Colorectal cancer and progression prediction system and equipment thereof

Abstract

The invention discloses a system and equipment for predicting colorectal cancer and progression thereof. Based on the found expression level difference of AXIN2 and / or EPHB2 in colorectal cancer and the progression thereof, the invention provides a colorectal cancer and progression prediction method, system and equipment, a computer readable storage medium and a computer program product, high-risk groups can be efficiently and accurately screened out from common groups, and colonoscopy is further completed in time. While the economic burden caused by endoscopic screening is relieved, patients suffering from colorectal adenoma and early colorectal cancer are screened out, and the method has great significance in early diagnosis and treatment of colorectal tumor and further remarkable reduction of the morbidity and mortality of colorectal cancer.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of intelligent medical treatment, and particularly relates to a prediction system and device for colorectal cancer and its progression. BACKGROUND

[0002] Colorectal cancer has become one of the most common malignant tumors in the world, and its morbidity and mortality rank the third and second among global malignant tumors. With the continuous improvement of people's living standards and the change of life style, the morbidity and mortality of colorectal cancer in China are showing a rising trend year by year. At present, colorectal cancer is the third most common malignant tumor in China.

[0003] Colonoscopy is the gold standard for screening of colorectal cancer and precancerous lesions, and can also determine the pathological diagnosis. However, the detection rate of colonoscopy for lesions is affected by factors such as intestinal preparation, endoscopic operation technology, the ability of the examiner to identify lesions, and the time of examination. Meanwhile, colonoscopy is an invasive examination with high cost, and the acceptance and compliance of patients may be low. There is a risk of bleeding and perforation during the examination, which limits the participation rate of colonoscopy in population-based screening practices.

[0004] Therefore, early diagnosis of colorectal cancer and precancerous lesions is crucial for improving treatment effectiveness and patient survival rate. SUMMARY

[0005] In order to make up for the deficiencies of the prior art, the present application provides a prediction system and device for colorectal cancer and its progression.

[0006] To achieve the above-mentioned purpose, the present application adopts the following technical solutions: The first aspect of the present application provides a prediction method for colorectal cancer and its progression, which is completed by a computer, and the method comprises: obtaining gene expression data of a to-be-tested sample; extracting expression data of target genes in the gene expression data, wherein the target genes include AXIN2 and / or EPHB2; performing classification prediction based on the expression data of the target genes to obtain a classification result of whether the to-be-tested sample has colorectal cancer and its progression; if the expression amount of the AXIN2 and / or EPHB2 is high, a classification result of the to-be-tested sample having colorectal cancer / serious progression is obtained; if the expression amount of the AXIN2 and / or EPHB2 is low, a classification result of the to-be-tested sample not having colorectal cancer / less serious progression is obtained.

[0007] Further, the target genes further include one or more of BACE2, MET, CD44, LIPG, TGFBI, TCN1, PRKDC, TNS4, CXCL1, MMP1 and MMP3.

[0008] The second aspect of the present application provides a prediction system for colorectal precancer / cancer, which comprises: an acquisition unit configured to acquire gene expression data of a sample to be tested; an extraction unit configured to extract expression data of target genes in the gene expression data, wherein the target genes comprise AXIN2 and / or EPHB2; a prediction unit configured to perform classification prediction based on the expression data of the target genes to obtain a classification result of whether the sample to be tested has colorectal cancer and its progression; if the expression amount of the AXIN2 and / or EPHB2 is high, a classification result of the sample to be tested having colorectal cancer / serious progression is obtained; if the expression amount of the AXIN2 and / or EPHB2 is low, a classification result of the sample to be tested not having colorectal cancer / less serious progression is obtained.

[0009] The third aspect of the present application provides a computer device, which comprises: a memory configured to store program instructions; a processor configured to invoke the program instructions, when the program instructions are executed, to perform the prediction method of the first aspect of the present application.

[0010] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to implement the steps of the method of the first aspect of the present application.

[0011] The fifth aspect of the present application provides a computer program product comprising a computer program, wherein the computer program is executed by a processor to implement the steps of the method of the first aspect of the present application.

[0012] The sixth aspect of the present application provides use of a reagent for detecting the level of AXIN2 and / or EPHB2 in the preparation of a product for diagnosing colorectal cancer and its progression.

[0013] Further, the reagent is selected from a probe specifically recognizing the AXIN2 and / or EPHB2 gene, a primer specifically amplifying the AXIN2 and / or EPHB2 gene, or a binding agent specifically binding to a protein encoded by the AXIN2 and / or EPHB2 gene.

[0014] Further, the reagent further comprises a detectable label.

[0015] Further, the detectable label comprises a radioisotope, a nucleotide chromophore, an enzyme, a substrate, a fluorescent molecule, a chemiluminescent moiety, a magnetic particle, a bioluminescent moiety.

[0016] The seventh aspect of the present application provides a product for diagnosing colorectal cancer and its progression, which comprises a reagent for detecting the level of AXIN2 and / or EPHB2.

[0017] Further, the product comprises a chip, a test paper, a kit or a nucleic acid membrane strip.

[0018] Further, the chip comprises a gene chip or a protein chip.

[0019] Further, the kit further comprises a buffer.

[0020] Further, the kit further comprises an instruction manual.

[0021] The eighth aspect of the present application provides a computer-aided drug screening system based on AXIN2 and / or EPHB2, which comprises: an acquisition unit for acquiring gene expression data of a sample; an extraction unit for extracting expression data of a target gene / protein in the gene expression data, the target gene comprising AXIN2 and / or EPHB2; a screening unit for obtaining a substance for inhibiting the level of AXIN2 and / or EPHB2 gene as a candidate drug for treating colorectal cancer through computer-aided screening.

[0022] Advantages and beneficial effects of the present application: Based on the discovered difference in the expression level of AXIN2 and / or EPHB2 in colorectal cancer and its progression, the present application provides a prediction method, system, device, computer readable storage medium and computer program product for colorectal cancer and its progression, which can efficiently and accurately screen out high-risk groups from the general population, and further complete colonoscopy in a timely manner. While reducing the economic burden caused by endoscopic screening, it screens out colorectal adenoma and early colorectal cancer patients, which is of great significance for early diagnosis and treatment of colorectal tumors and thus significantly reduces the incidence and mortality of colorectal cancer. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 is a schematic diagram of the prediction method for colorectal cancer and its progression of the present application; Figure 2 is a schematic diagram of the prediction system for colorectal cancer and its progression of the present application; Figure 3 is a device diagram of the prediction method for colorectal cancer and its progression of the present application; Figure 4 is a target gene screening flowchart; Figure 5 is a diagram of differentially expressed genes in the progression of colorectal cancer; Figure 6is a plot of expression of AXIN2 gene and EPHB2 gene in 33 TCGA cancer types; Figure 7 is a plot of gene expression profile in inflammatory bowel disease (IBD); Figure 8 is a plot of single cell RNA sequencing analysis of AXIN2 and EPHB2 expression in colorectal cancer; Figure 9 is a plot of change in AXIN2, EPHB2 transcript levels in colorectal tumor continuum; Figure 10 is a plot of immunohistochemistry (IHC) profiling of AXIN2 in Human Protein Atlas (HPA); Figure 11 is a plot of immunohistochemistry (IHC) profiling of EPHB2 in Human Protein Atlas (HPA); Figure 12 is a plot of clinical validation of serum AXIN2 in combination with EPHB2 for detection of colorectal precancerous lesions and colorectal cancer; Figure 13 is a plot of clinical validation of serum AXIN2 in combination with EPHB2 for differentiation of colorectal neoplastic lesions from benign colonic lesions; Figure 14 is a plot of colorectal cancer bioinformatics exploration based on AXIN2 driven mechanism; Figure 15 is a plot of colorectal cancer bioinformatics exploration based on EPHB2 driven mechanism. DETAILED DESCRIPTION

[0024] In order to make the personnel in the art better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the accompanying drawings in the embodiments of the present application.

[0025] In some of the descriptions in the specification and claims of the present application and the above-mentioned drawings, a plurality of operations appearing in a specific order are included, but it should be clearly understood that these operations can be executed in the order appearing in the text or in parallel, the serial numbers of the operations such as 101, 102, etc. are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes can include more or fewer operations, and the operations can be executed in sequence or in parallel. It should be noted that the "first", "second", etc. in the text are used to distinguish different messages, devices, modules, etc., and do not represent the order, nor do "first" and "second" represent different types.

[0026] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0027] Figure 1 is a schematic diagram of a prediction method of colorectal cancer and its progression of the present application, specifically comprising: 101: obtaining gene expression data of a sample to be tested.

[0028] 102: extracting expression data of target genes in the gene expression data, the target genes comprising AXIN2 and / or EPHB2.

[0029] 103: performing classification prediction based on the expression data of the target genes to obtain a classification result of whether the sample to be tested has colorectal cancer and its progression; if the expression amount of the AXIN2 and / or EPHB2 is high, a classification result of the sample to be tested having colorectal cancer / serious progression is obtained; if the expression amount of the AXIN2 and / or EPHB2 is low, a classification result of the sample to be tested not having colorectal cancer / less serious progression is obtained.

[0030] In some embodiments, AXIN2 comprises wild type, mutant or fragment thereof. The term encompasses full-length, unprocessed AXIN2, any form of AXIN2 that results from processing in the cell, as well as naturally occurring variants of AXIN2 (e.g., splice variants or allelic variants). The term encompasses, for example, human AXIN2 as well as AXIN2 from any other vertebrate source, including mammals such as primates and rodents (e.g., mice and rats), Gene ID 8313.

[0031] In some embodiments, EPHB2 comprises wild type, mutant or fragment thereof. The term encompasses full-length, unprocessed EPHB2, any form of EPHB2 that results from processing in the cell, as well as naturally occurring variants of EPHB2 (e.g., splice variants or allelic variants). The term encompasses, for example, human EPHB2 as well as EPHB2 from any other vertebrate source, including mammals such as primates and rodents (e.g., mice and rats), Gene ID 2048.

[0032] Figure 2 is a schematic diagram of a prediction system of colorectal cancer and its progression of the present application, specifically comprising: 201 acquisition unit: obtaining gene expression data of a sample to be tested.

[0033] 202 Extraction Unit: Extracts the expression data of the target gene from the gene expression data, wherein the target gene includes AXIN2 and / or EPHB2.

[0034] 203 Prediction Unit: Based on the expression data of the target gene, perform classification prediction to obtain the classification result of whether the test sample has colorectal cancer and its progression; if the expression level of AXIN2 and / or EPHB2 is high, the test sample is classified as having colorectal cancer / severe progression; if the expression level of AXIN2 and / or EPHB2 is low, the test sample is classified as not having colorectal cancer / slight progression.

[0035] Figure 3 This is a diagram of the device used in the method for predicting colorectal cancer and its progression, as described in this application, specifically including: Memory: The memory is used to store program instructions.

[0036] Processor: The processor is used to call program instructions, which, when executed, are used to perform the above prediction method.

[0037] The research methods and experimental techniques used in this application are as follows: Data Sources: Gene expression profiling data were obtained from publicly available databases: GeneExpression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Twelve independent datasets were acquired from GEO, along with two TCGA cohorts (TCGA-COAD and TCGA-READ), covering samples of normal colorectal mucosa, colorectal adenomas (classified by histology and grade), colorectal adenocarcinomas (stratified by stage), and inflammatory bowel diseases (ulcerative colitis and Crohn's disease).

[0038] Candidate upregulated genes were identified: Microarray data were analyzed using the limma package in R version 4.3.1, and RNA sequencing data were analyzed using the edgeR package to identify differentially expressed genes (DEGs) between colorectal lesion samples and normal mucosa. Genes with |log2FC| ≥ 0.58 (i.e., fold change ≥ 1.5) and corrected p-value < 0.05 were selected as significantly differentially expressed genes. The intersection of upregulated genes in 10 datasets was calculated using the ggvenn package, ultimately yielding 46 candidate upregulated genes.

[0039] Identification of genes encoding upregulated exocrine proteins: A manually proofread catalog of genes encoding exocrine proteins was compiled from the Human Protein Atlas (https: / / www.proteinatlas.org / ). This atlas defines the human endocrine genome by integrating signal peptide prediction tools (SignalP, Phobius, SPOCTOPUS), MDSEC scores, and expert annotations. Using the ggVenn software package, an intersection analysis was performed between this catalog and 46 candidate upregulated genes, ultimately identifying 13 genes encoding upregulated exocrine proteins.

[0040] Pan-cancer expression profile analysis of candidate genes: Transcriptome data (RNA-seq) from 33 malignant tumor types from TCGA were obtained from the UCSC Xena database. Subsequently, the pan-cancer expression profile of each gene was analyzed and visualized using the TCGAplot R package.

[0041] Single-cell RNA sequencing (scRNA-seq) analysis of candidate genes: Single-cell transcriptome profiling data were obtained from the scCancerExplorer platform (https: / / bianlab.cn / scCancerExplorer), corresponding to datasets HRA000201, GSE132465, GSE166555, GSE210347, and GSE144735. The expression patterns of candidate genes were visualized using the integrated visualization tools provided by scCancerExplorer.

[0042] Immunohistochemical validation of AXIN2 expression patterns: To validate the spatial distribution of AXIN2, immunohistochemical (IHC) data from various tumor and normal tissues in the Human Protein Atlas (HPA; https: / / www.proteinatlas.org) were examined.

[0043] The serum samples used for clinical validation in this study were residual samples from preoperative serological tests of patients who underwent colonoscopy at the Second Hospital of Hebei Medical University between July 2024 and May 2025. The study protocol was approved by the hospital's ethics committee (ethics approval number: 2022-R070). Based on endoscopic findings and biopsy histopathological results, the study subjects were divided into four groups according to the following inclusion and exclusion criteria: 1. Normal control group (19 cases) Inclusion criteria: No obvious abnormalities were found in the entire colon and rectal mucosa under colonoscopy, and biopsy pathology confirmed the absence of organic lesions.

[0044] Exclusion criteria: history of colorectal cancer, inflammatory bowel disease, or familial adenomatous polyposis; or coexisting malignant tumors of other systems.

[0045] 2. Colorectal adenoma group (16 cases) Inclusion criteria: Polypoid lesions detected by colonoscopy, biopsy pathology confirmed as tubular adenoma, tubulovillous adenoma or villous adenoma, without high-grade intraepithelial neoplasia.

[0046] Exclusion criteria: Concomitant colorectal cancer or multiple malignant tumors.

[0047] 3. Colorectal adenocarcinoma group (13 cases) Inclusion criteria: newly diagnosed cases with pathological confirmation of colorectal adenocarcinoma from colonoscopy biopsy or surgical resection specimens.

[0048] Exclusion criteria: coexisting primary malignant tumors in other organs; having received neoadjuvant chemoradiotherapy or targeted therapy before surgery.

[0049] 4. Colorectal inflammatory lesions group (18 cases) Inclusion criteria: Inflammatory changes such as mucosal congestion, erosion or ulceration can be seen under colonoscopy, and biopsy pathology confirms chronic inflammation or active inflammation, and neoplastic lesions are excluded.

[0050] Exclusion criteria: Concurrent adenoma or adenocarcinoma.

[0051] All patients' diagnoses were initially determined by the attending physician and then independently verified by at least two pathologists to ensure diagnostic accuracy. A total of 66 serum samples that met the criteria were included.

[0052] Enzyme-linked immunosorbent assay (ELISA): Serum AXIN2 and EPHB2 concentrations were measured using a commercially available human AXIN2 ELISA kit (catalog number EH2487, Wuhan Feien Biotechnology Co., Ltd.) and an EPHB2 ELISA kit (CSB-EL007730HU, CUSABIO, Wuhan, China), respectively, following the manufacturer's instructions. The specific procedure was as follows: Standards, patient serum (1:10 dilution for AXIN2 measurement, undiluted for EPHB2 measurement), or sample dilution (blank control) were added to 96-well plates coated with anti-AXIN2 and anti-EPHB2, respectively. After adding horseradish peroxidase (HRP) label, the plates were incubated at 37°C for 1 hour, followed by washing five times with washing buffer. Chromogenic substrates A and B were added to each well, and the plates were incubated at 37°C in the dark for 15 minutes. After stopping the reaction with stop solution, the absorbance at 450 nm was measured using a microplate reader (Synergy HT, BioTek). All samples were tested in duplicate, and the concentrations of AXIN2 and EPHB2 were calculated by interpolation using a seven-point standard curve.

[0053] Protein-protein interaction (PPI) network construction: Physical and functional associations in humans (Homo sapiens, NCBI Classification ID: 9606) were analyzed using STRING v12.0 (https: / / string-db.org). Only interactions with an interaction score ≥0.15 were retained, thus obtaining a set of proteins that are physically or functionally associated with candidate encoded proteins.

[0054] Functional enrichment analysis: Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was performed using the clusterProfiler R package (v4.10.0) based on the human reference genome (org.Hs.eg.db v3.18.0). Statistical significance was determined by hypergeometric test combined with Benjamini–Hochberg correction; a corrected p-value (FDR) <0.05 was considered significant. The enrichment results were visualized using the enrichplot and ggplot2 packages in R v4.3.1.

[0055] Statistical analysis: Continuous variables are expressed as mean ± standard deviation (SD). Comparisons between two independent samples were performed using either a two-tailed Student's t-test (parametric test) or a Mann–Whitney U test (nonparametric test), depending on the distribution of the data. For comparisons of three or more groups, one-way ANOVA followed by Tukey's post-hoc test, or the Kruskal–Wallis test combined with Dunn correction, was used. Diagnostic efficacy was quantified by the area under the receiver operating characteristic curve (AUC) and its 95% confidence intervals (CIs). All tests were two-tailed, and p < 0.05 was considered statistically significant. Analysis was performed using SPSS 25.0 statistical software and R v4.3.1.

[0056] result Serum biomarker screening: biomarkers upregulated at different stages of colorectal cancer and detectable in precancerous lesions. This study aims to identify a non-invasive, highly specific biomarker for initial screening of colorectal cancer or precancerous lesions in asymptomatic or healthy individuals. By improving detection rates, it can help identify high-risk individuals requiring further colonoscopy. An ideal diagnostic biomarker should meet the following criteria: 1) its serum level is significantly elevated in patients with colorectal cancer and detectable in the precancerous stage; 2) it has high specificity, capable of differentiating colorectal cancer from benign lesions.

[0057] Adopting such Figure 4The research proposal shown was screened and validated through the following steps: Adenoma Stage: Transcriptome data from six datasets were analyzed to identify genes significantly upregulated in colorectal adenomas (precancerous lesions) compared to normal colorectal mucosa. After rigorous screening (log2FC>0.585, P<0.05), 469-978 upregulated genes were identified across different datasets. Data integration revealed 72 genes that showed consistent upregulation across all datasets. Figure 5 A).

[0058] Early-stage colorectal cancer: mRNA expression profiles were obtained from the GSE39582 and GSE117606 databases, and 424 genes upregulated in the early stage of colorectal adenocarcinoma were screened. Advanced-stage colorectal cancer: Data were obtained from the TCGA-COAD and TCGA-READ databases, and 6998 genes upregulated in the advanced stage of colorectal adenocarcinoma were screened. Figure 5 BC).

[0059] Ultimately, 46 genes that showed consistent upregulation at all stages of colorectal cancer were identified, and these genes were significantly elevated even in the precancerous lesion stage. Figure 5 DF).

[0060] To identify serum biomarkers for the diagnosis of colorectal adenoma and colorectal cancer, a cross-analysis was performed on upregulated genes and 4,741 genes encoding extracellular secretory proteins. Figure 5 G). Thirteen genes persistently upregulated during the progression from adenoma to advanced adenocarcinoma were identified: BACE2, AXIN2, MET, CD44, LIPG, TGFBI, TCN1, EPHB2, PRKDC, TNS4, CXCL1, MMP1, and MMP3. To identify biomarkers with colorectal cancer-specific elevations, pan-cancer analysis of these 13 candidate genes was performed using Cancer Genome Atlas (TCGA) data. Among them, AXIN2 and EPHB2 showed significantly higher expression levels in colorectal cancer than in most other malignancies and normal tissues. Figure 6 ).

[0061] To further evaluate its ability to distinguish CRC from benign lesions, the mRNA expression profiles of inflammatory bowel disease (IBD) in the GSE4183 dataset were analyzed. Compared with normal tissues, AXIN2 expression was decreased in IBD tissues, while EPHB2 expression remained unchanged in IBD tissues. Figure 7(A) This indicates that AXIN2 and EPHB2 have differential specificity for CRC. To further investigate the expression levels of AXIN2 and EPHB2 in inflammatory bowel disease tissues, including ulcerative colitis and Crohn's disease, the dataset GSE222070 ( Figure 7 B). The analysis results showed that there were no significant differences in AXIN2 and EPHB2 expression between ulcerative colitis (UC) and Crohn's disease (CD) tissues compared with normal tissues. Furthermore, the analysis of the GSE87466 dataset also showed no abnormal increases in AXIN2 and EPHB2 expression between ulcerative colitis tissues and normal tissues. Figure 7 C). These findings highlight the specificity of AXIN2 and EPHB2 for CRC, making them promising organ-specific serum diagnostic biomarkers.

[0062] Single-cell RNA sequencing analysis revealed the enriched expression of AXIN2 and EPHB2 in malignant epithelial cells of colorectal cancer: To elucidate the cellular origin of AXIN2 and EPHB2 in colorectal cancer (CRC) tissues, the single-cell RNA sequencing dataset HRA000201 was analyzed. The results showed that the expression of both AXIN2 and EPHB2 was mainly enriched in epithelial cells, and both were significantly upregulated after malignant transformation. Figure 8 Specifically, 48.6% of cancer cells expressed AXIN2, while the expression rate for all other cell types was only 2.1%; 53.8% of cancer cells expressed EPHB2, while the expression rate for all other cell types was only 4.1%. This cancer cell-specific enrichment was validated in another independent dataset. In the GSE132465 dataset, 35.2% of CRC cells expressed AXIN2, while the expression rate for other cell types was only 1.2%; 48.5% of CRC cells expressed AXIN2, while the expression rate for other cell types was only 1.9% (AB). Figure 8 C).

[0063] In summary, these results indicate that the upregulation of AXIN2 and EPHB2 in colorectal cancer mainly originates from transformed epithelial cells, supporting their potential application value as markers of tumor progression.

[0064] Validating the expression patterns of AXIN2 and EPHB2 in public databases: To evaluate the practicality of AXIN2 and EPHB2 as early warning biomarkers for colorectal cancer, their transcriptional abundance at different stages of colorectal cancer was analyzed. Analysis of two independent datasets, GSE41657 and GSE117606, showed that the expression of AXIN2 and EPHB2 was significantly increased in both early-stage CRC and advanced-stage CRC compared to normal controls. Notably, this increase was already observed in the colorectal adenoma stage (a precancerous lesion). Figure 9 These findings suggest that high expression of AXIN2 and EPHB2 can serve as detectable early indicators in precancerous lesions.

[0065] To determine the specific upregulation of AXIN2 and EPHB2 in colorectal cancer, immunohistochemical (IHC) data were retrieved from the Human Proteome Atlas (HPA) database. Tissue microarrays, including colorectal cancer specimens and twelve other tumor solids—pancreatic cancer, gastric cancer, cervical cancer, cholangiocarcinoma, ovarian cancer, breast cancer, prostate cancer, head and neck cancer, carcinoid tumor, renal cell carcinoma, urothelial carcinoma, and lymphoma—were evaluated to assess AXIN2 and EPHB2 expression, respectively. The AXIN2 immunohistochemical antibody was identified as CAB012283, and the EPHB2 immunohistochemical antibody as CAB013647. Results showed that, compared to normal mucosa, the levels of AXIN2 and EPHB2 proteins were significantly elevated in colonic and rectal adenocarcinomas, and this elevation was significantly greater than in other tumor types. Figure 10 , Figure 11 Furthermore, consistent with single-cell transcriptome data, AXIN2 and EPHB2 proteins are primarily located in the cytoplasm and cell membrane of colorectal cancer cells.

[0066] Overall, these data establish AXIN2 and EPHB2 as specific biomarkers for colorectal cancer. Both biomarkers originate from transformed colorectal epithelial cells, highlighting their potential as biomarkers for early detection of colorectal cancer.

[0067] Clinical validation of the diagnostic efficacy of serum biomarkers AXIN2 and EPHB2: To systematically evaluate the diagnostic value of circulating AXIN2 and EPHB2 in precancerous lesions of colorectal cancer, this study separated 48 samples from the aforementioned 66 cases, including 13 histologically confirmed cases of colorectal adenocarcinoma, 16 cases of adenoma, and 19 colonoscopy-negative healthy controls. Serum AXIN2 and EPHB2 concentrations were quantitatively detected using enzyme-linked immunosorbent assay (ELISA).

[0068] The results showed that AXIN2 levels continued to rise with the progression of colorectal tumors compared to the normal control group. The mean AXIN2 concentration in the healthy control group was 23.594 ng / mL (95% CI: 19.000–28.188); in the adenoma group, it significantly increased to 58.729 ng / mL (95% CI: 35.355–82.103); and in the adenocarcinoma group, it remained significantly elevated, with a mean concentration of 50.990 ng / mL (95% CI: 36.876–65.105). Similarly, EPHB2 levels also continued to rise. The mean EPHB2 concentration in the healthy control group was 0.0368 ng / mL (95% CI: 0–0.080); in the adenoma group, it significantly increased to 0.383 ng / mL (95% CI: 0.263–0.503); and in the adenocarcinoma group, it remained significantly elevated, with a mean concentration of 0.938 ng / mL (95% CI: 0.440–1.435). Figure 12 AB).

[0069] To evaluate the sensitivity and specificity of AXIN2 and EPHB2 in non-invasive diagnosis, ROC curves were plotted. Serum AXIN2 showed an AUC of 0.855 (95% CI: 0.722-0.988) for differentiating adenomas from healthy controls and 0.87 (95% CI: 0.732-1.000) for differentiating adenomas from healthy controls. Serum EPHB2 showed an AUC of 0.880 (95% CI: 0.759-1.000) for differentiating adenomas from healthy controls and 0.945 (95% CI: 0.853-1.000) for differentiating adenomas from healthy controls. The combined use of serum AXIN2 and EPHB2 showed an AUC as high as 0.987 (95% CI: 0.962-1.000) for differentiating adenomas from healthy controls and 0.996 (95% CI: 0.985-1.000) for differentiating adenomas from healthy controls. Figure 12 CD). The above results confirm that AXIN2 and EPHB2 levels are significantly elevated in the early stages of CRC. The combined measurement of AXIN2 and EPHB2 has high sensitivity and specificity, and can accurately identify adenomas and adenocarcinomas. It has the potential to serve as a primary screening serological marker and provides a reliable basis for risk stratification before comprehensive endoscopy.

[0070] Clinical validation of the diagnostic efficacy of AXIN2 and EPHB2 in differentiating colorectal cancer from benign colonic lesions using serum samples: To evaluate the diagnostic efficacy of AXIN2 and EPHB2 in differentiating colorectal inflammatory lesions, serum samples were obtained from 18 patients with colorectal inflammatory lesions (CIL). The mean plasma AXIN2 concentration in these patients was 22.135 ng / ml (95% CI: 14.347–29.924), and the EPHB2 concentration was 0.087 ng / ml (95% CI: 0–0.174). In comparison, the mean plasma AXIN2 concentration in patients with colorectal tumor lesions (including colorectal adenomas and colorectal cancer) was 55.260 ng / ml (95% CI: 41.651–68.868), and the EPHB2 concentration was 0.632 ng / ml (95% CI: 0.392–0.871). The AUC value for AXIN2 in differentiating between patients with colorectal inflammatory lesions (CIL) and colorectal tumor lesions (CTL) was 0.843 (95% CI: 0.733–0.953); the AUC value for EPHB2 in differentiating between patients with colorectal inflammatory lesions and colorectal tumor lesions was 0.86 (95% CI: 0.752–0.968). The AUC value for AXIN2 combined with EPHB2 in differentiating patients with inflammatory colorectal lesions from those with colorectal neoplasia was 0.971 (95% CI: 0.934-1). Figure 13 ROC curve analysis demonstrated the diagnostic value of plasma AXIN2 combined with EPHB2 in differentiating these conditions. The results showed that plasma AXIN2 combined with EPHB2 can effectively differentiate between colorectal neoplastic diseases and inflammatory colorectal lesions, highlighting its potential as a diagnostic biomarker.

[0071] Bioinformatics Exploration of the AXIN2 and EPHB2-Mediated Colorectal Cancer Promotion Mechanism: To further elucidate the roles and mechanisms of AXIN2 and EPHB2 in the development of colorectal cancer (CRC), the GSE117606 dataset was queried. In the GSE117606 dataset, 65 normal colorectal tissue samples were divided into a high-expression group (N-AXIN2) based on the average AXIN2 mRNA expression level. high (n=28) and low expression group (N-AXIN2) low (n=37). Similarly, 133 colorectal cancer tissue samples (including adenoma, early and late colorectal cancer tissues) were divided into a high-expression group (C-AXIN2). high (n=87) and low expression group (C-AXIN2)low (n=46). Subsequently, N-AXIN2 low Group and C-AXIN2 high A comparative analysis was performed on groups (representing cancers associated with high AXIN2 expression). This was compared with N-AXIN2. low Compared to the previous group, C-AXIN2 high The mRNA expression level of AXIN2 was significantly higher in the group (P<0.001). Figure 14 A). Differential expression analysis showed that in C-AXIN2 high In the group, with N-AXIN2 low Compared to the previous group, 574 genes were upregulated and 827 genes were downregulated. Figure 14 These differentially expressed genes may provide insights into the mechanisms of AXIN2-related carcinogenesis. Proteins typically exert their biological functions through physical interactions. To characterize the AXIN2 interactome, a protein-protein interaction (PPI) network was constructed using the STRING database (https: / / string-db.org / ). This network contains 201 nodes and 5856 edges, interacting with 200 partner proteins centered on AXIN2. In this network, AXIN2 showed significant connectivity with key nodes (including AXIN1, GSK3B, APC, CSNK1A1, and CTNNB1), with an average node degree of 58.3. To identify components in the AXIN2 interactome that may promote tumorigenesis, the network was subjected to intersection analysis with differential expression profiles. Specifically, C-AXIN2 was compared. high and N-AXIN2 low The group retains the data that is present in both the AXIN2 PPI network and the CAXIN2 network. high Genes significantly upregulated in the cohort. This meta-analysis yielded 27 overlapping genes, which are candidate drivers of AXIN2-mediated tumor biology. Figure 14 D). These 27 genes are APCDD1, ASCL2, AXIN2, BMP4, CCND1, CD44, CDK6, CXXC5, EPHB2, ID1, LEF1, LFNG, LGR5, LGR6, MMP7, MSX1, MSX2, MYC, NKD1, NKD2, OLFM4, PROM1, RNF43, SOX9, TCF7, TP53, and ZNRF3.

[0072] To clarify the signaling pathways and related mechanisms by which AXIN2 functions, enrichment analyses were performed on these 27 genes using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). KEGG analysis showed that these genes were enriched in processes related to the pathogenesis of various tumors, including colorectal cancer, the focus of this study. This indicates that AXIN2 is involved in fundamental biological mechanisms shared by multiple tumor types. Since proliferation is a key characteristic of tumor cells, cell cycle and proliferation-related signaling pathways (Wnt, Hippo, and TGF-β) were identified among the top 30 biological processes enriched in the KEGG analysis. Figure 14 E). These findings suggest that AXIN2 may participate in cell proliferation and apoptosis by regulating the above-mentioned signaling pathways, with the Wnt signaling pathway showing the most significant enrichment.

[0073] GO analysis showed that the Wnt signaling pathway was the most significantly enriched item. Figure 14 F). AXIN2 may play an important role in regulating the stability of β-catenin in the Wnt signaling pathway. These results suggest that AXIN2 may promote excessive cell proliferation through the Wnt signaling pathway, thereby driving the development of colorectal cancer.

[0074] To further explore the molecular mechanism by which EPHB2 promotes the progression of precancerous lesions and colorectal cancer (CRC), the expression and function of EPHB2 were analyzed using the GSE117606 dataset. Sixty-five normal colorectal tissue samples were divided into a high-expression group (N-EPHB2) based on the average mRNA expression level of EPHB2. high (n=35) and low expression group (N-EPHB2) low (n=30). Meanwhile, 133 colorectal lesion samples (including adenoma, early colorectal cancer, and late colorectal cancer tissue) were divided into a high-expression group (C-EPHB2). high (n=70) and low expression group (C-EPHB2) low (n=63). Then, N-EPHB2 was analyzed. low Group and C-EPHB2 high A comparative analysis was conducted in the group. The results showed that N-EPHB2 low The EPHB2 mRNA expression level in the group was significantly lower than that in the C-EPHB2 group. high Group (P<0.05) Figure 15 A). Based on this, differential gene expression analysis was performed, identifying a total of 648 upregulated genes and 975 downregulated genes (A). Figure 15 These differentially expressed genes may include key genes that interact with EPHB2 and are involved in the occurrence and development of colorectal adenomas and adenocarcinomas.

[0075] A protein-protein interaction network was constructed using the STRING database (https: / / string-db.org / ). This network contains 201 nodes and 7212 edges, with EPHB2 as the core, interacting with its 200 ligand proteins. In this network, EPHB2 exhibits significant connectivity with key nodes such as L1CAM, EFNA3, and EFNA2, with an average node degree of 71.8.

[0076] To identify key components in the EPHB2 interactome that may be involved in tumorigenesis, this network was cross-analyzed with differential expression profiles. Specifically, we compared the C-EPHB2 high-expression group with the N-EPHB2 low-expression group, screening for genes that co-exist in the EPHB2 protein-protein interaction network and are significantly upregulated in the C-EPHB2 high-expression cohort. This integrated analysis identified 20 overlapping genes, which may be EPHB2-mediated drivers of tumor biology. Figure 15 D). To elucidate the signaling pathways underlying the mechanism of action of EPHB2, KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) enrichment analyses were performed on these 20 genes. KEGG analysis showed that they were enriched in processes related to multiple tumor pathogenesis mechanisms, including colorectal cancer, which is the focus of this study. This indicates that EPHB2 is involved in fundamental biological mechanisms shared by multiple tumor types. Given that proliferation is a key characteristic of tumor cells, among the top 30 biological processes enriched by KEGG analysis, we identified cell cycle and proliferation-related signaling pathways (Wnt, PI3K / AKT, and MAPK) (…). Figure 15 E). These findings suggest that EPHB2 may participate in cell proliferation by regulating the aforementioned signaling pathways, with the Wnt signaling pathway showing the most significant enrichment.

[0077] GO analysis showed that the ephrin receptor signaling pathway was the most enriched term. Figure 15 F). EPHB2 encodes a transmembrane glycoprotein receptor tyrosine kinase belonging to the Eph family. When it binds to ephrin-B1 / B2 on the surface of adjacent cells, it initiates downstream signaling to regulate cell migration, proliferation, and differentiation. These results suggest that EPHB2 may promote excessive cell proliferation and thus drive colorectal cancer development through ephrin-mediated activation of signaling pathways such as Wnt.

[0078] This invention provides the use of reagents for detecting AXIN2 and / or EPHB2 levels in the preparation of products for colorectal cancer and its progression.

[0079] The reagents are selected from probes that specifically recognize the AXIN2 and / or EPHB2 genes, primers that specifically amplify the AXIN2 and / or EPHB2 genes, or binding agents that specifically bind to the proteins encoded by the AXIN2 and / or EPHB2 genes.

[0080] In some embodiments, a probe is a molecule capable of binding to a specific sequence, subsequence, or other portion of another molecule. Unless otherwise specified, a probe typically refers to a polynucleotide probe capable of binding to another polynucleotide (often called a target polynucleotide) through complementary base pairing. Depending on the stringency of the hybridization conditions, the probe can bind to a target polynucleotide that lacks complete sequence complementarity with the probe. Probes can be labeled directly or indirectly, including primers. Hybridization methods include, but are not limited to, solution-phase, solid-phase, mixed-phase, or in situ hybridization assays.

[0081] In some implementations, the primer refers to a short nucleic acid sequence, which is a nucleic acid sequence having a short free 3' terminal hydroxyl group (free 3' hydroxyl), and can form a base pair with the complementary template and act as the starting point for replication template.

[0082] The primers or probes are labeled with a labeling substance.

[0083] In some embodiments, a label refers to a composition capable of generating a detectable signal indicating the presence of a target polynucleotide in a sample. Suitable labels include, but are not limited to, radioisotopes, nucleotide chromophores, enzymes, substrates, fluorescent molecules, chemiluminescent components, magnetic particles, and bioluminescent components. Therefore, a label is any composition detectable by a device or method, including but not limited to spectroscopic, photochemical, biochemical, immunochemical, electrochemical, optical, chemical detection devices, or any other suitable device. In some embodiments, a label can be visually detected without the aid of a device. The term "label" is used to refer to any chemical group or portion having a detectable physical property, or any compound capable of causing a chemical group or portion to exhibit a detectable physical property, such as an enzyme that catalyzes the conversion of a substrate into a detectable product. Labels also encompass compounds that inhibit the expression of a particular physical property. A label can also be a compound that is a member of a binding pair, the other member of which has a detectable physical property.

[0084] Among them, radioactive isotopes include but are not limited to 3 H, 14 C 35 S, 125 I, 131 I.

[0085] Enzymes include, but are not limited to, horseradish peroxidase, β-galactosidase, luciferase, alkaline phosphatase, and acetylcholinesterase.

[0086] Fluorescent molecules include, but are not limited to, FITC, rhodamine, and lanthanide phosphors.

[0087] The products include chips, test strips, reagent kits, or nucleic acid membrane strips.

[0088] In some implementations, a kit refers to a set of components provided in the context of a system for sequencing and / or isolating nucleotide sequences and / or diagnosing a subject with a disease based on the presence, absence, and / or amount of expressed nucleotide sequences from a sample or cell.

[0089] The kit includes a gene detection kit and a protein detection kit. The gene detection kit includes reagents or chips for detecting the transcriptional level of the AXIN2 and / or EPHB2 genes, and the protein detection kit includes reagents or chips for detecting the expression level of the AXIN2 and / or EPHB2 proteins.

[0090] In some embodiments, the kit also includes one or more substances from the group consisting of: containers, positive controls, negative controls, buffers, preservatives, and protein stabilizers.

[0091] The kit may also include an instruction manual, which explains how to use the kit for testing and how to use the test results to assess tumor development and select treatment options.

[0092] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0094] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0095] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0096] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0097] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0098] The computer device provided by the present invention has been described in detail above. For those skilled in the art, there will be changes in the specific implementation and application scope based on the ideas of the embodiments of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method of predicting colorectal cancer and its progression, characterized by, The method is completed by a computer, and the method comprises: obtaining gene expression data of a sample to be tested; extracting expression data of target genes in the gene expression data, the target genes comprising AXIN2 and / or EPHB2; performing classification prediction based on the expression data of the target genes to obtain a classification result of whether the sample to be tested has colorectal cancer and progression thereof; if the expression amount of the AXIN2 and / or EPHB2 is high, a classification result that the sample to be tested has colorectal cancer / serious progression is obtained; if the expression amount of the AXIN2 and / or EPHB2 is low, a classification result that the sample to be tested does not have colorectal cancer / less serious progression is obtained.

2. The method of claim 1, wherein, The target genes further comprise one or more of BACE2, MET, CD44, LIPG, TGFBI, TCN1, PRKDC, TNS4, CXCL1, MMP1 and MMP3.

3. A prediction system for colorectal precancer / cancer, characterized by, The system comprises: an obtaining unit configured to obtain gene expression data of a sample to be tested; an extracting unit configured to extract expression data of target genes in the gene expression data, the target genes comprising AXIN2 and / or EPHB2; a prediction unit configured to perform classification prediction based on the expression data of the target genes to obtain a classification result of whether the sample to be tested has colorectal cancer and progression thereof; if the expression amount of the AXIN2 and / or EPHB2 is high, a classification result that the sample to be tested has colorectal cancer / serious progression is obtained; if the expression amount of the AXIN2 and / or EPHB2 is low, a classification result that the sample to be tested does not have colorectal cancer / less serious progression is obtained.

4. A computer device, comprising: The device comprises: a memory configured to store program instructions; a processor configured to invoke the program instructions, when the program instructions are executed, to perform the prediction method of any one of claims 1-2.

5. A computer readable storage medium, characterized in that, A computer program is stored thereon, and the computer program is executed by a processor to implement the steps of the method of any one of claims 1-2.

6. A computer program product comprising a computer program, characterized in that, The computer program is executed by a processor to implement the steps of the method of any one of claims 1-2.

7. Use of a reagent for detecting the level of AXIN2 and / or EPHB2 in the preparation of a product for diagnosing colorectal cancer and progression thereof; Preferably, the reagent is selected from a probe specifically recognizing the AXIN2 and / or EPHB2 gene, a primer specifically amplifying the AXIN2 and / or EPHB2 gene, or a binding agent specifically binding to a protein encoded by the AXIN2 and / or EPHB2 gene.

8. Use according to claim 7, characterized in that, The reagent further comprises a detectable label; Preferably, the detectable label comprises a radioisotope, a nucleotide chromophore, an enzyme, a substrate, a fluorescent molecule, a chemiluminescent moiety, a magnetic particle, a bioluminescent moiety.

9. A product for diagnosing colorectal cancer and its progression, characterized in that, The product comprises a reagent for detecting the level of AXIN2 and / or EPHB2; Preferably, the product comprises a chip, a test paper, a kit or a nucleic acid membrane strip; Preferably, the chip comprises a gene chip or a protein chip; Preferably, the kit further comprises a buffer; Preferably, the kit further comprises an instruction manual. 10.A system for computer-aided screening of drugs based on AXIN2 and / or EPHB2, the system comprising: an acquisition unit configured to acquire gene expression data of a sample; an extraction unit configured to extract expression data of target genes / proteins in the gene expression data, the target genes comprising AXIN2 and / or EPHB2; a screening unit configured to obtain, by computer-aided screening, a substance that inhibits the level of AXIN2 and / or EPHB2 genes as a candidate drug for treating colorectal cancer.

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