in the early stages, the possibility to detect mutations in cfDNA derived from non tumor cells and the lack of standardized methods and large validation studies the analysis of ctDNA has not been introduced in the clinic screening yet.

#### **7.2 Identification and monitoring residual disease**

Measurement of residual disease after primary tumor treatment is an area of active investigation.

Efficient methods of identifying MRD in patients treated with surgery or adjuvant chemotherapy are currently lacking. Mutation monitoring can be a significant predictor of early relapses and MRD. Several studies have focused on detecting these mutations in ctDNA as an early indicator of relapse and a potential marker of residual disease.

Monitoring of ctDNA for residual disease has been used in several studies in lung cancer. Presence of ctDNA after local treatment was highly predictive of disease recurrence in a small cohort of lung cancer patients with stage I-III lung undergoing local treatment with radiation, surgery, or both [66].

A prospective trial is ongoing to investigate the ability of ctDNA mutations and methylation monitoring to detect MRD after surgery for stage Ia–III NSCLC [67].

The limit of the use of ctDNA in detect MRD in clinical practice beyond is the lack of circulating tumor specific alterations.

#### **7.3 Monitoring treatment response and cancer progression**

CtDNA analysis could be a way to monitor cancer status in real time. Methods for monitoring treatment response and changes in tumor burden with cfDNA involve the identification of genomic alterations specific to an individual patient's tumor and the relationship between changes in ctDNA levels, that can be monitored in real time during therapy (**Figure 3**).

In one study, long-term monitoring of a patient with NSCLC for analysis of EGFR mutations (p.L858R and p.T790M) using ctDNA isolated from serum and plasma a close correlation with the onset of metastasis was identified. In another study carried out with NGS technology on plasma-derived ctDNA from 168 patients with different types of cancer, the molecular alterations identified correlated to which of tissue [68].

ctDNA levels drop dramatically after one to two weeks in patients responding to treatment [69, 70]. Some authors suggested that a rise in ctDNA levels may precede radiographic progression.

Data obtained by several studies, conducted on different tumor type [71] using very sensitive new technologies involving multiplexed mutation-specific PCR and NGS suggest that the additionof ctDNA monitoring into clinical care could be a valuable tool to more accurately predict patient response and detect progression.

#### **7.4 Liquid biopsy and immuno-oncology**

Cancer immunotherapy is certainly the most profound innovation recorded in recent years in the fight against cancer. The recent use of anti-programmed death

#### **Figure 3.**

*Molecular follow up of a NSCLC patient. The figure shows the behavior of inspected molecular alterations [exon 19 deletion (blue line) and p.T790M point mutation (red line)] analyzed by serial liquid biopsy specimens in relation to the clinical outcome of a NSCLC patient.*

receptor-1 (PD-1) /PD-1 ligand 1 immune checkpoint inhibitors (IC) in clinical trials indicates their efficacy in immune therapy against cancer.

These immune checkpoint inhibitors have been shown to have an effective therapeutic response, particularly in tumors with high tumor mutation burden (TMB) [72]. If the ctDNA can be used to guide and monitor immune therapy is just beginning to be evaluated [73].

In several studies, tumor mutation burden (TMB) can be estimated from ctDNA with good concordance with tissue results [74, 75]. Moreover, the identification of a high TMB in the ctDNA correlates closely with the two inhibitors of programmed cell death (PD)1 and its ligand (PD-L1) [74].

In a recent study it was shown that ctDNA TMB it has a closer correlation with metastatic tissue than primary tumor. Furthermore, this concordance is greater in cases with high ctDNA concentrations [76].

Another possible application of ctDNA in immunotherapy is in response monitoring. Has been proven a good correlation between ctDNA modification and clinical response. Some studies show indeed that the amount of cfDNA correlate with the response to immunotherapy and a decrease of cfDNA was an indicator of good response. Moreover, also chromosomal instability, predictive for immunotherapy response canbe evaluated by NGS in cf-DNA [77, 78].

A new interesting area is represented by the evaluation of tumor microenviroment adopting liquid biopsy specimen in the clinical administration of lung cancer patients. Cai et al. compared IC positive outcome and inflammation markers (INFγ, lymphocites ratio CD4/CD8) in relation to the conventional target biomarkers (PD-L1, CTLA4) for the selection of lung cancer patients to IC administration. They showed that a wide range of inflammatory biomarkers may integrate clinical outcome in NSCLC patients clinical administration [79].

Other applications of cfDNA are likely to emerge in the near future, in the field of immuno oncology such as the detection of minimal residual disease for adjuvant immunotherapy, and the identification of resistance mechanisms linked to the onset of new mutations such as the acquired JAK1/2 or B2M mutations [73].

However, in this context it is not yet possible to think of a complete replacement of the liquid tissue biopsy. The tumor biopsy will have more and more value, both in the evaluation of PD-L1 expression on tumor cells and in the analysis of the tumor microenvironment.

And while it is possible to identify resistance mechanisms as acquired mutations in the blood, however, acquired resistance could be linked to dynamic changes in the microenvironment, which cannot be detected by a simple blood draw.

#### **7.5 Liquid biopsy in the management of other tumors**

Several pre clinical studies were performed in order to evaluate the role of cfDNA in the management of other tumor patients.

Wang et al. [80] demonstrated that ctDNA may be considered a diagnostic biomarker in head and neck squamous cell carcinoma (HNSCC) patients. 93 saliva and matching blood specimens were collected from HNSCC patients to identify somatic mutations in genes (TP53, PIK3CA, CDKN2A, HRAS, NRAS) that could play a potential clinical role in the management of this patient cohort. Results showed that ctDNA was successfully isolated from 76% and 87% of saliva and plasma samples, respectively. The authors, highlighting a percent detection rate for hot spot mutations of 100% and 76% for saliva and blood specimens respectively, defined how cfDNA extracted from saliva samples may be considered a reliable tool to identify HNSCC malignant lesions in early stage setting. Similarly, Salvi et al. [81] discussed how cfDNA may be adopted in early stage section for prostate cancer patients by

*Liquid Biopsy: A New Diagnostic Strategy and Not Only for Lung Cancer? DOI: http://dx.doi.org/10.5772/intechopen.94838*

elucidating an accuracy of 80% to discriminate cancer patients from benign lesions. In addition, Christensen et al. [82] showed how a digital droplet PCR approach is suitable to identify somatic alterations in urine cell free DNA (Ucf-DNA) by demonstrating how a correlation between Ucf-DNA alteration and tumor stage, size and grade, were statistically significant. In relation to this section, stool DNA also represents a promising diagnostic tool to early detect colorectal carcinoma patients in the early stage. According to this point, Imperiale et al. [83] showed that the sensitivity of novel technical approach DNA-based were characterized by higher analytical performance in the analysis of both CRC (92.3%) and advanced precancerous lesions (42.4%) respect the conventional screening test commercially available.

#### **8. Conclusion**

Is tissue still the issue?

One of the key questions facing oncologists today is whether ctDNA can replace biopsy or ribiopsy in clinical practice.

Liquid biopsy resulted improvements in the management of patients with NSCLC, offering an alternative to standard procedures in cases where tissue biopsy samples are insufficient or not feasible and providing a quick and dynamic assessment of emerging resistance mechanisms that can be used for guide treatment decisions so has been suggested to be included in clincal practice. However the fields of investigation using liquid biopsy are still restricted in routine practice. To date, FDA has approved the analysis EGFR gene assessment that is currently based on standardized and international practices recommendations and authorizes the administration of TKI. Recently, a document of the IASLC, stated that an EGFR, ALK, ROS1 or BRAF positive result of an NGS liquid biopsy analisys should be considered adequate for initiating first-line therapy in advanced NSCLC.

Although we can firmly state that liquid biopsy is a great help in NSCLC patient managing, however, in our opinion, for now it cannot replace tissue biopsy, which will remain the gold standard. Especially in the context of diagnosis where the definition of the tumor subtype can only be clarified through a cytomorphological analysis and immunohistochemical criteria. Furthermore, even the exact stage of cancer can only be obtained with tissue sampling. Moreover, in the setting of detect EGFR-sensitizing alterations in peripheral blood a negative plasma test it should be considered non-informative and will always need tissue confirmation.

Moreover, results of clinical studies have highlighted the existence of significant critical issues in the execution of a mutational test on liquid biopsy, either in the pre-analytical phase both in the analytical phase. Standardization of the various stages of the process is fundamental. It is certainly important that the analysis be performed in laboratories highly specialized, who already have experience in using highly sensitive molecular techniques in order to avoid false positives or false negatives results.

As indicated, there are numerous methods of studying circulating nucleic acids. In view of the large number of actionable targets in NSCLC, guidelines support the position that broad-based testing by NGS. The NGS technique requires workflow complex and use of multigene panels also requires the use of sophisticated software and, sometimes, the help of bioinformatics.

So it is therefore evident that the choice between the different technologies must hold account of their sustainability and the clinical use required in the context in which you operate.

In conclusion we think that ctDNA can play complementary roles in the management of patient NSCLC and act as a prognostic or predictive biomarker as a part of a thorough clinical evaluations to assess the disease, that include comparative sequence analyses of plasma DNA, and biopsies in combination with imaging studies and detailed functional studies.

#### **Conflict of interest**

The authors declare no conflict of interest.

#### **Author details**

Stefania Scarpino1 \* † and Umberto Malapelle2†

1 Pathology Unit, Department of Clinical and Molecular Medicine, Sapienza University, Sant'Andrea Hospital, Rome, Italy

2 Department of Public Health, University Federico II of Naples, Italy

\*Address all correspondence to: stefania.scarpino@uniroma1.it

† Both authors contributed equally to this manuscript.

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Liquid Biopsy: A New Diagnostic Strategy and Not Only for Lung Cancer? DOI: http://dx.doi.org/10.5772/intechopen.94838*

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#### **Chapter 8**

## Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a *Fluorescence-in-situ-Hybridization* Circulating Tumor Cell Approach

*Xin Ye, Xiao Zheng Yang, Roberta Carbone, Iris Barshack and Ruth L. Katz*

#### **Abstract**

Lung cancer (LC), is the most common and lethal cancer worldwide. It affects both sexes and in its early stages is clinically silent, until it reaches a more advanced stage, when it becomes highly incurable. In order to improve the high mortality associated with LC there has been an urgent need for screening high risk patients by low dose CT scan (LDCT) for the early detection of small resectable malignant tumors. However, while highly sensitive to detect small lung nodules, LDCT is nonspecific, resulting in a compelling need for a complementary diagnostic tool. For example, a non-invasive blood test or liquid biopsy, (LB), could prove quite useful to confirm a diagnosis of malignancy prior to definitive therapy. With the advent of LB becoming increasingly clinically accepted in the diagnosis and management of LC, there has been an explosion of publications highlighting new technologies for the isolation of and detection of circulating tumor cells (CTCs) and cell free tumor DNA (cfDNA). The enormous potential for LB to play an important role in the diagnosis and management of LC to obtain valuable diagnostic information via an approach that may yield equivalent information to a surgical biopsy, regarding the presence of cancer and its molecular landscape is described.

**Keywords:** Circulating Tumor Cells (CTCs), Cell Free Tumor DNA (ctDNA), *Fluorescence in situ hybridization (FISH)*, Multiplex FISH, Cytogenetically Abnormal Cells (CACs), Liquid biopsy (LB), Lung Cancer (LC), Low Dose CT Scan (LDCT), Artificial intelligence (AI), PD-L1, *ALK*

#### **1. Introduction**

Until recently, the clinical application of CTCs had been largely confined to an FDA approved test, CellSearch®, for testing patients with advanced breast, colorectal and prostate cancer, which relies on immuno-magnetic capture of circulating cells expressing EpCAM. However, this test has not been proved to be optimal for sensitive recovery of CTCs in early stage LC. Currently, in order to make real-time decisions on how to manage LC, there are several new and emerging label-free technologies for detecting CTCs which are more sensitive than the FDA approved test. While each platform differs in the methods that are employed for CTC enrichment and capture, all aim to accurately detect and enumerate CTCs [1]. In this chapter we present an overview of the current applications of LB, including both CTCs and cell free DNA (cfDNA) or circulating tumor DNA (ctDNA) for the detection, diagnosis and treatment of LC from early to advanced stages. We highlight the use of *fluorescence in situ hybridization* (FISH) to detect CTCs, in order to use these as adjunctive biomarkers, in conjunction with indeterminate nodules detected by LDCT scan, as a confirmatory test for early LC.

#### **2. Incidence of lung cancer**

Lung cancer (LC) is the leading cause of cancer incidence and mortality globally, with an estimation of 2.09 million new cases and 1.76 million deaths in 2018 [2]. GLOBOCAN Data shows that in industrialized nations, there is no substantial difference in LC deaths in males due to high cigarette consumption rates, but that there is a higher mortality rate in females. In developing countries, LC remains the second highest cancer-related mortality for women, behind breast cancer [3]. The LC incidence rate of women ranks from the highest in Northern America (30.7 per 100,000) and Western Europe (25.7 per 100,000) to the lowest in Western Africa (1.1 per 100,000). Even though women in China have a low prevalence of tobacco use, because of indoor pollution and occupational exposure [2, 4, 5], the incidence of LC in Chinese women also remains high (22.8 per 100,000) [2].

Because early-stage LC cases are asymptomatic, the majority of the patients are diagnosed with advanced disease [6]. The survival rate of stage I LC at 10 years is 92% [7], but the five-year survival rate of advanced LC with distant metastases is only 5% [8]; thus, early detection is critical in reducing lung cancer mortality rate.

#### **3. Screening by LDCT**

Lung cancer screening had become a controversial topic since the late 1990s, due to the fact that the risks, effectiveness, and procedures of screening, including the Early Lung Cancer Action Program and screening programs in Japan [9–11], were not verified. In 2002, a randomized trial, the National Lung Cancer Screening Trial (NLST) was initiated in the United States. The primary study goal was to compare the lung-cancer mortality rate between a large cohort of subjects screened for LC by conventional chest radiography versus low-dose computed tomography (LDCT). Follow up data until 2010 indicated that screening with LDCT can significantly reduce the death rate from LC, compared with the radiography group, and that, for the high-risk population [12] the lung cancer mortality rate was reduced by 20% in the LDCT group. The 10-year follow-up result of the Dutch Belgian Randomized Lung Cancer Screening trial (NELSON) that started in 2003 also successfully demonstrated a 26% mortality reduction of the high-risk population in the LDCT screening group, compared with the usual care group without screening [13]. These two studies have become the pivotal studies in LC screening history that have linked the utility of LDCT to reduced LC mortality amongst high-risk populations [14]. A growing list of organizations has established guidelines for LC screening with LDCT based on the evidence showed by the NLST and NELSON [15–17].

However, the benefits of LC screening with LDCT have been diminished by the high false-positive rate, as only 3.6% of the participants with positive LDCT screening results were diagnosed with lung cancer in NLST [12]. The substantial application of LDCT to lung cancer has resulted in a dramatic increase in pulmonary nodule

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

detection in adults at high risk, without a corresponding rise in lung cancer incidence [18]. About 80% of the patients with positive LDCT results are classified as intermediate risk of LC, thus requiring follow-up to rule out malignancy [19]. For patients in this category, most will be required to undergo invasive biopsy to further evaluate the risk of malignancy. Also, more than one-third of these patients will not be diagnosed with LC, subjecting them to potential biopsy-related complications such as pneumothorax and hemorrhage [20]. For patients who are at low-risk, repeated LDCT scans are required, which may be potentially harmful due to frequent radiation exposure [21]. In the case of ground glass nodules [GGNs], which may have an unpredictable clinical course, current diagnostic methods including biopsy and positron emission tomography (PET) are insufficient to differentiate malignant from benign nodules [22, 23]. Consequently, there is an urgent need for a non-invasive diagnostic tool such as a blood test or liquid biopsy (LB) that can evaluate the malignancy of pulmonary nodules in individuals with positive LDCT screening results (**Figure 1a** and **b**) by demonstrating the presence of circulating tumor cells (CTCs) in the blood.

#### **Figure 1.**

*(a) Schematic diagram demonstrating a hypothetical risk/benefit for lung cancer individual, undergoing LDCT scan with discovery of indeterminate lung nodule and complementary multiplexed FISH test performed on peripheral blood mononuclear cell fraction, to confirm presence of CTCs. (b) Real life example of a 55 year old lady with multiple nodules of uncertain etiology, and a fungal infection such as histoplasmosis was suspected. Multiplex 4 color FISH CTC assay performed on peripheral blood liquid biopsy showed more than 8 CTCs. Figure demonstrates CTCs stained with DAPI, and polysomy for 3p22.1 (three red signals) and polysomy 10q22.3 (3 gold signals) in same cells (merged images). Subsequent fine needle aspiration and cell block showed a well differentiated neuroendocrine tumor (diff Quik), which was positive with synaptophysin and CD56. [24].*

#### **4. Components of liquid biopsy**

Liquid biopsies (LB) comprise circulating tumor cells (CTCs) from the cellular fraction of blood, and circulating tumor DNA (ctDNA), derived from the plasma fraction of blood (**Figure 2**). ctDNA originates directly from the tumor or CTCs, that are thought to release ctDNA via apoptosis and necrosis from dying cells, or active release from viable tumor cells. Both fractions have been shown to have potential for detecting, monitoring, and treating a variety of different cancers across all stages of disease. The term LB is not just confined to the use of tumor derived material from the blood stream and may also be applied to other biofluids such as urine, saliva, cerebro-spinal fluid, pleural fluid or bile from cancer patients, however for the purpose of this review, LB refers to the blood stream. Use of LB obviates the need for invasive tissue biopsies, which are frequently from inaccessible organ sites, and usually require the use of anesthesia. Complications are not unusual, and may include hemorrhage and infection, while for lung biopsies, pneumothorax is not uncommon. LB is an easy to use approach, as a simple blood draw, requiring only 10 ml of blood, may reveal circulating tumor cells (CTCs), or cancer specific mutations or aberrant methylation patterns [26] in the ctDNA portion of the plasma, that are consistent with malignancy [27, 28].

LB may be used in order to diagnose early LC and can be easily repeated over time to detect relapse of cancer or minimal residual disease (MRD) following surgery, or to monitor a patient's response to various chemo- biological or immune checkpoint therapies. The constant replenishment of CTCs and cell free ctDNA from the primary tumor and/or metastatic sites, enables LB to detect and monitor the development of new clones of CTCs that express different mutations, as compared to an original tissue biopsy or a preceding LB, which may have arisen as a response to a targeted therapy. The rate -limiting factor for the widespread use of LB especially in early-stage LC, has been the scarcity of recovery of CTCs and ctDNA. In addition, due to the wide range of different methodologies for detecting and capturing CTCs, as well as the lack of standardization and clinical validation of different platforms, it is difficult to know which is the optimal platform to choose [1].

#### **Figure 2.**

*Mechanism of extravasation of CTCs and circulating tumor DNA from primary lung carcinoma into the blood stream. The left-hand panel shows the source of circulating tumor DNA derived from necrosis and apoptosis of CTCs. The right-hand panel shows the mechanism of extravasation into the blood stream via EMT [25].*

#### **5. Scenarios in which LB may be indicated preferentially over tissue biopsy**

First, as a complementary test in the face of abnormal images acquired by LDCT screening for lung cancer, where in order to determine the etiology of an indeterminate pulmonary nodule, a simple blood draw demonstrating the unequivocal presence of circulating tumor cells (CTCs) may be useful as a decision-making tool for the further clinical management of the patient. In this situation, tissue biopsy such as fine needle aspiration (FNA), needle biopsy or endoscopic ultra-sound guided biopsy, may be performed, however, occasionally may be both difficult and dangerous to the patient due to the small size and location of the mass and may be non-diagnostic because of the inability to procure representative tissue for pathological assessment. A positive CTC test (**Figure 1**) will lead to the procurement of an excisional surgical biopsy for standard pathological examination with curative intent or in other cases, patients may be candidates for stereotaxic radiation therapy. A negative CTC test will require follow up by LDCT, until the clinicians have determined that the nodule is stable and benign. However, in this scenario the patient will have been spared an invasive procedure for a non-malignant lesion.

Until now, current methods for detection and quantitation of CTCs have been time consuming and complex and require expensive instrumentation as well as a great deal of expertise available only at limited sites. As a result, large scale clinical trials involving thousands of patients at high risk for LC, evaluating the accuracy of screening for CTCs have not been possible. As an example, a large prospective multi-institutional study was performed using filtration of blood samples (ISET) to detect CTCs in COPD patients at high risk to develop lung cancer [29, 30]. Unfortunately, this study failed to confirm the initial promise of accurate early LC detection, due to difficulties in scaling up such technologies at multiple different sites [30]. Therefore, there is an urgent need for the establishment of platforms that can isolate CTCs from patients with early LC that are capable of producing reliable and reproducible results that are comparable amongst different populations.

Second, LB may be used as a minimally invasive, fairly rapid way, to obtain information on actionable mutations in order to deliver targeted therapies, especially in the case of advanced malignancy, where obtaining a tissue biopsy would be difficult. For advanced stage NSCLC, international guidelines have been developed by different pathology, molecular and oncology organizations, including amongst others the International Association for the Study of Lung Cancer (IASLC) and the Association for Molecular Pathology (AMP), the National Comprehensive Cancer Network (NCCN) and ASCO regarding a minimum panel of genes that should be tested to inform treatment decisions [27].

The recent introduction of comprehensive genomic profiling by NGS using ctDNA from LB in patients with advanced stage cancers, including NSCLC, has revolutionized the ability of oncologists to treat actionable mutations in this population in real time and sequentially, without resorting to invasive tissue biopsies, which frequently could not be performed due to lack of tissue or the poor state of health of the patient. Thus, in many cases, the convenience and quick turn-around time of LB may have significantly prolonged the overall survival of patients in this category, who were discovered to have developed actionable mutations following first and second -line therapies with conventional chemotherapy regimens or biological agents [27, 31].

Third, the ultimate aim or "the holy grail" of LB, is to prescreen at risk populations for the development of potentially lethal malignancies such as LC, in order to monitor these patients and institute rapid treatment if necessary.

### **6. Pathogenesis of CTCs**

Cancers develop in epithelial cells as a result of chronic exposure to inflammation or carcinogens, such as tobacco smoke or air pollution. In the lungs, exposed tissues, such as vulnerable epithelial cells in the upper and lower bronchial tracts, may manifest both dysplastic epithelial changes as well as concomitant molecular abnormalities, resulting in a "field -cancerization" effect (**Figure 3**). In these areas, certain cells may undergo unregulated proliferation due to the acquisition of tumor-suppressor genes and oncogenes as well as methylation of tumor suppressor genes. Other factors, including increased glucose uptake, angiogenesis, an altered tumor microenvironment (TME) and a cell's ability to avoid immune surveillance via masking of checkpoint inhibitors such as PD-L1, may allow invasion of these genetically and phenotypically abnormal cells into the blood stream where they present as circulating tumor or CTCs. One of the hallmarks of CTCs is genetic heterogeneity and genomic or chromosomal instability (CIN) [33]. CIN includes microsatellite instability (MSI), chromosome structural variations such as deletions, duplications and translocations, as well as chromosome number. Aneuploidy, due to errors in chromosomal segregation, is a consequence of CIN and is implicated in tumorigenesis as evidenced by the increased rate of malignancies found in patients with global or mosaic aneuploidies. The knowledge that aneuploidy is a *sine qua non* or essential element of a malignant cell forms the basis of certain LB tests that rely on the demonstration of aneuploidy to detect CTCs or CACs (cytogenetically abnormal cells [24, 25, 33, 34]. Genetic mutations arising in CTCs can be characterized by polymerase chain reaction (PCR) or next generation sequencing (NGS) on a single cell basis as well as by *fluorescence– in-situ-hybridization* (FISH) and immunohistochemistry. [23, 25, 35–37].

#### **Figure 3.**

*Left hand panel: A. section of histologically normal ciliated bronchial epithelial cells, overlying adenocarcinoma of bronchial origin. B. Microdissection of bronchial epithelial cells adjacent to NSCLC and hybridized by FISH showed deletion of gene for surfactant protein a (SP-A) in adjacent bronchial epithelial cells, with fewer green signals (SP-A) versus red signals (centromeric 10). C. Tumor cells (white arrow) show 3 signals of centromeric 10 versus 2 signals of 10q22.3 (SP-A) (green) consistent with deletion of 10q22.3 (SP-A). (adapted from Jiang et al. [32]). Right hand panel: Composite diagram of 110 cases of NSCLC demonstrating field cancerization effect of left lung following hybridization of lung sections from tumor, bronchus adjacent to tumor, proximal bronchus on side of tumor, and normal lung on contralateral side for 3 different DNA FISH probes at 3p, and 10q) expressed as percentage deletion. The highest percentages of deletion occur in the main tumor mass, however there is evidence of increased deletion of 3p and 10q throughout the lung parenchyma and in the proximal ipsilateral main bronchus (shaded areas), compared to the contralateral side. (SPORE grant, lung cancer, the University of Texas, M.D. Anderson cancer center).*

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

Before entering the blood stream, CTCs are required to undergo epithelial mesenchymal transition (EMT) in order to traverse the endothelial lining of small blood vessels and capillaries [37]. The CTCs have a much larger diameter than the diameter of a capillary and need to become deformable. This process requires CTC transformation involving micro- RNAs that can interfere with the translation of proteins by messenger RNA and facilitate the adhesion of the CTCs to the endothelium and subsequent migration into the blood stream [38]. The number of CTCs are extremely rare and are estimated at one CTC per 1x10−6 -10−7. The half- life of CTCs in the blood is very short and estimated to be less than 2.5 hours [39].

### **7. Circulating tumor DNA (ctDNA) and cell free tumor DNA (cfDNA)**

Studies have shown that tumor-specific biomarkers exist in the blood. These biomarkers represent tumor-derived elements from cancer cells undergoing apoptosis and death while traversing the blood stream. These biomarkers include circulating tumor DNA (ctDNA) which are fragments of DNA derived from


*Modified from [43].*

#### **Table 1.**

*Comparison of circulating tumor cells (CTCs) and cell free DNA (cfDNA).*

malignant cells which reside in a background of cell-free DNA (cfDNA). The DNA describes DNA that is freely circulating in the blood stream, but is not necessarily of tumor origin; cell free nucleic acid (cfNAs)includes DNA and RNA derived from cfDNA, cell free RNA (cfRNA),miRNA and exosomes [25]. Circulating tumor DNA fragments (ctDNA) result from activation of nucleases in apoptotic cells and increase in response to rapid cell turnover. The burden of ctDNA is proportional to the total tumor burden throughout the body as well as the metabolic tumor volume as measured by Positron Emission Tomography (PET-CT) [40]. ctDNA is cleared by the kidneys, liver and the spleen [41] and is easier to enrich from whole blood than CTCs, but until recently, before the advent of NGS for LB, its widespread use was limited by the need-to-know which mutations to target by PCR [42]. A comparison of CTCs versus ctDNA is presented in **Table 1**.

#### **8. EGFR mutations detected by LB**

In 2016, the U.S. Food and Drug Administration (FDA) approved the first test in LB for ctDNA, the Cobas® test (Roche, USA), which was a companion diagnostic test for the use of targeted therapy, for detecting the presence of common EGFR mutations (exon 19 deletions and the L858R point mutation), which are discovered in up to 16% of Western patients and in 50% of Asian patients with NSCLC [28]. The use of tyrosine kinase inhibitors (TKIs) in NSCLC, such as a first line TKI, like Erlotinib, is guided by the presence of alterations in EGFR with notably better response of patients harboring EGFR exon 19 deletions compared to point mutations in EGFR exon 21, whereas patients who have developed the T790M mutation after receiving first and second generation TKI's will have an improved PFS response to the third-generation EGFR TKI, Osimertinib. [44]. Resistance to TKI's may be intrinsic or acquired, with the latter occurring as an acquisition of an additional genetic mutation to a target therapy such as EGFR or through secondary mutations such as gene amplifications in other genes such as Her2neu or MET, or changes in tumor histology [28]. Thus, one disadvantage of LB compared to tissue biopsy for monitoring advanced disease, is the inability to detect transformation of NSCLC to a small cell lung cancer phenotype, which would necessitate different chemotherapy that would include etoposide and a platinum drug such as carboplatin or even the addition of an immunotherapy drug such as Atezolizumab (Tecentriq) that targets PD-L1 [28].

#### **9. LB for detection of actionable mutations in addition to EGFR**

By using a comprehensive multi-genome test panel, as opposed to a single targeted PCR test, a LB test may reveal several different mutations that may be amenable to targeted therapies. Serial blood monitoring may in addition, reveal newer actionable mutations. The use of NGS to look for actionable genes or biomarkers in formalin fixed paraffin embedded tissue sections in cancer patients with advanced disease, has been successfully applied in order to institute targeted therapies, and has resulted in improved clinical outcomes [45]. However, it has been shown that "undergenotyping" or incomplete testing for all guideline recommended biomarkers continues to be a challenge in the treatment of patients with metastatic NSCLC [27].

Studies have also shown that the results of mutational profiles from LB ctDNA in advanced or metastatic NSCLC can be very similar to that obtained in FFPE tissue from primary tumor or metastatic sites [27]. A large prospective study

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

of comprehensive ctDNA genotype analysis (Guardant360®) in patients with metastatic NSCLC compared to standard-of-care physician requested tissue genotyping, demonstrated that guide-line recommended biomarkers were significantly more likely to be discovered using the ctDNA LB test compared to tissue genotyping [27]. There are eight guideline recommendedbiomarkers and include *EGFR* mutations, *ALK* fusions, *ROS* fusions, *BRAF* V600E mutations, *RET* fusions, *MET* amplification and *MET* exon 14 skipping variants, and *ERBB2 (HER2)* mutations. There was >98% concordance for FDA –approved therapy targets (*EGFR, ALK, ROS1*, and *BRAF*) between tissue and cfDNA. In addition, there was a faster mean turnaround time in obtaining results of cfDNA compared to tissue (9 versus 15 days). Significantly, addition of the LB test in addition to tissue genotyping, increased the detection of actionable mutations, including those with negative, or not assessed or insufficient tissue results.

There are differences between the mutational profiles in ever-smoker versus never smokers in NSCLC, as well as differences in demographically different populations. As an example, 93% of 904 never smokers with lung adenocarcinomas in East-Asian populations using surgically resected frozen tumor tissue were shown to harbor an actionable mutation that could be exploited as a therapeutic target as compared to 31.2% of 1770 patients (779 current or former smokers) with NSCLC [46]. In this latter study, comprising 2674 patients, the incidence of METex 14 skipping was 1.3% in NSCLC and 1.9% in non-smokers with adenocarcinoma. By comparison, a NGS LB study of 6,034 Western patients with advanced NSCLC, reported METex14 skipping in 3.6% of all patients, demonstrating that this actionable mutation can be successfully detected by LB, with a genomic profile very similar to the aforementioned data obtained on tissue biopsy [47].

In another NGS study a hybrid-capture based 508-gene panel (Oseq-NT) was used, that included 119 patients with advanced EGFR –TKI-naïve NSCLC and 15 EGFR –TKI-resistant patients. In this study, somatic cfDNA mutations by NGS, were detected in 82.8% of patients. Actionable genetic mutations were detected as 27.7%, predominantly EGFR mutations, including the EGFR T790M mutation as well as BRAF mutations, MET mutation and gene fusions for EML4-ALK and KIF5B-RET [48]. In August 2020, the first NGS companion diagnostic test, the Guardant360® CDx test, that used LB to identify patients with specific types of mutations of EGFR in metastatic NSCLC was granted FDA approved [49]. This test uses a more sensitive and specific digital sequencing method compared to standard NGS assays, in 20 ml of blood, combined with high throughput tumor profiling or large panel genetic sequencing to simultaneously detect mutations in 55 tumor genes.

At the time of this writing, the FDA approval is only valid for targeted therapy in relation to EGFR. If other somatic mutations are detected by this EGFR assay, patients may then be referred to appropriate clinical trials where suitable targeted therapies are being used. There are 73 genes listed on the Guardant Health website for point mutations, indels, amplifications and fusions. These include amongst other genes, *ALK, BRAF, TP53, MET, NOTCH1, EGFR, ERBB2(Her2), CDK6, FGFR1, NTRK.* For a full description the reader is referred to the website (http:// www.guardanthealth.com/). A second similar test called Foundation One Liquid CDx®, (Roche, Switzerland), received expanded approval in late October 2020 by the FDA for additional targeted drugs, known as companion diagnostics [50]. This test covers single gene alterations in more than 300 cancer -related genes, as well as multi-gene signatures such as micro-satellite instability and tumor mutational burden (TMB). TMB may be used as a predictive biomarker for delivering immune check point inhibitors and refers to the totality of somatic, and coding base substitutions or mutations, and short insertions or deletions per tumor genome, which

may result in high numbers of tumor neo-antigens, and increase the likelihood of immune recognition by the immune system.

#### **10. Clonal hematopoiesis**

The development of somatic mutations in DNA as a result of the aging process can affect certain stem cells most commonly in blood and bone marrow, and less frequently in other tissues, such as the skin, colon and esophagus. In the blood, random somatic mutations in genes (*DNMT3A, TET2,* and *ASXL1*) involved in epigenetic regulation may confer relative "fitness" on certain hematopoietic stem cells, which permits unregulated proliferation of a process known as clonal hematopoiesis (CH). This results in clonal expansion of these cells [51, 52]. CH is highly prevalent in the elderly, with between 10 and 20% of individuals over the age of seventy, harboring a clone of appreciable size. Because break- down of peripheral blood cells, including CH, comprises a large component of cfDNA, CH, which may also contain somatic DNA mutations, may be a source of "biological background noise" that can lead to false positive plasma genotyping. This has been reported in patients with advanced EGFR-mutant NSCLC where mutations in *KRAS, JAK2 V617F* and *TP53* were detected and confirmed as derived from CH and not tumor [53]. To overcome the possibility of false-positive genotyping due to CH in patients with NSCLC, paired peripheral blood cell and plasma genotyping may need to be performed, so that inappropriate therapy can be avoided.

#### **11. CfDNA for early detection of cancer**

In spite of the spectacular success in applying precision therapy via LB to patients with advanced NSCLC, in early stage LC, the presence of very low amounts of mutated tumor DNA fragments in plasma, makes it difficult to be able to detect actionable genetic mutations in the pool of cell-free DNA (cfDNA). In 2019, the FDA granted break-through Device Designation to Cancer SEEK™, which was developed for early detection of eight common-cancer types, and combines multiplexed PCR detection of over 1000 mutations identified from numerous cancer samples in cfDNA, together with a panel of validated serum protein biomarkers [54, 55] including cancer-antigen 125(CA-125), carcinoembryonic antigen (CEA), cancer antigen 19–9(CA 19–9), prolactin(PRL), hepatocyte growth factor (HGF), osteopontin (OPN), myeloperoxidase (MPO) and tissue inhibitor of metallo-proteinases 1(TIMP-1) The median sensitivity to detect the different types of cancers was 70%, ranging from 98% in ovarian cancers to 33% in breast and lung cancers [54]. While this assay has very high specificity, it has low sensitivity to detect early stage 1 lung and breast cancers. In addition, because the assay is limited in its capacity to determine in which organ the cancer is present, it may be necessary to institute additional expensive screening tests such as LDCT scan, or other endoscopic or ultrasound tests, in order to discover the organ of origin of the cancer [56] which may call into question, the actual clinical value and expense of this screening test.

In recent years, large multi-center prospective clinical screening trials involving thousands of patients using cfDNA have been conducted, such as the Circulating Cell Free Genome Atlas (CCGA) study to determine if genome-wide cfDNA sequencing in conjunction with machine learning can accurately detect and determine the tissue of origin of a large number of cancer types [54] for early cancer screening purposes. An off-shoot of this study, whole genome bisulfite screening (WGBS) has examined methylation patterns of cell-free DNA fragments using a

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

vast targeted methylation panel based on the The Cancer Genome Atlas (TCGA) in a large variety of cancer patients versus non-cancer controls and was able to identify with high specificity, but with lower sensitivity, especially for the less advanced stage cancers, the presence of cancer as well as the tissue of origin (GRAIL) several years in advance of the manifestation of the tumor [55–57]. Studies are in progress employing computational biology and machine learning in prospective studies in large cohorts of healthy individuals for early detection of clinically actionable information from vast amounts of cell free nucleic acids (cfNAs) both DNA and RNA, released into the blood stream through high intensity sequencing. The goal is to discover unique genetic signatures indicative of early cancer.

#### **12. Composition of blood cells and numbers of CTCs**

CTCs are extremely rare events in the peripheral blood stream, with actual numbers depending on the platform used to evaluate the numbers of CTCs. For example, using a label-dependent method that relied on immuno-magnetic beads conjugated to an antibody to EpCAM, (CellSearch®) between 2 CTCs/ml of blood for early stage breast cancer, to >5 CTCs/ml of blood, could be detected in patients with advanced stage breast cancer [58, 59]. These rare cells are surrounded by up to several hundred million lymphocytes and neutrophils per ml of blood. On the other hand, using a label-free method to enumerate cytogenetically abnormal cells (CACs) by 2-color FISH, patients with NSCLC of all stages had significantly higher numbers of CACs than did controls. Depending on the DNA probe used, mean numbers of CACs ranged from 7.23 ± 1.32/μl for deletions of surfactant protein A gene at 10q22.3 to 45.52 ± 7.49/μl for deletions of EIF1B, eukaryotic translation initiation factor, a gene located on 3p22.1 [34]. The numbers of CACs detected for patients with NSCLC were far higher than the CTCs reported in NSCLC for the Cell Search Instrument [34] and could be accounted for by the definition of CACs as a single deletion of a genetic probe compared to the internal control DNA probe, as well as the label-free method of enumeration, in which all CACs irrespective of immunophenotype, and including cancer stem cells, malignant EMT cells and malignant epithelial cells, were counted.

In early stage LC, the vast majority of CACs are CK -/CD45- /EpCAM- and may express EMT or stem cell markers [25] hence the discrepancy between the FISH method and the Cell Search method [34]. In addition to single CTCs, clusters of cells may break off from the primary tumor and travel in clusters through the blood stream. CTC clusters may form "tumor micro-emboli "(TMI) consisting of up to 50 cells (**Figure 7**), that may demonstrate more aggressive properties than single CTCs, as they may be surrounded platelets, lymphocytes, neutrophils [60], similar to the cellular components that comprise the microenvironment seen in tumors, which may be protect TMI from destruction while circulating in the peripheral blood. TMI together with CTCs have also been detected in LB from patients with early breast cancer.

#### **13. Concept of lineage plasticity**

For malignant epithelial cells to metastasize, it is postulated that they need to adopt an epithelial to mesenchymal transition (EMT) phenotype and undergo lineage plasticity by changing their genotypic and phenotypic characteristics. During the shift from an epithelial to a mesenchymal state, the adhesion molecules expressed by the cell are modified, allowing it to adopt a migratory and invasive behavior. EMT is induced by specific transcription factors such as Snail, Zeb and Twist, and miRNA's which

together with epigenetic and post translational regulators, mediate the process of EMT. EMT is involved in wound healing, embryogenesis and cancer metastases. Most importantly, EMT has been shown to trigger the dissociation of cancer cells from the primary epithelial tumor mass and enable these cells to disseminate as CTCs into the blood stream. In a label- free study of peripheral blood mononuclear cells (PBMCs), it was demonstrated by FISH that there were higher numbers of CACs in patients with lung cancer and breast cancer across all stages than had previously been reported by other methods [25, 59, 61, 62]. This included label-dependent bead-based antibody capture systems for EpCAM, in which captured cells, that are CK+/ CD45- and stain for DAPI are defined as CTCs [58]. Notably, the FISH assay identified far higher numbers of CACs in patients in both early and advanced NSCLC compared to the low numbers of CTCs reported by EpCAM immune-antibody-cell capture methods including the CTC –chip [63]. It was also demonstrated by IHC for stem cell markers (ALDH1), mesenchymal markers (SNAIL) and CK combined with FISH, using a method known as FICTION, [64] that the CACs that were previously identified based solely on genetic abnormalities [34] actually represented diverse cohorts of pluri-potential CTCs including malignant stem cells and cells which had undergone EMT with loss of epithelial markers [25]. Further evidence for lineage plasticity and phenotypic switching was obtained by serial monitoring of blood for CTCs both before, and at several time points after, resection of LC [25]. In early stage LC the vast majority of CACs are negative for epithelial and lymphoid markers (CK-/CD45-), most likely representing EMT cells and stem cells. At later time points or as LC becomes more advanced, more CACs that are CD45+/CK+ or CK+/ CD45- are identified [25]. The not infrequent finding of genetically abnormal circulating cells co-expressing CD45+/CK+, or CK -/CD45- contradicts the classic definition of a CTC as defined by the FDA approved CellSearch® test [58]. This observation may account for the higher sensitivity of an antigen-independent gene-based test. It has also been shown that only a minority of CTCs with stem cell properties are able to survive and initiate metastases [65].

**Figures 4** and **5** depict a 43-year-old patient with stage IB, poorly differentiated squamous carcinoma, showed CACs of all lineages(lineage plasticity). a CD45–/ CK+ cell showing 3 red (10q22.3) and 3 green (Cep10) signals. b CD45+/CK– cell with 2 green (Cep10) and 3 red (10q22.3) signals. c CD45–/ALDH1+ stem cell with

**Figure 4.**

*Demonstrating lineage plasticity in CACs (by combined immunofluorescence and FISH (FICTION)).*

#### **Figure 5.**

*Histogram of CACs from the same patient as in Figure 4. FICTION method for CD45 and CK, combined with DNA probes for Cep3/3p22.1, Cep10/10q22.3, UroVysion Cep3,7,17, 9p21.3, and LAVysion, EGFR, TERT, C-MYC, and Cep6,showed increase of double-negative CTCs at 2 months in Cep3/3p22.1 abnormal cells and increase of CD45+/CK–CTCs in Cep10/10q22.3 abnormal cells, and increase of all CTC lineages in EGFR, C-MYC, and Cep6 abnormal cells at 2 months, followed by a marked decrease in all CTCs at 6 months [25]. Note that "CAC peaks" as shown in 3/4 of the above diagrams,occurred at two months post surgery, and returned to baseline at 6 months in patients with a good prognosis.*

2 red (10q22.3) and 1 green (Cep10) signal. d CD45+/CK– cell with 2 red (10q22.3) and 1 green (Cep10) signal. e CD45–/CK+ cell with 2 red (10q22.3) and 1 green (Cep10) signal. f EMT cell with 2 red (10q22.3) and 1 green (Cep10) signal. White arrows indicate the location of FISH signals [25]. **Figure 5** is derived from the same patient and demonstrates CACs from baseline before surgery to 6 months following surgery, with a return of CACs to baseline, following a peak in CACs observed at 2 months post surgery (**Figures 4**).

The significance of the EMT phenotype in initiating metastases was demonstrated by studies of CTC derived xenografts (CDX) from patients with advanced NSCLC, which demonstrated a mesenchymal phenotype [28, 66].

#### **14. Methods for isolation of CTCs from blood**

Different platforms have been developed to isolate CTCs. These can be divided into affinity, label or antigen dependent methods or affinity- or antigen-independent or label-free methods (**Figure 6**).

Affinity or label dependent devices include the CellSearch® System and the Mag –sweeper, as well as the CTC chip, because all rely on magnetic particles, beads, or posts, coated with antibodies to EpCAM that capture CTCs secondary to the expression of EpCAM on their surface membranes (**Figure 6a,b**).

Label free methods can isolate CTCs based on their physical properties and include:

a.CTC separation via density gradient centrifugation, which enables enrichment of CTCs [67] followed by *fluorescence in situ hybridization* (FISH) to identify cytogenetically abnormal cells (Sanmed Multiplex 4 color FISH test) (**Figure 6e**) [24] or immunocytochemistry for different biomarkers expressed on cancer cells such as Her2neu, estrogen receptors (ER) or cytokeratin's.

#### **Figure 6.**

*Diagram depicting methods for isolation and detection of CTCs using either a) affinity –dependent detection devices usually employing magnetic particles, beads or posts coated with EpCAM such as a) CellSearch®, MACS or mag-sweeper or b) CTC chip or B) affinity-free detection devices relying on physical properties of CTCs such as larger size or deformability compared to other blood cells using c) inertial focusing or d) trapping of cells when passed through a Parasortix® filtration cassette or e) enriched on a Ficoll–Hypaque gradient due to specific gravity and centrifugal forces and characterized based on genetic abnormalities by FISH such as the Sanmed™ multiplex 4-color FISH test or f) trapped on filtration membranes that only permit passage of white blood cells with a pore size smaller than CTCs such as cell-sieve, ISET™, screen cell™ Cyto and g) total cell capture coupled with red blood cell lysis and immunocytochemistry or FISH together with high resolution imaging for cell morphology for detection of CTCs, such as the Epic or Tethis SBS platforms.*


#### **15. Antigen dependent devices or methods**

#### **15.1 Immunomagnetic devices**

The CellSearch® (Menarini-Silicon Biosystems, San Diego, CA) method relies on ferrofluid based immunomagnetic separation of EpCAM expression to isolate epithelial cells [58, 59, 71] which are confirmed as CTCs by staining

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

positive for high expression of cytokeratin's CK8, 18 and 19, and absence of expression of CD45, a lymphoid marker. Thereafter the cell, is stained with DAPI (4, 6-diaminidino-2-phenylidole) a nuclear stain. The requirements tor this test are 7.5 ml of whole blood, collected in special CellSave tubes (**Figure 1**). Most CTCs will go through epithelial–mesenchymal transition (EMT) when they extravasate into the bloodstream, resulting in a loss or down regulation of EpCAM expression and are therefore poorly detected by this isolation method [60, 62, 71]. Loss of EpCAM is particularly notable in early stage NSCLC. In spite of the loss of epithelial marker expression in the CTC population, CellSearch® is the only CTC test that was approved in 2004 by the US Food & Drug Administration for clinical use for patients with metastatic breast, colorectal and prostate cancer, as well as prediction of survival in advanced NSCLC [58]. Since then, this test has been used in many studies with reliable and reproducible results [72–74]. CellSearch® has shown prognostic significance in detecting CTCs in most breast cancer subtypes, with a cut-off of ≤2 being a marker for long time survival [75] while ≥5 CTCs was associated with a decrease in 5 year survival. This device in its conventional set up, has drawbacks regarding sensitivity for capturing the whole dynamic range of plasticity that CTCs may demonstrate as it may not detect many cells that have lost or down regulated their EpCAM expression. Thus, numerous studies of solid tumors have reported zero or only 1–2 CTCs that can be recovered by the Cell Search instrument as currently configured [59, 71]. There are also certain solid tumors such as NSCLC, pancreatic cancer and triple –negative breast cancer, where the predominant component of CTCs are of the EMT type and hence, would not be detected by CellSearch® [25, 59].

#### **15.2 Microfluidic chips**

Microfluidic chips allow for cells to be captured, immobilized and then washed out, after which they can be subjected to molecular assays. Blood flows through 78,000 micro posts placed at very narrow intervals, forcing cells to move along narrow channels and enhancing their opportunities for contact with posts coated with EpCAM (**Figure 6b**), thus CTCs expressing EpCAM, become immobilized and attach to the walls of the chip resulting in the negative depletion of white blood cells (WBCs) which lack expression of EpCAM. Other chips may use antibodies such as anti-CD45 or anti CD66 for negative depletion resulting in retention of WBCs and elution of CTCs. The advantages of the CTC-chip compared to the CellSearch® instrument is the higher yield of CTC capture (median 50 CTCs per milliliter), as well as on-chip lysis which permits extraction of DNA and RNA for molecular analysis [63].

#### **15.3 Bead based subtraction-enrichment strategies**

Positive immunomagnetic bead-based CTC enrichment methods may rely on epithelial antigens such as EpCAM for capture and/or intra-cellular tumor cell antigens such as cytokeratin for detection, however, CTCs undergoing epithelialmesenchymal transition, may be missed [76–79]. To avoid this failure, negative selection approaches exist for unbiased CTC enrichment [80]. Negative immunomagnetic selection uses a cocktail of antibodies against hematopoietic antigens such as CD2, CD14, CD16, CD19, CD45, CD61, CD66b and Glycophorin A, to enrich for CTCs, by removing contaminating white blood cells and platelets. An example of such an assay is the RosetteSep™ (STEMCELL Technologies). Antibody labeled WBCs can also be removed by AutoMACS Separator (Miltenyi Biotec). A major disadvantage of negative selection approaches is the lower CTC purity as compared

to the positive selection approaches; however negative selection approaches show promise for identifying more CTCs for downstream analyses. Both epithelial and mesenchymal cancer cells could be enriched from patient samples [76, 79–82].

#### **15.4 Magsweeper**

MagSweeper technology is an automated immunomagnetic cell separator that uses a magnetic arm to collect cells coated with anti-EpCAM antibodies [79]. This EpCAM based isolation method can capture high-purity cells from metastatic cancer patients, but adsorption of background cells to the capturing device or the entrapment within the large magnetic particles used for labeling rare cells in large volume could lead to nonspecific contamination. However, MagSweeper is not commercially available, which might require further analysis to validate the effectiveness of the test [83].

#### **15.5 CellCollector**

The CellCollector is a modification of a medical device for use in vivo. It uses a wire with an antibody against EpCAM that is attached to the surface and is inserted through a cannula straight into patients' bloodstream and left exposed to a high volume of blood for 30 minutes to collect CTCs [84]. This device has been used successfully ex vivo to quantitate the number of CTCs in 15ml of blood from patients with prostate cancer [85]. In spite of the complicated in vivo application procedure, Luecke et al. [86] reported that the CellCollector can capture a higher volume of CTCs compared with the CellSearch method (73% vs. 29%) in 62 lung cancer patients. Further studies with larger samples will be required to demonstrate the efficiency of this technology.

#### **16. Antigen independent platforms**

#### **16.1 Enrichment free platforms or "No Cell Left Behind"**

Following red cell lysis of a whole blood sample, CTCs are captured by analyzing all nucleated cells present so that the final result is fully representative of the entire cell population in the blood sample except for the red blood cells. (Epic Science, San Diego, CA) [69, 87]. This test attempts to identify CTCs defined as: a) CK+/CD45- with abnormal morphology; b) CK - /CD45- with abnormal morphology, which may be cancer stem cells or cells undergoing EMT; c) Apoptotic CTCs, which are the abnormal cells described in a and b, but with nuclear fragmentation and d) CTC clusters, 2 or more individual cells bound together. Cells are stained with a cocktail of cytokeratin, CD45 and DAPI and then analyzed at high resolution by digital pathology methods for numerous nuclear, nucleolar and cytoplasmic features. Machine learning algorithms then quantify CTC subtypes into different categories. Cells of interest are confirmed by a trained operator as to whether they represent CTCs. This platform is also used for nuclear localization of AR-V7 in CTCs from patients with metastatic prostate cancer, which if positive, is indicative of resistance to androgen –targeted therapy, suggesting alternative therapies such as chemotherapy or other therapies [87].

A similar approach has been used for detection of CTCs and in early breast cancer using of IF for estrogen receptors and CK/and or Her2 and morphology in bright field. In combination with proprietary slides to enhance cell retention (Tethis,

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

#### **Figure 7.**

*CTC clusters in early breast cancer (a) 40x magnification of a CTC cluster stained with DAPI, and immunostained with CK and CD45, and stained with Papanicolau; (b) bright field analysis of a whole slide showing different CTC clusters (Papanicolau staining).*

Milan, Italy), this method allows gently and quick white blood cell adhesion as a monolayer with no selection, avoiding shear stress or manipulation associated with enrichment methods and thereafter examining the whole repertoire of nucleated cells [69] (**Figure 7**) thus leaving the architecture of CTCs in the peripheral blood intact. This method, which has been automated and standardized in its pre-analytical phase of sample preparation on slides, has shown high sensitivity and specificity in single CTCs and also CTCs cluster detection in a pilot study of early breast cancer [69]: identification of CTC clusters in early breast cancer is a novel finding that will deserve further confirmation in larger clinical trials. The presence of CTC clusters in metastatic settings has been clearly associated with a more aggressive tumor phenotype [70]: identification of such biomarkers in early settings could open new perspectives for the evaluation of their prognostic relevance and consequent therapeutic decision in early breast cancer.

#### **16.2** *Fluorescence-in-situ hybridization* **or FISH-based assays**

A novel way to look at the genotype of individual cells is to perform interphase FISH (iFISH) using DNA probes that may be localized to locus specific, centromeric or telomeric sites on the chromosomes. iFISH can identify if cells are diploid (normal) or aneuploid (malignant) based on the gains and/or loss of chromosomes. Panels of probes may be custom made and designed specifically to detect certain types of cancers, such as the Sanmed ™ test for LC, in which cDNA subtraction hybridization using DNA extracted from resected NSCLC specimens versus normal lung tissue was used to discover universally deleted genes [88]. The latest automated fluorescence technology using pseudo -confocal microscopy, permits up to 6 different DNA probes to be quantitated simultaneously in a single nucleus using different color fluorescent tags [89] thus allowing an opportunity for up to 6 different genetic markers to be analyzed on a per cell basis (Bioview, Rehovoth, Is.) and creating opportunities to devise novel biomarkers customized to different subtypes of cancers.

To maximize the enumeration of CTCs by FISH, a gradient centrifugation process is used, which causes the neutrophils and RBCs to precipitate at the bottom of the tube, while cells with abundant cytoplasm, such as CTCs, peripheral blood mononuclear cells (PBMCs) including monocytes and lymphocytes, band at the buffy coat due to the effect of specific gravity [24, 25, 67] (**Figure 8**). For chromosomal abnormality enumeration, thousands of purified cells from the buffy coat are subjected to iFISH, with multiple DNA probes labeled with different fluorescent tags [24] in order to identify nuclei containing gains or polysomies, and/or deletions of different targeted genes. These cells are also known as cytogenetically abnormal cells or CACs. Preparations are scanned on an automated fluorescent microscope

#### **Figure 8.**

*The workflow of CAC enumeration, from left to right, collection of 10 ml of peripheral blood, enrichment of peripheral blood mononuclear cells, hybridization of FISH probes, fluorescence image acquisition and analysis followed by cloud based data review and report [90].*

with multiple filter wheels of different wavelengths to detect different color signals (e.g., Bioview Duet Instrument Rehovoth™, Il). This instrument can be programmed to count cells of a certain size and to exclude cells the size of a lymphocyte or smaller cells. At the end of each scan, a pie chart is produced, according to a predetermined classification of signals. Digitization of cells subjected to FISH, can be performed fairly rapidly, however manual evaluation by a qualified technologist, of genetically abnormal cells, is mandatory, but can be time-consuming. Using strict criteria, only cells with intact nuclei that demonstrate good hybridization signals of all probes are analyzed (**Figure 8**).

In a 4-color FISH test such as the Sanmed™ test, the goal of the analysis is to find unequivocal aneuploid CTCs as defined by polysomy of 2 or > signals of different nucleic acid probes per nucleus. This criterion is the same one that is recommended for a similar 4-color FISH test, the Urovysion™ FISH test (Vysis, Abbott Labs, Chicago, Il) for the diagnosis of urothelial carcinoma in urine specimens in patients to rule out bladder cancer [91]. A threshold for calling a specimen positive or negative is established based on the lowest number of CTCs present in cancer patients with histologically confirmed primary cancers as compared to the highest number of CTCs present in a matched control population. The optimal threshold is the one that most accurately predicts the presence of cancer [24].

Recently, Katz et al. [24] used a 4-color FISH assay to evaluate cytogenetic abnormalities of 3p22.1 and 10q22.3 in 207 patients, including 100 control subjects, who were at risk of developing NSCLC, based on risk factors for LC as well as suspicious LDCT findings, using ≥3 CTCs as a threshold for malignancy, and successfully identified patients at stage I and II NSCLC with a high degree of accuracy (**Figure 9**, **Table 2**).

CTCs were identified as a complete cell with a nucleus larger than a lymphocyte nucleus that contained polysomy of at least 2 of 4 FISH probes per nucleus. Strikingly, the accuracy of this method to detect early-stage LC was significantly higher than other published EpCAM based technologies, most likely due to the high sensitivity of the 4-color probe cocktail that is used to detect cytogenetically abnormal circulating cells and is not dependent on EpCAM expression [24, 71, 95].

An environmental study that employed the 4-color FISH assay showed an 89.47% sensitivity and an 85.00% specificity to detect LC in 89 Chinese bus drivers who had indeterminate lung nodules on LDCT following chronic and consistent exposure to occupational pollutants [92]. Similarly, Liu et al. in a prospective

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

#### **Figure 9.**

*High degree of sensitivity and specificity demonstrated in 3 separate cohorts comprising patients with predominantly early stage cancer and controls using a threshold of* ≥*3 CTCs to determine the presence of malignancy, A) discovery cohort, first 118 B) validation cohort, subsequent 89 and C) overall cohort, 207 patients (107 patients and 100 controls) [24].*


#### **Table 2.**

*Performance of 4 color FISH test in LDCT detected lung nodules for identification of lung cancer in different populations [24, 90, 92–94].*

case–control study involving 339 participants, indicated that the 4 color FISH test yielded 67.2 sensitivity% and 80.8% specificity in stage I NSCLC patients, including those with solid nodules (38.7%), mixed ground-glass nodules (mGGn) (31.9%)

and pure ground-glass nodules (pGGn) (28.4%) [90] detected by LDCT. In addition, in this study the discriminatory capability between CACs and traditional tumor serum biomarkers such as CEA, TPSA, NSE, CA19–9 and CYFRA21-1 was compared to the results of the 4 color FISH assay and showed that the sensitivity of the CAC assay was significantly higher for small nodules and ground glass nodules when compared to the serum biomarkers [90].

In a different study, 125 individuals with newly discovered pulmonary nodules 5–10 millimeters in diameter by LDCT, underwent LB for the 4 color FISH test prior to surgery, followed by histopathological examination of the resected nodules. Here, in spite of the extremely small size of the nodules, the FISH test demonstrated a 70.4% sensitivity and an 86.4% specificity for the diagnosis of LC [93]. The advantages of using this assay were demonstrated in yet another study that collected lung LDCT images of 534 patients with pulmonary nodules and invited experienced physician to score the patients' lung cancer risk and to compare the risk score to that

#### **Figure 10.**

*(a) Overview of proposed clinical study to test robustness of AI assisted LDCT of lung nodules combined with evaluation of Sanmed test by AI in order to evaluate whether a pulmonary nodule is low, intermediate or high risk for cancer, with follow up recommendations. (b) Overview of AI based tools, include nodule segmentation, feature extraction, modeling and prediction based on established radiology guidelines, such as lung-RADS and the Fleischner society, in order to improve and standardize interpretation of lung nodules. Bueno et al. [96].*

#### *Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

calculated by Artificial Intelligence with deep learning. In all 11 cases where both physicians and AI incorrectly predicted the lung cancer risk factor, the results of the 4- color FISH test was consistent with the results of the histopathological examinations [94]. When LDCT image analysis is insufficient to make a clinical decision, the 4 -color FISH test may be a valuable complementary tool for individuals with indeterminate LDCT results.

Based on initial studies, it appears that the multiplex–FISH LB assay is robust and has the potential to be scaled up for widespread use. Reproducible results with an acceptable degree of clinical utility were obtained on numerous blood samples from different geographic locations, in which pre-analytical values were kept constant, regarding the volume of blood (10 mL collected in K2EDTA vacuum tubes), as well as methods of fixation and stabilization of blood samples for up to 96 hours at room temperature, before being processed in a centralized certified laboratory according to standard operating procedures. The multiplex- FISH CTC assay is currently being tested in a prospective study comprising large cohorts of at-risk subjects, in combination with computerized scanning of LDCT detected indeterminate lung nodules in order to confirm that the FISH assay, in conjunction with the artificial intelligence (AI) interpretation of the lung nodule may have an important and synergistic role to play in early LC detection (**Figure 10a** and **b**).

#### **16.3 FISH quantitation by artificial intelligence (AI)**

A drawback of the different FISH assays has been the length of time taken to manually evaluate and accurately enumerate fluorescent signals due to overlapping cells and/or other technical difficulties such as splitting of signals, resulting in inaccurate counting and overcalling of CTCs and distinguishing CTCs from debris and leukocytes [94, 97]. However, the development of machine learning algorithms in implementing the CTC counting procedure has been able to make the process far more efficient and accurate. Machine learning(ML) algorithms that function in advancing cell image analysis can automatically input layers with a geometric relationship, as well as precisely capture the rows and columns of images; thus ML can rapidly recognize CTCs with extra intra-nuclear structures compared to normal cells, in order to reduce the artificial errors and improve the precision of

#### **Figure 11.**

*Diagram of instrumentation (De novo®, BioView, Rehovoth, is) currently in use (left hand panel) for automated imaging comprising 3D image capture, cell segmentation, exposure adjustment and cell classification. Right hand panel depicts deep learning algorithms to improve classification of cells including cell segmentation, signal detection and CAC identification and characterization.*

CTC identification [98, 99]. For example, the BioView platform automates image collection and is able to utilize an algorithm for identifying CTCs according to cell size, cell shape, nucleus to cytoplasm ratios, and occurrence of biomarkers identified by target features, and can automatically select CTCS from other cells in peripheral blood in a timely manner and has been widely applied in many FISH based CTC enrichment processes [100, 101] (**Figure 11**). In another AI study involving analysis of the 4-color FISH LB assay, FISH probes were segmented using 3D-Unets, which enabled a significant reduction in false –positive enumeration of polysomies obtained during traditional computer vision microscopy, while retaining all verified CTCs, greatly improving the efficiency of the scoring pathologists and the accuracy of the test [102].

#### **16.4 Filtration methods**

#### *16.4.1 Filtration devices*

CTCs may be isolated by the size of epithelial cells (ISET) (Rarecells Diagnostics, Paris, France) [103, 104] via a blood filtration approach which enriches 10 ml of peripheral blood collected in buffered EDTA and kept at room temperature. The membrane used is made of polycarbonate and allows cells <8 microns to pass through, while the larger epithelial and mononuclear white blood cells remain on top (**Figure 6f**). Half of the membrane can be used for morphology via a May Grunewald Giemsa stain, and the second half can be used for immunocytochemistry using a pan-cytokeratin antibody and an anti-vimentin antibody applied to the filters. Malignant cells are identified cytologically according to usual characteristic nuclear and cytoplasmic features. Another similar platform is the CellSieve method that uses microfilters and a pressure monitored filtration pump from Creative MicroTech, Inc., Rockville, MD (**Figure 12**). Another filtration device similar to that has enhanced cell recovery for in vivo quantitation of rare CTCs via multiphoton intravital flow cytometry [105]. Successful size- based isolation of CTCs has been described using a microcavity array system that traps CTCs into 10,000 cavities arranged in a 100x100 array with each cavity fabricated to have a diameter of 8–9 μm [68]. This method was shown to be superior to CellSearch in detecting CTCs from patients with NSCLC and small cell lung cancer. Filtration devices have been successfully and

#### **Figure 12.**

*Filter preparation, screen cell, of CTCs derived from a patient with stage IV adenocarcinoma of lung showing numerous CTCs, both single and in clusters a) diff- Quik 20X b) diff -Quik 40X, c) same patient, clusters of adenocarcinoma, morphologically resembling CTCs, in pleural fluid, hematoxylin and eosin 10X, d) 40X, e) CTCs multiplex 4 color FISH (3, 3p, 10, 10q) demonstrating aneuploidy 400X, f) EML-ALK translocation, CTCs X400, g)pleural fluid X400, h) multiplex 4 color FISH (3, 3p, 10, 10q), pleural fluid X600.*

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

extensively used [103], to detect CTCs, both for screening for lung cancer in high risk COPD patients, as well as in patients with established diagnosis of LC [71]. In a large study of patients with and without COPD, investigators noted that 5/168 patients with COPD or 3%, all of whom had negative spiral CT scans, manifested CTCs one to 4 years before the appearance of indeterminate lung nodules. All nodules proved to be early stage lung cancer on surgical resection [104]. The CTCs were isolated by the ISET filtration method and were stained with both epithelial and mesenchymal markers. In a side-by-side comparison of 40 patients with advanced NSCLC, predominantly stage IV, using the filtrationbased size exclusion technology ISET (Rarecell Diagnostics), investigators detected higher numbers of CTCs including epithelial marker- negative cells in 32/40 or 80% of patients as compared to CellSearch where only 9/40 or 23% of patients were found to have CTCs In addition circulating tumor microemboli (CTM) were detected by filtration but were not detectable by CellSearch [71]. Immunohistochemistry stains on cells isolated by ISET showed variable expression of EGFR, CK and Ki67, however EpCAM expression was not detected. Despite the initial promising results of ISET capability for identifying high risk individuals that could develop LC, in a recent multicenter study, CTC detection using ISET was shown not to be suitable for lung cancer screening. In this study, factors limiting the widespread use of ISET for screening for LC, included preanalytical factors, such as use of different blood collection tubes such as EDTA (ethylenediaminetetra-acetic acid) or Streck BCT (Streck, Omaha Nebraska) tubes, and imprecise standardization of the filtration method, by different operators [30]. It was subsequently concluded that in order to define a robust CTC test, suitable for real world consumption, large multi-center trials with large numbers of patients, using uniform pre-analytical conditions and identical technical analysis is essential [30].

One notable disadvantage of the filtration methods is that there exist subpopulations of CTCs whose size is smaller or in the same size range as WBCs (around 5 microns) and therefore would be eliminated during the filtration process. This feature may contribute to a lower sensitivity of CTC detection compared to other methods for enrichment of CTCs that do not rely on filtration [81].

#### **Figure 13.**

*Left hand panel, showing ALK gene rearrangements (white arrows) in H2228 lung cancer cell line, Vysis ALK break apart FISH probe kit (Abbott, molecular diagnostics, Des Plaines, IL). Right hand panel showing CTCs demonstrating ALK break apart gene rearrangements (white arrow) in CTC and normal cells with fusion signal seen as closely opposed green and red signals (yellow arrows), BioView duet™, scanning system, Rehovot, is.*

#### **Figure 14.**

*(A) Multiplex fast FISH assay for detecting ROS1, RET and MET aberrations in FFPE non-small cell lung cancer specimens using BioView Duet™ scanning system for automated slide imaging and digital analysis of 6-color probe assay. Examples of case reports and representative images of cells positive for RET, ROS1 and MET aberration a) RET break apart probes labeled with Spectrum Green (5′ RET Cen) and Spectrum Red (3′ RET Tel) and captured with corresponding filters. b) ROS1 break apart probes labeled with SpectrumAqua (3' ROS1 Cen) and SpectrumGold (5' ROS1 Tel, pseudocolored in Orange) and captured with appropriate filters rearrangement probe. c) MET gene copy number probe labeled with Alexa 647 (pseudocolored in Magenta) and centromeric probe CEP7 labeled with Alexa 750 (Blue) and captured with appropriate filters. d) Combined image of the multiplex FISH assay with probe mix contained 6 differentially labeled fluorescent probes: 3' ROS1, 5' ROS1, 3′ RET, 5′ RET, MET and CEP7. (B) Figures supplied courtesy of Dr. Irina Sokolova, Tatyana Grushko and Katerina Pestova, Abbott, Molecular Diagnostics, Des Plains, IL [89].*

#### **16.5 Specific chromosomal abnormalities to detect CTCs**

A method known as FICTION which combines IFISH and IHC may be used to simultaneously analyze the genotype and phenotype of a single CTC and can be used to study phenotypic and genotypic changes in the same cell [25, 64] The anaplastic lymphoma kinase (*ALK)* fusion gene is a driver gene for non-small cell lung cancer (NSCLC) [106]. *ALK*-positive NSCLC has been considered as a molecular subtype of NSCLC that provides unique clinicopathological characteristics of cancer diagnosis and prognosis [106, 107]. Initially, researchers found *Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

that the *EML4-ALK* fusion gene exists in NSCLC patients by PCR and proteomics methods. However, due to the variation of fusion partners of ALK fusion genes, as well as the possibilities of unknown fusion partners, the FISH method with specific probes is an accepted and essential FDA approved companion diagnostic method performed on FFPE sections of NSCLC [108]. Currently, FISH has been considered as the gold standard of detecting ALK rearrangements [107, 109] using the Abbot Vysis *ALK* Break Apart FISH Probe Kit. The kit is designed with the 3′ and 5′ probes labeled by red and green signals; once abnormalities of *ALK* have occurred, deletion or splitting of the signals will be detected [110]. The limitation of the FISH based *ALK* test includes high cost and the utilization of specialized equipment [110, 111]. Studies have demonstrated CTCs containing the *ALK-EMLK1* gene rearrangements in patients with NSCLC [108–112] (see **Figure 13**) as well as in *ex vivo* cultures of CTCs from patients with NSCLC [113].

An enriched cell preparation can be used to detect oncogene fusions due to chromosomal translocations or inversions in lung cancer such as *ALK-EML1, ROS-1* or amplifications of oncogenes such as *Her2neu* or *EGFR*. Recently a novel FISH assay was described that can simultaneously detect *ROS1, RET*, and *MET* chromosomal aberrations in cells of NSCLC on FFPE tissue. This assay has the potential to be used on CTCs [89] (**Figure 14a**–**d**).

#### **17. PDL-1/PD-1 on CTCs**

In recent years the development of tumor immunotherapy drugs, especially immune checkpoint inhibitors (ICIs) targeting the programmed death protein (PD-1)/ programmed death ligand 1(PD-L1) has changed the paradigm in the treatment of malignant tumors and has shown superiority in terms of therapeutic effect and quality of life compared with traditional chemotherapy

#### **Figure 15.**

*Top panel: Example of metastatic adenocarcinoma of lung in pleural fluid in a patient with advanced lung cancer, A) papillary and acinar fragments of adenocarcinoma (H&EX20); B) PD/L1 IHC clone 22c3(pharm dx, Dako, CA) showed weak membranous expression, overall score < 50%; C) ALK IHC, clone D5F3 showed strong expression consistent with a positive test. Bottom panel: D) squamous carcinoma lung, moderately differentiated, transbronchial biopsy, H&E X40, E) and F) PD/L1 IHC22C3 shows strong positive membranous staining in >90% of malignant cells, G) Alk IHC, clone D5F3, showed negative expression consistent with a negative result.*

[114–118]. Single-agent immune checkpoint inhibitors are now standard of care for advanced non-small cell lung cancer (NSCLC), and emerging data show that combining these agents with established chemotherapy further improves progression free survival and overall survival. The Phase III KEYNOTE-189 and IMPower-130 trial showed significantly improved survival using this strategy for non-squamous NSCLC, and the phase III KEYNOTE-407 trial showed similar results in squamous disease [119].

PD-L1 is a type 1 transmembrane protein with an extra-cellular N-terminal domain which inhibits or blocks the immune response by interacting with the PD-1 receptor which is expressed on activated T- and B-cells, and macrophages. Anti-PD-L1/PD-1 antibodies can reactive the immune system to eradicate tumors by blocking checkpoint proteins from binding with their partner proteins. PD-L1 expression may inform the use of checkpoint inhibitor combination therapy, while overall tumor mutation burden is also an emerging biomarker for ICIs. Antibodies that have FDA approval for NSCLC are two that block PD-1, namely Nivolumab (Opdivo, Bristol-Myers Squibb) approved for third line approval and Pembrolizumab (Keytruda, MSD SHARP and DOHME GMBH), which has approval for first- and second line-treatment, and one antibody blocking PD-L1, namely Atezolizumab (Tecentriq, Roche) for third line–treatment settings.

Immunohistochemistry (IHC) on tumor tissue, using the recommended FDA approved IHC-companion diagnostic for PD-L1, Ventana PD-L1 SP142 assay (Ventana Medical Systems, Tucson, AZ, USA) and PD-L1 IHC 22C3 PharmDx (Dako, North America, Santa Barbara, CA, USA) is the gold standard (**Figure 15**) and is widely adopted in PD-L1 detection.

#### **17.1 Limitations of PD-1/PD-L1 inhibitors**


CTCs originate from different tumor sites and thus, better reflect the tumor heterogeneity compared to tissue biopsies. They could therefore be potentially useful as a non-invasive method to detect PD-L1 expression in NSCLC patients [114–120]. In 2016, Schehr et al. [121] reported the finding of PD-L1-positive (PD-L1+) CTCs in NSCLC via in-house immunomagnetic enrichment system. However, other than cells expressing EpCAM, the study also mentioned the co-isolation of CD11b+, CD45-low, and cytokeratin-positive (CK+)- cells that expressed PD-L1, that could be mislabeled as CTCs, thus stressing the importance of proper identification of CTCs to avoid false positive events. Recently, Wang et al. [122] mentioned the dynamic changes of PD-L1 expression by CTCs 13 non-metastatic NSCLC patients. CTCs were in all 13 samples, PD-L1+ CTCs were detected in 66.7% of the sample. A recent study from 106 NSCLC patients, showed a 93% concordance between PD-L1

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

status in CTCs and tumor tissue, indicating the potential of a CTC test in determining response to ICIs [120].

Another recent study used a novel SE-iFISH (subtraction enrichment interphase FISH) strategy to examine the presence of PD-L1 on aneuploid CTCs and aneuploid circulating tumor endothelial cells (CTECs) to evaluate if their presence could be used as a surrogate biomarker to evaluate the efficiency of second-line anti-PD-1 (Nivolumab) immunotherapy. This study demonstrated that significant numbers of PD-L1+ aneuploid CTCs and CTECs could be detected in histopathologic hPD-L1 patients. In contrast to decreased PD-L1+ CTCs, the number of multiploid PD-L1+ CTECs (≥tetrasomy 8) undergoing post-therapeutic karyotype shifting increased in patients along with tumor progression following anti-PD-1 treatment and was associated with a significantly shorter PFS compared to those without PD-L1+ CTECs [123].

Many issues of PD-1/PD-L1 expression still need to be validated, including ensuring that the clones of antibody cocktail used for staining are standardized and equivalent in performance to the antibody clones included in the IHC kits that have received regulatory approval as companion diagnostics, as well as the threshold used to call a test PD-L1 positive, and whether the effect of the therapeutic use of anti-PDL1 antibodies interferes with the binding of diagnostic PD-L1 antibodies on CTCs [124]. Currently there are over 400 listed clinical trials for LC patients using ICI's alone or in combination with traditional chemotherapies [124]. Thus, if the CTC test, can be standardized, it will be of tremendous value as a complementary diagnostic tool for real time monitoring of PD-L1 expression for advanced lung cancer patients.

#### **18. Conclusion**

LB has evolved as a transformative technology for cancer diagnosis. Enormous strides have been made in recent years by the scientific and oncology communities to expand upon the tremendous value contained in a LB specimen. These readily obtained samples provide a real time window into the presence of cancer cells, the molecular evolution of the underlying tumor and its metastatic cascade and represent a far more feasible method for the longitudinal monitoring of the cancer patients as compared to direct tissue biopsy. Currently CTCs and ctDNA may be used in screening for early stage LC, as a diagnostic test to discriminate between a benign or malignant nodule on LDCT scan, as a decision –making tool or companion diagnostic for instituting targeted therapy for different genetic mutations, for detecting the presence of minimum- residual disease and as a monitoring tool for detecting response to immune-check point inhibitors. There are however still discrepancies in how to harness the power of CTCs, especially in the area immunecheck point inhibitors, where standardization of CTC capture and companion PD-L1 antibodies, together with inter-laboratory standardization in interpretation of these tests, will be mandatory. Another key objective of future research will be the ability to establish mouse models from CTCs to monitor the epigenetic, and genetic profiling, functional and signaling pathways of malignant cells in response to different therapies. In order for LB for LC to become well accepted as a reliable source for actionable therapy large scale studies involving consortia of academic institutions and public/private partnerships are needed to establish reliable platforms for capturing and detecting CTCs and ctDNA that validate pre-existing discovery studies. Notwithstanding these caveats, it is apparent that LB is becoming an indispensable weapon in the battle against cancer.

#### **Acknowledgements**

The authors gratefully acknowledge the following people who have contributed to this book chapter: Ms. Sharon Mehl for assisting with the editing and references, Dr. Robert Mattaliano, Sanmed Diagnostics Inc. for permission to use **Figures 1a, 8, 10a, b,** and **11** adapted from his presentation on Liquid Biopsy at the Tricon Molecular Medicine Meeting, San Francisco, February 2021 as well as for editing and reviewing the manuscript, Dr. Irina Sokolova, Vysis, Abbott Molecular, Chicago, Il for supplying the multiplexed 6 color FISH figures and Dr. Efrat Ofek, of Sheba Hospital, Tel Hashomer, Tel Aviv University, Israel for supplying pleural fluid and transbronchial biopsy specimens (**Figure 14**), and Ms. Camilla Avivi of Sheba Hospital, Tel Hashomer, Tel Aviv University for her expert immunocytochemical staining.

The authors have obtained permission from Karger Publishers, License number 5001350625847, Feb 03,2021 to reproduce 3 figures and one table from Liquid Biopsy: Recent Advances in the Detection of Circulating Tumor Cells and Their Clinical Applications, authored by Katz Ruth L., Zaidi Tanweer M., Ni Xiaohui, Copyright © 2020, © 2020 S. Karger AG, Basel, Vol 25, license date Feb 03, 2021.

The authors have obtained permission from John Wiley and Sons, License number 5020371212886, to use licensed content from Cancer Cytopathology, Apr 22,2020, vol 128, entitled: Identification of circulating tumor cells using 4-color fluorescence in situ hybridization: Validation of a noninvasive aid for ruling out lung cancer in patients with low- dose computed tomography-detected lung nodules., authored by Ruth L. Katz, Tanweer M. Zaidi, Deep Pujara, et al., **Figures 2a, c**–**e,** and **3**.

#### **Funding**


#### **Conflict of interest**

Dr. Ruth Katz is a consultant for Sanmed Bio, and on the scientific board of Lung life AI, Dr. Xin Ye and Ms. Xiaozheng Yang are employed by Sanmed Bio, Zhuhai, China. Dr. Katz is also an inventor of the Mutiplex LB FISH Test, licensed by MD Anderson Cancer Center to Lunglife AI, and sublicensed to Sanmed Biotech Ltd., Zhuhai, China as the Sanmed test for CACs. Dr. Katz was an employee of MD Anderson Cancer center from 1976 to 2018, during which time she developed the Mutiplex LB FISH Test. Dr. Katz and MD Anderson Cancer center, may in the future, be beneficiaries of royalties from this test,

*Diagnosis of Non-Small Cell Lung Cancer via Liquid Biopsy Highlighting a* Fluorescence*… DOI: http://dx.doi.org/10.5772/intechopen.97631*

She holds the following patents:

UTMDACC, Katz RL, Feng J: Detection and diagnosis of smoking-related cancers, United States, 12/761,134/UTSC: 658USC2, 4/15/2010, issued.

• UTMDACC, Katz RL: Circulating tumor and tumor stem cell.

*Detection using genomic specific probes, United States, UTFC.*

*P1234WO, 12/10/2015, pending.*

*Chinese Application No. 201580075104.1 based on PCT/US2015/065057 and U.S. Provisional Application No. 62/090,167; Entitled "CIRCULATING TUMOR AND TUMOR STEM CELL DETECTION USING GENOMIC SPECIFIC PROBES" by Ruth Katz.*

*In the Name of Board of Regents, The University of Texas System Our Ref. UTFC.P1234CN; Your Ref. MDA14–035.*

• The four-color FISH test described within this chapter is licensed to LunglifeAI (Los Angeles, CA, USA) and sublicensed to San Med Bio (Zhuhai, China) and Livzhon Pharma, China.

Dr. Roberta Carbone is a Tethis employee and holds equity and/or stock options: she holds a patent on the SBS technology (Method for immobilizing biological samples for analytical and diagnostic purposes, WO2019021150A1).

#### **Author details**

Xin Ye1 , Xiao Zheng Yang1 , Roberta Carbone2 , Iris Barshack3 and Ruth L. Katz<sup>3</sup> \*

1 Sanmed Biotech Ltd., Zhuhai, China

2 Tethis S.p.A., Milan, Italy

3 Chaim Sheba Hospital, Tel Aviv University, Ramat Gan, Israel

\*Address all correspondence to: ruarik18@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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#### **Chapter 9**

## Current Advances in Clinical Application of Liquid Biopsy

*Shawn Baldacchino*

#### **Abstract**

Liquid biopsy solutions are available for niche clinical applications. The patient benefits of such solutions are evident: ease of sampling, acceptable and repeatable. To date a number of solutions have received regulatory approval with more comprehensive, multi-cancer companion diagnostic approaches receiving approval in late 2020. Given these breakthrough advances and the ongoing clinical studies in early detection of cancer, the liquid biopsy field is making strides in technology. While circulating tumour DNA (ctDNA) solutions are quickly penetrating the market, strides in circulating tumour cells (CTC) and extracellular vesicles (EV) technologies is unlocking their potential for liquid biopsy. ctDNA solutions are paving the way towards clinical translation into the distinct applications across the cancer continuum. This chapter presents a detailed review of current approved liquid biopsy tests and provides a summary of advanced-stage prospective technologies within the context of distinctive clinical applications.

**Keywords:** circulating tumour cells, CTC, extracellular vesicles, EV, cfDNA, ctDNA, methylation, liquid biopsy, cancer screening, precision medicine, companion diagnostics

#### **1. Introduction**

Precision medicine is driven by discoveries in cancer biology that enable targeted therapy against specific oncogenic molecular targets. Using small selective inhibitory molecules or monoclonal antibodies, therapies aim to effectively target tumour cells with minor effects on normal cells [1]. Targeted therapies significantly contribute to improved cancer survival, however the results have not been commensurate with expectations [2]. Tumours accumulate mutations, many of which are passenger or dispensable aberrations that can be bypassed to confer resistance. Malignant cells interact and exploit their immediate and distant microenvironment. Tumours exhibit clonal evolution that results in heterogeneity [3, 4]. Cancer is a cell disorder characterised not only by its genetics but transcriptomic, proteomic expression patterns and cellular interactions. This is driving an integrative approach to cancer diagnosis and therapeutic options [5–7].

Until recently, precision medicine was limited to the solid tissue space but is now becoming established in the liquid biopsy field with several approved solutions (**Tables 1** and **2**). The broad term, liquid biopsy, alludes to a test or series of tests that can provide information comparable and potentially beyond the limits of the tissue biopsy harnessing body fluid constituents. Body fluids investigated for liquid biopsy applications are comprehensive including but not limited to blood,



### **Table 1.**

*Overview of current approved (FDA/IVD) ctDNA liquid biopsy solutions for single cancer indications.*

#### *Current Advances in Clinical Application of Liquid Biopsy DOI: http://dx.doi.org/10.5772/intechopen.96086*


**Table 2.** *Overview of current approved (FDA/IVD) ctDNA liquid biopsy solutions indicated for use with 2 or more solid cancers.* *Current Advances in Clinical Application of Liquid Biopsy DOI: http://dx.doi.org/10.5772/intechopen.96086*

#### **Figure 1.**

*Comparison of workflows of emerging liquid biopsy tools with routine cancer diagnostics by tissue biopsy. Liquid biopsy solutions remain complimentary to the clinical standard of care. [CTC: Circulating tumour cells; EVs: Extracellular vesicles; ctDNA: Circulating tumour DNA; FISH: Fluorescent in situ hybridisation; H&E: Haematoxylin and eosin; IHC: Immunohistochemistry; TAT: Turn-around time; created with BioRender.com].*

urine [16], cerebrospinal fluid [23], stool [24], breast milk [25], saliva/sputum, oesophageal brushing, Pap smears/brushing [26], tears [27], pleural effusion [28] and ascitic fluid [29].

Liquid biopsy testing may encompass investigations of circulating tumour DNA (ctDNA) or cell-free DNA (cfDNA) and RNA (ctRNA), circulating tumour cells (CTCs), tumour-derived extracellular vesicles (EVs) and tumour-educated platelets [30]. Rapidly advancing technologies for immunoprofiling of leukocytes and T-cell receptor (TCR) profiling also present a potential liquid biopsy tool with a particular role in metastatic cancer patients for immunotherapy [31, 32].

The potential applications of liquid biopsy are numerous and throughout the cancer journey:

1.Cancer detection for screening or earlier detection [33, 34],

2.Diagnosis / Prognosis/Predictive (Companion Diagnostics, CDx) [30],

3.Therapeutic response monitoring (Detection of resistance mechanisms) [35, 36],


The main advantages of a liquid biopsy assay relate to the ease of sampling. Collecting the sample is generally not invasive and repeatable enabling longitudinal monitoring. The risk of complications and pain from sample collection is minimal presenting a very acceptable procedure that beckons better uptake as a screening procedure. Liquid biopsy methods are less laborious than tissue biopsy methods and can be analysed in a much shorter time-frame (**Figure 1**). Moreover, liquid biopsies offer an overall snapshot of the tumour which represents distinct tumour clones, mitigating tumour region selection bias [30]. Monitoring cancer over time also provides insight on the temporal heterogeneity, a potential tool to study mechanisms of response and resistance [32, 39].

Following is a review of the advances of liquid biopsy in the context of the current state of tissue molecular pathology for clinical application. A brief illustration of future prospects is also described based on ongoing clinical studies.

#### **2. Molecular pathology: overcoming challenges for solid and liquid biopsy**

Challenges to comprehensively characterise cancer in the clinical setting exist, relating to pre-analytical (sample collection & processing), analytical and postanalytical factors. Molecular pathology of solid cancer on formalin-fixed paraffin embedded (FFPE) tissue presents technical challenges arising from tissue fixation and processing but also sample availability.

A study evaluating factors for next-generation sequencing (NGS) testing failure showed that on average 22.5% of cases do not meet quality requirements. Insufficient tissue or insufficient DNA accounted for 62% and 29% of failures with 6% failing at library preparation [40]. The study highlights increased failure from fine needle aspirates and biopsy specimens with a low failure rate in excisional specimens (1.7%) [41]. Whole genome sequencing approaches show non-uniform coverage in FFPE DNA samples resulting in sub-optimal somatic copy number alteration detection. Nonetheless clinically actionable variants are generally detected [42]. Sensitive NGS applications require good quality DNA to achieve adequate assay performance and coverage. Recent developments in DNA extraction methods and optimisation improve assay performance [42, 43]. In fact NGS solutions have been achieving regulatory approval such like Oncomine Dx (ThermoFisher Scientific) for targeted therapies in non-small cell lung carcinoma (NSCLC) [44]; Praxis (Illumina) characterising 56 KRAS/NRAS mutations for colorectal cancer companion diagnostics (CDx); Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), the first U.S. Food & Drug Administration (FDA) approved tissue profiling test that detecting aberrations across 341 cancer genes for solid cancer tissue diagnostics but not prescriptive for any specific therapeutic product [45]; and FoundationOne CDx which is the first FDA-approved broad CDx test that is clinically and analytically validated for all solid tumours for therapeutic indication and has a success rate of >95% on FFPE [46].

Targeted gene panels or single gene polymerase chain reaction (PCR) assays are more easily translated to clinical application given their very specific intended use. Recent advances can mitigate the effects of DNA fragmentation and PCR

#### *Current Advances in Clinical Application of Liquid Biopsy DOI: http://dx.doi.org/10.5772/intechopen.96086*

inhibition [47]. Technical challenges are greater for detection of RNA signatures due to high degree of RNA fragmentation and introduced technical bias [48]. A study assessing the performance of PCR on RNA derived from FFPE reports that only 50% (37/74) of samples were informative. RNA profiling on FFPE samples requires alternative technologies that can robustly detect degraded RNA with reduced technical bias [49–51].

Liquid biopsy options involve far less sample processing and better sample quality. Nonetheless tumour signatures are generally rare, similar to finding 'the needle in a haystack', and assays require high sensitivity to avoid false negative results. In the search for a sensitive, specific and reliable method, liquid biopsy technologies are becoming more diverse and complex [52–54]. Moreover, pre-analytical considerations are critical to ensure high sensitivity and reproducible performance. These requirements vary depending on the analysed liquid biopsy component. Expert recommendations for minimal requirements for clinical cfDNA testing have been published to emphasise the need for standardisation of the test processes [55].

#### **3. Current state of liquid biopsy application**

#### **3.1 Liquid biopsy for companion diagnostics**

A particular study of previously untreated metastatic non-small cell lung carcinoma (NSCLC) shows that cfDNA technologies have the potential to detect guideline-recommended biomarkers with a higher sensitivity compared to standard of care tissue genotyping methodology [22]. Currently, ctDNA assays are being recommended for use in lung patients with progression of secondary clinical resistance and in some clinical settings where tissue is limited or insufficient for molecular testing. ctDNA assays are not recommended for the diagnosis of primary lung tumours [56]. ctDNA liquid biopsy solutions are currently approved as additional tools to the standard of care and when results are negative, tissue testing is recommended when available. Lung cancer tissue is not easily available and sampling implies potential serious complications such as pneumothorax, haemorrhage and respiratory failure. Only 50% of cases in the MarkER Identification Trial (MERIT) trial had sufficient sample for the planned molecular analyses [40]. This presents a clinical need for liquid biopsy to potentially identify a route for targeted treatment.

Advanced-stage technologies within the liquid biopsy field harness ctDNA. These approaches mainly focus on hallmark mutations or other changes in the DNA (methylation). The first FDA approved ctDNA liquid biopsy was the cobas® EGFR mutation test V2 (Roche) as a companion diagnostic [57]. This was followed by several other targeted panel companion diagnostics (**Table 1**). The main available plasma liquid biopsy solutions detect mutations in clinically actionable biomarkers that predict response to specific targeted therapies. The main biomarkers detected are EGFR, FGFR, KRAS, NRAS, BRAF and PIK3CA.

Selected diagnostic panels are useful as companion diagnostics for clinical trials and patient selection for specific targeted therapeutics. Nonetheless, established targets would then be integrated into larger diagnostic panels that provide a comprehensive and exhaustive approach to cancer diagnostics. Recently the FDA approved the first two NGS-based liquid biopsy solutions: Guardant360 (August, 2020) and FoundationOne CDx (November 2020) (**Table 2**). Unlike PCR-based targeted panels, large NGS panel tests interrogate a large-set of genes generating more clinically useful information but present a challenge to validate and regulate [58]. Similar to tissue-based NGS approaches, generated clinical information assists the definition of a spectrum of potential therapeutic options to identify a sequence of

treatments to achieve optimised response [59]. In contrast, to tissue biopsy molecular analysis, liquid biopsy solutions are expected to generate a collective picture of cancer heterogenous clones enabling a comprehensive therapeutic approach which may be key to avoid clonal residual disease or recurrence [60].

A recent study evaluated the post-progression ctDNA (Guardant360 assay) with matched multiple lesion biopsies to assess heterogeneity during acquired resistance [61]. This study reveals distinct mutational profiles across metastatic lesions of gastrointestinal origin. The majority of private alterations across lesions could be detected by cfDNA. In another study, combined analysis of solid (192 genes) and liquid biopsies (27 genes) (OncoSTRAT&GO™, OncoDNA, Gosselies, Belgium), only found 40% of variants to be shared between the solid and liquid biopsy, with 51% of variants being exclusive to tissue and 9% to blood [62]. The liquid exclusive variants increased to 14% after a year from tissue sampling reflecting temporal heterogeneity [62]. The disparity in mutation calling may be a result of distinct shedding rates across tumour stage and types or sensitivity of the ctDNA assay. Although further studies are needed, such studies suggest that liquid biopsy can complement tissue molecular pathology to improve the detection of clinically actionable aberrations to overcome spatial and temporal heterogeneity especially in late-stage disease.

#### **3.2 Liquid biopsy for cancer detection**

Similar to CDx assays, current solutions for primary cancer diagnosis are either ancillary solutions or to be used when the routine screening/diagnostic test is not an option. Thus, liquid biopsy approaches are currently another tool that assist and improve the overall performance of cancer detection. Approved liquid biopsy solutions for bladder cancer screening and colorectal cancer screening are available (**Table 1**) to support current screening methods. Evidently, when standard of care investigations are not available, liquid biopsy can provide means of detection. For instance, Epi proColon® (Epigenomics) is available only to patients who are unwilling or unable to be screened by recommended methods. This can potentially improve screening uptake with current colorectal cancer screening uptake reported between 53 and 61% [63–65]. The more acceptable, repeatable advantages of liquid biopsy enable multi-line testing or triage testing to select patients for further investigation, similar to the faecal immunochemical testing (FIT) to the colonoscopy procedure. Cologuard (ExactSciences) offers an approved stool molecular test for the detection of colorectal cancer with a reported increased sensitivity for detecting any stage CRC (92%) and 42% sensitivity for advanced precancerous lesions [12]. Specific cases presenting positive Cologuard test and negative follow-up colonoscopy raised concerns for lack of recommendations for patient management in these scenarios [66].

A first-line or triage test should be cost-effective, especially for screening purposes, to achieve a net cost–benefit. A recent health technology assessment evaluates EGFR T790M resistance mutation testing in patients with advanced NSCLC can lead to fewer tissue biopsies although a follow-up confirmatory tissue biopsy is required when liquid biopsy tests negative [67]. EGFR T790M mutation detection from urine has also been shown to be feasible for NSCLC patients to reduce biopsy procedures and mitigate biopsy related complications [68].

In a similar approach, the ExoDx Prostate test (ExosomeDx, a Bio-Techne brand), can be used to assess cancer risk in patients with elevated prostate specific antigen (PSA) to assist the decision to proceed or defer a prostate biopsy. ExoDx is the first exosome-based (RNA biomarkers) liquid biopsy solution to receive a Breakthrough Device Designation by the U.S. FDA [69]. Prostate cancer screening

by PSA has highlighted the risks of over diagnosis and over treatment accompanied by a lack of tangible benefit [70, 71]. This created a need to better inform clinical decisions to follow-up with invasive diagnostic procedures and treatment and accentuates the need for sensitive tests that are also highly specific. Specific clinical applications require performance parameters that balance risk of non-detection with overtreatment depending on the backbone standard of care tests.

#### **3.3 Liquid biopsy for prognosis and therapy intervention**

CellSearch® (Menarini Silicon Biosystems), a CTC detection system, was the first liquid biopsy approach to be approved by FDA in 2004. The CellSearch technology immunomagnetically captures CTCs from whole blood, that express the Epithelial cell adhesion molecule (EpCAM) and enumerates CTCs with the profile of CD45 negative and cytokeratin 8, 18, and/or 19 positive [72]. The CellSearch system provides prognostic information for patients with metastatic breast, prostate or colorectal cancer. A major limitation of this method is the reliance on the EpCAM marker. CTCs have been described to be heterogeneous and not all CTCs express EpCAM. Such methods are restrictive to the epithelial phenotype and have intrinsic selection bias [73]. Label-free CTC enrichment solutions, such as Parsortix® (ANGLE) and ClearCell® FX1 system (Biolidics) are European CE marked as *in vitro* diagnostic device (CE-IVD) solutions for CTC enrichment but require downstream analysis to derive clinically relevant information. Moreover, isolated CTC remain viable and can potentially be cultured and studied further although finding optimal conditions for culturing CTC subtypes is challenging [74]. CTC enrichment by size discrimination shows a reduced recovery rate (~60%) for smaller sized cell lines (SKBR3) [75] presenting with a selective enrichment and failing to detect a subset of cells similarly to immunoisolation methods. CTC enrichment by depletion of leukocytes also results in reduced recovery [76]. Current advances in flow cytometry resolution and imaging may enable the suppression of pre-enrichment to enable a quick and efficient detection of CTC [77–79]. These approaches have a definite role in therapeutic monitoring, identifying treatment response and early resistance and are ready for clinical studies [80, 81].

ctDNA abundance, mutation count and a KEAP1, KRAS, MET signature predict overall survival in advanced NSCLC patients (N = 949). Interestingly, patients with at least one ctDNA clearance during the course of treatment had a significantly better progression-free survival and overall survival than patients with consistent ctDNA levels throughout treatment [82]. The prognosis and predictive potential of ctDNA is yet to be translated into practical clinical assays. While the potential role of EV in cancer prognosis has been shown [83], further studies are required to define EV isolation and prognostic correlations in larger patient cohorts.

#### **4. Current outlook for early cancer detection**

5-year survival rates for patients diagnosed with stage I and stage IV cancer respectively are 98% and 26% for breast cancer, 92% to 10% for colorectal cancer and 57% to 3% for lung cancer [84]. Earlier diagnosis would greatly improve cancer survivability but is currently a great challenge. Detecting cancer early is a cornerstone of the UK's NHS Long term plan. There have been numerous efforts to achieve early cancer screening, through public awareness (Be Clear on Cancer and Detect Cancer Early campaigns), introducing new screening tests (Bowel screening) and targeted lung health checks (following the NELSON trial) and many more.

Complex approaches, by GRAIL [85], Thrive's CancerSEEK [86], FoundationMedicine, Base Genomics, Freenome aim to expand the potential of early diagnosis from blood. Grail's Galleri, Thrive's CancerSEEK and Natera's Signatera have achieved FDA Breakthrough device status while in the trial stage. Early diagnosis remains a challenge with sensitivity being a critical factor. Achieving early diagnosis in the blood using ctDNA is more complex, mainly because there is a huge amount of "normal" DNA circulating in the blood. The smaller the cancer the smaller and less detectible the cancer signature is in the blood. As any cancer grows, it sheds more DNA, more cellular debris and more cancer cells into the bloodstream which eventually leads to the cancer spreading to distant organs. Although the ctDNA shedding rate can vary among patients, a mathematical model can predict tumour size by assessing haploid genome equivalents per plasma volume (correlation: R2 = 0.32; P = 2.6x10–16) [87]. The smaller the tumour, the higher the probability of a false negative result for a particular actionable mutation.

Till date there is no FDA-approved solution for early cancer detection from blood with targeted panel solutions available as ancillary diagnostics from stools for colorectal cancer (ColoGuard & Epi ProColon) and from urine for bladder cancer (Xpert Bladder Cancer detection & Uromonitor). Interestingly, a blood test detecting Septin 9 (SEPT9) methylation to aid the detection of hepatocellular carcinoma (HCC) in patients with cirrhosis, has been CE-IVD marked (HCCBloodTest by Epigenomics) [9].

Following are some illustrative examples of ongoing clinical studies investigating the application of liquid biopsy for multi-cancer detection.

#### **4.1 CancerSEEK, PapSEEK, UroSEEK**

A series of liquid biopsy tests for early diagnosis have been developed at the Johns Hopkins University: CancerSEEK, PapSEEK and UroSEEK.

CancerSEEK measures 8 protein biomarkers by immunoassays and mutations on 16 genes by PCR and sequencing in blood samples to detect and localise the cancer. A study of eight cancer types (colorectal, ovary, pancreas, breast, upper gastrointestinal tract, lung and liver) resulted in a median sensitivity of 70%, ranging from 33% in breast and 98% in ovarian cancer. Across stages of the disease the test was 43%, 73% and 78% sensitive respectively [86]. In a following prospective, interventional study (DETECT-A) CancerSEEK was coupled with positron emission tomography– computed tomography (PET-CT) for cancer detection. During this trial, the blood test sensitivity for all cancer types was 27.1% and specificity of 98.9%. Of note, 108 participants out of 10,006 in this study had a positive blood test without cancer, most of who (101) were followed up by PET-CT and 38 also had a subsequent procedure to rule out cancer [34]. This highlights the importance of the high specificity levels required for potential screening tests and clearly defined second-line testing with a good consideration of the risk of overtreatment.

PapSEEK was developed for Pap brush samples or Tao brush samples and detects aneuploidy and somatic mutations on 18 genes by multiplex-PCR (AKT1, APC, BRAF, CDKN2A, CTNNB1, EGFR, FBXW7, FGFR2, KRAS, MAPK1, NRAS, PIK3CA, PIK3R1, POLE, PPP2R1A, PTEN, RNF43, and TP53). 81% endometrial cancer and 29% ovarian cancer were detected by PapSEEK on Pap brush samples which increased to 93% and 45% respectively when intrauterine samples were collected using a Tao brush. False positive rate was 1.4% for Pap brush samples which improved to >99% specificity when using the Tao brush [88].

UroSEEK detects mutations within 11 genes (FGFR3, TP53, CDKN2A, ERBB2, HRAS, KRAS, PIK3CA, MET, VHL, MLL, TERT promoter) as well as aneuploidy. In an early detection cohort UroSEEK was 83% sensitive and 93% specific while in the surveillance cohort sensitivity was 71% and specificity 80% which was a significant improvement compared to cytology alone [89].

#### **4.2 Galleri**

Recently, the UK's National Health Service (NHS) has taken bold steps and will be partnering with GRAIL to confirm Galleri's clinical and economic performance in the NHS system [90]. The study will investigate the effectiveness of the Galleri test on 140,000 asymptomatic, healthy patients and 25,000 participants showing signs and symptoms of cancer. The Galleri test is a genome-wide test interrogating methylation patterns in plasma samples, optimised during the The Circulating Cell-free Genome Atlas Study (CCGA). Methylation patterns, measured by whole genome-bisulfite sequencing, were found to perform better than whole genome and targeted (507genes) sequencing for the detection of cancer [85]. A further study to evaluate the performance of the optimised method, included 6,689 participants with more than 50 cancer types which were approximately equally distributed across stage of the disease (I- IV). The test achieved 99.3% specificity and 55.2% sensitivity across all cancers in the validation sets. Sensitivity improved when detecting more advanced cancer, reporting a detection of 39% of Stage I cancer, 69% of Stage II cancer and 83–92% sensitivity in Stage III & IV cancer. Cancer detection performance varied across different cancer types [85].

Such clinical studies represent landmark studies that paving the way for clinical service to initiate the introduction of liquid biopsy technologies for cancer screening.

### **5. Potential for EVs and integrative solutions**

Tumour derived extracellular vesicles (EV) show great potential for liquid biopsy. EVs carry protein, DNA, RNA and small-RNA cargo shielding it from degradation [33, 91]. The cargoes carried by EVs represents a molecular fingerprint of the cell of origin [30]. A study comparing cfDNA and EV DNA in pleural effusion for EGFR testing by qPCR, shows an improved detection rate when using EV DNA (72.2% vs. 61.1%) [28]. Moreover, research has described that 90% of prostate cancer ctDNA is found in large EVs [92]. EVs are released in abundant quantities presenting an intriguing solution for increase detection sensitivity [30]. TearExo® is a potential solution detecting EV diagnostic and prognostic markers from tears for diagnosis of breast cancer [27].

Despite these advantages, implementation of EVs into clinical cancer diagnostics is hampered by challenges and lack of standardisation in the isolation methods and analytical sensitivity [93]. With improved and standardised technologies and focused efforts, tumour EVs can potentially be used to selectively pick out tumourderived DNA from a background of normal DNA enhancing ctDNA technology sensitivity but also enable analysis of DNA, RNA and protein from the same sample, potentially for yet earlier detection.

Several challenges remain to be elucidated. EV populations are diverse and the functions and contents of EVs across their size distribution is not well known. The shedding rates across different tumour types or disease states are cannot be assessed without a standardised and accurate method for sizing and specific size isolation. Several concerted efforts are leading the way to technical standardisation to robustly understand the role of EVs [93, 94].

Solutions that integrate multi-modal testing are budding, such as Epic Sciences' Comprehensive cancer profiling that performs CTC, ctDNA and immune-cell analysis from a single blood draw relying characterising protein, morphology and genomics. CancerSEEK integrates protein markers with ctDNA analysis. Such approaches may be key to unlock the full potential of liquid biopsies but present technical, workflow and interpretation challenges [95].

#### **6. Conclusion**

Liquid biopsy is currently a clinically useful tool for assisting companion diagnostics, cancer screening programmes and surveillance. There is an evident prevalence of ctDNA solutions which are already available for the companion diagnostic space and are expected to be accessing the earlier diagnostic space soon following clear delineation of the clinical value and applications. CTC solutions, the first approved liquid biopsy tool for clinical use, have a role in defining cancer prognosis and therapeutic monitoring for timely and effective therapeutic decisions. The clinical value and approach remain to be defined by further clinical studies and translation into practical, clinically applicable solutions.

The full potential of EVs is being uncovered with concerted efforts to establish rigour and standardisation driving reproducible research. Apart from the role of EVs for therapeutic applications, EVs show great potential for early diagnosis of cancer, therapeutic monitoring and post-therapeutic surveillance. Versatile and open technologies could facilitate integrated solutions to maximise the potential of liquid biopsy. Nonetheless, translation to the clinical setting will require practical solutions with clearly defined clinical applications.

Promising data is emerging across potential applications for liquid biopsy with multi-cancer early detection solutions expected in the near future.

#### **Author details**

Shawn Baldacchino Applied Biotech Ltd, Cambridge, UK

\*Address all correspondence to: shawn.baldacchino@appliedbiotechltd.com; shawn.baldacchino@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Current Advances in Clinical Application of Liquid Biopsy DOI: http://dx.doi.org/10.5772/intechopen.96086*

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## Section 5 Pathophysiology

#### **Chapter 10**

### Dopamine: The Amazing Molecule

*Mehveş Ece Genç and Emine Nur Özdamar*

#### **Abstract**

Dopamine (DA) is a neurotransmitter in the central nervous system (CNS) and has been implicated in the pathogenesis of various diseases of motor functions and psychiatric conditions. Dopamine is also the key modulator for motivational behavior and brain reward system and regulates food intake as well. It has some neuroendocrine function too. It is noteworthy that dopamine has so many diverse roles in the CNS. DA has various pathways such as the Nigrostriatal pathway, Mesolimbic pathway, Mesocortical pathway and Tuberohypophyseal pathway. It has D1, D2, D3, D4 and D5 metabotropic receptors and interacts with cholinergic, GABAergic, opioidergic and glutamatergic systems. DA also activates diverse second messengers and pathways. These complicated interactions partly explain its diverse actions. The aim of the present chapter is to summarize data on the contribution of DA in the pathogenesis of many conditions such as Parkinson's disease, Schizophrenia, Attention Deficit Hyperactivity Disorder and addiction.

**Keywords:** dopamine, Parkinson's disease, Attention deficit hyperactivity disorder, valproic acid

#### **1. Introduction**

Dopamine is a neurotransmitter both in the periphery and in the central nervous system. It is synthesized from the amino acid tyrosine. Tyrosine is first hydroxylated by the rate limiting enzyme tyrosine hydroxylase to Levodopa (L-DOPA) and L-DOPA is further converted to Dopamine with the action of L-Amino acid decarboxylase.

#### **2. Dopamine and Parkinson's disease**

Parkinson's disease (PD) is a neurodegenerative disorder characterized by progressive loss of dopamine (DA) neurons in substantia nigra pars compacta. According to the epidemiological studies cigarette smoking, coffee, anti-inflammatory agents and high serum uric acid are protective against PD. Teaching staff, medical personnel, people who work in farms, people who are exposed to lead or manganese and people who are deficient of vitamin D have increased risk of getting the disease [1].

There is a prodromal phase in PD before the disease fully develops. Hyposmia and constipation appear first, then depression follows, and finally the motor symptoms become evident such as bradykinesia (slowness of movement), tremor (involuntary shaking, most commonly of the hands) and rigidity (stiff or inflexible muscles), [2]. The cardinal features of PD are summarized in **Figure 1**.

**Figure 1.** *Cardinal features of Parkinson's disease.*

#### **3. Incidence and prevalence of Parkinson's disease**

The prevalence and incidence of PD may differ depending on various determinants such as age and gender [3]. A higher incidence of PD were reported in males than females with a ratio ranging between 1.37 to 3.7 [4]. Several studies reported that the prevalence and incidence of PD rises with age [5], with a prevalence rate of 108–257 per 100.000 persons and incidence rate of 11–19 per 100.000 persons [6].

#### **4. Features of Parkinson's disease**

Hyposmia is an important feature of Parkinson's disease and might be a significant and valuable sign to take some precautions. As well known olfactory function declines as people age and might have detrimental effects in those people [7].

Dopamine is part of the neuronal system in olfactory system. Gamma Aminobutyric Acid (GABA), Acetylcholine and norepinephrine have been the other transmitters [7].

More recently α-synuclein (α-syn) overexpression in olfactory bulb has been observed and it was related to symptoms and pathology of Parkinson's disease [8]. Scientists developed methods to detect protein aggregation by nasal brushing as a guidance to early diagnosis [9]. Nasal brushing is a non-invasive technique to pick up olfactory epithelium from the olfactory mucosa which is thereafter analyzed by real-time quaking-induced conversion (RT-QuIC) assay. This method has a high sensitiviy (97%) and specificity (100%) for Creutzfeldt–Jakob disease (a neurodegenerative disease) diagnosis [10].

In addition to Parkinson's disease, other neurodegenerative disorders such as Alzheimer's disease and Amyotrophic Lateral Sclerosis are characterized by accumulation of particular proteins in cellular aggregates.

#### *Dopamine: The Amazing Molecule DOI: http://dx.doi.org/10.5772/intechopen.95444*

α-Syn is an important molecule of the synapse, under physiologic conditions it regulates synaptic function in its soluble form. In PD patient brains monomers form amyloid-β sheet fibrils that aggregate into Lewy bodies [11]. These presynaptic alterations mediated by accumulation of α-Syn change the size of vesicle pools and function of vesicles, impair neurotransmitter exocytosis, vesicle recycling and neural communication [2].

#### **5. Neuroinflammation and Parkinson's disease**

Injury, environmental toxins, endogenous proteins, infection or age cause microglia to become activated and release of inflammatory cytokines such as IL1-β, TNF-α, nitric oxide (NO) and reactive oxygen species (ROS) that cause dopaminergic neuronal deterioration. Damaged neurons further stimulate microglia by α-Syn, ATP and ROS [12]. The events related with neuroinflammation are summarized in **Figure 2**.

Neuroinflammation has been implicated in DA cell loss during Parkinson's disease [13]. In experiments conducted on rats and mice Kurkowska and colleagues have shown that dexamethasone treatment prevented striatal DA depletion and protected DA neurons in substantia nigra (SN) [14].

Aspirin given orally increases the expression of tyrosine hydroxylase in the nigra and upregulates DA in the striatum in both normal and α-syn transgenic mice, indometacin on the other hand, protects neurons in the 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine (MPTP) model of PD and diminishes microglial activation in the effected area [15, 16].

COX-2 inhibitor celecoxib has also been found to be effective in rats injected with 6-hydroxydopamine (6-OHDA) in the striata, a method that caused retrograde neuronal damage, by reducing DA cell degeneration [17].

In addition to these drugs, the antiinflammatory cytokine IL-10 and peroxisome proliferator-activated receptor gamma (PPAR-γ) ligand rosiglitazone have been found effective in 6-OHDA rat and MPTP mouse models of PD [18, 19].

However, unlike animal studies there are conflicting results in human reports. While several epidemiologic studies reported that the use of non-steroidal antiinflammatory drugs (NSAIDs) decrease the risk of PD [20], recent metaanalyses found no association between NSAIDs and the risk of Parkinson's disease [21, 22].

#### **6. Parkinson's disease and valproic acid**

Valproic acid (VPA) is an inhibitor of histone deacetylases (HDACs), and has been used in the treatment of epilepsy, migraine, schizophrenia and bipolar

#### **Figure 3.**

*Photomicrographs demonstrate TUNEL positive neurons and graph comparing TUNEL positive neurons in right substantia nigra pars compacta. Sham operated (S), sham operated and VPA treated (SV), sham operated and L-DOPA treated (SL), Nigrally 6-OHDA injected (PD), Nigrally 6-OHDA injected and VPA treated (PV), Nigrally 6-OHDA injected and L-DOPA treated (PL), Nigrally 6-OHDA injected and VPA and L-DOPA treated (PVL) groups. Apoptotic neuron (TUNEL positive neuron) is demonstrated with arrow. The magnification is x20. Scale bar represents 100* μ*m. Nigrally 6-OHDA injected and VPA and L-DOPA treated (PVL) groups. Data are presented as percentage of apoptotic neurons in right substantia nigra pars compacta compared to total neurons in right substantia nigra pars compacta. Data are expressed as mean ± SEM. \*\*\*p < 0.001 vs. S, SV, SL; ###p < 0.001 vs. PD;* ΘΘΘ*p<0.001 v PL.*

#### *Dopamine: The Amazing Molecule DOI: http://dx.doi.org/10.5772/intechopen.95444*

disorders [23]. It increases GABA activity, blocks Ca++ and Na + channels and decreases N-methyl-D-aspartate (NMDA) mediated excitation [24, 25].

In a study conducted in our laboratory, VPA was found to be effective in a PD model induced by 6-OHDA injected into the SN of rats. Sham operated animals demonstrated trace amounts of apoptotic neurons, 6-OHDA caused significantly increased amounts of TUNEL positive neurons in susbstantia nigra pars compacta as compared with sham operated groups. Valproic acid treatment significantly diminished the apoptotic neurons in susbstantia nigra pars compacta as compared with 6-OHDA lesioned and saline treated animals. Valproic acid treatment also significantly diminished the apoptotic neurons as compared with 6-OHDA lesioned and levodopa treated animals [26]. The results of the experiment have been illustrated in **Figure 3**.

The neuroprotective effects of VPA could be associated with the glycogen synthase kinase-3 (GSK3) alpha and beta, Akt, ERK and phosphoinositol pathways, tricarboxylic acid cycle, GABA and oxidative phosphorylation (OXPHOS) system [27].

#### **7. Parkinson's disease and therapeutic aids**

Parkinson patients are being treated with DA precursor L-DOPA that increases the synthesis of dopamine in the substantia nigra; Catechol-O-methyltransferase (COMT) inhibitors that increase the central uptake of levodopa (entecapone, talcapone), Monoamine oxidase B inhibitors (MAO-B inhibitors) that decrease the metabolism of dopamine (selegiline, rasagiline) and finally D1 and D2 receptor agonists pramipexole and ropinirole.

However, chronic use of dopaminergic medications in the treatment of Parkinson's disease (PD) might cause some motor and non-motor behavioral side effects such as dyskinesias, impulse control disorders (ICDs), (uncontrollable gambling, shopping, binge eating, hypersexuality), punding (aimless, stereotypical repetitive behaviors) and compulsive medication use [28]. The prevalence of ICDs in PD patients using dopamine agonists was reported to range from 2.6% to 34.8% [29]. This brings us to another significant function of dopamine which is IMPULSIVITY.

#### **8. Dopamine and impulsivity**

Impulsivity implicates a variety of behaviors that are unsuitable or overly risky, immature, poorly planned, and often results with undesired consequences. Impulsivity is the main symptom of a wide range of psychiatric disorders such as ICDs and drug addiction. Moreover, attention deficit hyperactivity disorder (ADHD) and mania, also contribute to the expression of impulsivity [30]. It is thought that dopamine has an important role in impulsive behavior, based on the therapeutic effects of psychostimulant drugs such as amphetamine and methylphenidate that increase dopaminergic transmission in attention deficit hyperactivity disorder. Namely, there is a paradox regarding why dopamine releasing psychostimulant drugs ameliorate ADHD symptoms, while the drugs that enhance dopamine transmission increase impulsivity, as in the case of medication induced adverse reactions in PD. This discrepancy means that other neurotransmitters also influence impulsivity [31].

The dopamine system and D2 receptors seem to be closely related to impulsive choice. The activation of D2 receptors in the nucleus accumbens region causes an increase in motor impulsivity. There are many studies highlighting the relationship between serotonin, norepinephrine and dopamine dysregulation and impulse control disorders. Particularly, studies with human and animal subjects demonstrated the role of serotonin and dopamine in impulsivity. The importance of serotonin and dopamine interaction in the nucleus accumbens is underlined for impulse control disorders [32, 33].

#### **9. Dopamine and attention deficit hyperactivity disorder**

ADHD is one of the most common psychiatric disorders of childhood which is characterized by problems in attention, concentration, mobility and impulse control. Dopamine and noradrenaline levels are low and dysregulated in ADHD and it is thought that symptoms of inattention may indicate dopamine and/or noradrenaline dysfunction in important regions of the cerebral cortex that control cognitive functions [34]. Neuroanatomical regions (cortical-striatal-thalamiccortical network) that are thought to be important in ADHD are regions known to be the area of dopamine concentration.

Dopamine and norepinephrine are the most well studied neurotransmitters in understanding the etiology of ADHD. These neurotransmitters and their degradation products are found at a lower rate in the cerebrospinal fluid (CSF), blood and urine of children with ADHD. Molecular genetics and neuroimaging studies, as well as therapies with stimulant drugs, have also supported the hypothesis of dopamine dysfunction in ADHD etiology. The fact that methylphenidate, which acts by preventing dopamine reuptake in ADHD pharmacotherapy, has brought the dopaminergic system to the fore in candidate gene studies. Molecular genetic studies have indicated some candidate genes related to the dopamine system, such as D1, D2, D3, D4 and D5 receptors and dopamine transporters (DAT). Among these, the genes that are most emphasized and with positive findings are DRD4 (D4) and DAT1 genes (**Table 1**).

Since stimulant drugs provide increase in extracellular DA by blocking DAT, molecular neuroimaging studies have mostly focused on the DAT [34]. In the meta-analysis of positron emission tomography (PET) and single photon emission computed tomography (SPECT) studies, higher striatal DAT density was reported in patients with ADHD [35].


#### **Table 1.**

*Candidate genes studied in the dopaminergic pathway.*

#### **10. Dopamine and addiction**

Addiction is defined as seeking and using substances and chemicals such as alcohol, cannabis, morphine, metamphetamine, nicotine despite their physical and psychological negative effects on individuals. The negative effects are characterized

#### *Dopamine: The Amazing Molecule DOI: http://dx.doi.org/10.5772/intechopen.95444*

by having trouble in stopping the intake after starting to use and by causing negative emotional states such as dysphoria, anxiety and irritability in case of discontinuation. In addition to addiction, these substances cause changes in the reward system, decision-making, memory and brain structures related to memory.

The mesocorticolimbic system, which is formed by the integration of mesolimbic and mesocortical pathways, is an important part of the reward system and dopamine (DA) is the main neurotransmitter in this system. The addictive substances essentially activate the mesolimbic dopamine pathway. Apart from the mesocorticolimbic system, another dopaminergic pathway, the nigrostriatal pathway also plays a role in addiction development.

There is good evidence that synaptic changes in mesolimbic pathways are involved in food and drug addiction. Namely, drug addiction and obesity are related to decreased striatal dopamine D2 receptor levels [36, 37]. Decreased D2 receptor levels in the striatum was also reported in patients with alcohol dependence [38]. In addition, lower striatal dopamine D2/D3 receptor levels were reported in cocaine and metamphetamine addicted subjects [39].

Even though the drugs that enhance DA activity could be effective for alcohol and/or substance use disorders, contradictory results have been reported by several studies. Hence, there is not enough evidence regarding the use of DA agonists for addiction [40].

#### **11. Dopamine and schizophrenia**

The neurotransmitter systems that have been investigated in schizophrenia are dopamine, noradrenaline, serotonin, glutamate and GABA. The most well-studied neurotransmitter in schizophrenia is dopamine. The fact that psychostimulant agents that increase dopamine activity such as amphetamine and cocaine cause schizophrenia-like symptoms in normal individuals and that neuroleptics that block postsynaptic dopamine D2 receptors regress the symptoms of schizophrenia supports the dopamine hypothesis. Overactivation of the dopaminergic neurons in the mesolimbic pathway is thought to play a role in the emergence of delusions and hallucinations, which are positive symptoms of psychosis. Neuroreceptor imaging studies indicated the higher levels of dopamine D2 receptor availability in individuals with schizophrenia [36]. The main mechanism of action of the current antipsychotic drugs is the antagonism of mainly dopaminergic D2 receptors [41].

#### **12. Conclusion**

As can be observed easily dopamine is involved in the pathogenesis of many conditions such as Parkinson's disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. It is the key substance for impulsivity and addiction as well. *Pathology - From Classics to Innovations*

#### **Author details**

Mehveş Ece Genç\* and Emine Nur Özdamar Faculty of Medicine, Department of Medical Pharmacology, Yeditepe University, İstanbul, Turkey

\*Address all correspondence to: egenc@yeditepe.edu.tr

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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### *Edited by Ilze Strumfa and Guntis Bahs*

Pathology is a diagnostic medical specialty dealing with the evaluation of tissues and body fluids to diagnose disease and predict prognosis or response to treatment. In particular, a biopsy is the "gold standard" in the diagnostics of certain diseases, especially tumours. *Pathology - From Classics to Innovations* is a collection of original peer-reviewed studies and review articles by a truly global scientific team on the recent advances in pathology. Chapters discuss classic surgical pathology and the application of microscopic tissue studies in anatomic research, immunohistochemistry, molecular pathology, liquid biopsy, and digital pathology.

Published in London, UK © 2021 IntechOpen © Stepan Khadzhi / iStock

Pathology - From Classics to Innovations

Pathology

From Classics to Innovations

*Edited by Ilze Strumfa and Guntis Bahs*