Polypeptide autoantibody marker for early diagnosis of esophageal squamous carcinoma and detection kit

Abstract

The invention belongs to the technical field of biomedicine, and particularly relates to a polypeptide autoantibody marker for early diagnosis of esophageal squamous carcinoma and a detection kit. The biomarker for early diagnosis of esophageal squamous carcinoma provided by the invention is at least one of an autoantibody of an MSTO1 antigen polypeptide, an autoantibody of an SNRPB antigen polypeptide, an autoantibody of a CASR antigen polypeptide, an autoantibody of a DAB2IP antigen polypeptide, an autoantibody of an RBPJ antigen polypeptide, an autoantibody of a TTN antigen polypeptide and an autoantibody of an RIMS2 antigen polypeptide. The expression level of the marker in serum of esophageal squamous carcinoma patients is obviously higher than that of normal people, and the difference has statistical significance. The invention also provides a kit for diagnosing esophageal squamous carcinoma. The kit contains the antigen polypeptide for detecting the biomarker. By detecting the expression level of the biomarker in human serum, the marker can be used for auxiliary diagnosis of esophageal squamous carcinoma.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to a polypeptide autoantibody biomarker and detection kit for the early diagnosis of esophageal squamous cell carcinoma. Background Technology

[0002] Esophageal cancer is one of the most common malignant tumors of the digestive tract, seriously threatening human life and health. According to the latest global cancer statistics, there are approximately 510,716 new cases of esophageal cancer and about 445,129 deaths. Based on histopathological type, esophageal cancer is mainly divided into esophageal adenocarcinoma and esophageal squamous cell carcinoma (ESCC). Because ESCC has an insidious onset and no obvious symptoms in the early stages, most patients are already in a locally advanced or advanced stage at the time of diagnosis; and for patients in the middle and late stages, the five-year survival rate after surgery, radiotherapy, and chemotherapy is less than 30%. Therefore, improving the early diagnosis rate of ESCC is key to reducing its mortality rate and is also one of the important directions for improving patient prognosis.

[0003] Upper gastrointestinal endoscopy combined with tissue biopsy is the gold standard for diagnosing esophageal squamous cell carcinoma (ESCC) and its precancerous lesions, but there is currently no universally accepted serological biomarker. While endoscopy can reduce the mortality rate of esophageal squamous cell carcinoma, it is highly dependent on advanced equipment and experienced physicians, and also has limitations such as high cost, poor patient compliance, low examination efficiency, and difficulty in detecting internal cancer cells. Studies have shown that the detection rate of early esophageal cancer using endoscopy in high-incidence areas is only about 2%, and 90% of asymptomatic "high-risk individuals" undergoing endoscopy are "accompanying patients," resulting in unnecessary waste of medical resources. These problems limit the application of endoscopy in the early detection of esophageal cancer, especially in areas without high esophageal cancer incidence or in areas with inadequate healthcare infrastructure.

[0004] The development of tumors is often accompanied by abnormal expression or structural changes of tumor-associated antigens (TAAs). These abnormal changes can induce an immune response, resulting in the production of autoantibodies against TAAs, namely tumor-associated autoantibodies (TAAbs). TAAbs have the advantages of high specificity, high stability, and ease of detection, showing great potential for application in the early diagnosis of tumors. It has been reported that TAAbs can be generated months or even years before the clinical diagnosis of a tumor, making it possible to use TAAbs for the detection of early-stage tumors. For example, in tumors such as liver cancer, colorectal cancer, and lung cancer, serum TAAbs have been found to be significantly elevated before clinical diagnosis. Furthermore, the clinical application of TAAbs has shown initial success, for example, based on seven TAAbs (anti-p53, anti-GAGE7, anti-PGP9.5, anti-CAGE, anti-MAGEA1, anti-SOX2, and anti-GBU4-5). These test kits have been widely adopted in several European and American countries. In 2015, my country's State Food and Drug Administration also approved the aforementioned seven TAAb detection kits. In summary, TAAb detection is expected to become an important supplement to early cancer diagnosis, providing more options for early cancer detection.

[0005] In esophageal squamous cell carcinoma (ESCC) research, serum TAAbs for over 40 ESCC types have been reported, and these TAAbs hold promise as biomarkers for early detection of ESCC. Although various ESCC-related autoantibodies or combinations have been identified, detection primarily relies on recombinant proteins as target antigens, a strategy with certain limitations. First, the preparation of recombinant proteins is complex, involving experimental steps such as vector construction, transfection, expression, screening, and purification. Second, the complex spatial structure of proteins makes it difficult to expose linear antigenic epitopes in recombinant proteins, and the purity of purified proteins is difficult to guarantee, leading to varying degrees of non-specific binding, thus affecting the specificity and sensitivity of detection. Overcoming these limitations and improving the accuracy of TAAbs in esophageal squamous cell carcinoma detection has become an urgent challenge. Antigenic epitopes (also known as antigenic determinants) are specific regions of 5-8 amino acids on the surface of antigen molecules, serving as the smallest structural and functional units that induce antibody production. As short amino acid sequences of proteins, antigenic epitopes theoretically induce immune responses more directly than complete proteins.

[0006] Compared to full-length proteins, antigenic epitope peptides possess numerous significant advantages, including small molecular weight, high stability, ease of chemical synthesis and modification, and low cost. Theoretically, in the detection of autoantibodies, antigenic peptides exhibit less non-specific binding, and their specific antigen recognition regions and low cross-reactivity make them ideal target antigens. Compared to full-length or recombinant proteins, antigenic peptides avoid non-specific binding interference caused by complex structures, allowing for more precise and efficient capture of disease-related autoantibody signals. Currently, the use of antigenic epitopes as target antigens to detect serum TAAbs levels and their application in ESCC detection is still in its infancy. Systematic research on "antigenic peptide-autoantibody" biomarkers could significantly improve the specificity and sensitivity of detection, providing new insights for improving the early diagnosis rate of esophageal squamous cell carcinoma, while also expanding the application potential of antigenic peptides in precision oncology. Summary of the Invention

[0007] In view of the problems and deficiencies in the existing technology, the present invention provides a biomarker and detection kit for the early detection and diagnosis of esophageal squamous cell carcinoma.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] The first aspect of this invention provides a biomarker for the early detection and diagnosis of esophageal cancer. The biomarker is at least one of the following: autoantibodies against MSTO1 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide, and RIMS2 antigen peptide. The expression levels of these autoantibodies in the serum of patients with esophageal squamous cell carcinoma are all higher than those in normal individuals, and the differences are statistically significant.

[0010] According to the above-mentioned biomarkers, preferably, the autoantibodies of MSTO1 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide and RIMS2 antigen peptide are the corresponding antitumor-related antigen peptide autoantibodies in the subject's serum, plasma, interstitial fluid or urine.

[0011] A second aspect of the present invention provides the use of reagents for detecting the biomarkers described in the first aspect in the preparation of products for the early diagnosis of esophageal cancer.

[0012] According to the above application, preferably, the reagent is a reagent for detecting the biomarker in the sample by enzyme-linked immunosorbent assay (ELISA), protein chip, immunoblotting, or microfluidic immunoassay.

[0013] According to the above application, preferably, the sample is serum, plasma, interstitial fluid or urine.

[0014] According to the above applications, preferably, the sequence of the MSTO1 antigen peptide is APGQSLPDSLMQFGGA, the sequence of the SNRPB antigen peptide is GRGTPMGMPPPGMRPPPPGMR, the sequence of the CASR antigen peptide is CVECPDGEYSDETDASA, the sequence of the DAB2IP antigen peptide is RSHLMPRLKESRSHESLLSP, the sequence of the RBPJ antigen peptide is TFTYTPEPGPRPHCSAAGA, the sequence of the TTN antigen peptide is CDTVFKPGPPGNPRVLDTSRSSISI, and the sequence of the RIMS2 antigen peptide is PPPQSRNVEQGLRGTRTMTGHYN.

[0015] According to the above applications, preferably, the product is a protein chip, a reagent kit, or a formulation.

[0016] A third aspect of the present invention provides a kit for the early diagnosis of esophageal cancer, the kit comprising an antigenic polypeptide for detecting the biomarkers described in the first aspect.

[0017] According to the above-described kit, preferably, the kit detects the biomarkers in the sample by enzyme-linked immunosorbent assay (ELISA), protein chip, Western blotting, or microfluidic immunoassay. More preferably, the kit detects the biomarkers in the sample by antigen-antibody reaction.

[0018] According to the above-described kit, preferably, the kit is an ELISA detection kit. More preferably, the ELISA detection kit includes a solid-phase support and an antigenic peptide coated on the solid-phase support; the antigenic peptide is at least one selected from MSTO1 antigenic peptide, SNRPB antigenic peptide, CASR antigenic peptide, DAB2IP antigenic peptide, RBPJ antigenic peptide, TTN antigenic peptide, and RIMS2 antigenic peptide.

[0019] According to the above kit, preferably, the sequence of the MSTO1 antigen peptide is APGQSLPDSLMQFGGA, the sequence of the SNRPB antigen peptide is GRGTPMGMPPPGMRPPPPGMR, the sequence of the CASR antigen peptide is CVECPDGEYSDETDASA, the sequence of the DAB2IP antigen peptide is RSHLMPRLKESRSHESLLSP, the sequence of the RBPJ antigen peptide is TFTYTPEPGPRPHCSAAGA, the sequence of the TTN antigen peptide is CDTVFKPGPPGNPRVLDTSRSSISI, and the sequence of the RIMS2 antigen peptide is PPPQSRNVEQGLRGTRTMTGHYN.

[0020] More preferably, according to the above-mentioned kit, the solid-phase carrier is a microplate, and the material of the solid-phase carrier is any one of polyvinyl chloride, polystyrene, polyacrylamide, and cellulose.

[0021] According to the kit described above, preferably, the ELISA detection kit further includes a sample diluent, a second antibody, a second antibody diluent, a chromogenic solution, and a stop solution.

[0022] According to the kit described above, more preferably, the second antibody is a horseradish peroxidase-labeled mouse anti-human IgG monoclonal antibody.

[0023] More preferably, according to the above-described kit, the ELISA detection kit further includes any one or more of the following: coating solution, blocking solution, washing solution, positive control serum, and negative control serum.

[0024] According to the kit described above, preferably, the sample is serum, plasma, interstitial fluid, or urine.

[0025] According to the above-described kit, preferably, the method for preparing the solid-phase carrier coated with antigen peptides in the ELISA detection kit includes the following steps:

[0026] (1) Coating antigen peptides: MSTO1 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide and RIMS2 antigen peptide were diluted with coating buffer and added to the solid support at 50 μL / well and incubated at 4℃ for more than 16 h; the coating concentration of MSTO1 antigen peptide, SNRPB antigen peptide and DAB2IP antigen peptide was 4 μg / mL, the coating concentration of CASR antigen peptide and TTN antigen peptide was 2 μg / mL, and the coating concentration of RBPJ antigen peptide was 1 μg / mL.

[0027] (2) Blocking: After incubation, the solid support was warmed to room temperature and the coating solution was removed. Then, the blocking solution was added to the solid support at 100 μL / well and blocked at 37°C for 2 h.

[0028] (3) After sealing, remove the liquid in the solid carrier, wash with washing solution, and pat dry to obtain the solid carrier coated with antigen peptide.

[0029] Preferably, the washing conditions are 350 μL washing solution / well, 10 s / cycle, and repeated washing 3 times.

[0030] According to the above-described kit, preferably, the detection method of the ELISA detection kit is as follows:

[0031] (1) Primary antibody incubation: The primary antibody was mixed and diluted with the sample diluent at a ratio of 1:100, and 50 μL / well was added to the solid-phase carrier coated with the antigen peptide. A blank control well was also set up. The mixture was incubated at 37°C for 2 h. The primary antibody was the serum sample to be tested, and the blank control was the sample diluent.

[0032] (2) Secondary antibody incubation: After the primary antibody incubation is completed, remove the liquid in the solid-phase carrier, wash with washing solution, pat dry, dilute the secondary antibody with secondary antibody diluent, add 100 μL / well to the solid-phase carrier, and incubate at 37℃ for 1 h; the dilution ratio of the secondary antibody is 1:5000.

[0033] (3) Color development and termination: After the second antibody incubation is completed, remove the liquid in the solid support, wash with washing solution, pat dry, add 50 μL of color development solution to the solid support, react at room temperature in the dark for 5-15 min, and then add 25 μL of termination solution to the solid support.

[0034] (4) Scanning: Wipe the bottom of the solid-phase carrier to remove foreign matter, place the solid-phase carrier into the microplate reader, start the scanning program, and record the absorbance difference of the above 7 polypeptide autoantibodies. If the OD value of the blank control well is higher than 0.1, it needs to be detected again; the absorbance difference = OD 450nm -OD 620nm .

[0035] Preferably, the washing conditions are 350 μL washing solution / well, 10 s / cycle, and repeated washing 5 times.

[0036] Compared with the prior art, the positive and beneficial effects achieved by the present invention are as follows:

[0037] (1) This invention first screens out potential antigenic peptides that can be used to detect or otherwise characterize cancer based on PhIP-Seq technology. Then, it screens out serum biomarkers for early detection of esophageal squamous cell carcinoma through peptide microarray. After verification by ELISA experiment, a group of serum biomarkers for combined detection of esophageal squamous cell carcinoma that can be used for early screening and diagnosis of esophageal squamous cell carcinoma are finally screened out. These include autoantibodies against MST01 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide, and RIMS2 antigen peptide. These can be used to assist in the early detection of esophageal squamous cell carcinoma and have good reference value.

[0038] (2) This invention is the first to discover that the expression levels of autoantibodies against MSTO1 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide, and RIMS2 antigen peptide in the serum of patients with esophageal squamous cell carcinoma are significantly higher than those in normal individuals, and the differences are statistically significant. The expression levels of anti-esophageal squamous cell carcinoma-related antigens MSTO1, SNRPB, CASR, DAB2IP, RBPJ, and TTN in human serum were also statistically significant. The expression levels of autoantibodies against N and RIMS2 can effectively differentiate esophageal squamous cell carcinoma from normal individuals. Verification showed that when seven biomarkers—autoantibodies against MSTO1 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide, and RIMS2 antigen peptide—are used in combination to differentiate esophageal squamous cell carcinoma from normal individuals, the AUC value of the ROC curve is 0.84, indicating good differentiation and diagnostic efficacy. Therefore, the biomarkers for esophageal squamous cell carcinoma diagnosis of this invention can be used as an adjunct to the diagnosis of esophageal squamous cell carcinoma.

[0039] (3) The kit of the present invention detects the expression levels of autoantibodies of MSTO1 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide and RIMS2 antigen peptide in human serum by indirect ELISA method. It can accurately distinguish esophageal squamous cell carcinoma patients from healthy controls, and provides new reference for clinicians to diagnose esophageal squamous cell carcinoma.

[0040] (4) The test sample of the kit of the present invention is serum, which can avoid invasive diagnosis. The risk of esophageal squamous cell carcinoma can be obtained by taking serum through a minimally invasive method. The detection method has the characteristics of high sensitivity, strong specificity and low cost. It is also simple and quick to operate, which can provide a basis for the early diagnosis of esophageal squamous cell carcinoma. Attached Figure Description

[0041] Figure 1 Heatmap of 36 candidate antigenic peptides screened by PhIP-Seq technology in esophageal squamous cell carcinoma and healthy controls;

[0042] Figure 2 The expression of 12 peptide autoantibodies screened by peptide microarray in esophageal squamous cell carcinoma and healthy controls; where ESCC represents the esophageal squamous cell carcinoma group and HC represents the healthy control group; ** represents P<0.01, *** represents P<0.001, and **** represents P<0.0001.

[0043] Figure 3 The expression of 12 peptide autoantibodies screened by peptide microarray in early esophageal squamous cell carcinoma and healthy controls; where ESCC is the esophageal squamous cell carcinoma group and HC is the healthy control group; * represents P<0.05, ** represents P<0.01, *** represents P<0.001, **** represents P<0.0001;

[0044] Figure 4 The expression levels of 12 polypeptide autoantibodies are shown in the validation group; where ESCC represents the esophageal squamous cell carcinoma group, HC represents the healthy control group, NormalizedOD represents optical density, * represents P<0.05, ** represents P<0.01, **** represents P<0.0001, and ns represents no statistically significant difference.

[0045] Figure 5 ROC curves for diagnosing esophageal squamous cell carcinoma using 10 types of peptide autoantibodies (validation group);

[0046] Figure 6 The graph shows the expression levels of 10 polypeptide autoantibodies (test group); where ESCC represents the esophageal squamous cell carcinoma group, HC represents the healthy control group, NormalizedOD represents optical density, * represents P<0.05, *** represents P<0.001, and **** represents P<0.0001.

[0047] Figure 7 ROC curves for diagnosing esophageal squamous cell carcinoma using 10 types of peptide autoantibodies (test group);

[0048] Figure 8 Example plot for PeptideAbRF tool prediction;

[0049] Figure 9The ROC curves and confusion matrix of the esophageal squamous cell carcinoma diagnostic model are shown in the training, validation and test sets. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below through embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] Example 1: Screening of antigenic peptides based on PhIP-Seq technology

[0052] 1. Experimental Samples

[0053] Serum samples were collected from 50 patients with primary esophageal squamous cell carcinoma (ESCC) at the First Affiliated Hospital of Zhengzhou University (ESCC group) and 50 healthy controls (health control group). The ESCC serum samples from the 50 patients were obtained from pathologically confirmed cases who had not undergone surgery, radiotherapy, chemotherapy, traditional Chinese medicine, or immunotherapy. Diagnosis occurred between June 2021 and December 2023. Of the 50 ESCC patients, 25 were male (50.0%) and 25 were female (50.0%), with a median age of 63.5 years and an age range of 58-66 years. The ESCC serum samples from the 50 healthy controls were obtained from healthy subjects who participated in annual health checkups and had no symptoms of malignant tumors. Of the 50 healthy controls, 25 were male (50.0%) and 25 were female (50.0%), with a median age of 61 years and an age range of 58-65 years. This study was conducted with the consent of the patients and approval from the institutional review committee and the hospital ethics committee.

[0054] Serum collection: 5-10 mL of whole blood was collected from all subjects using red-tipped blood collection tubes. After being placed at room temperature for 2 hours, the samples were centrifuged at 1000g for 15 minutes, and the supernatant was collected. Each sample was aliquoted, labeled, and stored in a -80℃ freezer to avoid repeated freeze-thaw cycles.

[0055] 2. PhIP-Seq (phage immunoprecipitation sequencing) technology

[0056] (1) Experimental method:

[0057] 1) Serum pretreatment: Place each serum sample at 4°C and centrifuge at 12,000 rpm for 20 minutes. Take the supernatant and dilute it to 1 mL with PBST buffer at a ratio of 1:1000. Add the solution to a pre-sealed 96-well plate and set up negative control, blank control and positive control wells in each 96-well plate.

[0058] 2) Phage display peptide library incubation: Diluted and centrifuged phage display peptide library (Humanproteome, Shanghai Anticode Biotechnology Co., Ltd.) was added to each well, ensuring a library diversity of 16,000× phages per well. The 96-well plate was then sealed with the matching sealing cap and incubated overnight at 4°C by rotation.

[0059] 3) Magnetic bead precipitation and enrichment: After incubation, add 20 μL of washed Protein G magnetic beads to each well and incubate at 4°C for 4 hours. After incubation, centrifuge at 500g for 3 minutes, place the reaction plate on a magnetic rack to adsorb Protein G magnetic beads, and discard the original solution. Add 200 μL of a solution containing 0.1% Protein G magnetic beads to each well. Wash the CA-630 beads with TBS buffer, resuspend them by pipetting, and transfer them to a new 96-well PCR plate. Repeat the washing process twice, then resuspend the magnetic beads in 40 μL of enzyme-free water and transfer them to a new 96-well PCR plate.

[0060] 4) PCR Library Construction: After sealing the plate, centrifuge briefly for 10 seconds and heat in a PCR instrument at 95°C for 10 minutes. Two rounds of PCR were used for sequencing library construction. The first round used universal primers matching the phage sequence, and the second round used primers containing barcode sequences and sequencing adaptor sequences for amplification. After quality monitoring of the amplification products by gel electrophoresis, the target band was obtained by gel electrophoresis and gel excision.

[0061] 5) High-throughput sequencing: High-throughput sequencing was performed on the library-constructed samples using the Illumina sequencing platform. Sequencing reads were 150 bp in length, and bidirectional sequencing was employed. Full-length sequences were obtained from paired-end sequencing results, with the number of reads per peptide segment used as the basic data.

[0062] (2) Data processing:

[0063] 1) Alignment analysis: After sequencing, the fastq files are aligned to the reference peptide library using bowtie2 software (https: / / bowtie-bio.sourceforge.net / bowtie2 / manual.shtml) to ensure efficient and accurate alignment results.

[0064] 2) Standardization and quality control: First, the sequencing volume of different samples was normalized (the sequencing volume of each sample was proportionally adjusted to 1.25M reads) to obtain the normalized reads (NR) value of each peptide detected in each sample; based on the initial library sequencing abundance of each peptide, i.e., the number of input reads, the enrichment factor (EF) of different peptides in each sample was further calculated; finally, the P value of each peptide was calculated according to the generalized Poisson distribution model.

[0065] 3) Calculation of enriched positive peptides: Enriched positive peptides in each sample were selected according to the set threshold criteria (NR>15, EF>5, -log10(p-value)>36.44). The -log10(p-value) threshold was determined based on the mock IP group. Mock IP is a control method, referring to an immunoprecipitation experiment without the addition of serum, used to assess the non-specific binding of peptides and provide a background signal baseline.

[0066] 4) Differential analysis: In order to eliminate false positives caused by a single statistical method, this study used the following three statistical methods to screen candidate antigen peptides: Wilcoxon differential analysis, Fisher's exact test, and edgeR differential analysis.

[0067] (3) Experimental results:

[0068] To identify antigenic peptides with potential diagnostic value for esophageal squamous cell carcinoma, two screening methods were employed. First, a comprehensive screening was conducted based on AUC, logFC, and the number of positive cases in the esophageal squamous cell carcinoma group. Twenty-four priority antigenic peptides were identified according to the criteria of AUC > 0.6, logFC > 1.5, and #ESCC > 5: #405016 (ZNF606), #529845 (GIN1), #495786 (SEMA6C), #278126 (DAB2IP), #549261 (DMBT1), #470167 (DIDO1), #13391 (C2CD4D), #7563 (OTOL1), #573684 (PSG11), and #411341. (TTN), #12980(HNRNPCL2), #232508(UBE3C), #607550(MYO15B), #584260(NRXN3), #476404(PAPPA2), #325162(CPEB2), #63328(NOL4), #302271(DCHS2), #272359(TTBK1), #441319(TMEM87B), #356982(ZNF444), #573011(RIMS2), #64338(SORBS2), and #630028(SNRPB). Secondly, some antigenic peptides, although their AUC values ​​were not statistically significant, had a high number of positive reactions in the ESCC group. Therefore, based on the screening criteria of #ESCC≥7 people and #HC≤2 people, 12 suboptimal antigen peptides were included, namely: #190341 (RBPJ), #465386 (SEMA3C), #354357 (KMT2E), #531312 (FAM53C), #352364 (COLGALT2), #267423 (UBXN11), #471512 (MSTO1), #140200 (CASR), #332330 (RIMS1), #45035 (ACSL4), #599629 (RCAN2), and #621731 (KLF7).

[0069] Combining the two screening methods above, a total of 36 candidate antigen peptides were obtained as candidate indicators. For example... Figure 1As shown, the 36 candidate antigenic peptides screened had good distinguishing ability between esophageal squamous cell carcinoma and healthy controls. Except for ten antigenic peptides, #405016 (ZNF606), #529845 (GIN1), #63328 (NOL4), #573011 (RIMS2), #64338 (SORBS2), #190341 (RBPJ), #465386 (SEMA3C), #354357 (KMT2E), #531312 (FAM53C), and #352364 (COLGALT2), which showed positive reactions in 1-2 people in healthy controls, the remaining 26 antigenic peptides did not show positive reactions in healthy controls.

[0070] Example 2: Prediction and design of B-cell epitopes of candidate related antigenic peptides for esophageal squamous cell carcinoma based on bioinformatics

[0071] For the 36 antigenic peptides obtained in Example 1, the B-cell epitopes of each antigenic peptide were predicted using the six prediction methods shown in Table 1. The predicted B-cell epitopes were compared with the sequence intervals of the 36 antigenic peptides obtained in Example 1, and the overlapping sequences were extracted to obtain candidate epitopes. This ensured that the selected candidate epitopes had both theoretical support for computational prediction and conformed to the sequence characteristics detected experimentally. Simultaneously, the location of the candidate epitopes in the protein structure was analyzed using the protein's three-dimensional structure file to determine whether these regions were located on the surface of the protein molecule. Finally, the combined prediction results were used as the B-cell epitopes for esophageal squamous cell carcinoma-related antigenic peptides, resulting in 56 peptide sequences with lengths ranging from 14 to 25 amino acids.

[0072] Table 1. Detailed information on six B-cell epitope prediction methods.

[0073]

[0074] The source antigens and sequence intervals of the 56 polypeptide sequences are as follows: ZNF606 (461-484, 489-510), GIN1 (286-308, 254-274), SEMA6C (629-649, 646-668), DAB2IP (121-140, 143-161), DMBT1 (1217-1236, 1193-1215), DIDO1 (113-136), C2CD4D (113-134, 135-159), OTOL1 (1 41-161,162-183), PSG11(112-133,85-103), TTN(22677-22701,22700-22719), HNRNPCL2(109-132), UBE3C(645 -664,666-682), MYO15B(408-431), NRXN3(932-954), PAPPA2(1122-1139,1152-1172), CPEB2(12-34), NOL4(569- 586,595-614), DCHS2(1009-1028,1046-1062), TTBK1(1037-1054), TMEM87B(400-423,435-448), ZNF444(228-2 52), RIMS2(1034-1056), SORBS2(256-274,225-244), SNRPB(208-228), RBPJ(466-489,441-459), SEMA3C(395-4 16), KMT2E(833-856), FAM53C(146-165,182-196), COLGALT2(389-413), UBXN11(243-260,272-288), MSTO1(420 -437,379-394), CASR(565-581), RIMS1(1506-1528,1531-1552), ACSL4(345-363), RCAN2(34-54), KLF7(10-32).

[0075] Example 3: Screening for biomarkers for the diagnosis of esophageal squamous cell carcinoma using peptide microarray chips.

[0076] The peptide microarray method was used to screen for biomarkers for the diagnosis of esophageal squamous cell carcinoma using 56 antigenic peptides obtained in Example 2.

[0077] 1. Experimental Samples

[0078] Serum samples were collected from the First Affiliated Hospital of Zhengzhou University (using the same selection criteria as in Example 1), including 308 esophageal squamous cell carcinoma samples (esophageal squamous cell carcinoma group) and 308 healthy control samples (healthy control group). Among the 308 newly diagnosed esophageal squamous cell carcinoma patients, there were 211 males (68.51%) and 97 females (34.49%), with a median age of 68 years (range 63-73). In contrast, among the 308 normal serum samples, there were 195 males (63.31%) and 113 females (36.69%), with a median age of 67 years (range 60.8-72). Of the 308 esophageal squamous cell carcinoma samples, 97 were TNM stage I-II, belonging to the early-stage esophageal squamous cell carcinoma group.

[0079] Serum collection: 5-10 mL of whole blood was collected from all subjects using red-tipped blood collection tubes. After being placed at room temperature for 2 hours, the samples were centrifuged at 1000g for 15 minutes. The supernatant was collected, and each sample was aliquoted, labeled, and stored in a -80℃ freezer to avoid repeated freeze-thaw cycles.

[0080] 2. Detection using peptide microarray chips

[0081] (1) Experimental reagents:

[0082] 1) 3% BSA blocking solution: Add 3 mL of 10% BSA to 7 mL of 1×PBS solution, mix well, and place on ice;

[0083] 2) Serum diluent: Add 9 mL of 1×PBST solution to 1 mL of 10% BSA, mix well, and place on ice;

[0084] 3) Cleaning solution: 1×PBST, stored at 4℃;

[0085] 4) Secondary antibody incubation solution: fluorescently labeled anti-human IgG secondary antibody (cy3 labeled, appearing green);

[0086] 5) 56 antigenic polypeptides: synthesized by Shanghai Sangon Biotech.

[0087] (2) Preparation of polypeptide microarray chips:

[0088] 1) Prepare antigen peptide samples: Dilute the dissolved antigen peptide with nuclease-free water to the same concentration, and take the same volume of... Protein chip spotting solution B (1:1) (Beijing Biochip Biotechnology Co., Ltd., catalog number: 440016) is used to dilute the antigen peptide to the spotting concentration, and 120 μL is transferred to a 96-well PP plate and stored at 4°C in the dark for later use.

[0089] 2) Clean the spotting instrument before the experiment, replace the ultrapure water, and turn on the humidifier and temperature regulator 30 minutes in advance. Set the humidity of the chip spotting instrument to 60% and the temperature to 25℃. After the humidity and temperature have stabilized and balanced to the set values, prepare to start the spotting.

[0090] 3) Simulated spotting: Before the actual spotting, place a glass slide at each of the four corners, draw spotting liquid to perform a simulated spotting, and ensure that the instrument's robotic arm, height detector, liquid circuit, etc. are operating normally, and observe whether the position and shape of the spotting point are normal.

[0091] 4) Remove the epoxy-based slides from the 4℃ freezer beforehand. After equilibrating to room temperature for 30 minutes, open the vacuum packaging. Carefully use tweezers to place the slides in a Z-shape, starting from the top left, into the dustproof glass cover. Then, place the 96-well PP plate containing the antigen peptide sample into the spotting instrument and cover it with the dustproof glass cover. If there are any remaining epoxy-based slides, promptly place them into a vacuum packaging bag, vacuum-seal, and store in a 4℃ freezer.

[0092] 5) After the temperature and humidity inside the dustproof glass cover have balanced and stabilized, start running the pre-set sampling program to officially begin sampling.

[0093] 6) After spotting, rinse the spotting needle and fluid path with ultrapure water, and do not move the substrate for half an hour. After the substrate has been placed in the dustproof glass cover of the spotting instrument for 2 hours, adjust the temperature to 37°C and incubate for 4 hours to ensure full binding.

[0094] 7) Affixing the fence: using The chip fence pasting tool and clamping tool are used to paste 12 sample fences on the sample spot surface. In this step, it is important to make sure that the fence is pasted on the sample spot surface.

[0095] 8) Chip preservation: The peptide chip is now ready for immediate use. If immediate testing is not possible, the chip can be vacuum-sealed and stored in a -80°C refrigerator (dark environment) with a desiccant inside to ensure a longer shelf life.

[0096] (3) Experimental methods:

[0097] 1) Chip temperature equilibration: Remove the peptide microarray chip from the -80℃ freezer and quickly place it sequentially into freezers at -20℃ and 4℃ for a gradual transition to avoid condensation on the glass slide surface. After removal, equilibrate for 30 minutes under sealed conditions at room temperature, ensuring the chip remains sealed during this process. Open the vacuum packaging bag only after equilibration is complete.

[0098] 2) Prepare the hybridization box: Take out For the protein chip reaction cassette, place a piece of appropriately sized filter paper at the bottom, add 100–150 μL of ultrapure water to maintain the necessary humidity, and place the side with the guardrail facing up inside the hybridization box.

[0099] 3) Blocking: Use 3% BSA as the blocking solution. Slowly add 25 μl of blocking solution to each enclosure using a pipette. After covering and sealing the hybridization box, place it in the chip hybridization instrument and block the reaction at 37°C and 10 rpm for 2 hours.

[0100] 4) Cleaning and drying: Carefully remove the slide from the hybridization cassette using tweezers, and wash it three times with Washing Buffer I (1×PBST) for 5 minutes each time, with a washing intensity of 5. After cleaning, carefully place the slide into the centrifuge drying chamber for centrifugation and drying.

[0101] 5) Cover with a cap: Remove the plastic film covering the cap, and carefully place the dried chip into the cap using tweezers. For the protein chip reaction cassette, cover each chip with its corresponding chip cover, ensuring the raised side of the cover faces the chip. First, touch the top of the chip, then slowly close the cover. If there are any plastic debris on the cover, blow them away with nitrogen.

[0102] 6) Serum hybridization: Remove the serum samples to be tested from the -80℃ freezer in advance and place them in the 4℃ freezer for slow thawing. Then, vortex and centrifuge. Dilute the serum to the final concentration using serum diluent at a dilution ratio of 1:50. Use a pipette to slowly add 25μl of diluted serum to each subarray through the sample well. Place the subarray in a chip hybridization instrument and perform hybridization reaction at 37℃ and 10rpm for 1 hour.

[0103] 7) Cleaning and drying: Repeat step 4).

[0104] 8) Secondary antibody reaction and washing: In a light-protected environment, immediately add 25 μL of diluted secondary antibody reaction solution (Cy3-IgG) through the sample well, and place it in a chip hybridization instrument for hybridization reaction at 37℃ and 10 rpm for 1 hour in the light-protected environment.

[0105] 9) Cleaning and drying: After removing the chip from the hybridization box, place it in the chip cleaner. First, clean it 3 times with washing solution I (1×PBST), then rinse it once with washing solution II (ultrapure water), and then immediately place it in the centrifuge drying chamber for centrifugation and drying.

[0106] 10) Scanning: Turn on the chip scanner in advance and preheat for at least 30 minutes. Place the dried chip into the instrument for scanning, adjust the appropriate photomultiplication factor (PMT) and laser power, use LuxScan 3.0 software to extract signal values, save the image and original file, and record the scanning results.

[0107] (3) Data processing:

[0108] 1) Chip quality control

[0109] a) Substrate quality control: First, the detection signal values ​​are quality controlled to identify abnormal slides. This is done using Bio-LuxScan. TM A 10K / A dual-laser microarray chip scanner is used to scan the slide. A positive control point foreground value >20000 and a negative control point <100 indicate that the slide test is qualified.

[0110] b) Spotting quality control: Each antigenic peptide is spotted three times, and the CV value between the foreground and background values ​​is calculated for each spot. If the CV value of the foreground or background value in the same sample exceeds 40%, the test result of that sample is considered invalid and needs to be retested.

[0111] c) Repeatability test: The same serum sample was subjected to peptide microarray detection both within the same batch and between different batches. Pearson correlation analysis was used to evaluate the stability and repeatability of the prepared peptide microarray chip.

[0112] 2) In-chip normalization

[0113] To eliminate signal inhomogeneity caused by inconsistent background values ​​between different points within the same chip, a background normalization method is used. The signal-to-noise ratio (SNR) is calculated for each point, and the average SNR of the three repeated sampling points is then used as the detection signal value of the polypeptide autoantibody.

[0114]

[0115] 3) Standardization between different chips

[0116] Signal intensity differences between different microarrays often involve systematic errors from sample testing or instrument operation, necessitating standardization. First, the signal intensity in the 12th subarray of each chip is linearly fitted to a reference dataset, and the normalization factor (NF) is calculated. NF is used to adjust the SNR value of each chip to match the reference dataset, thus achieving data standardization between different chips. This process effectively reduces batch-to-batch variation, ensuring the comparability and reliability of experimental results. The specific method is as follows:

[0117] a) Constructing a reference dataset: For the 12th subarray of each microarray, first calculate the SNR value of each peptide autoantibody. Then, summarize the signal intensity of each peptide autoantibody in all detection microarrays in the 12th subarray and calculate the average value, which serves as the reference dataset.

[0118] b) Exclude low-signal antigen peptides: Low-signal peptides may affect the standardization results. Exclude antigen peptides with a mean SNR of less than 1.00 for subsequent standardization.

[0119] c) Calculate the correlation coefficient and exclude outliers: Calculate the Pearson correlation coefficient between the reference dataset and the data of the 12th subarray of each slide. If the correlation coefficient is less than 0.96, exclude outliers that are far from the diagonal.

[0120] d) Linear fitting and calculation of NF: The linear relationship between each slide and the reference dataset is calculated using the lm function in R language, and the correction factor is obtained by coef().

[0121] Model N i =lm(Reference Signal Intensities~Slide i Block-1)

[0122] Factor N i =coef(Model N) i )

[0123] Note: Reference Signal Intensities are the SNR values ​​of the reference dataset, and Slide i Block 12 is the SNR value of the 12th subarray in the i-th slide.

[0124] e) Standardize the signal strength of different microarrays: For the SNR value measured in each slide, multiply it by the NF value calculated for the corresponding slide to obtain the standardized data.

[0125] To screen for autoantibodies against antigenic peptides with diagnostic potential in early-stage esophageal squamous cell carcinoma (ESCC), the following criteria were used: 1) Statistical differences (P < 0.05) were required between the ESCC group and the healthy control group, as well as between the early-stage ESCC group and the healthy control group; 2) To ensure sufficient immunogenicity, the median signal-to-noise ratio (SNR) in ESCC needed to be greater than 1.2; 3) To meet the criteria for differential expression, the fold change between the two groups needed to be greater than 1.3. Autoantibodies against ESCC-related antigens that met these criteria were then selected.

[0126] (4) Experimental results:

[0127] After screening, 12 potential antigenic peptide autoantibodies with early diagnostic value were obtained: anti-PEP_06, anti-PEP_07, anti-PEP_11, anti-PEP_18, anti-PEP_29, anti-PEP_36, anti-PEP_37, anti-PEP_39, anti-PEP_41, anti-PEP_49, anti-PEP_50, and anti-PEP_51. These antigenic peptide autoantibodies are respectively derived from PEP_06 antigenic peptide (from SEMA6C), PEP_07 antigenic peptide (from DAB2IP, sequence range 121-140), PEP_11 antigenic peptide (from DIDO1), and PEP_18 anti-PEP_06. Autoantibodies against the original polypeptide (derived from TTN, sequence interval 22677-22701), PEP_29 antigenic polypeptide (derived from NOL4), PEP_36 antigenic polypeptide (derived from RIMS2, sequence interval 1034-1056), PEP_37 antigenic polypeptide (derived from SORBS2), PEP_39 antigenic polypeptide (derived from SNRPB, sequence interval 208-228), PEP_41 antigenic polypeptide (derived from RBPJ, sequence interval 441-459), PEP_49 antigenic polypeptide (derived from MSTO1 antigenic polypeptide), PEP_50 antigenic polypeptide (derived from MSTO1 antigenic polypeptide, sequence interval 379-394), and PEP_51 antigenic polypeptide (derived from CASR, sequence interval 565-581) were identified. The expression of these 12 polypeptide autoantibodies in the esophageal squamous cell carcinoma group and the healthy control group is shown below. Figure 2 As shown, the expression of 12 polypeptide autoantibodies in the early esophageal squamous cell carcinoma group and the healthy control group is as follows: Figure 3 As shown, by Figure 2 , Figure 3 It can be seen that the expression levels of these 12 polypeptide autoantibodies in the serum of the esophageal squamous cell carcinoma group / early esophageal squamous cell carcinoma group were higher than those in the healthy control group.

[0128] Example 4: ELISA detection of serum expression levels of autoantibodies against esophageal squamous cell carcinoma-associated antigens

[0129] The expression levels of the 12 anti-esophageal squamous cell carcinoma-related antigen autoantibodies screened in Example 3 were further detected in a large sample of human serum using an indirect enzyme-linked immunosorbent assay (ELISA).

[0130] 1. Experimental Samples

[0131] The samples were the same as in Example 3, including 308 esophageal squamous cell carcinoma samples and 308 healthy controls, which served as the validation group.

[0132] Serum collection: 5-10 mL of whole blood was collected from all subjects using red-tipped blood collection tubes. After being placed at room temperature for 2 hours, the samples were centrifuged at 1000g for 15 minutes, and the supernatant was collected. Each sample was aliquoted, labeled, and stored in a -80℃ freezer to avoid repeated freeze-thaw cycles.

[0133] 2. Experimental reagents:

[0134] (1) Blocking solution: 3 mL of 10% BSA, add 7 mL of 1×PBS solution, mix well, and place on ice.

[0135] (2) Serum incubation solution: 1 mL of 10% BSA, add 9 mL of 1×PBST solution, mix well, and place on ice.

[0136] (3) Cleaning solution: 1×PBST, stored at 4℃.

[0137] (4) Secondary antibody incubation solution: HRP-labeled mouse anti-human IgG.

[0138] 3. Experimental methods:

[0139] (1) Coating: The 12 antigenic polypeptide sequences screened in Example 3 above (chemically synthesized by Sangon Biotech (Shanghai) Co., Ltd.) were coated respectively. The following antigenic polypeptides were coated at a concentration of 4 μg / ml: PEP_07, PEP_36, PEP_37, PEP_39, PEP_49, PEP_50; the following antigenic polypeptides were coated at a concentration of 1 μg / ml: PEP_06, PEP_11, PEP_18, PEP_51; and the following antigenic polypeptides were coated at a concentration of 0.5 μg / ml: PEP_29, PEP_41; 50 μL / well, overnight at 4°C.

[0140] (2) Blocking: 100 μL / well of 2% BSA in PBST (PBS, Tween 20) solution, incubated overnight at 4°C.

[0141] (3) Cleaning: Wash 3 times with 350μL / well PBST.

[0142] (4) Primary antibody incubation: The serum to be tested was diluted with PBST containing 1% BSA at a ratio of 1:100, 50 μL / well, and incubated in a half-water bath at 37°C for 1 h.

[0143] (5) Washing: Wash 5 times with 350μL / well PBST.

[0144] (6) Secondary antibody incubation: HRP-labeled mouse anti-human IgG was diluted with PBST containing 1% BSA at a ratio of 1:5000, 50 μL / well, and incubated in a half-water bath at 37°C for 1 h.

[0145] (7) Washing: Wash 5 times with 350 μL / well PBST.

[0146] (8) Color development: TMB color development system, mix solution A (Solepro, Beijing) and solution B in a 1:1 ratio, 25 μL / well, room temperature and protected from light, to achieve the desired color.

[0147] (9) Termination: Measure absorbance within 10 min after termination with 25 μL of 10% concentrated sulfuric acid per well.

[0148] (10) Measure absorbance: using OD 450 -OD 620 The relative OD values ​​were calculated, and then the blank control was subtracted. The detection values ​​between different ELISA plates were normalized based on the detection values ​​of the quality control wells, and then subsequent data processing was performed (for details of the data processing method, please refer to "4. Data Processing" below).

[0149] 4. Data Processing:

[0150] For the data obtained from the ELISA reader, the OD values ​​at 450nm wavelength in each ELISA plate were first processed as follows: the OD value at 620nm wavelength was subtracted, and then the average OD value of the two blank wells in each plate was subtracted to eliminate the influence of background signals. The result was then used as the detection signal value of the sample. Next, the following methods were used for quality control and standardization:

[0151] (1) Sample quality control: Two blank control wells are set in each ELISA plate to monitor background noise and nonspecific binding. If the OD value of the blank control well is higher than 0.1, the samples in the plate need to be retested to ensure the reliability of the data.

[0152] (2) Standardization Processing: Each ELISA plate has six control wells for standardizing OD values ​​between different ELISA plates. For the same polypeptide autoantibody, the mean, standard deviation, and CV value of the control samples in each ELISA plate are calculated. If the CV value of a control sample well exceeds 20%, the test result of that well is discarded. For the same detection index, the mean values ​​of all control wells of the ELISA plates are used as a reference set. The test values ​​of each plate are standardized based on the reference set to eliminate systematic errors between different plates.

[0153] (3) Statistical analysis: The diagnostic value of single-peptide autoantibodies for esophageal squamous cell carcinoma was evaluated using ROC curves. The cutoff value was the OD value at which specificity was greater than 90% and the Youden index was maximized. The corresponding AUC, sensitivity, specificity, positive predictive value, negative predictive value, accuracy, precision, and Youden index were calculated and reported. In addition, the Delong test was used to compare the differences in AUC values ​​between the two groups, and P < 0.05 was considered to indicate a statistically significant difference between the two groups.

[0154] 5. Experimental Results:

[0155] The expression levels of 12 polypeptide autoantibodies in the esophageal squamous cell carcinoma group and the healthy control group in the validation group are as follows: Figure 4 As shown, 10 polypeptide autoantibodies with statistically significant differences were obtained after ELISA validation: anti-PEP_07, anti-PEP_18, anti-PEP_29, anti-PEP_36, anti-PEP_37, anti-PEP_39, anti-PEP_41, anti-PEP_49, anti-PEP_50, and anti-PEP_51.

[0156] Depend on Figure 4 It can be seen that the 10 polypeptide autoantibodies, namely anti-PEP_07, anti-PEP_18, anti-PEP_29, anti-PEP_36, anti-PEP_37, anti-PEP_39, anti-PEP_41, anti-PEP_49, anti-PEP_50, and anti-PEP_51, show statistical differences.

[0157] Further, based on the expression levels of 10 polypeptide autoantibodies in the esophageal squamous cell carcinoma group and the healthy control group, ROC curves were constructed to differentiate esophageal squamous cell carcinoma from healthy controls using these 10 polypeptide autoantibodies. The results are as follows: Figure 5 As shown. By Figure 5The diagnostic value of the 10 polypeptide autoantibodies anti-PEP_07, anti-PEP_18, anti-PEP_29, anti-PEP_36, anti-PEP_37, anti-PEP_39, anti-PEP_41, anti-PEP_49, anti-PEP_50, and anti-PEP_51 in the validation group samples was obtained, and the results are shown in Table 2. As can be seen from Table 2, the AUC range of the 10 polypeptide autoantibodies was 0.56-0.69, the sensitivity range was 13.64%-35.71%, and the specificity range was 90.26%-95.13%. Among them, anti-PEP_50 had the highest AUC value of 0.69 (95% CI 0.65-0.73), with a sensitivity of 30.52%, specificity of 90.58%, positive predictive value of 76.42%, negative predictive value of 56.59%, accuracy of 60.55%, and Youden index of 0.21. Anti-PEP_36 and anti-PEP_41 had the same AUC value of 0.68 (95% CI 0.64-0.72), with sensitivities of 31.17% and 35.71%, specificities of 90.91% and 90.26%, positive predictive values ​​of 77.42% and 78.57%, negative predictive values ​​of 56.91% and 58.40%, accuracy of 61.04% and 62.99%, and Youden indices of 0.22 and 0.26, respectively.

[0158] Table 210 Diagnostic Value of 10 Polypeptide Autoantibodies for Esophageal Squamous Cell Carcinoma (Validation Group)

[0159]

[0160] Note: AUC: Area under the receiver operating characteristic curve, 95% CI: 95% confidence interval, Sen: sensitivity, Spe: specificity, Pr+: positive predictive value, Pr-: negative predictive value, Acc: accuracy, Precision: precision, YI: Youden index.

[0161] Example 5: Assessment of the ability of 10 polypeptide autoantibodies for the diagnosis of esophageal squamous cell carcinoma

[0162] The experimental sample included 124 patients with esophageal squamous cell carcinoma and 124 healthy controls, collected from Henan Cancer Hospital; the control group served as the test group. Among the 124 esophageal squamous cell carcinoma patients, 77 were male (62.10%) and 47 were female (37.90%), with a median age of 66 years (range 60-72). Among the 124 healthy controls, 83 were male (66.94%) and 41 were female (33.06%), with a median age of 65.6 years (range 60-71). The esophageal squamous cell carcinoma patients had not received surgery, radiotherapy, chemotherapy, traditional Chinese medicine, or immunotherapy before blood collection, and were diagnosed between August 2017 and October 2018. Serum samples from healthy controls were collected from individuals who participated in annual health checkups and had no symptoms of malignant tumors.

[0163] Serum collection: 5-10 mL of whole blood was collected from all subjects using red-tipped blood collection tubes. After being placed at room temperature for 2 hours, the samples were centrifuged at 1000g for 15 minutes, and the supernatant was collected. Each sample was aliquoted, labeled, and stored in a -80℃ freezer to avoid repeated freeze-thaw cycles.

[0164] To further test the diagnostic capabilities of 10 peptide autoantibodies for esophageal squamous cell carcinoma, serum samples from the test group were analyzed. The expression levels of the 10 peptide autoantibodies were as follows: Figure 6 As shown, by Figure 6 It can be seen that the expression levels of the 10 polypeptide autoantibodies all showed statistical differences.

[0165] ROC curves were constructed for diagnosing and differentiating esophageal squamous cell carcinoma from healthy controls using 10 peptide autoantibodies. The results are as follows: Figure 7 As shown. By Figure 7 The diagnostic value of the 10 polypeptide autoantibodies (anti-PEP_07, anti-PEP_18, anti-PEP_29, anti-PEP_36, anti-PEP_37, anti-PEP_39, anti-PEP_41, anti-PEP_49, anti-PEP_50, and anti-PEP_51) in the test group samples was obtained, and the results are shown in Table 3. Table 3 shows that the AUC values ​​of the 10 polypeptide autoantibodies ranged from 0.59 to 0.73, the sensitivity ranged from 28.23% to 48.39%, and the specificity ranged from 90.32% to 95.97%. Among them, anti-PEP_50 had the highest AUC value of 0.73 (95% CI 0.66-0.79), a sensitivity of 31.45%, and a specificity of 95.97%. The AUC values ​​of anti-PEP_07 and anti-PEP_49 were the lowest, at 0.59 (95% CI 0.51-0.66) and 0.59 (95% CI 0.52-0.66), respectively.

[0166] Table 3. Diagnostic value of 310 polypeptide autoantibodies for esophageal squamous cell carcinoma (test group)

[0167]

[0168] Example 6: Construction, evaluation, and development of application tools for esophageal squamous cell carcinoma diagnostic models

[0169] Ten peptide autoantibodies (anti-PEP_07, anti-PEP_18, anti-PEP_29, anti-PEP_36, anti-PEP_37, anti-PEP_39, anti-PEP_41, anti-PEP_49, anti-PEP_50, anti-PEP_51) obtained from Example 5, which were validated by ELISA, were further screened using a recursive feature selection algorithm. This resulted in the identification of seven peptide autoantibodies (anti-PEP_50, anti-PEP_51, anti-PEP_41, anti-PEP_18, anti-PEP_36, anti-PEP_39, anti-PEP_07), and seven others (anti-PEP_50, anti-PEP_51, and anti-PEP_P_07). EP_41, anti-PEP_18, anti-PEP_36, anti-PEP_39, and anti-PEP_07 are autoantibodies against the following antigenic peptides: PEP_50 (derived from MSTO1, sequence interval 379-394), PEP_39 (derived from SNRPB, sequence interval 208-228), PEP_51 (derived from CASR, sequence interval 565-581), PEP_07 (derived from DAB2IP, sequence interval 121-140), PEP_41 (derived from RBPJ, sequence interval 441-459), PEP_18 (derived from TTN, sequence interval 22677-22701), and PEP_36 (derived from RIMS2, sequence interval 1034-1056).

[0170] The amino acid sequence of the PEP_50 antigen peptide is: APGQSLPDSLMQFGGA (SEQ ID NO.1);

[0171] The amino acid sequence of the PEP_39 antigen polypeptide is: GRGTPMGMPPPGMRPPPPGMR (SEQ ID NO.2);

[0172] The amino acid sequence of the PEP_51 antigen peptide is: CVECPDGEYSDETDASA (SEQ ID NO.3);

[0173] The amino acid sequence of the PEP_07 antigenic polypeptide is: RSHLMPRLKESRSHESLLSP (SEQ ID NO.4);

[0174] The amino acid sequence of the PEP_41 antigen polypeptide is: TFTYTPEPGPRPHCSAAGA (SEQ ID NO.5);

[0175] The amino acid sequence of the PEP_18 antigen polypeptide is: CDTVFKPGPPGNPRVLDTSRSSISI (SEQ ID NO.6);

[0176] The amino acid sequence of the PEP_36 antigen polypeptide is: PPPQSRNVEQGLRGTRTMTGHYN (SEQ ID NO.7);

[0177] Subsequently, a random forest model was used to construct models for the seven polypeptide autoantibodies, resulting in a diagnostic model for esophageal squamous cell carcinoma.

[0178] The method for constructing a diagnostic model for esophageal squamous cell carcinoma is as follows:

[0179] 1. Training dataset setup:

[0180] Training and validation set samples: Serum samples from 308 esophageal squamous cell carcinoma cases and 308 healthy controls in Example 3 were randomly divided into training and validation sets at a ratio of 7:3. The training set was used to build the model, and the validation set was used for internal validation and parameter adjustment of the model.

[0181] Test set samples: Serum samples from Example 5 were used for external validation of the model.

[0182] 2. Construction of a diagnostic model for esophageal squamous cell carcinoma:

[0183] The detection values ​​of anti-PEP_50, anti-PEP_51, anti-PEP_41, anti-PEP_18, anti-PEP_36, anti-PEP_39, and anti-PEP_07 autoantibodies in serum samples from the training set were used to construct an esophageal squamous cell carcinoma diagnostic model. The construction process is as follows:

[0184] (1) Construct a dataset of expression levels of peptide autoantibodies for each sample in the training set, including anti-PEP_50, anti-PEP_51, anti-PEP_41, anti-PEP_18, anti-PEP_36, anti-PEP_39, and anti-PEP_07.

[0185] (2) Construct a binary label for each sample in the training set (whether or not the patient has esophageal cancer, 0 indicates healthy, 1 indicates disease);

[0186] (3) The training set samples were sampled 50 times using the Bootstrap sampling method to determine the optimal parameters of the random forest model: mtry=2, splitule=extratrees, min.node.size=51, resulting in a model for esophageal squamous cell carcinoma diagnosis. The input features of the esophageal squamous cell carcinoma diagnosis model are the expression levels of anti-PEP_50, anti-PEP_51, anti-PEP_41, anti-PEP_18, anti-PEP_36, anti-PEP_39, and anti-PEP_07 autoantibodies; the output label is the probability value of whether or not the patient has esophageal squamous cell carcinoma.

[0187] When the P-value is ≥0.5, the sample is initially identified as a suspected esophageal squamous cell carcinoma.

[0188] When the P value is < 0.5, it is preliminarily determined to be a normal sample.

[0189] Since the results obtained by the method in this embodiment can only serve as intermediate information and cannot directly determine whether a patient has esophageal squamous cell carcinoma, they are mainly used for auxiliary diagnosis. Therefore, further analysis of clinical symptoms, imaging, and histopathological information is needed to ultimately determine the patient's condition.

[0190] To improve the usability and scalability of the esophageal squamous cell carcinoma diagnostic model, an online prediction platform for the esophageal squamous cell carcinoma diagnostic model (https: / / litdong.shinyapps.io / PeptideAbRF / ) was built using R software. Based on the shiny (version 1.10.0), shinydashboardPlus (version 2.0.5), and dashboardthemes (version 1.1.6) packages, the RF_model was deployed to the shinyapps online server for access and use. An example prediction figure for the PeptideAbRF tool is shown below. Figure 8 As shown.

[0191] The implementation code for building an online prediction platform using R software is as follows:

[0192]

[0193] probs_test<-predict(RF_model,test[,!names(test%in%c("Group")],type="prob")

[0194] roc_test<-roc(test$Group,probs_test$ESCC)

[0195] The ROC curves and confusion matrices of the esophageal squamous cell carcinoma diagnostic model of this invention on the training set, validation set, and test set are shown below. Figure 9 As shown, by Figure 9 The model's AUCs on the training, validation, and test sets were 0.86 (95% CI 0.83-0.89), 0.84 (95% CI 0.79-0.90), and 0.84 (95% CI 0.79-0.88), respectively, indicating that the model can be well used for the diagnosis of esophageal squamous cell carcinoma.

Claims

1. The use of reagents for detecting biomarkers in the preparation of products for the early diagnosis of esophageal squamous cell carcinoma, wherein the biomarker is at least one of the following: autoantibody of MSTO1 antigen peptide, autoantibody of SNRPB antigen peptide, autoantibody of CASR antigen peptide, autoantibody of DAB2IP antigen peptide, autoantibody of RBPJ antigen peptide, autoantibody of TTN antigen peptide, and autoantibody of RIMS2 antigen peptide.

2. The application according to claim 1, characterized in that, The reagent is used to detect the biomarkers in the sample by enzyme-linked immunosorbent assay (ELISA), protein chip, immunoblotting, or microfluidic immunoassay.

3. The application according to claim 2, characterized in that, The reagent is an antigen used to detect the biomarker.

4. The application according to claim 1, characterized in that, The sequence of the MSTO1 antigen peptide is APGQSLPDSLMQFGGA, the sequence of the SNRPB antigen peptide is GRGTPMGMPPPGMRPPPPGMR, the sequence of the CASR antigen peptide is CVECPDGEYSDETDASA, the sequence of the DAB2IP antigen peptide is RSHLMPRLKESRSHESLLSP, the sequence of the RBPJ antigen peptide is TFTYTPEPGPRPHCSAAGA, the sequence of the TTN antigen peptide is CDTVFKPGPPGNPRVLDTSRSSISI, and the sequence of the RIMS2 antigen peptide is PPPQSRNVEQGLRGTRTMTGHYN.

5. The application according to claim 2, characterized in that, The sample may be serum, plasma, interstitial fluid, or urine.

6. The application according to any one of claims 1 to 5, characterized in that, The product is a protein chip, reagent kit, or formulation.

7. A kit for early detection and diagnosis of esophageal squamous cell carcinoma, characterized in that, The kit contains an antigenic peptide for detecting a biomarker, wherein the biomarker is at least one of the following: an autoantibody of the MSTO1 antigenic peptide, an autoantibody of the SNRPB antigenic peptide, an autoantibody of the CASR antigenic peptide, an autoantibody of the DAB2IP antigenic peptide, an autoantibody of the RBPJ antigenic peptide, an autoantibody of the TTN antigenic peptide, and an autoantibody of the RIMS2 antigenic peptide.

8. The reagent kit according to claim 8, characterized in that, The kit detects the biomarkers in the sample by enzyme-linked immunosorbent assay (ELISA), protein chip, immunoblotting, or microfluidic immunoassay.

9. The reagent kit according to claim 7, characterized in that, The kit is an ELISA detection kit, which includes a solid-phase carrier and an antigen peptide coated on the solid-phase carrier; the antigen peptide is at least one of MSTO1 antigen peptide, SNRPB antigen peptide, CASR antigen peptide, DAB2IP antigen peptide, RBPJ antigen peptide, TTN antigen peptide and RIMS2 antigen peptide.

10. The reagent kit according to claim 9, characterized in that, The sequence of the MSTO1 antigen peptide is APGQSLPDSLMQFGGA, the sequence of the SNRPB antigen peptide is GRGTPMGMPPPGMRPPPPGMR, the sequence of the CASR antigen peptide is CVECPDGEYSDETDASA, the sequence of the DAB2IP antigen peptide is RSHLMPRLKESRSHESLLSP, the sequence of the RBPJ antigen peptide is TFTYTPEPGPRPHCSAAGA, the sequence of the TTN antigen peptide is CDTVFKPGPPGNPRVLDTSRSSISI, and the sequence of the RIMS2 antigen peptide is PPPQSRNVEQGLRGTRTMTGHYN.

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