**1.2.3 The 3rd generation of serum peptidomics research platform: ClinTOF**

Considering features of the serum polypeptide profiling and defects of the ClinProt system, it is fair to say that ClinTOF is the representative of the latest platform up to now.

On one hand, ClinTOF is capable of detecting the biomarker pattern or biomarker profiling indicating specific diseases in the biological liquid; on the other hand, this technology can identify the candidate for a single biomarker. ClinTOF composes of three parts, including magnetic beads, time-of-flight mass spectrometer (TOF MS) and analysis software BioExploer ™.

1. Magnetic Beads

The magnetic beads includes hydrophobic magnetic beads, metal affinity magnetic beads, ion exchange magnetic beads, glycoprotein magnetic beads and immunoaffinity magnetic beads. Further, SPE-C magnetic beads, the reagent dedicated for the serum polypeptide fingerprint diagnosis is available. Presently, magnetic beads have been found in biomedicine fields like immuno-magnetic separation (IMS), cell and cell organelle separation, microorganism detection and nucleic acid hybridization. The whole system is used in the clinical research of serum peptidomics.

2. TOF MS

Time-of-flight mass spectrometer (TOF MS) is used to obtain mass ratio and content of proteins captured by magnetic beads. ClinTOF, the clinical mass spectrometer, has adopted the cutting-edge 60Hz pulsed nitrogen laser which allows the data generated at the fastest speed compared with its counterparts. The zoom optics technology is employed with the laser speckle ranging from 50µm to 200 µm (adjustable), also the greatest adjustable range among like products, so that the size of laser speckles can meet the demands of different samples. The unique gap design in ion source has been utilized, keeping ion sources from contaminations and greatly reducing maintenance frequency. The laser system has been added with the laser energy leveling function, presenting more stable light intensity of the laser and more accurate data. The unique touch screen design has integrated MALDI-TOF control system and the PC system, making operations more simple and handy.

3. Analysis Software BioExploer™

BioExploer™ software is used both in processing genetic data and also protein data. BioExploer™ has combined visualized analysis and multiple mathematical algorithms to build pattern recognition models for MS data classification and forecast, and hunt the disease markers from data. It can perform data visualization, data reduction and data

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Group

Peak Intensity of Site 32

Fig. 3. ClinTOF System 3D Sample Distribution Diagram

Fig. 4. ClinTOF System Typical Value Variogram

Average Variance of Site 32

Peak Intensity of Site 37

Fig. 5. ClinTOF System 3D Stack Diagram

mining over various types of MS data and build category prediction models. This software features: data of multiple forms can be analyzed with this software even if they have converted their formats; signal spectrogram can be visualized through the virtual gel graph and stack diagram; wavelet transform is used to deal with the mass spectrogram, including baseline elimination, spectrogram smoothing, peak selection and normalization; random statistical analysis can be made on one and more groups of spectrogram protein peaks; compatibility analysis is designed for the pairing data; the building and verification of the pattern recognition models involve in optimistic algorithms including genetic algorithm, radial basis neural network and the support vector machine and allow users to select the modeling space; output of data analysis reports and backup and storage at any moment.

The BioExploer™ control and analysis system adopts the display forms of scanning profiling (Fig.1) and electrophoresis patterns (simulation gel graph) (Fig.2). Statistical analysis graphs include the 3D sample distribution diagram (Fig.3), typical value-variogram (Fig.4) and 3D stack diagram (Fig.5). The user may switch the three graphs by clicking the three buttons at the lower left corner.

Fig. 1. ClinTOF System Scanning Profiling

Fig. 2. Electrophoresis Graph of the ClinTOF System

mining over various types of MS data and build category prediction models. This software features: data of multiple forms can be analyzed with this software even if they have converted their formats; signal spectrogram can be visualized through the virtual gel graph and stack diagram; wavelet transform is used to deal with the mass spectrogram, including baseline elimination, spectrogram smoothing, peak selection and normalization; random statistical analysis can be made on one and more groups of spectrogram protein peaks; compatibility analysis is designed for the pairing data; the building and verification of the pattern recognition models involve in optimistic algorithms including genetic algorithm, radial basis neural network and the support vector machine and allow users to select the modeling space; output of data analysis reports and backup and storage at any moment.

The BioExploer™ control and analysis system adopts the display forms of scanning profiling (Fig.1) and electrophoresis patterns (simulation gel graph) (Fig.2). Statistical analysis graphs include the 3D sample distribution diagram (Fig.3), typical value-variogram (Fig.4) and 3D stack diagram (Fig.5). The user may switch the three graphs by clicking the

three buttons at the lower left corner.

Fig. 1. ClinTOF System Scanning Profiling

Fig. 2. Electrophoresis Graph of the ClinTOF System

Fig. 3. ClinTOF System 3D Sample Distribution Diagram

Fig. 4. ClinTOF System Typical Value Variogram

Fig. 5. ClinTOF System 3D Stack Diagram

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procedure (SOP), BIOYONG has studied the polypeptide profiling of the 200 hepatic carcinoma cases and 200 normal serum cases. 28 differential polypeptides (P<0.0001) were obtained, with the molecular weight of 900 ~5000Da (Fig.6). Among them, 9 were down regulated (2.5~8 times) and 19 up-regulated (2.5~20 times). For the model built with SNN, the recognition rate is 100% and predictive ability, 98.39%. 100 samples were used for double-

> Training Set Testing Set Sensitivity 84.17% 77.4%(24/31) Specificity 95.95% 91.4%(32/35)

> Accuracy --- 84.85(56/66)

nitrogen 337nm 10Hz

Coaxial laser technology

Unique remote ion source design of big gap, keeping ion source from contamination

Proteomics, SNP, biomarker analysis, tissue imaging, microorganism, organ-small molecules,

clinical examination in hospitals

Positive Predictive Value (PPV) --- 88.89%(24/27) Negative Predictive Value (NPV) --- 82.1%(32/39)

microflex ClinTOF PBSII/C PCS4000

nitrogen 337nm 1-60Hz adjustable

10-6pa 10-7pa 10-4pa

≤150ppm ≤100ppm ≤2500ppm ≤250ppm

Micro-channel plate detector Electron multiplier

blind determination, with the correctness rate exceeding 90%.

nitrogen 337nm 1- 20Hz adjustable

Laser light source

Ion source technology

Ion source pattern

capacity

Detection system

Vacuum system

Accuracy (inner calibration)

Accuracy (outer calibration)

Other features Patented

AnchorChip MALDI sample

WishperMode technology reduces lab sound pollution

biomarker analysis

Table 2. Serum Peptidomics Research Technical Systems

target

Applications Proteomics, SNP,

Table 1. Colon and Rectal Cancer Diagnosis Model of the ClinTOF System

Delayed extraction technology

Positive and negative ion sources

Sensitivity <1fmol <10fmol

Shielding the "gate" function of noise peaks Mass range >600KDa >500KDa >500KDa >380KDa

Resolution >3500FWHM >2500FWHM >700FWHM >1000FWHM

Zoom optics technology, with the laser speckle ranging 50um to 200um adjustable

≤50ppm ≤50ppm ≤100ppm

Performance Bruker Bioyong CipherGen CipherGen

#### 4. Applications of ClinTOF Platform

ClinTOF can be used in disease peptidomics, early tumor diagnosis and curative effect evaluation, mental disease diagnosis, biomarker discovery, microorganism identification, single nucleotide polymorphism (SNP) detection and medicine quality control. This system as a breakthrough can detect more than 200 polypeptides at the same time by utilizing magnetic bead reagent, mass spectrometry and pattern analysis. BIOYONG is the only manufacturer in China for ClinTOF system development and certification and has obtained many patents. For the moment, this technology has been widely used in the clinical based researches, granted a solid scientific foundation for future promotion.

Besides the intrinsically strength of MALDI-TOF, the ClinTOF system has improved its stability and repeatability for clinical analysis. So far, it has detected more than 10,000 clinical samples and established detection models for colon and rectal cancers, lung cancer, hepatic carcinoma and brain glioma. Its accuracy for the early detection of cancers is above 85% and its specificity and sensitivity exceed 80%. MS models for some tumors based on the Clin TOF system have been built and many patents have gained authorization.

The ClinTOF system has been widely applied in studies on the early diagnosis of ovarian cancer, prostatic cancer, breast cancer, brain glioma, head and neck squamous cell carcinomas (HNSCC) and carcinoma of urinary bladder and disease diagnosis models have been built. For the colon and rectal cancers, the model is shown in Table 1. In the model built in the experiment, 70 of the normal cases and 60 of colon and rectal cancer cases are used; 31 of the normal cases and 35 of colon and rectal cancer cases are used; the sensitivity of the model is 84.17% and the specificity, 95.95%. For the model verified by blind samples, the normal/colon and rectal cancer cases is (31/35) and the sensitivity and specificity of the model both exceed 80%, with the accuracy reaching 84.85%. For the hepatic carcinoma, the diagnosis model is shown in Table 2. According to the established standard operating

Fig. 6. Hepato Carcinoma Diagnosis Model of the ClinTOF System

ClinTOF can be used in disease peptidomics, early tumor diagnosis and curative effect evaluation, mental disease diagnosis, biomarker discovery, microorganism identification, single nucleotide polymorphism (SNP) detection and medicine quality control. This system as a breakthrough can detect more than 200 polypeptides at the same time by utilizing magnetic bead reagent, mass spectrometry and pattern analysis. BIOYONG is the only manufacturer in China for ClinTOF system development and certification and has obtained many patents. For the moment, this technology has been widely used in the clinical based

Besides the intrinsically strength of MALDI-TOF, the ClinTOF system has improved its stability and repeatability for clinical analysis. So far, it has detected more than 10,000 clinical samples and established detection models for colon and rectal cancers, lung cancer, hepatic carcinoma and brain glioma. Its accuracy for the early detection of cancers is above 85% and its specificity and sensitivity exceed 80%. MS models for some tumors based on the

The ClinTOF system has been widely applied in studies on the early diagnosis of ovarian cancer, prostatic cancer, breast cancer, brain glioma, head and neck squamous cell carcinomas (HNSCC) and carcinoma of urinary bladder and disease diagnosis models have been built. For the colon and rectal cancers, the model is shown in Table 1. In the model built in the experiment, 70 of the normal cases and 60 of colon and rectal cancer cases are used; 31 of the normal cases and 35 of colon and rectal cancer cases are used; the sensitivity of the model is 84.17% and the specificity, 95.95%. For the model verified by blind samples, the normal/colon and rectal cancer cases is (31/35) and the sensitivity and specificity of the model both exceed 80%, with the accuracy reaching 84.85%. For the hepatic carcinoma, the diagnosis model is shown in Table 2. According to the established standard operating

researches, granted a solid scientific foundation for future promotion.

Fig. 6. Hepato Carcinoma Diagnosis Model of the ClinTOF System

Clin TOF system have been built and many patents have gained authorization.

4. Applications of ClinTOF Platform

procedure (SOP), BIOYONG has studied the polypeptide profiling of the 200 hepatic carcinoma cases and 200 normal serum cases. 28 differential polypeptides (P<0.0001) were obtained, with the molecular weight of 900 ~5000Da (Fig.6). Among them, 9 were down regulated (2.5~8 times) and 19 up-regulated (2.5~20 times). For the model built with SNN, the recognition rate is 100% and predictive ability, 98.39%. 100 samples were used for doubleblind determination, with the correctness rate exceeding 90%.



Table 1. Colon and Rectal Cancer Diagnosis Model of the ClinTOF System

Table 2. Serum Peptidomics Research Technical Systems

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pathological group and the healthy control group are collected and then the serum is separated from the blood. The serum is mixed with magnetic beads to extract serum polypeptides for detection with the mass spectrometry. The spectra obtained can produce characteristic spectrum peaks. The meaningful characteristic spectrum peaks are screened out with the statistical method. A prediction model is built with the pattern recognition method and validated with test data. After continuous optimization, a disease diagnosis

Briefly, the research includes magnetic beads, detection instrument, analysis software,

The separation and purification methods adopted in the serum peptidomics research depend on the nature of the extracted substance. The commonly used methods for polypeptide extraction and separation include: salting removal method, ultra-filtration process, gel filtration, isoelectric point precipitation method, ion-exchange chromatography, affinity chromatography, adsorption chromatography, countercurrent distribution and enzymolysis

HPLC is a favorable method for peptides separation, because the HPLC can complete the separation in a short time under suitable chromatographic conditions, and more importantly, HPLC is capable of producing polypeptide of bioactivity at the preparative scale. Many scholars therefore have done substantive work in looking for the best conditions for separating and preparing polypeptide substances. How to maintain the activity of polypeptide, how to select stationary phase material and eluent type, how to make analytic determination are all contents of the present study. Common methods include: reversed phase high pressure liquid chromatography (RP-HPLC), hydrophobic interaction chromatography (HIC), Size-Exclusion chromatography (SEC), Ion-Exchange chromatography (IEC), Chromatography of Membrane Protein (CMP), High-Performance

Affinity Chromatography (AC) is the method of separating substances based on the specific affinity between ligand connecting to the stationary phase matrix and the ligand having interaction with the specificity. Since 1968 when Cuatrecasas put forward the concept of affinity chromatography, in searching for the specific affinity interaction substances many combinations have been found, like antigen-antibody, enzyme-substrate, agglutinin-polyose, oligonucleotides and their complementary strands. For the separation of polypeptide substances, currently the monoclonal antibody or biological simulation ligand can be used for affinity to such substances. These ligands can be natural or artificially synthesized according to their structure. Immobilized Metal Affinity Chromatography (IMAC) is an affinity method developed in recent years. Some metal ions are chelated on the stationary phase substrate, like Cu2+, Ni2+ and Fe3+. The magnetic beads can be chelated through the coordination bond to connect polypeptides that contain Lys, Met, Asp, Arg, Tyr, Glu and His on the side chain. In

method. These methods often work together to separate and purify specific substances.

Displacement Chromatography (HPDC) and Perfusion Chromatography (PC).

model and a group of characteristic spectrum peaks can be obtained.

polypeptide identification and clinical model.

**2.1.1 High Pressure Liquid Chromatography (HPLC)** 

**2.1 Polypeptide extraction** 

**2.1.2 Affinity Chromatography** 
