Biosensors

### **Chapter 8**

## Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs)

*Susan McDonnell, Raymon Floyd Principe, Maycou Soares Zamprognio and Jessica Whelan*

### **Abstract**

Therapeutic antibodies dominate the biopharmaceutical market with continual innovations being made to provide novel and improved antibody treatment strategies. Speed to-market and cost-efficiency are of increasing importance due to the changing landscape of the biopharmaceutical industry. The increasing levels of competition from biosimilars, the increase in small volume products and political and social pressure to reduce the cost of treatments are some of the challenges currently being faced. Chinese hamster ovary (CHO) cells have been the workhorse in the production of therapeutic antibodies over the last 36 years due to the robust nature and high productivity of these cell lines. However, there are many biomanufacturing challenges remaining. The aim of this review is to examine the current biological, and engineering challenges facing the biomanufacturing of antibodies and to identify the mitigations and emerging technologies that can be employed to overcome them. Developments in cell line engineering, intensified processing, continuous manufacturing, automation and innovations in process analytical technologies and single use technology will be discussed with regard to their ability to improve the current performance of mAb production processes.

**Keywords:** mAbs, biomanufacturing, challenges, emerging technologies, therapeutic antibodies

### **1. Introduction**

Therapeutic monoclonal antibodies, referred to as mAbs throughout this chapter, have emerged as the dominant player in the Pharmaceutical/Biopharmaceutical sector and are extremely effective agents for the treatment of cancer, inflammatory disorders and infectious diseases [1]. The effectiveness of mAbs as therapeutics is due primarily to their specificity in recognizing and binding to specific antigens through the antigen binding site. The efficacy of full length mAbs as anti-cancer agents is due to their ability to activate both complement-dependent cytotoxicity (CDC) and antigen-dependent cell cytotoxicity (ADCC) [2].

Worldwide, the mAbs market represents approximately 50% of the biotherapeutics market and according to Global Market Insights Inc., the global antibody therapy market is projected to reach \$445 billion by 2028 which represents a 13.2% compound annual growth rate (CAGR) [3]. The first mAb, Muromonab-CD3 (proprietary name rather than brand name will be used throughout this chapter) was approved in 1986 and in June 2021 a landmark achievement was reported with the approval of the 100th mAb by the FDA [4]. As of May 2022 there are currently over 111 mAbs approved by either the European Medicine Agency (EMA) or the US Food & Drug Administration (FDA) [5]. In addition, there are over 15 mAbs pending confirmation of approval by either one or both regulatory agencies. Interestingly, several of the products pending approval are targeting the Covid-19 spike protein [6]. Over the same time period marketing authorisation for several products including Daclizumab, a humanized mAb for the treatment of multiple sclerosis, has been withdrawn and several products including the first approved mAb Muromonab-CD3 have been discontinued. Biosimilars are generic versions of biologics and thus far, over 20 mAb biosimilar products have been approved by the EMA or FDA [7]. Humira, a human antibody targeting tumor necrosis factor alpha used to treat rheumatoid arthritis and related disorders, is the top selling biopharmaceutical drug with a market value of \$20 billion in 2021 [8]. Currently at least 8 biosimilar versions of Humira have been approved in various markets [7].

Immunoglobulin G (IgG) the dominant type of immunoglobulin manufactured is composed of two heavy (H) chains and two light (L) chains and has a molecular weight ranging from 140 to 160 kDa depending on the type of IgG subtype. Each of the light chains contain a variable (VL) and constant (CH) domain and the heavy chains contain one variable (VH) and 3 constant domains (CH1, CH2 and CH3). mAbs contain a number of glycosylation sites in the CH3 region. There is a huge variety in the type of mAb products approved with the major mAb formats being: canonical (full-length antibodies), antibody drug conjugates (ADCs) and antigenbinding fragments (Fabs). **Figure 1A** shows the distribution of the major types of mAbs currently approved by EMA or FDA [5].

Currently there are 92 canonical antibodies approved (83% of total) which are typically of the IgG1 subtype, have a molecular weight of ~150 kDa and are subdivided into chimeric, humanized or human antibodies. The majority of approved

### **Figure 1.**

*A: Pie chart shows number of different mAbs format approved B: Bar chart shows the number of products produced in a range of host cells.*

### *Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

canonical mAbs target autoimmune diseases and many different types of cancers. Most canonical mAbs are monospecific with 3 bispecific antibodies (bsAbs) which recognize two different antigens (Emicizumab, Amivantamab and Faricimab) approved. ADCs are full-length antibodies with the addition of a highly toxic molecule usually attached to cysteine residues via a linker molecule. Upon arrival at specific cancer cells, targeted by the mAb component, the ADC is internalized by the cell and the toxin released through enzymatic cleavage [9]. ADCs represent highly specific and targeted therapies due to the specificity of the mAb component and currently 10 ADCs (9% of total) have been approved, of which two are targeting Her-2 positive breast cancer, ado-trastuzumab emtansine and trastuzumab deruxtecan [9]. Antibody fragments come in a variety of formats with molecular weights ranging from 12 to 50 kDa and contain a wide range of heavy and light variable and constant domains [10]. Currently, 4 Fab antibodies (4% of total) which contain the antigen binding site (i.e. one heavy and one light chain each with a variable and constant domain) have been approved. Fabs have a molecular weight between 40 and 50 kDa which improves tissue penetration due to their smaller size. The lack of the Fc domain means that these mAbs are not glycosylated so they can be produced in bacterial expression systems. There are 4 (4% of total) scFv products approved which are typically 25 kDa in molecular weight and are all produced in *E.coli* [10]*.* Interestingly, the scFv mAbs have the most diverse range of functionality: one is bispecific, one is a fusion-protein and the other is linked to an immunotoxin. The smallest of all therapeutic antibodies is the Nanobody with a molecular weight of 12 kDa. The first and currently only approved Nanobody is Caplacizumab which targets von Willebrand factor and is being used for the treatment of acquired thrombotic thrombocytopenic purpura [11].

Glycosylation plays an essential role in the biological efficacy of antibodies and is one of the critical quality attributes of mAbs [12]. N-linked glycosylation occurs in the Fc domain of the antibody. Canonical antibodies require glycosylation so production of full length mAbs is in mammalian cells, primarily CHO and murine myeloma cells (**Figure 1B**) as they have the biological capability to make these types of post-translational modifications (PTMs). CHO cells have been the workhorse in the production of antibody products over the last 36 years. CHO cells currently act as hosts for approximately 69% of all mAbs approved. Approximately 23% of approved products are produced in mouse myeloma cells lines with the predominant type being the non-secreting NS0 cell line followed by Sp2/0. Interestingly, the first mAb product approved Muromonab-CD3 was produced in a murine hybridoma cell line. A small number of Fab and scFv products that do not require glycosylation have been produced in bacterial cells, Escherichia Coli (*E.coli*). Thus far, just 1 product, Eptinezumab which is a humanized antibody has been produced in yeast cells Pichia *pastoris* [13]. Biomanufacturing of mAbs in CHO cells will be the focus of this chapter and looking at alternative expression systems is beyond the scope. Several comprehensive reviews of expression in bacterial, insect and yeast cells have been published [14–16].

**Figure 2** shows a typical process flow diagram for the production of mAb drug substance, divided into upstream and downstream processing and formulation and fill-finish. Upstream processing encompasses the steps from vial thaw through inoculum and cell expansion with the aim of generating sufficient cells for the production stage bioreactor where the mAb is produced. Downstream processing encompasses all the operations from product capture, purification to formulation and fill finish.

### **Figure 2.**

*Process flow diagram of mAb biomanufacturing process. Typical fed-batch process duration indicated.*

The biomanufacturing process is initiated with a vial of cryopreserved cells from the working cell bank (WCB) which is thawed into a small volume of media and then expanded through a series of shake flasks and bioreactors of increasing size, in order to generate sufficient cell numbers to inoculate into the production scale bioreactor. The final production vessel referred to as the N-stage bioreactor, is in the order of between 1000 and 20,000 L depending requirements. A fed-batch upstream production bioreactor step typically takes 10–20 days [17]. The production stage bioreactor duration can increase up to approximately 60 days if operated in perfusion [18]. The upper limit is determined by the validated Limit of In Vitro Cell Age (LIVCA) which is the number of generations for which the cell line has been demonstrated to be genetically stable.

The downstream process begins with recovery of the product from the bioreactor. Since CHO based systems secrete the product into the media, the product is usually harvested through centrifugation and/or depth filtration. Purification generally involves several chromatography steps for capture, intermediate purification and polishing. Affinity chromatography using Protein A which specifically binds to the Fc domain of the mAb is used to capture full length antibodies. Protein L can be used for purification of Fab fragments as it binds specifically to kappa light chains [19]. Anion and cation-exchange chromatography are typically used for intermediate purification and hydrophobic interaction chromatography can be used for final polishing. In addition to purification to >99.9%, the downstream process must include a viral removal and inactivation step before final formulation and finishing [19].

mAb processing methods have become the model for the production of both therapeutic proteins and emerging products like cell and gene therapy-based products as these have matured and been optimized over the last 36 years. However, with the increasing focus on speed-to-market and cost efficiency, it is necessary to continue to

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

innovate and improve mAb biomanufacturing. The aim of this chapter is to examine the current challenges facing the industry and to discuss the mitigations and emerging technologies that have the potential to address them. This chapter is presented in 2 sections and will focus on the *biological and engineering* aspects associated with the manufacture of mAbs in CHO cells. The main challenges and mitigations within these themes are discussed and future directions and innovations for the biopharmaceutical industry are presented.

### **2. Biological and bioprocessing challenges and mitigations involved in biomanufacture of mAbs**

Mammalian expression systems are chosen for full-length mAb production as they have the necessary cell machinery required to facilitate the correct proteinfolding and glycosylation. Advances in genetic engineering and cell line development methods have been used to improve cell productivity and glycosylation control [20]. However, cell-based expression systems are challenging due to their inherent biological nature which results in variations in product yields and protein quality inconsistencies which can lead to challenges in manufacturing and increased production costs.

### **2.1 Production cell lines**

CHO cell lines are the preferred host expression system in mAb production due to their capacity for complex human-like post translational modification, ease of genetic manipulation, lack of susceptibility to human viral infection and regulatory approval [21]. In terms of bioprocessing, CHO cells are robust and are easily adapted to grow in suspension in chemically defined and serum-free media making them readily amenable to process scale-up. CHO cell line development has generated cells with specific productivities (Qp) in the range of 5-20 pg/cell/day [22] and advances in single cell sequencing could increase this further [23]. Other mammalian cell lines like baby hamster kidney (BHK) cells and murine lymphoma cells lines such as NS0 and Sp2/0 also provide human-like glycosylation patterns but productivity levels can be significantly lower [24]. In addition, both NS0 and Sp2/0 have been shown to express two predominant glycan epitopes, galactose-alpha 1,3-Gal (alpha-gal) and N-glycolylneuraminic acid (Neu5Gc), which are immunogenic in humans and can lead to deleterious side effects [24].

### **2.2 Genetic engineering of cells**

The first step in developing a biomanufacturing process is to generate a cell line producing the desired product, referred to as a '*production cell line*'. Generation of production cell lines involves many steps as outlined in **Figure 3** and includes transfection of the gene of interest into the cells, followed by selection and screening to generate the optimal clonal production cell line for manufacturing. Once a production cell line has been generated there are regulatory guidelines in place governing the use of cells in production processes (Q5D ICH, 1998) that must be followed. The most common industrial approach for cell line development is transfection of the gene of interest using a non-targeted plasmid delivery system that contains a selection marker (Section 2.3) to enable the selection of stably transfected cells. Ideally, a high-quality

**Figure 3.**

*Cell line development process showing the steps required for the generation of production cell lines. Created with BioRender.com.*

production cell line should demonstrate high stability, scalability and high titer levels, in order to provide reproducible results with consistent product quality attributes.

CHO cell lines used commercially were derived from the original spontaneous immortalized culture established in 1956 by Dr. Theodore Puck [25]. Several variants referred to as subclones were generated using both chemical and radiation mutagenesis. The most frequently used variants are CHO-K1 (single copy of dihydrofolate reductase (DHFR)), CHO-DG44 (both copies of DHFR missing) and CHO-DUBX [26]. The plasmids typically used in the transfection of the genes encoding the product are not designed for integration at specific chromosomal sites so this step generates a population or pool of cells with a wide range of expression levels that reflects the gene copy number and the transcriptional activity of the locus based on the integration site [27]. The transfection efficiency can range between 15 and 80% depending on the system used [28]. This means that if 1 million cells were transfected, potentially between 10,000 and 100,000 potential new cell lines can be generated. This random integration can provide a diverse range of expression levels but can also result in integration into unstable areas of the genome [29], resulting in varying levels of expression and lack of genetic stability.

Although the original CHO cell line contained 22 chromosomes, the subclones used commercially contain a range of chromosome numbers, e.g. CHO-K1 typically contains between 18 and 21 chromosomes [30]. CHO cells are inherently genetically unstable which has resulted in a genetically and phenotypically diverse lineage, manifested by many single nucleotide polymorphisms (SNPs), copy number variations, and karyotypes [31]. A recent review by Wurm and Wurm described CHO cell lines as having a "quasi species" genome [32]. Studies have shown that over the course of passaging of CHO cells, the DNA is unstable. The notion that CHO-K1 cells were truly clonal in origin has also been questioned [32].

This random integration of plasmid DNA approach has remained relatively unchanged over the last 36 years but the availability of advanced gene-editing tools now makes transfection at targeted chromosomal sites more feasible. These include *Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

CRISPR/Cas9, zinc finger nucleases (ZFNs), and transcription activator-like effector nucleases (TALENs), with alongside RNAi (RNA interference) and ribozyme engineering which facilitates "multiplexing gene-editing approach[es]" allowing precision and acceleration of genomic rearrangements for enhanced generation of successful clones with improved product yield and quality [33]. It is expected that future cell line development will include vectors targeted to stable areas of the CHO genome and will also be capable of expressing not only the transgene for the product required but additional genes involved in regulatory cell processes like apoptosis [34].

### **2.3 Selection, cloning and screening**

In order to identify the transfected cells that have stably integrated the plasmid into the host genome, a selective marker is used for selection of cells which have acquired the highest expression of the associated product gene. First generation products were produced in CHO-K1 and CHO-DG44 cells that incorporated DHFR as the selection marker on the plasmid [35]. Transfected cells could be selected in media that did not contain nucleotides required for growth in the absence of DHFR activity. One advantage of the DHFR selection system was that gene expression and ultimately product production could be amplified using methotrexate (MTX). Antibiotic resistant genes like neomycin (selected with geneticin), are frequently used. The use of glutamine synthetase (GS) enzyme as a selection marker allows selection of cells growing in media without glutamine. The GS system has been successfully employed for the production of several mAbs. CHO cells produce low levels of GS activity and require selection in methionine sulfoximine (MSX). Interestingly, several studies have shown that amplification methods using DHFR and methotrexate may be susceptible to instability of the transgene that results in a decrease of recombinant gene copies in long-term culture [36]. For this reason, the MSX-GS selection system tends to be the most widely used alternative. NS0 cells do not express endogenous GS therefore can be selected without using MSX, thereby creating a simpler selection process [37].

The guidelines for using cells to manufacture products must be strictly adhered to and a key regulatory requirement is that production cells must originate from a single clone i.e. individual cell. Following the selection process, cells must be separated or cloned into single cells using limited dilution in suspension cultures or clonal rings if cells have been adapted to grow as adherent cultures. Single cell limited dilution relies strictly on a probabilistic approach which is time consuming and offers low throughput as a process platform. The use of plasmids incorporating green fluorescent protein (GFP) and the application of fluorescence-activated cell sorting (FACS) has helped simplify this process. Following transfection, GFP positive cells can be selected as pools of transfected cells and can be automatically separated into individual cells using single-cell isolation technologies such as FACS, magnetic activated cell sorting (MACS), microfluidic and manual cell picking [38]. Advancements in automated screening and selection systems such as Clonepix and CellCelector offer multitude cell screening through immobilization of cells within a semi-solid media matrix and relies with a fluorescent identifier in the vicinity of a resulting colony [39]. Additionally, these automated cloning systems are combined with imaging analysis to provide compelling visual evaluation that can be used in real-time.

Selection and cloning generate a large number of individual candidate cell lines that require screening and evaluation to select the optimal production cell line which is challenging with regard to throughput and creates a major bottleneck in upstream process development. A key requirement is a high specific productivity level and

evaluation of mAb production by ELISA or ELISA spot assay is the first step in the screening process. A typical screening strategy will involve multiple evaluation stages in which a proportion of cell candidates are discarded after each stage to attain a small number of highly ranked possible cell line candidates [40]. A typical screening scenario involves initial screening of ~300 individual clones for productivity. Following elimination of low producing cell lines, the candidate cell line panel of ~50 is screened for proliferation capacity. Cells with high productivity (2-7 g/L) and specific growth rates (0.010-035 h-1) are then expanded into shake flasks and screened for their ability to adapt to production conditions [41]. The final step will generally involve ~5–10 cells lines grown under different bioreactor conditions in order to finally select the optimal cell line for commercial production. The introduction of miniature bioreactors such as the Ambr system allows for significant scale-down of this step and increased through-put significantly accelerating the final evaluation step.

### **2.4 Cell line characterization**

A key requirement and challenge for manufacturing is to maintain optimal productivity and consistent quality between batches of product. As part of the regulatory requirements, a master cell bank (MCB) must be created from the initial cell line generated. A WCB is generated from the MCB and a new vial of cells is used to initiate each batch. As mentioned previously there are specific guidelines that must be followed when working with cell lines and these guidelines include specific tests that must be undertaken to characterize and authenticate cells within the MCB and WCB to ensure purity, identity and stability of the cells. In terms of purity the lack of microbial or viral contamination must be confirmed. The identity of the cells can be confirmed using STR profiling. Maintaining the genetic stability of the cells for more than 60 generations at high cell density must be demonstrated [42].

### **2.5 Media selection and optimization**

Cell culture media are complex mixtures of nutrients, hormones, growth factors, salts, trace elements and buffers. Early media formulations used serum but regulatory concerns about possible prion and viral contamination led to the development of serum-free, protein-free and chemically defined media formulations that were free from animal-derived material. Serum-free media is widely used in CHO biomanufacturing and the basal media consists of 50–100 components. The optimal composition and amounts of these components must be determined to be capable of supporting cell growth and production of product with acceptable quality attributes. Overall, media development is an multiple process with iterative rounds of performance testing. Spent media analysis allows the development of feeding strategies for cells in fed-batch and nutrients like glucose and specific amino acids are routinely added to extend the lifetime and productivity of cells in culture [43]. Design of Experiments (DoE) has been used for development of cell culture media to evaluate both component concentrations and component interaction [44]. Many companies use a platform based approach and use the same media formulation for several different products.

Bioreactor systems like the Ambr systems have benefitted the media development process as it allows for much greater throughput, smaller volumes and less labourintensive experimentation. Dynamic flux balance analysis (DFBA) is a new approach which elucidates the relationship between media supplementation with amino acids, feeding strategy, increased product yield, an extended growth phase and increased

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

density [44]. DFBA illustrates that metabolic state varies more at the beginning of the culture and rather less in the middle of culture [45]. Other advancements are towards multiplexed at-line and operator-independent analytics in benchtop bioreactors such as use of multi-analyte analyzers including NIR, Raman and 2D-fluorescence spectrometry which provide useful process measurements for feed media optimization [44–45].

### **3. Engineering challenges and mitigations**

Commercial manufacture of mAbs has evolved significantly since the first approval almost 40 years ago. The unit operations and technology routinely used are mature and well-understood. However, the landscape and business considerations associated with their production continue to evolve and drive new innovations and approaches. Increased expectations on the part of regulatory authorities, a burgeoning biosimilars market, ever-growing numbers of approved mAbs and wide ranging volume requirements have resulted in new challenges that must be addressed in order to successfully meet the patients' needs while maintaining a viable business. Efforts typically focus on accelerating the time to market and reducing CoGs. There are several engineering-related challenges to achieving this, namely: process variability, sub-optimal volumetric productivity, long cycle-times, and the complexity of managing multi-product facilities [46–47]. In this section, a number of technologies and strategies capable of addressing these challenges are presented alongside the opportunities that they provide the industry with as it moves towards the paradigm of Industry 4.0.

### **3.1 Bioprocessing considerations**

The challenges facing mAb production include producing the product with a tight product quality profile, maintaining the biophysical properties of protein and reducing product and process-related impurities below the acceptable levels to meet quality specifications and ensure safety, efficacy and stability [48]. The first step is to produce a product of acceptable quality within the N stage bioreactor. Many of the critical quality attributes (CQAs) including glycosylation profile can be affected by operating conditions within the bioreactor including pH, temperature, dissolved oxygen (DO), media formulation and metabolites. Real time monitoring and control of CQAs is still aspirational and currently these attributes are at best managed through a QbD-based approach and automated control of basic parameters such as temperature, pH and DO as well as procedural controls such as raw material specifications which will be further discussed in later sections.

Impurities typically fall into two categories: product-related and process-related. Product-related impurities occur where the biophysical properties of the product are compromised and a portion of it degraded. This can occur by multiple mechanisms including aggregation, oxidation, fragmentation, deamidation and denaturation. These degradative mechanisms are the result of the conditions to which the protein is exposed such as high mechanical or physical stress due to agitation or gassing in vessels or fluid flow through piping, filtration and chromatography skids. Enzymatic reactions during cell cultivation can result in cleavage of the protein backbone and the generation of mAb fragments [49]. Aggregation where protein is converted from the desired monomers to dimers, trimers or even larger structures is one of the most

common product-related impurities that results from physical stress [50]. Chemical degradation occurs predominantly during downstream processing as a result of changes in pH or buffer solutions. This generally occurs during the viral clearance, chromatography and ultrafiltration/diafiltration (UF/DF) steps. Mitigation strategies are focussed on reducing the residence time at low pH conditions and gentle pH shifts in UF/DF can circumvent the inherent critical effects of these processes in the final mAb product [51].

Process-related impurities are introduced as a result of the materials used in the process and include growth selection agents, surfactants, purification column binding agents and viral inactivation agents. Cell lysis within the bioreactor and harvest equipment results in the release of host cell proteins (HCP) and DNA. The final product must contain less than 100 pg of cellular DNA per dose, and ppm or ng quantities of HCP per mg of antibody product [52]. Conventionally, intact cellular components are removed during the harvest step by centrifugation and depth filtration, but additional purification steps are required to remove contaminants resulting from cell lysis. Whilst Protein A affinity chromatography is the gold standard for the capture step in the mAb purification process, it can leach from the column matrix and contaminate the product and so must be removed at a later stage with additional chromatography steps like ion exchange (IEX) and hydrophobic interaction to levels less than 1 ppm or 1 ng Protein A per mg product [52].

Effective purification is challenging due to the similarities between many of the contaminants and the product of interest in conjunction with the extremely low acceptable levels of contaminants, due to the parenteral nature of mAb products. Therefore, the best approach is to minimize the generation or introduction of these species. QbD, process monitoring and control and process modeling discussed in Section 3.2 and 3.3 can be leveraged to support this goal.

### **3.2 Quality-by-design (QbD), process monitoring and control**

Much greater process variability is observed for mAb biomanufacturing processes as compared to traditional small molecule pharmaceutical processes. The main sources of variability fall into four main categories: biological factors, raw materials and consumables, operational inputs (measurements, methods, personnel and equipment) and environmental conditions [53]. Ultimately, the result of this is variable productivity and product quality, both of which must be controlled and optimized in order to minimize the CoGs. Additionally, from a regulatory perspective, the FDA's guidance document on process validation recommends that manufacturers understand and control the sources of variation [54]. Understanding and reducing variability can be achieved by effective application of QbD, process monitoring and control.

Traditionally, biomanufacturing companies have maintained that "the process is the product" or the quality-by-testing (QbT) approach. Under QbT, the product quality attributes are empirically linked with the manufacturing process and its inputs, both materials and process parameters, during the clinical phases of development, with little or no mechanistic understanding. One of the many disadvantages to this approach is that Proven Acceptable Ranges (PARs) for process parameters are extremely narrow, limiting both the opportunity for post-approval optimization and the capacity for the process to be adjusted in response to process variability [55].

QbD overcomes the limitations of QbT by taking a science and risk-based approach to drug development in order to ensure process and product understanding and to implement effective control strategies. According to the European Medicine

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

Agency (EMA): *"Quality by design (QbD) is an approach that aims to ensure the quality of medicines by employing statistical, analytical and risk-management procedures in the design, development and manufacturing of medicines"*. Summarily, this methodology is focused on the 1) identification of each source of process variability, 2) understanding of their effects on product's critical quality attributes and 3) control strategies by applying statistical inferences, such as multivariate analysis. Additionally, according to EMA, process analytical technology (PAT) is commonly part of QbD methodologies and it is defined as the system of integrated technologies and methods for control of critical quality attributes of raw and in-process materials [56]. An excellent overview of the QbD approach is provided by Yu et al. [57].

The result of using QbD during drug development is a strong understanding of the link between process inputs and product quality within the design space mapped. The benefits of this are manifold and include:


Once a mAb moves from development into production, it is necessary to implement a control strategy. There are three levels of control possible [57]:


Moving from Level 3 to 1 is desirable, due to regulatory pressure and the business benefit of reducing the CoGs through reduced variability, batch failures, process optimization and the removal of the time and cost associated with product quality testing. In order to reach Level 1, it is essential to be able to quantify both the control targets and the associated process responses. This may be done by direct measurement or with the use of predictive models coupled with indirect measurements.

Currently, a few variables (e.g. DO, pH and temperature) are measured routinely with in-line probes, however, most key process parameters (e.g. cell density and viability etc.) are measured off-line and the delay between sample extraction and analytical results can hinder the process productivity and the ability to implement

adaptive closed loop control [58]. Much work has been done to address the gap in process measurement through the development of various sensors.

Sensors can be classified by their principle and their structure:


The availability of real time process measurements is a prerequisite for the implementation of automated closed-loop feedback control which can adapt and respond to process variability in order to maintain a steady CQA profile in the final product. Automated control also reduces the risk of human error in the process. There have been reports in the literature demonstrating the capability and benefit of such control. Craven et al. [62] applied a nonlinear model predictive controller NMPC to a 15 L CHO fed-batch bioreactor to control glucose concentration at a defined setpoint (11 mM) by adjusting the feed rate to the bioreactor. The substrates (glucose and glutamine) and byproducts (lactate and ammonia) were measured by in-situ Raman spectroscopy and the concentration values were determined by a partial least squares (PLS) calibration model analysis. The determined metabolite concentrations were inputted to the NMPC algorithm which used a first principles mechanistic process model in conjunction with an optimization algorithm to determine the optimal control output or feed rate. Both simulated and real-time application of the NMPC showed similar performance and the results highlighted the feasibility and capability of NMPC for bioreactor control. While it was shown that process model inaccuracy could hinder NMPC performance, the controller showed good ability to function with both noisy and non-continuous process measurements. While there are multiple reports of the benefits of this type of control in literature, currently, it is not implemented in commercial manufacture due to the conservative nature of the biopharmaceutical industry. It is however routinely employed in other sectors such as commodity chemicals and petrochemicals e.g. Quin & Badgell [63] reported 93 industrial applications of NMPC due to the improved safety, quality and efficiency that it enables [64]. As such, it presents a future opportunity for mAb production.

In summary, innovations in and implementation of QbD, process monitoring and control in mAb biomanufacturing can address the key challenge of reduction of CoGs by increasing process capability and robustness, reducing process variability and failures and facilitating post-approval optimization.

### **3.3 Process modeling**

Process modeling or process simulation can be applied in order to address the challenges of speed-to-market and the reduction in CoGs. There are numerous types of models that may be deployed depending on the objective. These range from mechanistic to data-driven models with reports of hybrid model approaches for bioprocesses increasing in the literature [65–66].

Mechanistic models, also known as mathematical, first principle or white-box models depend on the laws of nature to describe a specific phenomenon. They require fundamental understanding of the phenomenon being studied. This is often difficult for bioprocesses due to the complexity of the system and the strong level of interaction and dependency between multiple parameters. They have high extrapolation capacity but are limited by the degree of accuracy of the model equations describing the behavior. Conversely, data-driven or black-box models rely on larger data sets and greater computational efforts in order to predict process responses, with no reference to the underlying mechanisms. This limits the ability to extrapolate predictions to unseen scenarios but significantly reduces the complexity of the model [65]. Hybrid models have elements of both mechanistic and data-driven models, circumventing the challenges of both by reducing the amount of data and level of process knowledge required. It should be noted that regardless of the type of model used, it is crucial to verify and validate the model outputs using independent or unseen datasets before using them.

Process models can be used to accelerate process development. Typically bioprocess development has a heavy reliance on experimentation under a traditional Design of Experiment (DoE) framework, augmented with prior expert knowledge. Moller et al. [67] reported the use of model-assisted DoE for bioprocess development. A mathematical model was developed that described cell growth, metabolism and antibody production for a CHO DP-12 cell line under both a batch and fed-batch mode of operation. The model was then used to reduce the boundary values for the experimental DoE. It was found that the same optimal conditions were identified for both the traditional and model-assisted approaches with a reduction in the number of experiments required from 16 to 4 in the case of batch and 29 to 4 in the case of fed-batch. Given the time-consuming, expensive nature of bioprocess experiments, this represents a significant potential to accelerate development timelines.

A key enabler for commercial production is the scale up of the bioprocess from small laboratory scale equipment sets through an intermediate scale required to supply the clinical trials to large scale commercial manufacturing plants. As discussed in Section 3.1, both the cell and the mAb product can be affected by factors such as shear stresses, extremes of temperature and pH among other things. As an example, as the production scale increases, it becomes more difficult to maintain a fully homogenous environment and so a balance needs to be identified and maintained between effective mixing and exposure of the cell and product to damaging conditions. This may be achieved empirically, however, the conditions identified by such means are potentially sub-optimal and the opportunity to develop fundamental process understanding for use subsequently for troubleshooting and tech transfer is missed. As an alternative, computational fluid dynamics (CFD) can be used to support and enhance process scale up.

CFD mathematically models fluid flow and its interactions with solid bodies by numerically solving systems of partial differential equations governing fluid dynamics problems (e.g. Navier-Stokes equations) [68, 69]. CFD can be used to derisk and support process scale up by predicting the conditions created under a range of agitation and aeration rates. For example, Mishra et al. [70] studied the effect of agitation and aeration rates on the mass transfer of oxygen and shear stress in the liquid phase of a 10 L single-use bioreactor. Their approach combined computational fluid dynamics with species transport and population balance models in order to predict the maximum total stress and energy dissipation rates that the cell culture would be exposed to. The simulations were performed for stirring speeds between 50 and 300 rpm and aeration rates between 0.1 and 0.2 LPM, considering 45% fill volume. The results indicated a maximum total stress of 34.17 Pa and energy dissipation rate of 1.352 m2 /s3 (at 300 rpm and 0.2 LPM), which are unlikely to affect mammalian cells according to the author's consulted literature. The simulations were validated by experimental determination of the oxygen's mass transfer coefficient (stirring speed range: 50 rpm - 200 rpm, 0.2 LPM and 6.75 L of liquid volume) and the observed errors (predicted *vs* experimental) were between 0.47% and 10%.

Process modeling can support a reduction in CoGs via a number of approaches. One such approach is the use of multivariate data analysis to generate a "golden batch trajectory", a form of data-driven process model, against which real time production plant data is compared. The process insight gained can be used to rapidly identify root causes for batch failures and deviations and to prevent them reoccurring, hence reducing the rate of batch failures and process variability experienced. The knowledge gained can also be used to fine-tune the Normal Operating Ranges (NORs) for a process within its design space and maximize the productivity or particular CQA of the product. Sokolov et al. [71] applied multivariate analysis in the form of partial least square regression - PLSR to predict mAb-based product quality attributes (aggregates, fragments, charge variants and glycan profile) from process data (media supplements, pH and temperature shifts). The data set was obtained from a 91 run DoE at milliliter scale and the model performance was evaluated using the root mean square error in cross-validation (RMSECV). They firstly used principal component analysis (PCA) to analyze the correlation among 14 product quality attributes (QAs) and, since their findings indicated a strong correlation among QAs, they concluded that the variables should be treated as one characteristic. Additionally, PLSR1 and PLSR2 were used to predict product quality attributes and provided comparable prediction accuracy. The PLSR2 models were further investigated by the addition of genetic algorithm (GA), in which the results became more accurate and, in complex cases, the GA was able to remove noise, inconsistency and redundancy in the data set. Availability of such models can also enable statistical model predictive control the benefits of which were be discussed further in Section 3.2.

Digital twins are another approach to supporting a reduction in CoGs. Essentially, a digital twin is a digital representation of a physical process. The application is similar to that of the golden batch trajectory, however, digital twins are typically hybrid process models which may leverage PAT and other process monitoring (see Section 3.2). They are used to identify process bottlenecks, key engineering targets and identify operational strategies that improve the reliability and productivity of their physical twin. As an example, a digital twin of a production bioreactor could represent the physiology and metabolism of the cell culture by applying genome-scale metabolic models (e.g. Flux Balance Analysis - FBA, with appropriate objective function and adequate constraints) alongside the process kinetics obtained from in-line

monitoring (e.g. Raman-based monitoring system) [72, 73]. Digital twins are key enablers of Industry 4.0, which seeks to revolutionize how industry operates through the use of smart, autonomous systems running on data and machine learning and have huge potential to improve the biomanufacturing of mAbs [66].

### **3.4 Process intensification**

An intensified process can be defined as one that increases productivity (e.g. per batch, per facility) and/or reduces environmental impact (energy, waste, materials), facility footprint (smaller equipment, shorter process streams), manufacturing costs, process times, or process bottlenecks. It should be noted that having a genetically stable cell line with good growth and productivity characteristics and media systems capable of supporting the increased nutrient demands are prerequisites for upstream process intensification.

The pre-production stage encompasses all process steps before the production bioreactor, i.e. cell revival from the working cell bank (WCB) and the inoculum and seed train (**Figure 2**). These steps represent a significant portion of the process cycle time and typically require highly skilled labour and expensive equipment and infrastructure in order to be reliably executed. Two main approaches to circumventing the time and resources required at this stage have been reported in the literature, namely the modification of the cell banking approach to provide a greater number of cells upon thaw by either increasing volume or cell density or a combination of both and the use of the perfusion mode of operation at the N-1 seed bioreactor stage.

Intensification of cell banking eliminates multiple expansion steps which reduces the resources and time required to inoculate the production reactor, an example of which is described by the work of Seth et al. [74]. Their work investigated the cryopreservation of CHO cells at low density (LD, ~30x106 cell/mL), mid density (MD, ~70x106 cells/mL) and high density (HD, ~110x106 cells/mL) in single-use cryopreservation bags. They named the strategy the Frozen Accelerated Seed Train for Execution of a Campaign (FASTEC) which allowed the seed train to be bypassed. Seth et al. [74] evaluated the FASTEC approach in an 80 L seed bioreactor by comparing two processes: i) an inoculum seed train with 3 passages; ii) an inoculum seed train with only 1 passage. The processes were able to produce final cell densities of approximately 7x106 viable cells/mL in 10 days and 4 days, respectively. Additionally, after inoculating the production bioreactor (400 L) operated in fed-batch, product titres (1.1 g/L & 1.2 g/L), triple-light chain impurities (3LC, 1.7% & 2.6%) and aggregates (3.1% & 2.2%) were comparable to the seed train control (1.1 ± 0.2 g/L; 3.7 ± 1.0%; 4.3 ± 1.0%, respectively). Seth et al. [74] concluded that, despite cells displaying lower growth rate and viability immediately post-inoculation, the FASTEC process was able to produce comparable titer and quality of mAbs than the standard process whilst significantly reducing the duration of the upstream process.

The second strategy commonly reported in the literature is the use of a perfusion N-1 seed bioreactor. The benefit of this approach is that a significantly higher cell density is achieved in the seed train which allows a fed-batch production reactor to be inoculated at a higher initial cell density. As a result the duration of the production reactor can be reduced by a number of days and/or higher titres can be achieved due to the increased cell time within the reactor. Xu et al. [75] applied an N-1 perfusion seed step in conjunction with media enrichment to a CHO fed-batch production reactor for four processes producing four different mAb products. They reported that increasing the initial seed density from 0.3–1.2 x 106 cells/ml to 10–20 x 106 cell/ml resulted in an up to 10 fold increase in titer in addition to up to a 4 day decrease in production reactor duration while maintaining product quality.

The benefits of continuous processing have been discussed extensively in the literature for a range of industries including the small molecule pharmaceutical sector [76]. They are generally smaller, faster and cheaper with greater levels of flexibility and quality assurance achievable. As such there is much interest in the application to mAb production. However, fully integrated end-to-end continuous processes in this space are not yet a reality in commercial manufacture although research and development of such systems is ongoing and has demonstrated feasibility [77]. As a first step, continuous unit operations, primarily perfusion bioreactor steps and continuous chromatography have been implemented.

Many authors have discussed the advantages and disadvantages of perfusion and fed-batch operations for mAb production. The discussion is complex as the best choice is dependent on the specific scenario i.e. the quantity of material required, the productivity of the cell line, the nature of the protein, the cycle times of the processes etc. Direct comparison is often hampered by differing scales and definitions of productivity [78]. For instance, Lee et al. [79] studied the change from perfusion to fed-batch for expression of biosimilar monoclonal antibody A (CR-mAb-A) by recombinant Sp2/0 mouse myeloma cells. The fed-batch operation was evaluated in 8 runs at the following bioreactor scales: 3 L (3×), 100 L (2×) and 12,500 L (3×). The results indicated that, although the perfusion mode provided higher volumetric productivity, the fed-batch operation showed increased total productivity (7.5 fold increase) due to its higher volume capacity. Lee et al. [79] also investigated the mAb-based product quality by measuring oligosaccharide profiles and charge variants of mAbs expressed by fed-batch and perfusion. They observed slight differences in heavy chain glycoforms (G0, G1 and G2) between fed-batch and perfusion, while different scales of fed-batch provided comparable proportions. Additionally, by performing capillary electrophoresis sodium dodecyl sulfate (CE-SDS), they observed a slightly lower amount of intact IgG (4%, normalized) obtained in fed-batch in comparison to perfusion.

It is important to highlight that, in order to benefit from upstream intensification, one must guarantee that downstream operations are capable of handling high volumes and titres while maintaining the product quality. To this end, efforts to improve resin capture and capacity in chromatography operations have been documented in addition to continuous processing. Gerstweiler et al. [80] highlighted applications to enable continuous processing, such as: periodic countercurrent chromatography (PCC), simulated moving bed chromatography (SMB), continuous flow-through chromatography and multi-column designs (e.g. continuous multicolumn countercurrent solvent gradient purification). Moreover, in regard to Protein A ligand-based columns, Somasundaram et al. [81] stated that the dynamic binding capacity and resin reusability are important aspects to be considered in continuous processing.

### **3.5 Platform processes**

Producers of mAbs typically have platform production processes that span the majority of their portfolio. A platform process comprises the expression system, typically a suspension CHO cell line, the associated basal and feed media formulations and the series of unit operations used to produce and purify the mAb. The platform may be fine-tuned for each product, for example, the media formulation may be slightly modified for the particular nutrient requirements of a specific clone in order

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

to boost productivity or ensure product quality, but there are no major fundamental changes unless essential for a given product. The benefits of utilizing a platform approach are: faster process development, easier facility fit for scale up and tech transfer, greater process knowledge and more robust processes, all of which contribute to delivering a faster time to market and lower CoGs.

The majority of manufacturers rely on a CHO fed-batch upstream process platform with serum-free media although a significant number have opted for perfusion. There is also a general move away from using undefined media components such as hydrolysates to fully chemically defined media formulations in order to reduce raw material and hence, process variability. The downstream process generally follows a platform process flow of one or two harvest steps (centrifugation/ depth filtration) followed by a Protein-A chromatography step for product capture, a low pH hold for viral inactivation, two polishing chromatography steps, a virus filtration and a final ultrafiltration/diafiltration step to the final concentration in the formulation buffer [82].

Efforts to improve the existing platform processes focus on process intensification strategies such as high cell density cell banks and N-1 perfusion steps as discussed in Section 3.4 as well as the potential to replace the Protein-A capture step. Protein-A is the single biggest contributor to the Op-Ex costs associated with mAb production. It is widely used as it is extremely effective and reliable. Both chromatographic and non-chromatographic options have been explored. These include: precipitation, crystallization, cation exchange chromatography and multimodal chromatography [82–83]. Other approaches seek to improve the efficiency of Protein-A usage. Typically, Protein-A is used in a single product, packed bed format. There is work currently underway exploring resin use across multiple products, particularly useful for small volume products, as well as alternative formats such as membrane chromatography and monolithic chromatography which allow for higher flow rates and hence, throughput [84].

### **3.6 Facility design and single use technology (SUT)**

The portfolio of mAb products currently approved ranges from large volume blockbuster therapies to low volume products that address orphan indications. Therefore, the scale of commercial manufacture varies considerably across products. For a given product, the annual requirement can also vary significantly. It may increase as a new product gains market share or is approved for additional indications or may decrease if a competing product, a new alternative therapy or a biosimilar version of the product in question, is launched. Biosimilar manufacturers target high volume products coming off patent, supplying a comparable product at a reduced cost. This results in a significant drop in the volume required for the original product, as observed for granulocyte colony stimulating factor (G-CSF). According to an IMS report [85], in 2016 within the EU, biosimilars accounted for 88% of the market as compared with the reference product. This resulted in a 37% reduction in price as compared with the year prior to entry of the biosimilars into the market.

As a result, where once a dedicated high volume production plant using stainless steel equipment was the norm, there has been a shift towards flexible multi-product facilities in order to accommodate the ever-changing numbers and volumes of mAbs to be supplied to meet patient needs. SUT and modular or ballroom style facilities help to satisfy these requirements.

In SUT, all surfaces that come in contact with the process are disposable and are replaced after a single batch. This includes the vessel itself which is typically a bag supported externally by a metal exoskeleton and fabricated from FDA (Food and Drug Administration) approved polymers such as polyethylene (PE), polytetrafluoroethylene (PTFE) and polypropylene (PP) supplemented with additives to enhance performance and/or extend useable life as well as impellers, probes, resins, filter cartridges etc. SUT eliminates the need for the validation requirements associated with cleaning and sterilization of equipment, reduces the turn-around time between batches and reduces the risk of both microbial contamination and cross-product contamination in multi-product facilities [86]. The cap-ex investment required to establish a single use facility is significantly lower than the stainless steel equivalent and the utility requirements particularly for steam and water for injection (WFI) are massively decreased [87]. Studies have also reported that despite the increased plastic waste produced from SUT, overall they are environmentally less impactful than stainless steel [87]. Currently, there are commercially marketed SUT solutions for each unit operation typically used to produce a mAb [86].

There are however some disadvantages and challenges that remain to be overcome. Firstly, leachables and extractables are a concern due to the material of construction. These substances may be detrimental to process performance and/or human health [86]. Typically this is overcome by performing studies on the material to prove suitability. Secondly, scale is limited. There are mechanical challenges in producing what are essentially plastic bags with sufficient strength to withstand the loads associated with large volumes. The largest volume routinely seen at commercial scale is 2000 L as opposed to 25,000 L in stainless steel [86, 88–89]. There is one system currently on the market at 6000 L made by ABEC [90]. Other challenges include extremely long lead times of 9–12 months currently for the sterile consumables required in addition to high op-ex costs associated with them. The SUT available for downstream is less mature than in the upstream space and as such is less likely to be adopted. This is evolving over time especially when considering the increase of demand by industry. According to American Pharmaceutical Review [91], 46.9% of a survey's respondents (12th Annual Report and Survey of Biopharmaceutical Manufacturing) had claimed to investigate single-use technologies in downstream bioprocessing to improve purification operations, in contrast to 36.8% in 2012. Despite these challenges however, many manufacturers have adopted either fully SU equipment trains or a hybrid approach where the upstream process up to a volume of 2000 L is SU and the remainder of the upstream and the downstream processes are stainless steel.

Facility design and construction takes an average of 1 year to design and 3–4 years to build and costs several hundred million to over one billion euros depending on the size of the facility. To maintain strategic relevance in the current market, biopharmaceutical companies must design these facilities to be flexible and multi-product while still maintaining a high standard of product safety and efficacy. Modified-ballroom or dance-floor facility design integrated with closed systems and SUT is the most common approach to achieve these objectives while managing the risks associated with large integrated production spaces. In this type of design, a series of rooms that meet the Clean-Not-Classified (CNC) criteria are interconnected through wall panels. Within each room, single use, closed systems are operated. This equipment can be based on modular skids that can be changed if requirements change in the future. This approach reduces the footprint of the facility by removing the need for personnel and material airlocks to a large extent as well as decreasing the both cap-ex and op-ex costs associated with graded cleanroom environments. Time for construction is also

reduced. It eliminates the need for gowning and simplifies installation, maintenance and operation of equipment as there are less restrictions on activities in the production space [92].

### **4. Conclusion**

mAbs represent the largest category of biopharmaceuticals on the market and the number of approved products continues to grow. The commercial production of these products has evolved significantly since the first approval in 1986. Expression systems, once only capable of titres in the mg/L range, are now routinely producing 5–10 g/L due to advances in cell line development. Efforts have moved from establishing reliable robust platform processes to optimization of product quantity and quality. New technologies and approaches are being adopted in order to achieve this despite the mAb specific challenges associated with processing protein molecules and controlling biological processes. QbD, process monitoring, and control can be harnessed to manage the inherent variability associated with the raw materials and biological expression system. Process modeling, particularly hybrid models, can mitigate the expensive, time-consuming nature of experimental approaches and the empirical approach taken to process development historically in order to accelerate time to market and optimize and troubleshoot the manufacturing process. There are currently multiple strategies for process intensification being adopted in order to reduce cycle time and increase productivity. New approaches to facility design coupled with SUT reaching greater levels of maturity have reduced the risk and complexity associated with multi-product facilities. Alternative technologies on the horizon such as greater offerings for SUT in the downstream space and cheaper alternatives to Protein-A packed bed chromatography are opening up new avenues for significant cost reduction. Over the coming decades, mAb production will continue to evolve. There are many promising technologies and approaches to address the existing challenges. While adoption is slow due to the regulated, conservative nature of the biopharmaceutical industry, where strong business drivers exist, this will be overcome and, in the future, integration of these technologies will become widespread. It is exciting to consider the next evolution of mAb production.

### **Acknowledgements**

The authors acknowledge receipt of funding to Raymon Floyd Principe From the UCD Advance PhD Core Scheme and funding for Maycou Soares Zamprognio from SSPC, the Science Foundation Ireland Research Centre for Pharmaceuticals (12/ RC/2275\_P2).

### **Conflict of interest**

The authors declare no conflict of interest.

### **Author details**

Susan McDonnell1 \*, Raymon Floyd Principe1 , Maycou Soares Zamprognio2 and Jessica Whelan2

1 Biomanufacturing Research Group, UCD School of Chemical and Bioprocess Engineering, UCD, Ireland

2 SSPC – The Science Foundation Ireland Research Centre for Pharmaceuticals, Bernal Institute, University of Limerick, Ireland

\*Address all correspondence to: susan.mcdonnell@ucd.ie

© 2022 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.

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

### **References**

[1] Ecker D, Jones SD, Levine HL. The Therapeutic Monoclonal Antibody Market. mAbs. 2015;**7**:9-14. DOI: 10.4161/19420862.2015.989042

[2] Halimi V, Daci A, Netkovska KA, Suturkova L, Babar ZUD, Grozdanova A. Clinical and regulatory concerns of Biosimilars: A review of literature. International Journal of Environmental Research and Public Health. 2020;**17**(16):5800. DOI: 10.3390/ ijerph17165800

[3] Global Market Insights. Antibody Therapy Market size to exceed \$445bn by 2028 [Internet]. 2022. Available from: https://www.gminsights.com/ pressrelease/antibody-therapy-market. [Accessed: April 26, 2022]

[4] Mullard A. FDA approves the 100th monoclonal antibody product. Nature Reviews: Drug Discovery. 2021;**20**:491- 495. DOI: 10.1038/d41573-021-00079-7

[5] The Antibody Society. Therapeutic monoclonal antibodies approved or in review in the EU or US [Internet]. 2022. www.antibodysociety.org/resources/ approved-antibodies. [Accessed: May 2022]

[6] Chavda VP, Prajapati R, Lathigara D, Nagar Bhumi N, Kukadiya J, Redwan EM, Uversky VN, Kher MN, Rajvi P. Therapeutic monoclonal antibodies for COVID-19 management: An update Expert Opinion on Biological Therapy. 2022;**22**:763-780. DOI: 10.1080/14712598.2022.2078160

[7] Gherghescu I, Begoña D-CM. The biosimilar landscape: An overview of regulatory approvals by the EMA and FDA. Pharmaceutics. 2021;**13**:48. DOI: 10:3390/pharmaceutics13010048 [8] Fierce Pharma. Humira rings up \$20.7B in 2021, but AbbVie still mum on post-biosimilar expectations [Internet]. 2022. Available from: https:// www.fiercepharma.com/pharma/ humira-rings-up-20-7-billion-sales-butabbvie-still-mum-a-projection-for-2023 when-it-faces

[9] Fu Z, Li S, Han S, Shi C, Zhang Y. Antibody drug conjugate: The "biological missile" for targeted cancer therapy. Signal Transduction and Targeted Therapy. 2022;**7**:93. DOI: 10.1038/ s41392-022-00947-7

[10] Kang TH, Seong BL. Solubility, stability, and avidity of recombinant antibody fragments expressed in microorganisms. Frontiers in Microbiology. 2020;**11**:1927. DOI: 10.3389/fmicb.2020.01927

[11] Palanques-Pastor T, Megias-Vericat JE, Boso RV, Gomez SI, Poveda AJL. Effectiveness of Caplacizumab Nanobody in acquired thrombotic thrombocytopenic purpura refractory to conventional treatment. Acta Haematologica. 2022;**145**:75-76. DOI: 10.1159/000517813

[12] Delobel A. Glycosylation of therapeutic proteins: A critical quality attribute. In: Delobel A, editor. Mass Spectrometry of Glycoproteins. Methods in Molecular Biology. Vol. 2271. New York, NY: Humana; 2021. DOI: 10.1007/978-1-0716-1241-5\_1

[13] Datta A, Maryala S, John R. A review of Eptinezumab use in migraine. Cureus. 2021;**13**(9):e18032. DOI: 10.7759/ cureus.18032

[14] Tripathi NK, Shrivastava A. Recent developments in bioprocessing of

recombinant proteins: Expression hosts and process development. Frontiers in Bioengineering and Biotechnology. 2019;**7**(420):1-35. DOI: 10.3389/ fbioe.2019.00420

[15] Madhavan A, Arun KB, Sindhu R, Krishnamoorthy J, Reshmy R, Sirohi R, et al. Customized yeast cell factories for biopharmaceuticals: From cell engineering to process scale up. Microbial Cell Factories. 2021;**20**(124): 1-17. DOI: 10.1186/s12934-021-01617-z

[16] Cox MMJ. Innovations in the insect cell expression system for industrial recombinant vaccine antigen production. Vaccine. 2021;**9**(1504):1-12. DOI: 10.3390/vaccines9121504

[17] Yongky A, Xu J, Tian J, Oliveira C, Zhao J, McFarland K, et al. Process intensification in fed-batch production bioreactors using non-perfusion seed cultures. MAbs. 2019;**11**(8):1502-1514. DOI: 10.1080/19420862.2019.1652075

[18] Bunnak P, Allmendinger R, Ramasamy SV, Lettieri P, Titchener-Hooker NJ. Life-cycle and cost of goods assessment of fed-batch and perfusionbased manufacturing processes for mAbs. Biotechnology Progress. 2016;**32**(5):1324- 1335. DOI: 10.1002/btpr.2323

[19] Rodrigo G, Gruvegard M, Alstine JMV. Antibody fragments and their purification by protein L affinity chromatography. Antibodies. 2015;**4**:259- 277. DOI: 10.3390/antib4030259

[20] Dangi AK, Sinha DS, Gupta SK, Shukla P. Cell line techniques and gene editing tools for antibody production: A review. Frontiers in Pharmacology. 2018;**9**(630):1-12. DOI: 10.3389/ fphar.2018.00630

[21] Fisher S, Handrick R, Otte K. The art of CHO cell engineering: A comprehensive retrospect and future perspectives. Biotechnology Advances. 2015;**3**:1878-1896. DOI: 10.1016/j. biotechadv.2015.10.015

[22] Tihanyi B, Nyitray L. Recent advances in CHO cell line development for recombinant protein production. Drug Discovery Today: Technologies. 2021;**38**:25-34. DOI: 10.1016/j. ddtec.2021.02.003

[23] Diep J, Le H, Le K, Zasadzinska E, Tat J, Yam P, et al. Microfluidic chipbased single-cell cloning to accelerate biologic production timelines. Biotechnology Progress. 2021;**37**(e3192):1-9. DOI: 10.1002/ btpr.3192

[24] Kunert R, Reinhart D. Advances in recombinant antibody manufacturing. Applied Microbiology and Biotechnology. 2016;**100**:3451-3461. DOI: 10.1007/s00253-016-7388-9

[25] Puck TT, Cieciura SJ, Robinson A. Genetics of somatic mammalian cells: III. Long-term cultivation of euploid cells from human and animal subjects. The Journal of Experimental Medicine. 1958;**108**(6):945-956. DOI: 10.1084/ jem.108.6.945

[26] Drug Target Review. Cell line development for therapeutic proteins – current perspectives and future opportunities [Internet]. 2020. Available from: https://www. drugtargetreview.com/article/57784/ cell-line-development-for-therapeuticproteins-current-perspectives-andfuture-opportunities/. [Accessed: May, 2022]

[27] Fus-Kujawa A, Prus P, Bajdak-Rusinek K, Teper P, Gawron K, Kowalczuk A, et al. An overview of methods and tools for transfection of eukaryotic cells in vitro. Frontiers in

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

Bioengineering and Biotechnology. 2021;**9**(701031):1-15. DOI: 10.3389/ fbioe.2021.701031

[28] Elshereef AA, Jochums A, Lavrentieva A, Stuckenberg L, Scheper T, Solle D. High cell density transient transfection of CHO cells for TGF-1 expression. Engineering in Life Sciences. 2019;**19**:730-740. DOI: 10.1002/ elsc.201800174

[29] Kim JY, Han SK, Yoon S, Kim CW. Rich production media as a platform for CHO cell line development. AMB Expr. 2020;**10**(93):1-13. DOI: 10.1186/ s13568-020-01025-3

[30] Xu X, Nagarajan H, Lewis NE, Pan S, Cai Z, Lui X, et al. The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line. Nature Biotechnol. 2011;**29**:735- 741. DOI: 10.1038/nbt.1932

[31] Welch JT, Arden S. Considering "clonality": A regulatory perspective on the importance of the clonal derivation of mammalian cell banks in biopharmaceutical development. Biologicals. 2019;**62**:16-21. DOI: 10.1016/j.biologicals.2019.09.006

[32] Wurm FM, Wurm MJ. Cloning of CHO cells, productivity and genetic stability—A discussion. PRO. 2017;**5**(20):1-13. DOI: 10.3390/ pr5020020

[33] Gupta SK, Shukla P. Gene editing for cell engineering: Trends and applications. Critical Reviews in Biotechnology. 2016;**37**:672-684. DOI: 10.1080/ 07388551.2016.1214557

[34] Hong JK, Lakshmanan M, Goudar C, Lee DY. Towards next generation CHO cell line development and engineering by systems approaches. Current Opinion in Chem Eng. 2018;**22**:1-10. DOI: 10.1016/j. coche.2018.08.002

[35] Urlaub G, Kas E, Carothers AM, Chasin LA. Deletion of the diploid Dihydrofolate reductase locus from cultured mammalian cells. Cell. 1983;**33**:405-412. DOI: 10.1016/ 0092-8674(83)90422-1

[36] Ainavarapu SRK, Li L, Badilla CL, Fernandez JM. Ligand binding modulates the mechanical stability of Dihydrofolate reductase. Biophysical Journal. 2005;**89**:3337-3344. DOI: 10.1529/ biophysj.105.062034

[37] Barnes LM, Bentley CM, Moy N, Dickson AJ. Molecular analysis of successful cell line selection in transfected GS-NS0 myeloma cells. Biotechnology and Bioengineering. 2007;**96**(2):337-348. DOI: 10.1002/ bit.21119

[38] Hu P, Zhang W, Xin H, Deng G. Sing cell isolation and analysis. Frontiers in Cell and Development Biology. 2016;**4**(116):1-12. DOI: 10.3389/ fcell.2016.00116

[39] Sifniotis V, Cruz E, Eroglu B, Kayser V. Current advancements in addressing key challenges of therapeutic antibody design, manufacture, and formulation. Antibodies. 2019;**8**(36): 1-23. DOI: 10.3390/antib8020036

[40] Porter AJ, Racher AJ, Preziosi R, Dickson AJ. Strategies for selecting recombinant CHO cell lines for cGMP manufacturing: Improving the efficiency of cell line generation. Biotechnology Progress. 2010;**26**(5):1455-1464. DOI: 10.1002/btpr.443

[41] Lopez-Mez J, Araiz-Hernandez D, Carrillo-Cocom LM, Lopez-Pacheco F, Rocha-Pizana MDR, Alvarez MM. Using simple models to describe the kinetics of growth, glucose consumption, and monoclonal antibody formation in naive and infliximab producer CHO cells.

Cytotechnology. 2016;**68**:1287-1300. DOI: 10.1007/s10616-015-9889-2

[42] BioPharm International. Best Practices for Selecting a Top-Quality Cell Line [Internet]. 2019. Available from: http://www.processdevelopmentforum. com/articles/best-practices-forselecting-a-top-quality-cell-line/. [Accessed: May, 2022]

[43] Ling WL. Development of proteinfree medium for therapeutic protein production in mammalian cells: Recent advances and perspectives. Pharm Bioprocess. 2015;**3**(3):215-226. DOI: 10.4155/PBP.15.8

[44] Cell Culture Dish. Fed-batch culture – Optimizing feed strategies now and in the future [Internet]. 2017. Available from: https://cellculturedish. com/fed-batch-culture-optimizing-feedstrategies-now-and-in-the-future/

[45] Reimonn TM, Park S, Agarabi CD, Brorson KA, Yoon S. Effect of amino acid supplementation on titer and glycosylation distribution in Hybridoma cell cultures—Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis. Biotechnology Progress. 2016;**32**(5):1163-1173. DOI: 10.1002/btpr.2335

[46] Kelley B. Industrialization of mAb production technology: The bioprocessing industry at a crossroads. MAbs. 2009;**1**(5):443-452. DOI: 10.4161/ mabs.1.5.9448

[47] Papathanasiou MM, Kontoravdi C. Engineering challenges in therapeutic protein product and process design. Current Opinion in Chemical Engineering. 2020;**27**:81-88. DOI: 10.1016/j.coche.2019.11.010

[48] Basle YL, Chennell P, Tokhadze N, Astier A, Sautou V. Physicochemical

stability of monoclonal antibodies: A review. Journal of Pharmaceutical Sciences. 2020;**109**(1):169-190. DOI: 10.1016/j.xphs.2019.08.009

[49] Vlasak J, Ionescu R. Fragmentation of monoclonal antibodies. Landes Bioscience. 2011;**3**(3):253-263. DOI: 10.4161/mabs.3.3.15608

[50] Goswami S, Wang W, Arakawa T, Ohtake S. Developments and challenges for mAb-based therapeutics. Antibodies. 2013;**2**:452-500. DOI: 10.3390/ antib2030452

[51] Shukla AA, Hubbard B, Tressel T, Guhan S, Low D. Downstream processing of monoclonal antibodies—Application of platform approaches. Journal of Chromatography B. 2007;**848**:28-39. DOI: 10.1016/j.jchromb.2006.09.026

[52] Flatman S, Alam I, Gerard J, Mussa N. Process analytics for purification of monoclonal antibodies. Journal of Chromatography B. 2007;**848**:79-87. DOI: 10.1016/j. jchromb.2006.11.018

[53] Hutchinson N. Understanding and controlling sources of process variation: Risks to achieving product critical quality attributes. Bioprocess International. 2014;**12**:24-29

[54] Guidance for Industry. Process Validation, General Principles and Practices. Silver Spring: US Food and Drug Administration; 2011

[55] Val IJD, Jedrzejewski PM, Exley K, Sou SN, Kyriakopoulos S, Polizzi KM, et al. Application of quality by design paradigm to the manufacture of protein therapeutics. In: Petrescu S, editor. Glycosylation. London: IntechOpen; 2012. DOI: 10.5772/50261

[56] Maruthamuthu MK, Rudge SR, Ardekani AM, Ladisch MR,

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

Mohit S, Verma MS. Process analytical technologies and data analytics for the manufacture of monoclonal antibodies. Trends in Biotechnology. 2020;**38**:1169- 1186. DOI: 10.1016/j.tibtech.2020.07.004

[57] Yu LX, Amidon G, Khan MA, Hoag SW, Polli J, Raju GK, et al. Understanding pharmaceutical quality by design. AAPS Journal. 2014;**16**:771- 783. DOI: 10.1208/s12248-014-9598-3

[58] Luo Y, Kurian V, Ogunnaike BA. Bioprocess systems analysis, modeling, estimation, and control. Current Opinion in Chemical Engineering. 2021;**33**:00705. DOI: 10.1016/j.coche.2021.100705

[59] Narayanan H, Behle L, Luna MF, Sokolov M, Guillén-Gosálbez G, Morbidelli M, et al. Hybrid-EKF: Hybrid model coupled with extended Kalman filter for real-time monitoring and control of mammalian cell culture. Biotechnology and Bioengineering. 2020;**117**:2703-2714. DOI: 10.1002/bit.27437

[60] Roch P, Mandenius CF. On-line monitoring of downstream bioprocesses. Current Opinion in Chemical Engineering. 2016;**14**:112-120. DOI:10.1016/J.COCHE.2016.09.007

[61] Whelan J, Craven S, Glennon B. In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors. Biotechnology Progress. 2012;**28**(5):1355-1362. DOI: 10.1002/btpr.1590

[62] Craven S, Whelan J, Glennon B. Glucose concentration control of a fedbatch mammalian cell bioprocess using a nonlinear model predictive controller. Journal of Process Control. 2014;**24**(4):344-357. DOI: 10.1016/j. jprocont.2014.02.007

[63] Qin SJ, Badgwell TA. A survey of industrial model predictive control

technology. Control Engineering Practice. 2003;**11**(7):733-764. DOI: 10.1016/S0967-0661(02)00186-7

[64] Schwenzer M, Ay M, Bergs T, Abel D. Review on model predictive control: An engineering perspective. The International Journal of Advanced Manufacturing Technology*.* 2021;**117**:1327-1349. DOI: 10.1007/ s00170-021-07682-3

[65] Zendehboudi S, Rezaei N, Lohi A. Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review. Applied Energy. 2018;**228**:2539-2566. DOI: 10.1016/j.apenergy.2018.06.051

[66] Narayanan H, Luna MF, Von M, Cruz MN, Polotti G, Morbidelli M, et al. Bioprocessing in the digital age: The role of process models. Biotechnology Journal. 2020;**15**:1900172. DOI: 10.1002/ biot.201900172

[67] Möller J, Kuchemüller KB, Steinmetz T, Koopmann KS, Pörtner R. Model-assisted Design of Experiments as a concept for knowledge-based bioprocess development. Bioprocess and Biosystems Engineering. 2019;**42**:867- 882. DOI: 10.1007/s00449-019-02089-7

[68] Blazek J. Computational Fluid Dynamics: Principles and Applications. 3rd ed. Oxford: Butterworth-Heinemann - Elsevier; 2005. p. 3. DOI: 10.1016/ B978-0-08-099995-1.00001-4

[69] Jamshed S. Using HPC for Computational Fluid Dynamics. 1st ed. Oxford: Academic Press, Elsevier; 2015. p. 4. DOI: 10.1016/ B978-0-12-801567-4.00001-5

[70] Mishra S, Kumar V, Sarkar J, Rathore AS. CFD based mass transfer modeling of a single use bioreactor for production of monoclonal antibody

biotherapeutics. Chemical Engineering Journal. 2021;**412**:128592. DOI: 10.1016/j. cej.2021.128592

[71] Sokolov M, Ritscher J, MacKinnon N, Souquet J, Broly H, Morbidelli M, et al. Enhanced process understanding and multivariate prediction of the relationship between cell culture process and monoclonal antibody quality. Biotechnology Progress. 2017;**33**:1368- 1380. DOI: 10.1002/btpr.2502

[72] Park S-Y, Park C-H, Choi D-H, Hong JK, Lee D-Y. Bioprocess digital twins of mammalian cell culture for advanced biomanufacturing. Current Opinion in Chemical Engineering. 2021;**33**:100702. DOI: 10.1016/j. coche.2021.100702

[73] Cinar ZM, Nuhu AA, Zeeshan Q, Korhan O. Digital Twins for Industry 4.0: A Review. In: Calisir F, Korhan O, editors. Industrial Engineering in the Digital Disruption Era. GJCIE 2019. Lecture Notes in Management and Industrial Engineering. Cham: Springer; 2020. DOI: 10.1007/978-3-030-42416-9\_18

[74] Seth G, Hamilton RW, Stapp TR, Zheng L, Meier A, Petty K, et al. Development of a new bioprocess scheme using frozen seed train intermediates to initiate CHO cell culture manufacturing campaigns. Biotechnology and Bioengineering. 2013;**110**:1376-1385. DOI: 10.1002/bit.24808

[75] Xu J, Rehmann MS, Xu M, Zheng S, Hill C, Qin H, et al. Development of an intensified fed-batch production platform with doubled titers using N-1 perfusion seed for cell culture manufacturing. Bioresources and Bioprocessing. 2020;**7**:17. DOI: 10.1186/ s40643-020-00304-y

[76] Domokos A, Nagy B, Szilágyi B, Marosi G, Nagy ZK. Integrated

continuous pharmaceutical technologies - a review. Organic Process Research & Development. 2021;**25**(4):721-739. DOI: 10.1021/acs.oprd.0c00504

[77] Gomis-Fons J, Schwarz H, Zhang L, Andersson N, Nilsson B, Castan A, et al. Model-based design and control of a small-scale integrated continuous endto-end mAb platform. Biotechnology Progress. 2020;**36**:e2995. DOI: 10.1002/ btpr.2995

[78] Bausch M, Schultheiss C, Sieck JB. Recommendations for comparison of productivity between fed-batch and perfusion processes. Biotechnology Journal. 2019;**14**:1700721. DOI: 10.1002/ biot.201700721

[79] Lee SY, Kwon YB, Cho JM, Park KH, Chang SJ, Kim DL. Effect of process change from perfusion to fed-batch on product comparability for biosimilar monoclonal antibody. Process Biochemistry. 2012;**47**:1411-1418. DOI: 10.1016/j.procbio.2012.05.017

[80] Gerstweiler L, Bi J, Middelberg APJ. Continuous downstream bioprocessing for intensified manufacture of biopharmaceuticals and antibodies. Chemical Engineering Science. 2021;**231**:116272. DOI: 10.1016/j. ces.2020.116272

[81] Somasundaram B, Pleitt K, Shave E, Baker K, Lua LHL. Progression of continuous downstream processing of monoclonal antibodies: Current trends and challenges. Biotechnology and Bioengineering. 2018;**115**:2893-2907. DOI: 10.1002/bit.26812

[82] Grilo AL, Mateus M, Aires-Barros MR, Azevedo AM. Monoclonal antibodies production platforms: An opportunity study of a non-protein-a chromatographic platform based on process economics. Biotechnology

*Challenges and Emerging Technologies in Biomanufacturing of Monoclonal Antibodies (mAbs) DOI: http://dx.doi.org/10.5772/intechopen.108565*

Journal. 2017;**12**:1700260. DOI: 10.1002/ biot.201700260

[83] Kateja N, Kumar D, Sethi S, Rathore AS. Non-protein a purification platform for continuous processing of monoclonal antibody therapeutics. Journal of Chromatography A. 2018;**1579**:60-72. DOI: 10.1016/j. chroma.2018.10.031

[84] Gagnon P. Technology trends in antibody purification. Journal Chromatography. 2012;**1221**:57-70. DOI: 10.1016/j.chroma.2011.10.034

[85] IMS. The Impact of Biosimilar Competition in Europe [Internet]. 2017. Available from: https://www. medicinesforeurope.com/wp-content/ uploads/2017/05/IMS-Biosimilar-2017\_ V9.pdf [Accessed: May 31, 2022]

[86] Galliher PM. Chapter 29 - single use technology and equipment. In: Jagschies G, Lindskog E, Łącki K, Galliher P, editors. Biopharmaceutical Processing. Oxford: Elsevier; 2018. pp. 557-577. DOI: 10.1016/ B978-0-08-100623-8.00029-3

[87] Guldager N. Cost advantages of single-use technologies. Pharmaceutical Technology. 2010;**S26**(S28):S30-S31

[88] Bioprocess International. Upstream Single-Use Bioprocessing Systems [Internet]. 2012. Available from: https://bioprocessintl.com/ upstream-processing/upstream-singleuse-technologies/upstream-singleuse-bioprocessing-systems-326675/. [Accessed: May 31, 2022]

[89] Allison N, Richards J. Current status and future trends for disposable technology in the biopharmaceutical industry. Journal of Chemical Technology and Biotechnology. 2014;**89**:1283-1287. DOI: 10.1002/jctb.4277

[90] Bioprocess International. ABEC breaks plastic ceiling again with 6,000 L single-use bioreactor [Internet]. 2019. Available from: https:// bioprocessintl.com/bioprocess-insider/ upstream-downstream-processing/ abec-breaks-plastic-ceiling-againwith-6000-l-single-use-bioreactor/. [Accessed: May 31, 2022]

[91] American Pharmaceutical Review. Single-Use Systems Not Helping Downstream Bioprocessing, Yet… Alternatives to Chromatography Still Slow in Adoption [Internet]. 2015. Available from: https://www. americanpharmaceuticalreview.com/ Featured-Articles/177871-Single-Use-Systems-Not-Helping-Downstream-Bioprocessing-Yet-Alternativesto-Chromatography-Still-Slow-in-Adoption/. [Accessed: June 1, 2022]

[92] Jones S. BioPhorum Operations Group Technology Roadmapping, Part 4: Efficiency, Modularity, and Flexibility As Hallmarks for Future Key Technologies. BioProcess Int. 2017;**15**:14-19

### **Chapter 9**

## Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art

*Hao Yu, Zhihai Han, Cunrong Chen and Leisheng Zhang*

### **Abstract**

Cancers including hematological malignancies and metastatic solid tumors are one of the life-threatening diseases to the general population, which have become a heavy burden for patients and their caregivers physically and mentally. Despite the great progression in preclinical and clinical studies, effective implementation strategies are urgently needed to optimize the advancements in cancer diagnosis and treatment. State-of-the-art updates have indicated the application of multifunctional nanotheranostics as an emerging diagnostic and therapeutic tool for cancer management. Herein, this chapter displayed the literature and description of various nanomaterialbased noninvasive diagnostic and therapeutic approaches for cancer administration from the view of nanomaterial classification and nanomaterial-based application in nanotheranostics as well as the promising perspectives and grand challenges in nanomedicine. Collectively, this review will provide overwhelming new references for cancer supervision and benefit the medical and pharmaceutical practice in the field of nanotheranostics.

**Keywords:** nanomaterials, nanotheranostics, chemoradiotherapy, cancer immunotherapy, nanomedicine

### **1. Introduction**

Cancers with high heterogeneity and uncontrolled cell division are notoriously hard to conquer and have emerged as one of the leading causes of death worldwide with a prevalence of over 10 million mortalities annually [1, 2]. Over the years, a certain number of investigations have been accomplished to figure out the fundamental pathogenesis and the concomitant treatment regimens including surgery, oncolytic virotherapy, radiotherapy, chemotherapy, photothermal therapy, RNA vaccine, peptide-based neoantigen vaccine, hormone therapy, and immunotherapy [3–6]. Generally, surgery (e.g., robotic surgery, laparoscopic rectal surgery) has been considered the best option for localized cancers without transfer and diffusion, which usually works in combination with chemoradiotherapy for the eradication of residual cancerous cells [7, 8]. Chemoradiotherapy has become a notable and synergistic anticancer treatment for a variety of locally advanced solid tumors through a rationale of two concepts (chemotherapy, radiotherapy) of in-field cooperation

and spatial cooperation but inevitably increases microbiota resistance and damage to normal tissues [9–11]. Current progresses have also highlighted the potential of anticancer immunotherapy including immune cells and checkpoint inhibitors for the significant clinical benefit [3, 4, 9, 12–14]. Meanwhile, despite new insights into RNA vaccine-derived immunity in melanoma treatment, those cancer vaccine trials in the late-stage patients with various treatment-refractory tumors have not been successful [6, 15–17]. Therefore, in overall consideration of the shortcomings (e.g., off-target effects, severe toxicity, drug delivery barriers, and graft-versus-host disease), the aforementioned treatment regimens fell short of expectation in cancer administration [1, 3, 12, 18–20].

State-of-the-art updates have highlighted the feasibility of nanomaterials as promising agents for cancer diagnosis and therapy based on the rapid progress of nanobiotechnology and clinical biomedicine [21–23]. To date, multidisciplinary research has further highlighted the superiority of the newly emerging bidimensional (2D) nanomaterials in multiple physicochemical properties and ultrathin layer-structured topology for theragnostic nanomedicine such as graphene and its derivatives, transition metal carbides (MXenes), hexagonal boron nitrides (h-BN), black phosphorus (BP), transition metal dichalcogenides (TMDCs), palladium (Pd) nanosheets, and transition metal oxides (TMOs) [24–27].

Therefore, this chapter principally focused on the current progress in nanomaterials for cancer nanotheranostics including the classification of nanomaterials (e.g., inorganic nanomaterials, organic nanomaterials, organic-inorganic hybrid nanomaterials), nanomaterials in cancer diagnostics (e.g., contrast agents for in vivo imaging, signal modes for *in vitro* diagnostics) and cancer treatment (e.g., cancer phototherapeutics, photothermal therapy, photodynamic therapy, cancer immunotherapy, combined therapy), and ultimately summarized the opportunities and challenges of nanomaterial-based cancer nanotheranostics. Collectively, the nanomaterial-mediated nanotheranostics had constituted a promising area of oncology theragnostics.

### **2. Nanomaterials and classification**

Nanoparticles, with a size ranging from 1 nm to 100 nm, reveal many unique properties in terms of light, heat, electricity, magnetism, sound and chemistry, and in particular, the "hobby" of lodging with tumor cells endow themselves with enhanced permeability and retention (EPR) effect [28, 29].

Generally, nanomaterials are categorized as inorganic nanomaterials, organic nanomaterials, and organic-inorganic hybrid nanomaterials, which have been extensively developed for tumor diagnosis and treatment based on their unique biofunctions and biomedical characteristics [30, 31]. Among them, inorganic nanomaterials are the earliest studied and most widely used biomaterials in clinical oncology treatment including noble metal nanoparticles, metal chlorocarbon nanomaterials, magnetic nanoparticles, and quantum dots. These inorganic nanomaterials usually possess a series of excellent properties such as strong near-infrared light absorption capacity, high photothermal conversion efficiency, easy preparation, and modification, which thus enable the applications in fluorescence imaging, photoacoustic imaging, or nuclear magnetic resonance imaging [32]. Organic nanomaterials can be divided into organic small molecule nanomaterials and organic polymer (polymeric) nanomaterials, which are employed in the area of bioluminescent probes, photothermal therapy, and drug carriers due to their unique properties (e.g., diverse structure,

*DOI: http://dx.doi.org/10.5772/intechopen.105700 Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art*

easy to cut, low assembly cost) [33]. Organic-inorganic hybrid nanomaterials not only possess improved stability and biocompatibility of inorganic nanoparticles but also reveal enhanced hardness and strength of organic matrix materials, which thus have a wider range of applications over organic and inorganic materials [34].

Of note, the pathological structure of tumor tissue has the characteristics of low pH value, hypoxia, new blood vessels, and lymphatic vessels in the microenvironment owing to the anatomical structure and physiological function are quite different from normal tissues [35, 36]. Owing to the aforementioned characteristics, tumor tissues can be specifically targeted by nanoparticles in order to achieve an efficient and accurate diagnosis and treatment.

### **3. Contrast agents for** *in vivo* **imaging**

As one of the most life-threatening diseases worldwide, the morbidity and mortality of cancer are increasing year by year [37]. Traditional diagnostics mainly focus on pathological examinations and endoscopic examinations, which often cause certain trauma to the patient's body. In recent years, clinical imaging diagnoses of solid tumors have mainly relied on computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound (**Figure 1**). However, these methodologies are not safe and efficient enough for monitoring the changing microstructure of tumors due to the ionizing radiation damage, insufficient resolution, and lack of targeting. Therefore, it is urgently needed to develop a new

**Figure 1.** *Schematic illustration of the biofunction of nanomaterials.*

type of nanomaterial contrast agent with high efficiency, accuracy, low toxicity, and side effects for clinical tumor diagnosis and treatment, which thereby benefits the enhancement of sensitivity and accuracy of tumor diagnosis [38, 39].

### **3.1 Metal nanomaterials and CT**

CT is a noninvasive imaging technique that uses X-rays, γ-rays, or ultrasound to scan a certain area of the human body in order to achieve differential diagnosis via the variations in signal absorption among different types of cells [40]. In recent years, the application of based-metal elements (e.g., gold, bismuth, tantalum, and ytterbium) of nanomaterials as contrast agents has been extensively reported (**Table 1**).

Generally, differing from the iodine-containing nanoparticle imaging system (denoted as "soft particles"), metal-based compound nanoparticles (denoted as "hard particles") manifest more reliable stability in the body and are easier to bypass the body's immunity system barrier to reach the tumor lesions and improve imaging efficiency. Meanwhile, these metal elements exhibit higher density and atomic numbers for effective absorption of X-rays, which makes up for the insufficient contrast ability of iodine as a contrast agent and sharply reduces the X-ray radiation dose of patients during imaging. In addition, the surface of metal-based nanoparticles is easy to be modified by physically or chemically methods, which enhances the targeting and versatility of CT imaging probes in clinical applications [22]. For instance, Luo et al. reported the accumulation of prostate-specific membrane antigen (PSMA) targeted AuNPs in prostatic cancer revealed a size-dependent pattern [41]. Shao et al. developed a novel Bi2S3 nanoparticle coated with a hyaluronic acid (HA)-modified tantalum oxide (TaOx) nanoshell (Bi2S3@TaOx-HA) for multimodality breast cancer diagnosis, which manifested excellent biocompatibility, photothermal transducing performance and computed tomography imaging capacity [42]. Instead, the carboxybetaine zwitterioniccoated tantalum oxide (TaCZ) nanoparticle CT contrast agent was reported with greater contrast enhancement compared with a conventional iodinated contrast agent in swine models [43]. Notably, thrombocytopenia and neutropenia in patients could be predicted


### **Table 1.**

*CT imaging system based on metal nanomaterials.*

after 177Lutetium-lilotomab satetraxetan treatment based on the SPECT/CT-derived absorbed dose [44].

### **3.2 Magnetic nanomaterials and MRI**

MRI is a type of noninvasive tomographic imaging, which is used to obtain electromagnetic signals from the body and reconstruct human body information. The combination of nanomaterials and MRI technology can improve the sensitivity and accuracy of MRI, and in particular, the iron-based magnetic nanomaterials with various shapes and sizes are extensively explored. For example, superparamagnetic iron oxide (SPIO) nanoparticles serve as an ideal MRI contrast agent and have been approved for clinical application attributed to their unique properties such as dualfunction angiography, longer half-life in blood, specificity reticuloendothelial system, venography effect, and *in vivo* tracking of cell labeling [45].

Meanwhile, various raw materials with outstanding characteristics have also been reported such as high magnetic torque, saturation, and coercivity. For example, Wang et al. synthesized the Au-Fe3O4@PDA-PEG-DTPA-Gd hetero-nanostructure with reasonable biocompatibility and high photothermal conversion efficiency, which was adequate to completely inhibit the growth of MDA-MB-231 tumor *in vivo* [46]. Xu et al. generated the tumor-targeted NPs (DOX@Gd-MFe3O4 NPs) by combining Gd-doped mesoporous Fe3O4 nanoparticles with doxorubicin (DOX), which exhibited good colloidal dispersity, superior magnetic properties, superior NIR photothermal conversion, and NIR-triggered DOX release [47]. Additionally, amine-functionalized CuFeSe2-NH2 nanoparticles were reported with specificity against 4 T1 and HepG2 cells due to the multifaceted signatures including water solubility, cytocompatibility, hemocompatibility, and biosafety [47].

### **3.3 Isotope nanomaterials and PET**

Fluorodeoxyglucose is the main medium in PET, which functions as a critical element in various metabolisms and accumulates in high-metabolic tumor tissues rather than in low-metabolic normal tissues [48]. In recent years, radionuclidelabeled nanomaterials in PET have become a research hotspot for cancer diagnosis and monitoring due to their preferable properties such as high sensitivity and precise spatial quantification capabilities (**Table 2**). For example, Song *et al.* took advantage


### **Table 2.**

*Methodologies of radionuclide-labeled nanomaterials for PET.*

of the 131I-labeled copper sulfide-loaded microspheres for the treatment of hepatic tumors via hepatic artery embolization [49]. Peng *et al.* confirmed the excellent safety profile and favorable pharmacokinetics of a self-assembling [68Ga] Ga-NOTA supramolecular dendrimer nanosystem for PET imaging, which was more competent for the detection of imaging-refractory low-glucose-uptake tumors compared to the clinical 18F FDG [50]. Co-injection of CBT-NODA-68Ga with CBT-NODA or CBT-NODA-Ga has been reported for the enhanced micro-PET tumor imaging in mice via accelerating the synthesis of hybrid gallium-68 nanoparticles in furin-overexpressing cancer cells [51].

### **4. Application of different signal modes in diagnostics** *in vitro*

Nanomaterials can be used to generate different types of detection signals, amplify the intensity of detection signals, and simplify the detection process attributed to their unique optical properties (e.g., magnetic, electrical, and thermal), which thus have broad application prospects *in vitro* diagnosis upon nucleic acids, proteins, small molecules, bacteria and viruses (**Figure 2**). Currently, the applications of fluorescent signals, surface-Raman signals, magnetic signals, electrochemical signals, color signals, and thermal signals of nanomaterials are the most representative signal detection modes for diagnostics *in vitro* (**Table 3**). For instance, Liu et al. generated a versatile nanoprobe based on reduced graphene oxide (rGO) and nucleic acid (DNA) nanoprobe, which provided a general sensing platform for highly sensitive imaging of dual miRNAs in living cells [52]. Lin et al. developed a microfluidic biosensor for Salmonella detection based on viscoelastic inertial microfluidics for separating magnetic bacteria from unbound magnetic nanoparticles (MNPs) and enzyme catalytic colorimetry for amplifying biological signals [53]. Compared with the unmodified electrode, a glassy carbon electrode (GCE)-based ultrasensitive electrochemical biosensor modified by a unique sandwich-like nano-Au/ZnO sol-gel/nano-Au compound revealed high absorbability and surface activity, good electro-conductivity, and biocompatibility [54].

### **5. Nanomaterials in cancer treatment**

For decades, multifaceted treatment options for cancer such as surgery, chemotherapy, radiation therapy, pharmacotherapy, targeted therapy, cellular therapy, and combined therapy have been developed, yet the clinic prognosis of tumor patients is still unsatisfactory [4, 55, 56]. For instance, despite the great efforts focused on cancer drug discovery pipeline (e.g., PD1/PDL1 axis), the undesirable outcomes and burdensome expenditures of pharmacotherapy alone or in combination with other strategies including nanomaterials still need to be overcome [57, 58].

### **5.1 Nanomaterials in cancer chemoradiotherapy**

Radiotherapy, including external radiation and internal radiation therapy, is one of the main treatments and adjuvant therapy for oncologic treatment, which can efficiently reduce the misery and pressure as well as affect the tumor environment (TME) but may cause a severe untoward effect upon patients [59, 60]. Chemotherapy is treatment with specific drugs to obliterate or shrink the metastatic cancer cells

*DOI: http://dx.doi.org/10.5772/intechopen.105700 Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art*

### **Figure 2.**

*Nanomaterial-based tumor diagnostics.*


### **Table 3.**

*Application of representative signal detection modes for diagnosis.*

before or after surgery. The chemotherapy drugs can be divided into antimetabolites (e.g., 6-mercaptopurine), alkylating agents (e.g., cyclophosphamide), topoisomerase inhibitors (e.g., Topotecan), and anticancer antibiotics (e.g., Bleomycin), which

mainly function by suppressing cell division of both cancer cells and normal cells in the body (e.g., bone marrow, gastrointestinal mucosa) and thus cause adverse effects.

State-of-the-art updates have reported the involvement of unidimensional (1D) and bidimensional nanomaterials (2D) with aromatic ring carbon particles in cancer chemoradiotherapy and device fabrication based on the unique nanosheet structures, tunable chemical composition, the large surface areas, surface functionalization, minimal thickness, and other extraordinary physicochemical properties (**Figure 3**) [61, 62]. For drug delivery via encapsulation or covalent linking or surface adsorption, nanoparticles are loaded with biomolecules and chemotherapeutic drugs based on noncovalent bonding (e.g., van der Waal's force, hydrophobic interaction, π–π stacking) [63, 64].

To date, a variety of 2D nanomaterials with potential of acting as drug delivery nanoplatforms have been synthesized by different methodologies, which attract the tremendous interest of investigators in the field such as transition metal dichalcogenides (TMDC), layered double hydroxides, transition metal dichalcogenides, nitrides and carbonitrides, metal-organic framework nanosheets, graphene and its derivatives, and black phosphorus nanosheets [61, 65]. In particular, those with unique X-ray attenuation and easily tunable properties such as graphene and TMDCs are adequate to be harnessed for radiotherapy or phototherapy of cancer.

### **5.2 Nanomaterials in cancer phototherapeutics**

Phototherapeutics, a next-generation therapeutic modality, is a type of photoresponsive regulation of biological function and relative stimuli-responsive features, which thus supplies promising prospective for promoting the accuracy and efficacy of cancer treatments via producing reactive oxygen species (ROS) by photosensitizers and eliminating cancer cells by specific wavelength light irradiation [66, 67]. Generally, phototherapeutics can be divided into three typical categories including photobiomodulation (PBM), photodynamic therapy (PDT), and photothermal therapy, which are widely applied to cancer administration such as colorectal cancer, head and neck cancer, breast cancer, and colorectal cancer [68, 69]. However, ineffective treatment of cancers by PDT can be caused by specific tumor environments and even hindered by the deep tumor cells [70].

**Figure 3.** *Categories of nanomaterial-based tumor therapeutics.*

### *DOI: http://dx.doi.org/10.5772/intechopen.105700 Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art*

To date, increasing literatures in the cutting-edge research area have turned to phototherapy combined with various nanomaterials in cancer therapy. Of them, carbon-based materials such as graphene and carbon nanotubes have attracted attention in the field of cancer phototherapy worldwide attribute to their unique physical and chemical properties including large surface area, thermal conductivity, and electrical properties [68]. Additionally, several kinds of nontoxic photosensitizers involved in phototherapy are also functionalized on the aforementioned carbon-based nanomaterials. Current research has also highlighted the potential role of stimuli-responsive nanomaterials (PNMs) with characteristics of responding to endogenous pathological changes for smart tumor-specific phototherapeutics [66]. For instance, Fu et al. took advantage of the porous shuttle-shape platinum methylene blue (IV-Mb) coordination polymer nanotheranostics-loaded 10-hydroxycamptothecin (CPT) for synergistically enhancing the in situ mitochondrial reactive oxygen species (ROS) and highly efficient tumor ablation by phototherapy, which was regarded as a promising method for synergistic oncotherapy [70]. Furthermore, a TME-sensitive oxygen-dualgenerating nanosystems named MnO2@Chitosan-CyI (MCC) has been developed to decrease the level of glutathione (GSH) and relieve environmental tumor hypoxia, which reveals synergistic effects with PDT in cancer treatment by triggering an acute immune response and reducing tumor metastasis [67].

Of note, the chemodynamic therapy (CDT) based on photothermal-enhanced Fenton has also attracted considerable research attention in the field, and the nanocatalyst-based strategy with high specificity and limited side effects has also emerged as a promising therapeutic option for the in-situ treatment of various cancers [71]. For instance, a number of multifunctional nanomaterials (e.g., metal oxide- or metalsulfide-based nanocatalysts) have been manufactured to trigger the reaction within the TME and generate highly cytotoxic hydroxyl radicals as well [71].

### *5.2.1 Nanomaterials in cancer photothermal therapy (PTT)*

Nanomaterial-based PTT has been recognized as a promising therapeutic modality for whole-body anti-tumor immune response and tumor ablation in the tumor microenvironment [72, 73]. Recently, Yang et al. took advantage of the magnetite nanomedicine in the administration of lung cancer and reported the synergistic effect with hyperthermia and chemotherapy, which collectively suggested the designed SPIO@PSS/CDDP/HSA-MTX nanoparticles with good biocompatibility and stability as powerful candidate nanoplatform for future antitumor treatment strategies [55]. Meanwhile, gold-nanobranched-shell-based vehicles and near-infrared nanomaterialliposome hybrid nanocarriers (NIRN-Lips) with dual superiorities such as higher tumor permeability, enhanced photoluminescence, stimulus-responsive drug release, better tumor-targeted drug delivery, and anti-tumor efficacy have been applied in cancer PTT and chemo-photothermal therapy as well [23, 74, 75]. Collectively, it is of paramount importance for the future improvement of photothermal therapy (PTT) via incorporating drug conjugates and polymer linkers with the surface of nanomaterials, which will further enhance the multiplexing capability and surface functionalization of nanomaterials as well as the advanced cancer imaging and therapies [61].

### *5.2.2 Nanomaterials in cancer photodynamic therapy (PDT)*

Photodynamic therapy (PDT) is a noninvasive form of therapy that combines both photophysical and photochemical processes, which has emerged as a promising therapeutic modality for cancer and nononcological diseases of various types and locations [59]. Differ from the aforementioned chemoradiotherapy, the third-generation photosensitizers of PDT are more affordable and dispense with hospitalization. PDT mainly functions via the activation of photosensitizers with an applicable wavelength of light and the upregulation of transient concentration of reactive oxygen species (ROS) accumulated at tumor sites, which has emerged as an important therapeutic option in oncology [76]. In recent years, PDT has attracted widespread attention as a highly selective and noninvasive approach for various cancer treatments, and in particular, the carrier nanoparticles with additional active supplementary and complementary roles [77]. However, PDT has inherent defects in treating deep tumors due to the insufficient luminous flux and limitation in approved drugs as well as the inevitable occurrence of peripheral tissue damage [59]. Additionally, due to the unique tumor microenvironment, the PDT-induced immune responses upon cancers are generally mild and thus not sufficient to ultimately eradicate metastatic cells as well [67].

The combination of nanomaterials with photosensitizers can further potentiate the efficiency and selectivity of PDT and help eliminate the side effects [78]. Current investigations have illuminated the practicality of utilizing the persistent or scintillation luminescence nanoparticles (e.g., porphyrins) with conjunctive photosensitizers for photodynamic therapy, which is adequate to enhance the effectiveness of X-raybased ionizing radiation and minimalize the potential damage to healthy cells [79]. For example, Wang et al. developed novel biphasic and bimetallic Rh-based core-shell Au@Rh-ICG-CM nanostructures with good biocompatibility and photoacoustic imaging properties for the treatment of hypoxic tumors in combination with PDT and verified the synergistic enhancement upon oxygen generation from the endogenous hydrogen peroxide in cancer [80].

Generally, nanoparticles as delivery vehicles in PDT can be functional and classified into active participants and passive carriers during photosensitizer excitation [76]. Meanwhile, a series of oxygen-evolving agents (e.g., perfluorocarbon, catalase, HbO2) for self-supplying oxygen and Manganese dioxide (MnO2)-based nanoparticles with high reactivity toward H2O2 have been incorporated into the PDT nanosystems [67]. Distinguish from the nonbiodegradable carriers with extraneous functions, active nanoparticles can be mechanistically subclassified and divided into self-illuminating nanoparticles, upconverting nanoparticles, and photosensitizer nanoparticles [81]. Nevertheless, the cancer regions deep in the body and the deficiency of the second-generation PDT nanoparticles still remain the major obscure challenges before the adoption in large-scale clinical application [67]. In consequence, there is an urgent need for the development of intelligent nanosystems capable of functioning in the TME and enhancing the therapeutic efficacy of PDT for deep cancers.

### **5.3 Nanomaterials in cancer immunotherapy**

The complex orchestration of cancer cells with tumor immune microenvironment results in the emergence of novel immunotherapy-based treatment regimens in patients [3, 14]. Immunotherapy such as immune checkpoint blockade and adoptive cell infusion has turned into a powerful clinical alternative for cancer administration attributes to their durable responses in hematologic malignancies and multiple metastatic solid tumors [82–85]. Generally, cancer immunotherapy functions mainly via stimulating or training the inherent immunological systems and thus benefits the recognition, attack, and eradication of cancer cells with minimal damage to normal cells

### *DOI: http://dx.doi.org/10.5772/intechopen.105700 Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art*

as well [13, 83]. Notably, cancer immunotherapy (e.g., natural killer cells, chimeric antigen receptor transduced T cells, cytotoxic T-lymphocyte antigen 4, programmed cell death-1) might cause unique toxicity profiles or an insignificant spectrum of immune-related adverse events (irAEs) differ from the toxicities of chemoradiotherapy and phototherapeutics depending on their mode of action [82, 86]. Worse still, despite the potentially favorable outcomes for advanced-stage patients such as complete cures and long-term survival, it is reported that cancer immunotherapy only works well in a relatively small subset of patients [87]. For example, Gong et al. recently reported the prominent challenges to the further broad implementation of T-cell-based immunotherapies including insufficient expansion, decreased cellular vitality *in vitro*, and trafficking of T cells into solid tumors [88].

In recent years, nanoparticle-based nanomedicine has revealed dramatic progress in the fast-rising field of cancer immunotherapy and has boosted therapeutic outcomes. Nanomaterials with unique chemical and physical features offer advantaged therapeutic platforms for photo-induced hyperthermia and cancer immunotherapy by turning the "cold" nonimmunoresponsive cancers and metastases into the "hot" immuno-responsive lesions [87, 89]. Moreover, nanomaterial-based nanomedicines can also be employed to target the tumor immune microenvironment, potentiate antigen presentation, trigger the release of danger-associated molecular patterns, inhibit immunosuppressive cells, and thus boost the therapeutic outcomes of cancer immunotherapy [87]. Of note, the fourth generation of biomaterials including nanomaterials is expected to stimulate a more specific cellular response and a more accurate control of sophisticated immunomodulation to the implants or cancers [90]. Collectively, nanomaterials after rational designation are uniquely suited to overcome the aforementioned challenges in cancer immunotherapy.

### **5.4 Nanomaterials in combined therapy of cancer**

Due to the aforementioned deficiency in cancer treatment, investigators have turned to exploring the feasibility of combining nanomaterials with other strategies (e.g., surgery, chemotherapy, radiotherapy, immunotherapy) for increasing the coordination of treatment effects as well as reducing the side effects [77, 91, 92]. Different from monotherapy, combination therapy for cancer patients usually provokes a good response to tumor surveillance and clearance [93]. Of note, Wang et al. recently summarized the ferroptosis-inducing nanomedicine by combining ferroptosis with nanomaterials, the conventional treatment, and emerging therapy for cancer therapy, yet most of the ferroptosis inducers such as system Xc-inhibitors (e.g., erastin and sorafenib) and GPX4 inhibitors (e.g., RSL3 and altretamine) had not been clinically approved due to nonspecific distribution, poor solubility, and unpredictable side effects [1, 94].

In the last years, a variety of 2D nanomaterials (e.g., ceramic-based biomaterials and 2D MXenes) with prominent physiochemical properties and specific surface properties (e.g., protein corona formation, unique planar structure, and chemical modification) have been explored in cancer management in combination with surgical treatment, radiotherapy, chemotherapy, photothermal therapy, photodynamic therapy, chemodynamic therapy, radiodynamic therapy, and immunotherapy [84, 95]. For example, current achievements in the combination therapy of glioblastoma with nanocarriers have demonstrated increasing benefits against the disappointing clinical outcomes and existing challenges such as blood-brain barrier (BBB), tumor heterogeneity, glioma stem cells, drug efflux pumps, and toxicity, which are particularly

formidable challenges in developing cancer therapeutics [63, 64]. In addition, nanocarrier-based combination therapy has been supposed to ensure the targeted colocalization of drugs into the tumor sites and facilitate sequential drug exposures and the synergistic drug ratio [64]. As reviewed by Zhao et al., numerous nanoformulations (e.g., Doxil, Abraxane, and DaunoXome) were not only adequate to load hydrophobic and hydrophilic drugs and prolong the half-life of diagnostic or theranostic agents, but also could reduce the toxicity of the parent compound and thereby ameliorate its therapeutic index [64].

### **6. Discussion and conclusions**

Cancers of various kinds remain a core challenge and life-threatening disease taking millions of peoples' lives as well as exacerbating the quality of life of the survivors [2, 13]. Despite the inspiring advances in the cancer treatment paradigm, high mortality and the concomitant toxicities of traditional therapies result in a significant challenge to adherence and tolerability of patients, and in particular, the severe adverse effects and toxic effects of chemoradiotherapy and phototherapeutics on patients cannot be neglected [96, 97]. Therewith, pioneering clinicians and researchers turned to alternate treatment regimens with a complete response and minimum side effects during cancer treatment. Among them, anticancer nanomedicine has been studied for over 30 years and a handful of formulations have been approved for clinical purposes, which has revolutionized the remedy of several advanced-stage tumors [30, 98]. For example, Chen et al. reported a novel and low-cost modality for augmented efficacy upon cancers *via* a combination of *in vivo* luminescent nanoparticle agent-based radiation and photodynamic therapies [79]. Meanwhile, chemodynamic therapy (CDT) in combination with photothermal therapy (PTT) and multifunctional nanomaterials has also been utilized to enhance therapeutic efficacy in cancer theragnostic, which also provides more effective efficacy when compared with monotherapy [71]. Despite the unique physical and chemical properties including targeting specificity and profound stability, the application of nontoxic nanomaterials coated with appropriate structures and biocompatibility for *in vivo* imaging is of great importance for clinical purposes. Moreover, considering the influence of the large size of nanomaterials for localization in tissues, nanoparticles should be degraded into the essential components before they can be excreted *via* metabolism or the kidneys.

Nevertheless, the tumor microenvironment as well as the toxic and side effects of current therapeutic regimens still remain the major obstacle to be overcome [3, 58, 60, 72]. For this purpose, great efforts have been expended on the modification of the physicochemical surface properties of nanomaterials with increased complexity and adaptability for the more sophisticated immunomodulation against various tumor cells in the past decades [90, 93]. For instance, a series of novel nanomaterials based on the surface modification of MXenes for combination therapy with magnetic resonance (MR), magnetic resonance imaging (MRI), or computed tomography (CT) have been manufactured such as Nb2C nanosheets with polyvinylpyrrolidone (PVP) decoration, PEGylation assembled into Ti3C2 nanosheets, Ta4C3 nanosheets modified with the soybean phospholipid (SP), Ta4C3 nanosheets coupled with Fe3O4 nanoparticles, Ti3C2 MXene attached to mesoporous silica nanoparticles (MSNs) [99].

To date, topographical modification of nanomaterials has become an attractive and expanding field aiming to dissect the sophisticated diversity of synergistic interactions between surface nanotopography and cancer cells, and thus holds the

*DOI: http://dx.doi.org/10.5772/intechopen.105700 Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art*

promising prospect for solving the long-lasting challenges in cancer nanotheranostics [84, 90]. Notably, self-assembled nanomedicines with unique and versatile features have been extensively explored for dealing with the malignancy and heterogeneity of tumors, which are designed to enhance antitumor immune responses *via* a series of immuno-potentiating biofunctions and controlled pharmacokinetics in the tumor regions [98]. However, considering the heterogeneity of tumors and inefficiency of nanoparticle loading and releasing, it remains challenging to ensure agents specifically targeting cancer cells and alleviating collateral toxicity to healthy tissue. Most of all, despite the plethora of information on cell-surface interaction and nanofabrication at the research level, there is still a long way to obtain more advanced nanopatterning techniques and transform the academic knowledge into commercial technologies or clinical practice [90, 100]. Nanomaterials are acknowledged as advantaged sources for tumor surveillance and elimination. Distinguish from our previously reported biomaterials and various counterparts of immune cells such as T cells, dendritic cells, natural killer cells, and Treg cells, the nanomaterial-based nanomedicine efficaciously fulfills the function of combating transformed hematological malignancies and metastatic solid tumors. Moreover, considering the inherent properties, nanomaterials are "off-the-shelf" products satisfying the clinical demand for large-scale manufacture for cancer diagnosis and treatment.

### **Acknowledgements**

The coauthors thank the members of the Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province & NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, The First Affiliated Hospital of Shandong First Medical University, Hefei Institute of Physical Science in Chinese Academy of Sciences, Tianjin Key Laboratory of Engineering Technologies for Cell Pharmaceutical, and National Engineering Research Center of Cell Products for their technical support. This work was supported by grants from the project Youth Fund supported by Shandong Provincial Natural Science Foundation (ZR2020QC097), Fujian Provincial Ministerial Finance Special Project (2021XH018), Jiangxi Provincial Key New Product Incubation Program Funded by Technical Innovation Guidance Program of Shangrao City (2020G002), Science and technology projects of Guizhou Province (QKH-J-ZK[2021]-107), The 2021 Central-Guided Local Science and Technology Development Fund (ZYYDDFFZZJ-1), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT320005), Medical Innovation Project of Fujian Provincial Health and Health Commission (2019-CX-21), Natural Science Foundation of Jiangxi Province (20212BAB216073), Key project funded by Department of Science and Technology of Shangrao City (2020AB002, 2020 K003, 2021F013), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT320005), Gansu Key Laboratory of Molecular Diagnosis and Precision treatment of surgical tumors (18JR2RA033), and Horizontal Project upon Retrospective Analyses of COVID-19 (2020XH001).

### **Conflict of interest**

The authors declare no conflict of interest.

### **Notes/thanks/other declarations**

Not applicable.

### **Appendices and nomenclature**


### **Author details**

Hao Yu1,2,3, Zhihai Han4 , Cunrong Chen<sup>5</sup> \* and Leisheng Zhang6,7,8,9\*

1 School of Medicine, Nankai University, China

2 National Engineering Research Center of Cell Products, AmCellGene Engineering Co., Ltd, China

3 Tianjin Key Laboratory of Engineering Technologies for Cell Pharmaceutical, China

4 Jiangxi Research Center of Stem Cell Engineering, Jiangxi Health-Biotech Stem Cell Technology Co., Ltd., China

5 Department of Critical Care Medicine, Union Hospital of Fujian Medical University, China

6 Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province and NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, China

7 Key Laboratory of Radiation Technology and Biophysics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, China

8 Institute of Health-Biotech, Health-Biotech (Tianjin) Stem Cell Research Institute Co., Ltd., China

9 Center for Cellular Therapies, The First Affiliated Hospital of Shandong First Medical University, China

\*Address all correspondence to: 13705056799@139.com and leisheng\_zhang@163.com

© 2022 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.

### **References**

[1] Wang Y, Liu T, Li X, Sheng H, Ma X, Hao L. Ferroptosis-inducing nanomedicine for cancer therapy. Frontiers in Pharmacology. 2021;**12**:735965

[2] Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. CA: A Cancer Journal for Clinicians. 2021;**71**:7-33

[3] Zhang L, Liu M, Yang S, Wang J, Feng X, Han Z. Natural killer cells: Of-the-shelf cytotherapy for cancer immunosurveillance. American Journal of Cancer Research. 2021;**11**:1770-1791

[4] Depil S, Duchateau P, Grupp SA, Mufti G, Poirot L. 'Offthe-shelf' allogeneic CAR T cells: Development and challenges. Nature Reviews Drug Discovery. 2020;**19**:185-199

[5] Chen M, Hu S, Li Y, Jiang TT, Jin H, Feng L. Targeting nuclear acid-mediated immunity in cancer immune checkpoint inhibitor therapies. Signal Transduction and Targeted Therapy. 2020;**5**:270

[6] Sahin U, Oehm P, Derhovanessian E, Jabulowsky RA, Vormehr M, et al. An RNA vaccine drives immunity in checkpoint-inhibitor-treated melanoma. Nature. 2020;**585**:107-112

[7] Holyoake DLP, Smyth EC. Chemoradiotherapy or surgery for very early esophageal squamous cancer: Can a nonrandomized trial give us the answer? Gastroenterology. 2021;**161**:1793-1795

[8] Solaini L, Perna F, Cavaliere D, Vaccaro C, Avanzolini A, Cucchetti A, et al. Average treatment effect of robotic versus laparoscopic rectal surgery for

rectal cancer. The International Journal of Medical Robotics. 2021;**17**:e2210

[9] Rallis KS, Lai Yau TH, Sideris M. Chemoradiotherapy in cancer treatment: Rationale and clinical applications. Anticancer Research. 2021;**41**:1-7

[10] He Y, Liu QW, Liao HX, Xu WW. Microbiota in cancer chemoradiotherapy resistance. Clinical and Translational Medicine. 2021;**11**:e250

[11] Conibear J, Astra Zeneca UKL. Rationale for concurrent chemoradiotherapy for patients with stage III non-small-cell lung cancer. British Journal of Cancer. 2020;**123**:10-17

[12] Basar R, Daher M, Rezvani K. Nextgeneration cell therapies: The emerging role of car-nk cells. Hematology American Society of Hematology Education Program. 2020;**2020**:570-578

[13] Daher M, Melo Garcia L, Li Y, Rezvani K. CAR-NK cells: The next wave of cellular therapy for cancer. Clinical & Translational Immunology. 2021;**10**:e1274

[14] Zhang L, Meng Y, Feng X, Han Z. CAR-NK cells for cancer immunotherapy: From bench to bedside. Biomarker Research. 2022;**10**:12

[15] Bordon Y. An RNA vaccine for advanced melanoma. Nature Reviews Immunology. 2020;**20**:517

[16] Rohatgi A, Kirkwood JM. Cancer vaccine induces potent T cell responses but is it enough? Nature Reviews Clinical Oncology. 2020;**17**:721-722

[17] Sahin U, Derhovanessian E, Miller M, Kloke BP, Simon P, et al. Personalized RNA mutanome vaccines mobilize

*Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art DOI: http://dx.doi.org/10.5772/intechopen.105700*

poly-specific therapeutic immunity against cancer. Nature. 2017;**547**:222-226

[18] Liu E, Marin D, Banerjee P, Macapinlac HA, Thompson P, et al. Use of car-transduced natural killer cells in CD19-positive lymphoid tumors. New England Journal of Medicine. 2020;**382**:545-553

[19] Zhang Y, Li Y, Cao W, Wang F, Xie X, Li Y, et al. Single-cell analysis of target antigens of car-t reveals a potential landscape of "on-target, off-tumor toxicity". Frontiers in Immunology. 2021;**12**:799206

[20] Pan J, Tan Y, Wang G, Deng B, Ling Z, Song W, et al. Donor-derived CD7 chimeric antigen receptor t cells for t-cell acute lymphoblastic leukemia: First-in-human, phase I trial. Journal of Clinical Oncology. 2021;**39**:3340-3351

[21] Ning L, Zhu B, Gao T. Gold nanoparticles: Promising agent to improve the diagnosis and therapy of cancer. Current Drug Metabolism. 2017;**18**:1055-1067

[22] Nazir S, Hussain T, Ayub A, Rashid U, MacRobert AJ. Nanomaterials in combating cancer: Therapeutic applications and developments. Nanomedicine. 2014;**10**:19-34

[23] Liang P, Mao L, Dong Y, Zhao Z, Sun Q, Mazhar M, et al. Design and application of near-infrared nanomaterial-liposome hybrid nanocarriers for cancer photothermal therapy. Pharmaceutics. 2021;**13**:2070

[24] Huang X, Tang S, Mu X, Dai Y, Chen G, Zhou Z, et al. Freestanding palladium nanosheets with plasmonic and catalytic properties. Nature Nanotechnology. 2011;**6**:28-32

[25] Wyatt BC, Nemani SK, Anasori B. 2D transition metal carbides (MXenes) in metal and ceramic matrix composites. Nano Convergence. 2021;**8**:16

[26] Wu Z, Shang T, Deng Y, Tao Y, Yang QH. The assembly of mxenes from 2d to 3d. Advanced Science (Weinh). 2020;**7**:1903077

[27] Hong YL, Liu Z, Wang L, Zhou T, Ma W, Xu C, et al. Chemical vapor deposition of layered twodimensional MoSi2N4 materials. Science. 2020;**369**:670-674

[28] Stater EP, Sonay AY, Hart C, Grimm J. The ancillary effects of nanoparticles and their implications for nanomedicine. Nature Nanotechnology. 2021;**16**:1180-1194

[29] Bayda S, Adeel M, Tuccinardi T, Cordani M, Rizzolio F. The history of nanoscience and nanotechnology: From chemical-physical applications to nanomedicine. Molecules. 2019;**25**:112

[30] Chiang CL, Cheng MH, Lin CH. From nanoparticles to cancer nanomedicine: Old problems with new solutions. Nanomaterials (Basel). 2021;**11**:1727

[31] Ang MJY, Chan SY, Goh YY, Luo Z, Lau JW, Liu X. Emerging strategies in developing multifunctional nanomaterials for cancer nanotheranostics. Advanced Drug Delivery Reviews. 2021;**178**:113907

[32] Tang L, Zhang A, Zhang Z, Zhao Q, Li J, Mei Y, et al. Multifunctional inorganic nanomaterials for cancer photoimmunotherapy. Cancer Communication (Lond). 2022;**42**:141-163

[33] Cheng Z, Li M, Dey R, Chen Y. Nanomaterials for cancer therapy: Current progress and perspectives. Journal of Hematology & Oncology. 2021;**14**:85

[34] Yang C, Lin ZI, Chen JA, Xu Z, Gu J, Law WC, et al. Organic/ inorganic self-assembled hybrid nano-architectures for cancer therapy applications. Macromolecular Bioscience. 2022;**22**:e2100349

[35] Zhang M, Gao S, Yang D, Fang Y, Lin X, Jin X, et al. Influencing factors and strategies of enhancing nanoparticles into tumors in vivo. Acta Pharmaceutica Sinica B. 2021;**11**:2265-2285

[36] Huang D, Sun L, Huang L, Chen Y. Nanodrug delivery systems modulate tumor vessels to increase the enhanced permeability and retention effect. Journal of Personalized Medicine. 2021;**11**:124

[37] Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA-A Cancer Journal for Clinicians. 2020;**70**:7-30

[38] Chaturvedi VK, Singh A, Singh VK, Singh MP. Cancer nanotechnology: A new revolution for cancer diagnosis and therapy. Current Drug Metabolism. 2019;**20**:416-429

[39] Han X, Xu K, Taratula O, Farsad K. Applications of nanoparticles in biomedical imaging. Nanoscale. 2019;**11**:799-819

[40] Reuveni T, Motiei M, Romman Z, Popovtzer A, Popovtzer R. Targeted gold nanoparticles enable molecular CT imaging of cancer: An in vivo study. International Journal of Nanomedicine. 2011;**6**:2859-2864

[41] Luo D, Wang X, Zeng S, Ramamurthy G, Burda C, Basilion JP. Prostate-specific membrane antigen targeted gold nanoparticles for prostate cancer radiotherapy: Does size matter for targeted particles? Chemical Science. 2019;**10**:8119-8128

[42] Jin Y, Tang C, Tian J, Shao B. Integration of taox with bi2s3 for targeted multimodality breast cancer theranostics. Bioconjugate Chemistry. 2021;**32**:161-171

[43] Lambert JW, Sun Y, Stillson C, Li Z, Kumar R, Wang S, et al. An intravascular tantalum oxide-based ct contrast agent: Preclinical evaluation emulating overweight and obese patient size. Radiology. 2018;**289**:103-110

[44] Blakkisrud J, Londalen A, Dahle J, Martinsen AC, Kolstad A, Stokke C. Myelosuppression in patients treated with (177)lutetium-lilotomab satetraxetan can be predicted with absorbed dose to the red marrow as the only variable. Acta Oncologica. 2021;**60**:1481-1488

[45] Cheng FY, Su CH, Yang YS, Yeh CS, Tsai CY, et al. Characterization of aqueous dispersions of Fe(3) O(4) nanoparticles and their biomedical applications. Biomaterials. 2005;**26**:729-738

[46] Xu F, Li X, Chen H, Jian M, Sun Y, Liu G, et al. Synthesis of heteronanostructures for multimodality molecular imaging-guided photothermal therapy. Journal of Materials Chemistry B. 2020;**8**:10136-10145

[47] Zheng S, Jin S, Jiao M, Wang W, Zhou X, Xu J, et al. Tumor-targeted Gd-doped mesoporous Fe3O4 nanoparticles for T1/T2 MR imaging guided synergistic cancer therapy. Drug Delivery. 2021;**28**:787-799

[48] Ni D, Jiang D, Ehlerding EB, Huang P, Cai W. Radiolabeling silicabased nanoparticles via coordination chemistry: Basic principles, strategies, and applications. Accounts of Chemical Research. 2018;**51**:778-788

*Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art DOI: http://dx.doi.org/10.5772/intechopen.105700*

[49] Liu Q, Qian Y, Li P, Zhang S, Liu J, Sun X, et al. (131)I-labeled copper sulfide-loaded microspheres to treat hepatic tumors via hepatic artery embolization. Theranostics. 2018;**8**:785-799

[50] Garrigue P, Tang J, Ding L, Bouhlel A, Tintaru A, Laurini E, et al. Self-assembling supramolecular dendrimer nanosystem for PET imaging of tumors. Proceedings of the National Academy of Sciences of the United States of America. 2018;**115**:11454-11459

[51] Chen P, Wang H, Wu H, Zou P, Wang C, Liu X, et al. Intracellular synthesis of hybrid gallium-68 nanoparticle enhances micropet tumor imaging. Analytical Chemistry. 2021;**93**:6329-6334

[52] Xiong X, Dang W, Luo R, Long Y, Tong C, Yuan L, et al. A graphene-based fluorescent nanoprobe for simultaneous imaging of dual miRNAs in living cells. Talanta. 2021;**225**:121947

[53] Yao L, Zheng L, Cai G, Wang S, Wang L, Lin J. A rapid and sensitive salmonella biosensor based on viscoelastic inertial microfluidics. Sensors (Basel). 2020;**20**:2737

[54] Zhang L, Wang Y, Wang J, Shi J, Deng K, Fu W. rhEPO/EPO discrimination with ultrasensitive electrochemical biosensor based on sandwich-type nano-Au/ZnO sol-gel/ nano-Au signal amplification. Biosensors & Bioelectronics. 2013;**50**:217-223

[55] Yang SJ, Huang CH, Wang CH, Shieh MJ, Chen KC. The synergistic effect of hyperthermia and chemotherapy in magnetite nanomedicine-based lung cancer treatment. International Journal of Nanomedicine. 2020;**15**:10331-10347 [56] Siegler EL, Zhu Y, Wang P, Yang L. Off-the-shelf CAR-NK cells for cancer immunotherapy. Cell Stem Cell. 2018;**23**:160-161

[57] Mullard A. Addressing cancer's grand challenges. Nature Reviews Drug Discovery. 2020;**19**:825-826

[58] Elkin EB, Bach PB. Cancer's next frontier: Addressing high and increasing costs. Journal of the American Medical Association. 2010;**303**:1086-1087

[59] Chilakamarthi U, Giribabu L. Photodynamic therapy: Past, present and future. Chemical Record. 2017;**17**:775-802

[60] Jarosz-Biej M, Smolarczyk R, Cichon T, Kulach N. Tumor microenvironment as a "game changer" in cancer radiotherapy. International Journal of Molecular Sciences. 2019;**20**:3212

[61] Murugan C, Sharma V, Murugan RK, Malaimegu G, Sundaramurthy A, et al. Two-dimensional cancer theranostic nanomaterials: Synthesis, surface functionalization and applications in photothermal therapy. Journal of Controlled Release. 2019;**299**:1-20

[62] Da Silva GH, Franqui LS, Petry R, Maia MT, Fonseca LC, Fazzio A, et al. Recent advances in immunosafety and nanoinformatics of two-dimensional materials applied to nano-imaging. Frontiers in Immunology. 2021;**12**:689519

[63] Karim R, Palazzo C, Evrard B, Piel G. Nanocarriers for the treatment of glioblastoma multiforme: Current stateof-the-art. Journal of Controlled Release. 2016;**227**:23-37

[64] Zhao M, van Straten D, Broekman MLD, Preat V, Schiffelers RM. Nanocarrier-based drug combination therapy for glioblastoma. Theranostics. 2020;**10**:1355-1372

[65] Cheng L, Wang X, Gong F, Liu T, Liu Z. 2D nanomaterials for cancer theranostic applications. Advanced Materials. 2020;**32**:e1902333

[66] Zhou B, Guo Z, Lin Z, Jiang BP, Shen XC. Stimuli-responsive nanomaterials for smart tumor-specific phototherapeutics. Chem Med Chem. 2021;**16**:919-931

[67] Shen Z, Xia J, Ma Q, Zhu W, Gao Z, Han S, et al. Tumor microenvironmenttriggered nanosystems as dual-relief tumor hypoxia immunomodulators for enhanced phototherapy. Theranostics. 2020;**10**:9132-9152

[68] Sundaram P, Abrahamse H. Phototherapy combined with carbon nanomaterials (1d and 2d) and their applications in cancer therapy. Materials (Basel). 2020;**13**:4830

[69] Antunes HS, Herchenhorn D, Small IA, Araujo CMM, Viegas CMP, de Assis RG, et al. Long-term survival of a randomized phase III trial of head and neck cancer patients receiving concurrent chemoradiation therapy with or without low-level laser therapy (LLLT) to prevent oral mucositis. Oral Oncology. 2017;**71**:11-15

[70] Fu X, Yin W, Shi D, Yang Y, He S, Hai J, et al. Shuttle-shape carrier-free platinum-coordinated nanoreactors with O2 self-supply and ros augment for enhanced phototherapy of hypoxic tumor. ACS Applied Materials & Interfaces. 2021;**13**:32690-32702

[71] Manivasagan P, Joe A, Han HW, Thambi T, Selvaraj M, Chidambaram K, et al. Recent advances in multifunctional nanomaterials for

photothermal-enhanced Fenton-based chemodynamic tumor therapy. Materials Today Bio. 2022;**13**:100197

[72] Xu P, Liang F. Nanomaterial-based tumor photothermal immunotherapy. International Journal of Nanomedicine. 2020;**15**:9159-9180

[73] Darrigues E, Nima ZA, Griffin RJ, Anderson JM, Biris AS, Rodriguez A. 3D cultures for modeling nanomaterialbased photothermal therapy. Nanoscale Horizons. 2020;**5**:400-430

[74] Liu Y, Zhang X, Luo L, Li L, Zhu RY, et al. Gold-nanobranched-shell based drug vehicles with ultrahigh photothermal efficiency for chemophotothermal therapy. Nanomedicine. 2019;**18**:303-314

[75] Lee SY, Shieh MJ. Platinum(ii) drug-loaded gold nanoshells for chemophotothermal therapy in colorectal cancer. ACS Applied Materials & Interfaces. 2020;**12**:4254-4264

[76] Chatterjee DK, Fong LS, Zhang Y. Nanoparticles in photodynamic therapy: An emerging paradigm. Advanced Drug Delivery Reviews. 2008;**60**:1627-1637

[77] Zhang Q, Li L. Photodynamic combinational therapy in cancer treatment. Journal of BUON. 2018;**23**:561-567

[78] Kwiatkowski S, Knap B, Przystupski D, Saczko J, Kedzierska E, Knap-Czop K, et al. Photodynamic therapy - mechanisms, photosensitizers and combinations. Biomedicine & Pharmacotherapy. 2018;**106**:1098-1107

[79] Chen W, Zhang J. Using nanoparticles to enable simultaneous radiation and photodynamic therapies for cancer treatment. Journal of

*Nanomaterials as Novel Biomarkers for Cancer Nanotheranostics: State of the Art DOI: http://dx.doi.org/10.5772/intechopen.105700*

Nanoscience and Nanotechnology. 2006;**6**:1159-1166

[80] Wang J, Sun J, Hu W, Wang Y, Chou T, Zhang B, et al. A porous au@ rh bimetallic core-shell nanostructure as an h2o2-driven oxygenerator to alleviate tumor hypoxia for simultaneous bimodal imaging and enhanced photodynamic therapy. Advanced Materials. 2020;**32**:e2001862

[81] Bakalova R, Ohba H, Zhelev Z, Ishikawa M, Baba Y. Quantum dots as photosensitizers? Nature Biotechnology. 2004;**22**:1360-1361

[82] Kennedy LB, Salama AKS. A review of cancer immunotherapy toxicity. CA-A Cancer Journal for Clinicians. 2020;**70**:86-104

[83] Riley RS, June CH, Langer R, Mitchell MJ. Delivery technologies for cancer immunotherapy. Nature Reviews Drug Discovery. 2019;**18**:175-196

[84] Ma B, Bianco A. Recent advances in 2d material-mediated immuno-combined cancer therapy. Small. 2021;**17**:e2102557

[85] Wang Q, Su X, He Y, Wang M, Yang D, Zhang R, et al. CD11c participates in triggering acute graftversus-host disease during bone marrow transplantation. Immunology. 2021;**164**:148-160

[86] Wang G, Sun X, Zuo S, Li C, Niu Q, Xia Y, et al. Homogeneously high expression of CD32b makes it a potential target for CAR-T therapy for chronic lymphocytic leukemia. Journal of Hematology & Oncology. 2021;**14**:149

[87] Shi Y, Lammers T. Combining nanomedicine and immunotherapy. Accounts of Chemical Research. 2019;**52**:1543-1554

[88] Gong N, Sheppard NC, Billingsley MM, June CH, Mitchell MJ. Nanomaterials for T-cell cancer immunotherapy. Nature Nanotechnology. 2021;**16**:25-36

[89] Liu Y, Crawford BM, Vo-Dinh T. Gold nanoparticles-mediated photothermal therapy and immunotherapy. Immunotherapy. 2018;**10**:1175-1188

[90] Harawaza K, Cousins B, Roach P, Fernandez A. Modification of the surface nanotopography of implant devices: A translational perspective. Materials Today Bio. 2021;**12**:100152

[91] Chang M, Hou Z, Wang M, Li C, Lin J. Recent advances in hyperthermia therapy-based synergistic immunotherapy. Advanced Materials. 2021;**33**:e2004788

[92] Pan J, Zuo S, Deng B, Xu X, Li C, Zheng Q, et al. Sequential CD19-22 CAR T therapy induces sustained remission in children with r/r B-ALL. Blood. 2020;**135**:387-391

[93] Anand S, Chan TA, Hasan T, Maytin EV. Current prospects for treatment of solid tumors via photodynamic, photothermal, or ionizing radiation therapies combined with immune checkpoint inhibition (a review). Pharmaceuticals (Basel). 10 May 2021;**14**(5):447

[94] Wang R, Su Q, Yin H, Wu D, Lv C, Yan Z. Inhibition of SRSF9 enhances the sensitivity of colorectal cancer to erastin-induced ferroptosis by reducing glutathione peroxidase 4 expression. International Journal of Biochemistry & Cell Biology. 2021;**134**:105948

[95] Lin H, Chen Y, Shi J. Insights into 2d mxenes for versatile biomedical applications: Current advances and challenges ahead. Advanced Science (Weinh). 2018;**5**:1800518

[96] Mun EJ, Babiker HM, Weinberg U, Kirson ED, Von Hoff DD. Tumor-treating fields: A fourth modality in cancer treatment. Clinical Cancer Research. 2018;**24**:266-275

[97] Tsimberidou AM, Fountzilas E, Nikanjam M, Kurzrock R. Review of precision cancer medicine: Evolution of the treatment paradigm. Cancer Treatment Reviews. 2020;**86**:102019

[98] Cabral H, Kinoh H, Kataoka K. Tumor-targeted nanomedicine for immunotherapy. Accounts of Chemical Research. 2020;**53**:2765-2776

[99] Liu Z, Lin H, Zhao M, Dai C, Zhang S, Peng W, et al. 2D superparamagnetic tantalum carbide composite mxenes for efficient breastcancer theranostics. Theranostics. 2018;**8**:1648-1664

[100] Ye Z, Sang T, Li K, Fischer NG, Mutreja I, Echeverria C, et al. Hybrid nanocoatings of self-assembled organicinorganic amphiphiles for prevention of implant infections. Acta Biomaterialia. 1 Mar 2022;**140**:338-349

### **Chapter 10**

## Biosensor for the Detection of Cyanobacterial Toxin Microcystin-LR

*Rasmus Rohtla, Kairi Kivirand, Eerik Jõgi and Toonika Rinken*

### **Abstract**

Cyanobacteria are found everywhere in the environment, and their growth accelerates significantly with rising amounts of sunlight and temperatures. The proliferation of cyanobacteria begins when the average temperatures rise above 15°C. The proliferation can lead to high amounts of secondary metabolites, such as cyanotoxins, in surrounding waters. The most common cyanotoxin is microcystin-LR (MC-LR). MC-LR can cause rashes, abdominal cramps, and liver damage in humans and animals, so continuous monitoring of its content in water is of great importance. MC-LR is commonly detected with high-performance liquid chromatography, but phosphatase inhibition-based bioassays and enzymelinked immunosorbent tests are also available. However, these are all lab-based methods and require sample transport and preparation for analytical procedures, not allowing for obtaining quick results. Therefore, there is a need for a rapid and field-based analysis method, and one promising option is to use biosensors. The present study aimed to design and construct an aptamer/antibody-based biosensor to detect MC-LR and test its applicability to detect MC-LR in cyanobacteria culture *(Microcystis aeruginosa)*.

**Keywords:** cyanobacteria, microcystin-LR, biosensor, aptamer, antibody, field-based method, environment, monitoring

### **1. Introduction**

Cyanotoxins are metabolites produced by cyanobacteria, a group of photosynthetic prokaryotes found in freshwater. The intake of contaminated water, skin contact, or swallowing water during swimming are among the most common reasons for poisoning caused by cyanotoxins [1]. An increase in temperature causes the cyanobacteria to grow faster. In addition, the spread of cyanobacteria is also affected by the pH of the environment, salinity, the presence of necessary nutrients (e.g., nitrogen and phosphorus), and light. It has been observed that global warming may increase the frequency and extent of cyanobacterial proliferation [2, 3]. Cyanobacteria can release toxins into the environment during the mass spread of microorganisms, that is, the water blooming.

### **1.1 Cyanotoxins**

Microcystins are the most widespread cyanobacterial toxins produced by *Microcystis aeruginosa* in freshwater lakes and rivers worldwide [4]. Microcystins are hepatotoxins that substantially affect serine/threonine protein phosphatases (PPs), which can remove phosphate from the protein in many biochemical pathways [5]. They are cyclic heptapeptides with a molecular weight of 800–1100 Da, and more than 250 different microcystins have been described [6]. The general structure of microcystins is cyclo-D-Ala1 -X<sup>2</sup> -D-MeAsp3 -Z4 -Adda5 -D-Glu6 -Mdha7 (superscript number indicates the position number, **Figure 1**), where X and Z are variable L-amino acids, D-MeAsp is D-erythro-β-methylaspartic acid, Adda is 3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid, and Mdha is N-methyldehydroalanine [5, 7]. Structure variations occur in all seven amino acid residues; most common are the replacement of L-amino acids in positions 2 and 4, replacement of Mdha by dehydrobutyrine (Dhb) or by serine in position 7, and a lack of methylation of amino acids in positions 3 and/or 7 [7]. The variations in Adda are essential because they may affect analytical test results, which use Adda as a marker, and in addition, Adda moiety is critical to microcystin activity [5]. The hydrophobicity of the amino acids at positions two and four influences the overall hydrophobicity. Hydrophobicity of the microcystin congener determines how the toxin interacts with cell membranes, and therefore, affects its specific toxicity [8].

The most common and most toxic is microcystin-LR (MC-LR), with leucine (Leu = L) in the second position and arginine (Arg = R) in the fourth position (**Figure 1**). Modeling of the MC-LR molecule has shown that the alanine and leucine residues in positions 1 and 2 extend beyond the ring plane; thus, allow selective binding to receptor molecules, which causes high toxicity of MC-LR and another metabolite, a cyclic non-ribosomal pentapeptide nodularin [7]. Also, three-dimensional structure studies of the MC-LR have shown that Adda and Arg side chains protrude from the ring distal from one another caused by the repulsion between the guanidino function of Arg and the hydrophobic Adda [9]. Microcystin-LR inhibits protein phosphatase type 1 and type 2A (PP1 and PP2A) activities in the cytoplasm of liver cells [10, 11], which leads to an increase in the phosphorylation of proteins in liver cells. The Adda

### **Figure 1.**

*Generic structure of microcystin-LR: Superscript numbers indicate the position numbers, and X and Z are the variable L-amino acids in different microcystins. The two specific L-amino acids of MC-LR are shown in black (leucine, L) and blue (arginine, R). Abbreviations: Ala is alanine; Leu is leucine; MeAsp is erythro-βmethylaspartic acid; Arg is arginine; Adda is 3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid; Glu is glutamic acid, and Mdha is N-methyldehydroalanine.*

### *Biosensor for the Detection of Cyanobacterial Toxin Microcystin-LR DOI: http://dx.doi.org/10.5772/intechopen.107366*

side-chain is accommodated to the hydrophobic channel [7]. The carboxylic D-Glu site makes hydrogen bonds to metal-bound water molecules [7]. The carboxyl group of the MeAsp site makes hydrogen bonds to conserved arginine and tyrosine residues in the PPP enzyme [7]. Finally, the methylene group at the Mdha site binds to an S-atom of a cysteine residue, and the leucine residue folds closely to another wellmaintained tyrosine residue [12].

The degradation of microcystins is slow in most water environments [13]. Most mycotoxins are heat-resistant [14], and the water treatment process cannot altogether remove them. Still, they can be degraded, when using UV treatment close to their absorption peak (UV lambda max for microcystin-LR is 238 nm) [4, 15]. Due to carboxyl, amino, and acylamino groups in the structure, mycotoxins have different ionization propensities at different pH values.

Limits for MC-LR in natural waters have been set in only a few countries. In Hungary and some US states, such as Indiana and New York, the MC-LR limit in water is 4 μg/l [16]. The World Health Organization (WHO) has set a limit of 1 μg/l for MC-LR in drinking water [6, 17].

### **1.2 Methods to detect cyanotoxins**

For the detection of cyanotoxins in water, the following methodologies are used: high-performance liquid chromatography (HPLC) combined with mass spectrometry (MS, MS/MS) or ultraviolet/photodiode array detectors (UV/PDA), enzyme-linked immunosorbent assays (ELISA), and protein phosphatase inhibition assay (PPIA).

HPLC is a selective and sensitive method that allows the simultaneous determination of different microcystins at very low concentrations (0.02 μg/l). Still, the determination is technically complex and time-consuming, and the cost of the apparatus and analysis is high [18]. In addition, pretreatment of samples is required [19]. Chromatographic methods do not allow on-site monitoring, and given the need to transport samples, results can be obtained in a minimum of 4–6 hours [19]. It is also important to consider matrix effects in chromatographic analysis, and prior calibration with the matrix is required [20].

ELISA and PPIA are the other technologies often used to detect microcystins. ELISA assays are based on antigen-antibody interactions, and analytes are detected by the color change resulting from the reaction. The ELISA assay is highly sensitive and relatively straightforward [19]. For commercial ELISA rapid tests, the limit of determination for microcystins is 0.06 μg/l, and the test time varies between 4 and 6 h [21]. A significant disadvantage of many commercial ELISAs is that they are based on anti-Adda antibodies and do not measure the specific microcystin, but the total microcystin and nodularin content [22] and there is cross-reactivity [20]. ELISA tests based on a monoclonal antibody against arginine at position 4 limit detection of as low as 0.002–0.006 μg/l [18, 23].

PPIA allows to perform assays efficiently and quickly (approx. 2 h), and is based on a protein phosphatase-catalyzed protein dephosphorylation reaction in which the presence of a chromogenic substrate (e.g., p-nitrophenol phosphate) releases p-nitrophenol, which is detected at 410 nm [24]. The enzymes used, such as protein phosphatase 1 (PP1), are readily available, and this method has a medium sensitivity of 0.1 μg/l for MC-LR [25]. The main disadvantage of PPIA is the low selectivity because cyanobacteria contain phosphatases, and it is impossible to identify different microcystins [26]. The interaction of microcystins with PP1 is thought to be related to non-coding amino acid residues: Adda, D-Glu, and Mdha at positions 5, 6, and 7


*LOD: limit of detection; HPLC-UV: high-performance liquid chromatography with UV detector; LC-MS/MS: liquid chromatography combined with mass spectrometry; ELISA: enzyme-linked immunosorbent assay; and PPIA: protein phosphatase inhibitors.*

### **Table 1.**

*Overview of MC-LR determination methods.*

of the microcystin molecules, respectively [27]. The essential analytical parameters characterizing the above-described microcystin determination methods are summarized in **Table 1**.

Each technique has some limitations in sensitivity, reliability, detection limit, or speed and cost. The selection of a suitable method is based on the information they provide and the technical expertise needed. The cost of analytical equipment, long-lasting measurements, and the need for qualified personnel to perform the analysis are a challenge for routine monitoring. Nowadays, methods suitable for the end-user that can be validated and accepted worldwide continue to be an objective for regulators and the industry. The variety of commercially available assays or testing kits for marine toxin analysis remains limited. The list of currently available point-on-site marine toxin end-product testing technologies is provided in ref. [28].

### **1.3 MC-LR biosensors**

Cyanotoxins are not monitored regularly in most countries due to technical complications in the detection and quantification. Biosensors for freshwater monitoring and safety applications are prospective alternatives to traditional methods. Biosensors are analytical devices that include a bio-recognition element linked to a transducer that transforms the chemical information produced into a readable signal followed by a detector. Most biosensors used to detect MC-LR are immunosensors that use antibodies or aptamers to recognize the analyte. The detection limit of biosensors ranges from 0.00003 to 0.37 μg/l, and the assay time is from 0.8 to 2.3 hours [29–34]. The most important parameters characterizing the biosensors used to determine microcystins are summarized in **Table 2**. High selectivity of bio-recognition is assured by using specific antibodies or aptamers.

### *1.3.1 Bio-recognition elements*

Antibodies or immunoglobulins (Ig) are glycoproteins used in nature to detect and neutralize foreign objects. They have a characteristic basic structure consisting *Biosensor for the Detection of Cyanobacterial Toxin Microcystin-LR DOI: http://dx.doi.org/10.5772/intechopen.107366*


### **Table 2.**

*An overview of MC-LR biosensors.*

of a protein chain linked by a disulfide bridge and a very high affinity for the antigen detected, described by the dissociation constant of the antigen/antibody complex. The values of this constant are usually between 10<sup>−</sup>12 and 10−<sup>8</sup> M [35]. The MC-LR monoclonal antibody used in the present work has an affinity toward mycotoxins, which have arginine in the 4th position, with the dissociation constant of 1.4 · 10<sup>−</sup>11 M [36].

Aptamers are synthetic single-stranded oligonucleotides capable of binding various molecules with high affinity and specificity. Aptamers are considered artificial antibodies and can adapt through intermolecular interactions [37, 38]. Nevertheless, compared with antibodies, they are more stable. When interacting with its target, the "lock key" is formed by matching the spatial conformation with the aptamer molecules [39]. Aptamers are produced using SELEX (systematic evolution of ligands by exponential enrichment), and once the aptamer sequence is developed, it can be reproduced with high precision. The characteristics of the aptamers selected for microcystin, identifying modifications at 3′ or 5′ ends to label or link the aptamers to the sensor platform, and their affinity to the target toxin are summarized in refs. [40, 41]. The MC-LR aptamer used in the present work, AN6 (5′ GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC 3′), is a microcystin-LR specific aptamer with the affinity (Kd) of 5 x 10<sup>−</sup><sup>8</sup> M. It can also bind to microcystin-LA but with 3-fold reduced affinity (approx. 15.8 · 10<sup>−</sup><sup>8</sup> M), and no binding to microcystin-YR has been observed [40, 41]. AN6 is a synthetic 60-base DNA aptamer with a molecular weight of 18167.79 Da.

### **1.4 Bead injection analysis**

It is promising to use measurements in analyte-containing flows for continuous monitoring of toxins for continuous monitoring of on-site analyses. One option for designing in-flow sensor systems is to use the principle of BIA (Bead Injection Analysis) [42, 43]. This microgranule insertion assay uses microgranule transport in a flowing solution to form microcolumns required for the assay. A selective component recognizing an analyte is immobilized on the surface of the microcolumnforming granules allowing it to pre-concentrate and bind the targeted compound. After removing the sample matrix, selective detection of the bound analyte occurs, for example, using an antigen/antibody interaction. The signal of the recognition

### **Figure 2.**

*Working principle of bead insertion analysis (BIA) . [44]: (A) injection of bio-activated granules into a flow channel to form a micro-column. (B) Sample injection (the sample binds to the activated granules). (C) Washing of the column to remove unbound sample components and matrix. (D) Labeled bio-component injection, incubation, and washing out of the unbound components. (E) Signal detection. (F) System regeneration.*

reaction is detected spectrometrically or by measuring the fluorescence signal. The scheme of BIA operation is shown in **Figure 2** [44].

The amount of activated granules required to form a microcolumn is small (approx. 20 μg), which allows the assay to be a single-use one. This technique eliminates the need to regenerate the bio-recognition system, the risk of contamination, and the risk of denaturation of the bio-component bound to the granules. It allows operation in a continuous flow system. To ensure the reliability and accuracy of the results obtained, it is also essential to ensure a consistently high quality of the bioactivation of the granules [45].

### **2. Experimental part**

### **2.1 Materials**

Solutions of aptamer (5' GGC GCC AAA CAG GAC CAC CAT GAC AAT TAC CCA TAC CAC CTC ATT ATG CCC CAT CTC CGC 3′ (AN6, Integrated DNA Technologies)) and microcystin (Enzo Life Sciences, ALX-350-012-C100) were prepared in 0.01 M phosphate buffer saline (0.15 M NaCl, pH 7.2, PBS). Monoclonal MC-LR antibody (Enzo Life Sciences, MC10E7) solution was prepared in 0.5 M carbonate buffer (pH 9.5). The solutions were stored at 4°C. Epichlorohydrin was from Acros Organics (A0386058) and Coomassie brilliant blue R-250 was from Fluka AG (99%, CH-9470). Sephadex G-50 medium granules were from Pharmacia Fine Chemicals (FB-14567). All other chemicals used were at analytical grade. Buffer solutions were prepared using ultrapure MilliQ water (specific resistance 18.2 MΩ·cm).

### **2.2 Preparation of activated microgranules**

Epichlorohydrin (Acros Organics, A0386058) was used to activate the Sephadex G-50 medium granules (Pharmacia Fine Chemicals, FB-14567). The antibody was covalently attached to the epoxy carbon of the epichlorohydrin via the amino group, using a previously published protocol with minor modifications was used [46]. First, 47 mg of granules were allowed to swell overnight at 4°C in 1 ml of water. After swelling, 400 μl of NaOH solution (concentration 0.1 M - 1 M) and 100 μl of epichlorohydrin to activate the granules were added and left on a shaker for 3 hours at room temperature. The beads were then washed twice with water and once with 0.5 M carbonate buffer (pH 9.5). The mixture was centrifuged at 2450 x g for 5 min after each washing step to separate beads. 0.5 to 2 ml of MC-LR antibody in 0.5 M carbonate buffer (pH 9.5) was added, with the antibody concentration varying from 10 to 350 μg/ml (the total amount). The mixture was incubated on a shaker for 24 h at room temperature. After incubation, the suspension was centrifuged (5 min at 2450 x g) and washed once with 0.5 M carbonate buffer (pH 9.5). To block free binding sites on the surface of the granules, ethanolamine solution (85 μl/ml in 0.5 M carbonate buffer) was added. The mixture was incubated on a shaker for 2 hours at room temperature. The suspension was centrifuged (5 min at 2450 x g), washed twice with water and several times with PBS buffer, and stored in PBS buffer at 4°C.

The yield of the attached antibody on the granules was evaluated with two different methods. First, it was visually inspected by adding 0.1% Coomassie brilliant blue R-250 (99% (Fluka AG, CH-9470)) to 30 μl of granules before adding ethanolamine. It was assessed by whether the granules turned blue, indicating the presence of bound protein on the granules. In addition, the protein content in the antibody solution was spectrophotometrically evaluated before and after the antibody attachment process. The protein content of the samples was determined at 280 nm, and the concentration was calculated using an absorption coefficient of 1.37 for IgG (ε 1%).

### **2.3 Carrying out measurements with biosensor**

The outflow channel of the BIA system was partially sealed with a moving cap, and 20 μl of bio-activated microgranules were injected into the measuring cell at a flow rate of 1 μl/sec to form a microcolumn. 30 μl of PBS buffer was added at a flow rate of 2 μl/sec to ensure the column's packing. A sample containing 150 μl of MC-LR was added at a flow rate of 1 μl/sec, the flow was stopped, and the system was incubated for 30 min. The measuring cell was washed with 150 μl of PBS at a flow rate of 2 μl/sec to remove the unbound toxin. Then 30 μl of MC-LR aptamer labeled with a fluorescence marker (Alexa Flour 647) was added at a flow rate of 1 μl/sec and incubated for 30 min. The concentration of the marker varied from 0.5 to 5 μg/ml. The unbound aptamer was removed from the microcolumn by adding 350 μl of PBS at a flow rate of 1 μl/sec. After each measurement, the cap was opened, and the system was washed at least four times with PBS buffer. PBS buffer with no added MC-LR was used for experimental determination of the system's background signal (all other measurement steps were left unchanged).

All measurements were performed in triplicate. Measurements were performed at room temperature. The fluorescence intensity was measured at 670 nm (excitation wavelength 650 nm) of the Alexa Flour 647 emission peak perpendicular to the excitation light. To calculate the signal change, the signal after washing off the unbound

MC-LR was subtracted from the final signal (signal after washing off unbound aptamer, recording started 5 min after completion of aptamer wash). The signal was recorded at 1-sec intervals. After stabilization, the mean signal was calculated as an average of 100 points to reduce experimental noise.

### **2.4 Cultivation and preparation of cyanobacteria sample**

To cultivate *Microcystis aeruginosa* (Norwegian Culture Collection of Algae, K-0540) cells, 1 ml of culture was inoculated into 50 ml of liquid sterilized BG11+ medium, and grown under artificial light for 14 days at 16°C [47]. A LED lamp (16 h white/8 h dark, 6 W 3000 K) kept at a distance of 20 cm from the culture vessel was used as a light source. The cells were stored at -20°C.

After thawing, the samples were concentrated. Repeated centrifugation (5 min at 10000 x g) reduced the sample volume five times. An ultrasonic probe sonicator (Bandelin HD 2020 Sonopuls, horn 3 mm) was used to disrupt the cyanobacterial cells for 1 min at a cycle intensity of 7/10 and a power of 75%.

### **2.5 The characterization of the formation of MC-LR complexes with size-exclusion chromatography (SEC)**

The formation of MC-LR complexes with antibody/aptamer was studied with an ÄKTA Purifier 10 liquid chromatography system (GE Healthcare) equipped with a UPC detector (280 nm) and a conductivity detector. The column (height 29 cm and diameter 1 cm) was loaded with Sephacryl S-200 HR (GE Healthcare, product ID: 10090795) gel pre-expanded overnight at room temperature in PBS buffer (pH 7.2) and packed under pressure to ensure the high quality of packing. For analyses, we optimized the flow rate (0.18 to 0.39 ml/min), sample volume (50 and 100 μl), and sample concentration (0.05 to 1 mg/ml). The column was calibrated with different proteins with molar weights ranging from 20 to 240 kDa. Dextran blue (2000 kDa) and potassium dichromate (294 Da) were used to determine the column void volume and total volume. All optimizations, calibrations, and measurements were performed at 8°C.

The experiments were performed at an optimum flow rate of 0.18 ml/min, a sample volume of 50 μl, and the column was flushed with 70 ml of PBS buffer (pH 7.2). The aptamer/microcystin mixture was prepared, the aptamer was incubated with MC-LR for 30 min (1:1 molar ratio). To prepare the aptamer/microcystin/ antibody mixture, the antibody was incubated with microcystin for 30 minutes and re-incubated for another 30 minutes with the aptamer (1:2:43 molar ratio).

### **3. Results and discussion**

### **3.1 Aptasensor design**

In the MC-LR aptasensor, a sandwich system consisting of an antibody, MC-LR, and an aptamer was used. MC-LR molecule is relatively small compared to the antibody and aptamer molecules (molecular weights 0.995, 150, and 18.17 kDa). To assure effective binding, the binding sites of the antibody and the aptamer to the MC-LR molecule should be different. According to the manufacturer, the MC-LR monoclonal antibody binds to the MC-LR molecule in position two [23]. The AN6 aptamer is used to detect the bound MC-LR molecules and was selected to bind to another

*Biosensor for the Detection of Cyanobacterial Toxin Microcystin-LR DOI: http://dx.doi.org/10.5772/intechopen.107366*

**Figure 3.** *MC-LR aptasensor.*

characteristic amino acid residue in position four [41]. In addition to the amino acid residues in positions two and four in the MC-LR molecule, the ADDA residue in position five can be used for interactions. Still, its use would reduce the selectivity of the biosensor because ADDA is present in all microcystins and nodularin. The MC-LR determination scheme is shown in **Figure 3**.

The MC-LR Sephadex G-50 M granules were activated with MC10E7 monoclonal antibody for selective binding. The granules were chosen according to their size, to enable the collection of granules into a closed measuring channel, and the diameter of the granules must be >80 μm (Sephadex G-50 M is approximately 100–300 μm in a buffer solution) [45].

During immobilization, 44 ± 0.1% of the antibody in solution adhered to the surface of the microgranules. Visual inspection revealed that the granules turned light blue after mixing them with Coomassie brilliant blue, indicating the presence of bound antibodies on the granules. Coomassie brilliant blue stain is a widely used method for routine visualization of proteins because it makes complexes with essential amino acids, such as lysine, histidine, tyrosine, and arginine [48]. The efficiency of the immobilization process did not depend on the concentration of antibodies in the immobilization solution.

### **3.2 The formation of a detectable antibody/MC-LR/aptamer complex**

The complex components have a significant molecular weight difference: MC-LR molecule 995 Da; the antibody and the aptamer of 150 kDa and 18.17 kDa, respectively. Considering these significant differences in molecular size, the potential formation of an antibody/MC-LR/aptamer triple complex was studied using SEC. The optimization was needed to achieve a sufficient resolution: flow rate, sample volume, and analyte concentration in a sample were modified. The best resolution over a significant range of molecular weights (100–200 kDa) was achieved at a flow rate of 0.18 ml/min, and a sample concentration of 0.5 mg/ml. Changing the sample volume did not significantly affect the resolution of the peaks, so 50 μl was chosen. These optimal conditions were used for all experiments. Dextran blue (M = 2000 kDa) was used to determine column void volume, and the total volume of the column was obtained with potassium dichromate. Individual compounds were analyzed and compared to investigate the formation of possible complexes. The chromatograms of

MC-LR monoclonal antibody, aptamer AN6, and microcystin alone were compared to chromatograms of component mixtures, which were incubated before analysis in different modes:


As SEC separates particles according to their size, several peaks were obtained from the various spatial structures of the aptamer AN6 [49], which moved through the column significantly faster than expected. The chromatogram of the aptamer showed two clear peaks at flow volumes of 8.10 ml and 11.50 ml (± 4%). For the antibody, it was also possible to identify two characteristic peaks at flow rates of 8.40 ml and 9.99 ml (± 4%).

Due to the aptamer AN6, it is impossible to characterize the chromatograms of mixtures by molecular weights; instead, the shape, intensity, and area of the peaks were compared. There were no differences in incubating the aptamer with MC-LR (mode 1) compared to the chromatogram of aptamer alone. The chromatogram of the mixture of the antibody, MC-LR, and the aptamer prepared according to mode 2 showed that there was no peak with an elution volume of 8.1 ml, and the intensity of the peak with an elution volume of 11.5 ml was increased (**Figure 4**), which may indicate interactions between different components. Comparing the areas under peaks for aptamer, antibody, and antibody/MC-LR/aptamer solutions, where the amount of material injected into the column was similar, the difference was less than

### **Figure 4.**

*Aptamer (red line), antibody (green line), and antibody, MC-LR and aptamer mixture (blue line) chromatograms (Sephacryl S-200 HR (1/29) column). Aptamer and antibody concentrations were 0.06 mg/ml and 0.24 mg/ml, respectively. In the mixture of antibody/MC-LR/aptamer the toxins concentration was 0.07 mg/ ml (aptamers and antibody concentrations 0.06 mg/ml and 0.24 mg/ml, respectively). The flow rate was 0.18 ml/ min, sample size of 50 μl.*

one unit (approximately 6%), indicating that all substances injected into the column had passed through the column, and nothing was stuck into the column.

### **3.3 Determination of MC-LR**

### *3.3.1 Optimization of the protocol*

Measurements were performed using a protocol for detecting pathogens with a BIA-based sensor with some modifications [45]. To achieve a low limit of quantification, both antibody/MC-LR (MC-LR binding to activated microgranules) and MC-LR/aptamer (MC-LR binding to aptamer) incubation times were 30 minutes as the incubation at 15 minutes was not sufficient to obtain a reliable signal below the established WHO limit of 1 μg/l [6, 16]. The minimum volume of PBS for the efficient removal of unbound aptamer was 350 μl, as with lower PBS amounts, some of the aptamer remained in the flow channel and caused unstable signals (signal increased by hundreds of units in 5 minutes). We also optimized the aptamer concentration from 0.5 μg/ml to 5.0 μg/ml. With higher aptamer concentration, no stable end signal was achieved within 5 minutes. These results show aptamer concentration of 0.5 μg/ ml was used in further experiments. The optimal protocol used for the determination of MC-LR was as follows:


### *3.3.2 The calibration of MC-LR biosensor*

A calibration graph was plotted to characterize the sensitivity and operating range of the aptasensor (**Figure 5**).

The results showed that the signal of the aptasensor was linearly dependent on the concentration of MC-LR over a relatively wide concentration range from 1.3·10<sup>−</sup><sup>7</sup> to 8.0·10<sup>−</sup><sup>4</sup> mg/ml, and the experimental errors in this range were relatively minor from 0.8 to 4.3 AU. The coefficient of determination (R2 ) of the graph was 0.97. The sensitivity of

**Figure 5.** *The dependence of aptasensors signal on MC-LR concentration.*

the aptasensor was characterized by the slope of the graph being 0.151 ± 0.006 logAU/ log(mg/ml). The background signal was measured using PBS without added MC-LR, and the background value was 4.6 ± 0.9 AU. The theoretical detection limit (LOD) of the MC-LR aptasensor was calculated as the background signal + three standard deviations of the background signal, and the limit of quantification (LOQ ) as the background signal +10 standard deviations of the background signal. The LOD and LOQ values for the aptasensor were 1.7·10<sup>−</sup><sup>8</sup> mg/ml and 3.4·10<sup>−</sup><sup>8</sup> mg/ml, respectively.

Comparing the LOD of the MC-LR aptasensor with the allowed limit of MC-LR in drinking water, established by the WHO (1 μg/l = 10<sup>−</sup><sup>6</sup> mg/ml) [50], the LOD value of the proposed aptasensor is significantly lower, serving as a good precondition for the application of this aptasensor for the determination of MC-LR content and monitoring quality of natural water bodies.

The analysis took approximately 75 minutes, of which 60 minutes were for the analyte binding and the formation of a detectable complex. Compared to laboratorybased methods for detecting MC-LR, typically taking 4–6 hours [18–20], this method allows the determination of cyanotoxins much faster. However, compared to other aptasensors, the results can be obtained within a longer time. The time of analysis can be reduced by reducing the incubation time. It is also interesting to mention that the average material cost for one measurement was estimated to be 4.4 €.

### *3.3.3 Testing of the aptasensor*

A cyanobacterial culture was used to test the performance of the designed aptasensor. The sample of the cultured cyanobacteria treated with ultrasound to break up the bacterial cells was diluted 50 times as it contained broken blue-green algae cells, and the solution had green color. The MC-LR concentration in the diluted culture sample was 3.0·10<sup>−</sup><sup>7</sup> mg/ml, indicating that the designed aptasensor was sensitive enough in the matrix, assumingly more complex than the one of natural water.

### **4. Conclusions**

An aptasensor was designed and constructed to detect the cyanobacterial toxin MC-LR. The aptasensor was integrated with a bead injection system, where bioactivated micro-granules formed a disposable microcolumn in a partially closed flow channel. It took about 75 minutes to determine MC-LR. The aptasensor's detection limit (LOD) was 1.7·10<sup>−</sup><sup>8</sup> mg/ml, and the limit of quantitation (LOQ ) was 3.4·10<sup>−</sup><sup>8</sup> mg/ml. The LOD and LOQ values of the aptasensor were below the allowed MC-LR limit of 1 μg/l in drinking water set by WHO. The MC-LR aptasensor was used for testing the MC-LR concentration in a cyanobacterial culture. The sensitivity of the aptasensor is sufficient to determine MC-LR in samples containing algae, which creates good conditions for using the constructed aptasensor in natural water bodies for water quality monitoring.

### **Conflict of interest**

The authors have no conflicts of interest to declare. We certify that the submission is original work and is not under review at any other publication.

### **Author details**

Rasmus Rohtla1 , Kairi Kivirand1 , Eerik Jõgi1,2 and Toonika Rinken1 \*

1 Faculty of Science and Technology, Institute of Chemistry, University of Tartu, Estonia

2 Tartu Health Care College, Estonia

\*Address all correspondence to: toonika.rinken@ut.ee

© 2022 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.

### **References**

[1] U.S. Environmental Protection Agency. Health Effects from Cyanotoxins: Human Health Effects Caused by the Most Common Toxinproducing Cyanobacteria. https://www. epa.gov/cyanohabs/health-effectscyanotoxins. [Accessed: May 27, 2022]

[2] Savadova K, Mazur-Marzec H, Karosienė J, et al. Effect of increased temperature on native and alien nuisance cyanobacteria from temperate lakes: An experimental approach. Toxins (Basel). 2018;**10**:445. DOI: 10.3390/toxins10110445

[3] Paerl HW, Huisman J. Climate change: A catalyst for global expansion of harmful cyanobacterial blooms. Environmental Microbiology Reports. 2019;**1**:27. DOI: 10.1111/j.1758-2229. 2008.00004

[4] Wu X, Hou L, Lin X, et al. Application of novel nanomaterials for chemo- and biosensing of algal toxins in shellfish and water. Novel Nanomaterials for Biomedical, Environmental and Energy Applications. 2019. DOI: 10.1016/ B978-0-12-814497-8.00012-6

[5] Campos A, Vasconcelos V. Molecular mechanisms of microcystin toxicity in animal cells. International Journal of Molecular Sciences. 2010;**11**:268. DOI: 10.3390/ijms11010268

[6] World Health Organization. Cyanobacterial toxins: microcystins. Background document for development of WHO Guidelines for drinkingwater quality and Guidelines for safe recreational water environments. WHO/HEP/ECH/WSH/20206. https://apps.who.int/iris/bitstream/ handle/10665/338066/WHO-HEP-ECH-WSH-2020.6-eng.pdf. [Accessed: May 27, 2022]

[7] Bouaïcha N, Miles CO, Beach DG, et al. Structural diversity, characterization and toxicology of microcystins. Toxins. 2019;**11**:714. DOI: 10.3390/toxins11120714

[8] Vesterkvist PSM, Misiorek JO, Spoof LEM, et al. Comparative cellular toxicity of hydrophilic and hydrophobic microcystins on Caco-2 cells. Toxins (Basel). 2012;**25**:1008. DOI: 10.3390/ toxins4111008

[9] Rudolph-Böhner S, Mierke DF, Moroder L. Molecular structure of the cyanobacterial tumor-promoting microcystins. FEBS Letters. 1994;**349**:319. DOI: 10.1016/0014- 5793(94)00680-6

[10] Toivola DM, Eriksson JE, Brautigan DL. Identification of protein phosphatase 2A as the primary target for microcystin-LR in rat liver homogenates. FEBS Letters. 1994;**344**:175. DOI: 10.1016/0014-5793(94)00382-3

[11] Sun Y, Zheng Q, Sun YT, et al. Microcystin-LR induces protein phosphatase 2A alteration in a human liver cell line. Environmental Toxicology. 2014;**29**:1236. DOI: 10.1002/tox.21854

[12] Pereira SR, Vasconcelos VM, Antunes A. Computational study of the covalent bonding of microcystins to cysteine residues - a reaction involved in the inhibition of the PPP family of protein phosphatases. The FEBS Journal. 2013;**280**:674. DOI: 10.1111/j.1742-4658.2011.08454.x

[13] Gagala I, Mankiewicz-Boczek J. The natural degradation of microcystins (cyanobacterial Hepatotoxins) in fresh water - the future of modern treatment systems and water quality improvement. *Biosensor for the Detection of Cyanobacterial Toxin Microcystin-LR DOI: http://dx.doi.org/10.5772/intechopen.107366*

Polish Journal of Environment and Studies. 2012;**21**:1125

[14] Kabak B. The fate of mycotoxins during thermal food processing. Journal of the Science of Food and Agriculture. 2009;**89**:549. DOI: 10.1002/jsfa.3491

[15] National Center for Biotechnology Information. PubChem Compound Summary for CID 445434, Microcystin-LR. https://pubchem. ncbi.nlm.nih.gov/compound/445434. [Accessed: May 27, 2022]

[16] EPA (822-R-19-001): United States Environmental Protection Agency, Ross DP. Recommended Human Health Recreational Ambient Water Quality Criteria or Swimming Advisories for Microcystins and Cylindrospermopsin. Federal Register; 84. Available from: https://www.epa.gov/sites/default/ files/2019-05/documents/hh-rec-criteriahabs-document-2019.pdf [Accessed: May 27, 2022]

[17] World Health Organization. Cyanobacterial toxins: Microcystin-LR in Drinking-water. WHO/SDE/ WSH/0304/57. 1998 https://www. who.int/water\_sanitation\_health/ dwq/chemicals/cyanobactoxins.pdf. [Accessed: May 27, 2022]

[18] Kaushik R, Balasubramanian R. Methods and approaches used for detection of cyanotoxins in environmental samples: A review. Critical Reviews in Environmental Science and Technology. 2013;**43**:1349. DOI: 10.1080/10643389.2011.644224

[19] Massey IY, Wu P, Wei J, et al. A mini-review on detection methods of microcystins. Toxins. 2020;**12**:641. DOI: 10.3390/toxins12100641

[20] Kumar P, Rautela A, Kesari V, et al. Recent developments in the methods of quantitative analysis of microcystins. Journal of Biochemical and Molecular Toxicology. 2020;**34**:e22582. DOI: 10.1002/jbt.22582

[21] Novus Biologicals. Microcystin-LR ELISA Kit (Colorimetric). https://www. novusbio.com/products/microcystinlr-elisa-kit\_ka1496. [Accessed: May 27, 2022]

[22] U.S. EPA. Method 546: Determination of Total Microcystins and Nodularins in Drinking Water and Ambient Water by Adda Enzyme-Linked Immunosorbent Assay. https://www. epa.gov/sites/default/files/2016-09/ documents/, https://www.epa.gov/ esam/method-546-determination-totalmicrocystins-and-nodularins-drinkingwater-and-ambient-water. [Accessed: May 27, 2022]

[23] Enzo Life Sciences. Microcystin-LR monoclonal antibody (MC10E7). https:// www.enzolifesciences.com/ALX-804-320/microcystin-lr-monoclonalantibody-mc10e7/. [Accessed: May 27, 2022]

[24] Ward CJ, Beattie KA, Lee EYC, et al. Colorimetric protein phosphatase inhibition assay of laboratory strains and natural blooms of cyanobacteria: Comparisons with high-performance liquid chromatographic analysis for microcystins. FEMS Microbiology Letters. 1997;**153**:465. DOI: 10.1016/ S0378-1097(97)00290-5

[25] Bouaı̈cha N, Maatouk I, Vincent G, et al. A colorimetric and fluorometric microplate assay for the detection of microcystin-LR in drinking water without pre-concentration. Food and Chemical Toxicology. 2002;**40**:1677. DOI: 10.1016/S0278-6915(02)00103-5

[26] Rapala J, Erkomaa K, Kukkonen J, et al. Detection of microcystins with

protein phosphatase inhibition assay, high-performance liquid chromatography-UV detection and enzyme-linked immunosorbent assay: Comparison of methods. Analytica Chimica Acta. 2002;**466**:213. DOI: 10.1016/S0003-2670(02)00588-3

[27] Ren L, Hu Z, Wang Q, et al. Regulation efficacy and mechanism of the toxicity of microcystin-LR targeting protein phosphatase 1 via the biodegradation pathway. Toxins (Basel). 2020;**12**:790. DOI: 10.3390/ toxins12120790

[28] Dillon M, Zaczek-Moczydlowska MA, Edwards C, et al. Current trends and challenges for rapid smart diagnostics at point-of-site testing for marine toxins. Sensors. 2021;**21**:2499. DOI: 10.3390/ s21072499

[29] Li X, Cheng R, Shi H, et al. A simple highly sensitive and selective aptamer-based colorimetric sensor for environmental toxins microcystin-LR in water samples. Journal of Hazardous Materials. 2016;**304**:474. DOI: 10.1016/j. jhazmat.2015.11.016

[30] Lv J, Zhao S, Wu S, et al. Upconversion nanoparticles grafted molybdenum disulfide nanosheets platform for microcystin-LR sensing. Biosensors & Bioelectronics. 2017;**90**:203. DOI: 10.1016/j. bios.2016.09.110

[31] He D, Wu Z, Cui B, et al. A novel SERS-based aptasensor for ultrasensitive sensing of microcystin-LR. Food Chemistry. 2019;**278**:197. DOI: 10.1016/j. foodchem.2018.11.071

[32] Eissa S, Ng A, Siaj M, et al. Labelfree voltammetric aptasensor for the sensitive detection of microcystin-LR using graphene-modified electrodes.

Analytical Chemistry. 2017;**86**:7551. DOI: 10.1021/ac501335k

[33] Tang L, Ouyang X, Peng B, et al. Highly sensitive detection of microcystin-LR under visible light using a self-powered photoelectrochemical aptasensor based on a CoO/Au/g-C3N4 Z-scheme heterojunction. Nanoscale. 2019;**11**:12198. DOI: 10.1039/c9nr03004b

[34] Pang P, Teng X, Chen M, et al. Ultrasensitive enzyme-free electrochemical immunosensor for microcystin-LR using molybdenum disulfide/gold nanoclusters nanocomposites as platform and Au@Pt core-shell nanoparticles as signal enhancer. Sensors Actuators, B Chemistry. 2018;**266**:400. DOI: 10.1016/j. snb.2018.03.154

[35] Nelson DL, Cox MM. Lehninger principles of biochemistry 7th edition. W.H. Freeman; 2017. IBAN-13: 978-1464126116

[36] Zeck A, Eikenberg A, Weller MG, et al. Highly sensitive immunoassay based on a monoclonal antibody specific for [4-arginine]microcystins. Analytica Chimica Acta. 2001;**441**:1. DOI: 10.1016/ S0003-2670(01)01092-3

[37] Thiviyanathan V, Gorenstein DG. Aptamers and the next generation of diagnostic reagents. Proteomics - Clinical Applications. 2012;**6**:563. DOI: 10.1002/ prca.201200042

[38] Sola M, Menon AP, Moreno B, et al. Aptamers against live targets: Is In vivo SELEX finally coming to the edge? Molecular Therapy - Nucleic Acids. 2020;**21**:192. DOI: 10.1016/j. omtn.2020.05.025

[39] Ye W, Liu T, Zhang W, et al. Marine toxins detection by biosensors *Biosensor for the Detection of Cyanobacterial Toxin Microcystin-LR DOI: http://dx.doi.org/10.5772/intechopen.107366*

based on aptamers. Toxins. 2020;**12**:1. DOI: 10.3390/toxins12010001

[40] Cunha I, Biltes R, Sales MGF, et al. Aptamer-based biosensors to detect aquatic phycotoxins and cyanotoxins. Sensors (Switzerland). 2018;**18**:2367. DOI: 10.3390/s18072367

[41] Ng A, Chinnappan R, Eissa S, et al. Selection, characterization, and biosensing application of high affinity congener-specific microcystintargeting aptamers. Environmental Science & Technology. 2012;**46**:10697. DOI: 10.1021/es301686k

[42] Ruzicka J, Scampavia L. From flow injection to bead injection. Analytical Chemistry. 1999;**71**:257A. DOI: 10.1021/ ac990293i

[43] Idris AM. An overview of the generations and recent versions of flow injection techniques. Critical Reviews in Analytical Chemistry. 2010;**40**:150. DOI: 10.1080/10408340903103437

[44] Viirlaid E, Ilisson M, Kopanchuk S, et al. Immunoassay for rapid on-site detection of glyphosate herbicide. Environmental Monitoring and Assessment. 2019;**191**:507. DOI: 10.1007/ s10661-019-7657-z

[45] Peedel D, Rinken T. Rapid biosensing of Staphylococcus aureus bacteria in milk. Anal. Methods. 2014;**6**:2642. DOI: 10.1039/c3ay42036a

[46] Juronen D, Kuusk A, Kivirand K, et al. Immunosensing system for rapid multiplex detection of mastitis-causing pathogens in milk. Talanta. 2018;**178**:949. DOI: 10.1016/j.talanta.2017.10.043

[47] www.dsmz.de. Cyanobacteria Medium BG11+. https://www.dsmz. de/microorganisms/medium/pdf/

DSMZ\_Medium1593.pdf. [Accessed: May 27, 2022]

[48] Coomassie Brilliant Blue Stain Protocol. https://conductscience. com/coomassie-brilliant-blue-stain/ [Accessed: May 27, 2022]

[49] Zhao L, Huang Y, Dong Y, et al. Aptamers and aptasensors for highly specific recognition and sensitive detection of marine biotoxins: Recent advances and perspectives. Toxins. 2018;**10**:427. DOI: 10.3390/ toxins10110427

[50] Welker M, Steinberg C. Rates of humic substance photosensitized degradation of microcystin-LR in natural waters. Environmental Science & Technology. 2000;**34**:3415. DOI: 10.1021/ es991274t

### *Edited by Luis Jesús Villarreal-Gómez*

Biomedical technology is continually changing, and new approaches are being developed daily. Although widely used, conventional solutions are losing efficacy due to the evolution of microorganisms and the environment. Pathologies and diseases negatively affect humans and animals, but nanotechnology appears promising in the diagnosis and treatment of a variety of health conditions. This book examines some of these nanotechnologies, discussing their advantages and limitations. It is organized into four sections and includes ten chapters that address such topics as drug delivery systems for cancer treatment, photodynamic and photothermal treatments for bacterial infections, electrospun fibers for nanomedical applications, monoclonal antibodies, nanotheranostics, and much more.

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Biotechnology - Biosensors, Biomaterials and Tissue Engineering Annual Volume 2023

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*Edited by Luis Jesús Villarreal-Gómez*