Use of marker sema6b in preparation of products for diagnosis and prognosis prediction of colorectal cancer

Abstract

The application belongs to the field of biomedicine, and particularly relates to the use of a marker SEMA6B in the preparation of a colorectal cancer diagnosis and prognosis prediction product. Specifically, the application provides a reagent for detecting the expression amount and methylation level of SEMA6B or a promoter thereof in the preparation of a product for diagnosing colorectal cancer and predicting the prognosis of a colorectal cancer patient; and the use of a SEMA6B inhibitor in the preparation of a product for treating colorectal cancer.

Description

Technical Field

[0001] This invention belongs to the field of biomedicine, specifically relating to the use of the biomarker SEMA6B in the preparation of products for colorectal cancer diagnosis and prognosis prediction. Background Technology

[0002] Colorectal cancer (CRC) is one of the most common malignant tumors. It is a common malignant tumor of the gastrointestinal tract. Early symptoms are not obvious, but as the tumor grows, symptoms appear such as changes in bowel habits, rectal bleeding, diarrhea, alternating diarrhea and constipation, and localized abdominal pain. In advanced stages, systemic symptoms such as anemia and weight loss may occur. Its incidence and mortality rates are second only to stomach cancer, esophageal cancer, and primary liver cancer among malignant tumors of the digestive system.

[0003] In recent years, tumor immunotherapy has developed rapidly. Although immune checkpoint inhibitors (ICIs) have achieved good treatment results for CRC patients with high frequency microsatellite instability (MSI-H) and mismatch repair deficiency (dMMR), most patients with low frequency microsatellite instability (pMMR) and microsatellite stable (MSS) subtypes cannot benefit from immunotherapy. Therefore, it is necessary to find effective biomarkers to predict patients' sensitivity to immunotherapy.

[0004] Semaphorin 6B (SEMA6B) is a member of the axon guidance family and has been shown to induce and inhibit tumor progression. However, the role of SEMA6B in colorectal cancer remains unclear. Summary of the Invention

[0005] This study aims to elucidate the clinical significance of SEMA6B expression in predicting the prognosis of colorectal cancer and to investigate its potential molecular mechanisms, revealing the impact of SEMA6B molecules on the immune microenvironment.

[0006] Indicator combination

[0007] On the one hand, the present invention provides a combination of indicators for predicting the prognosis of colorectal cancer patients, wherein the combination of indicators is selected from any one of the following groups:

[0008] 1) SEMA6B expression level, M stage, and T stage;

[0009] 2) SEMA6B expression level, M stage, N stage, and T stage.

[0010] The "T staging," "M staging," and "N staging" mentioned in this invention refer to the staging in the TNM staging system. "T staging" refers to the primary tumor (T) staging, with specific results including: Tx: Primary tumor cannot be assessed; T0: No evidence of primary tumor; T1: Tumor invades the submucosa; T2: Tumor invades the muscularis propria; T3: Tumor penetrates the muscularis propria to reach the subserosa, or invades the pararectal tissues not covered by peritoneum; T4: Tumor has penetrated the peritoneum or directly invaded other organs. "N staging" refers to lymph node metastasis (N) staging, with specific results including: Nx: Regional lymph nodes cannot be assessed; N0: No regional lymph node metastasis; N1: 1–3 regional lymph node metastases; N2: ≥4 regional lymph node metastases. "M staging" refers to distant metastasis (M) staging, with specific results including: M0: No distant metastasis; M1: Distant metastasis present.

[0011] Diagnostic and prognostic applications

[0012] On the other hand, the present invention provides the application of a reagent for detecting SEMA6B expression levels in the preparation of products for diagnosing colorectal cancer; wherein SEMA6B is highly expressed in colorectal cancer patients.

[0013] Preferably, the colorectal cancer includes colon cancer and rectal cancer.

[0014] The "colorectal cancer" mentioned in this invention includes colon cancer and rectal cancer, also known as colorectal cancer, which can be abbreviated as CRC. In this invention, "colorectal cancer", "CRC" and "colorectal cancer" have the same meaning and can be used interchangeably.

[0015] On the other hand, the present invention provides a reagent for detecting SEMA6B expression and the application of the aforementioned combination of indicators in the preparation of products for predicting the prognosis of colorectal cancer patients;

[0016] The SEMA6B is highly expressed in patients with poor prognosis.

[0017] Preferably, the colorectal cancer includes colon cancer and rectal cancer.

[0018] Preferably, the prognosis includes venous infiltration, T stage, MSI, KRAS mutation, and CMS.

[0019] In this invention, "venous invasion" and "venous infiltration" have the same meaning and can be used interchangeably.

[0020] The "MSI" mentioned in this invention refers to "microsatellite instability." Microsatellites, also known as simple repetitive sequences, are small, repetitive sequences of nucleotides present in the genome. Each repetitive unit typically consists of 1 to 6 nucleotides, and the number of repetitions does not exceed 60. They are highly mutable. During DNA replication, especially in microsatellites, base mismatches and other errors may occur. These errors accumulate and are passed down through generations, eventually leading to gene mutations and ultimately, cell carcinogenesis. This insertion or deletion of simple repetitive sequences during DNA replication is called microsatellite instability.

[0021] The “CMS” mentioned in this invention refers to the “Consensus of Molecular Subtypes (CMS)”. The consensus molecular subtype aims to distinguish the intrinsic heterogeneity of patients at the gene expression level and divides CRC patients into 4 subtypes: CMS1 (MSI immune type), CMS2 (classical type), CMS3 (metabolic type) and CMS4 (mesenchymal type).

[0022] Preferably, the prognostic indicators include overall survival rate (OS), 5-year survival rate, 3-year survival rate, progression-free survival (PFS), 3-year PFS, 5-year PFS, time to progress (TTP), disease-free survival (DFS), time to treatment failure (TTF), objective response rate (ORR), response rate (RR), complete response rate (CR), and partial response rate (PR).

[0023] Specifically, this invention provides the application of reagents for detecting SEMA6B expression levels in predicting overall survival, 5-year survival, disease-free survival, and progression-free survival; the application of detecting SEMA6B expression levels + M stage + N stage in predicting 3-year progression-free survival and 5-year progression-free survival; and the application of detecting SEMA6B expression levels + M stage + N stage + T stage in predicting overall survival and progression-free survival.

[0024] Preferably, the product also includes reagents for collecting and / or processing samples.

[0025] Preferably, the samples include: tissue, blood, urine, saliva, semen, breast milk, cerebrospinal fluid, tears, nasal epithelial cells, sputum, mucus, lymph, cytokine, ascites, pleural effusion, amniotic fluid, bladder irrigation fluid, and bronchoalveolar lavage fluid.

[0026] Preferably, the sample is tissue.

[0027] Preferably, the expression level includes protein expression level and / or mRNA expression level.

[0028] Preferably, the reagents for detecting protein expression levels include those used in the following methods: Western blotting, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), sandwich assay, immunohistochemical staining, mass spectrometry, immunoprecipitation analysis, complement fixation analysis, flow cytometry, fluorescence edge separation technology, and protein chip method.

[0029] Preferably, the reagent for detecting protein expression levels includes an antibody that specifically binds to SEMA6B.

[0030] Preferably, the specifically binding antibody includes monoclonal antibodies and polyclonal antibodies. The specific antibody includes complete antibody molecules, any fragment or modification of the antibody, such as chimeric antibodies, scFv, Fab, F(ab')2, Fv, etc., as long as the fragment retains its binding ability to the aforementioned markers. The preparation of antibodies for protein-level applications is well known to those skilled in the art, and the present invention can use any method to prepare the antibody.

[0031] Preferably, the specific antibody can be labeled with a radioactive isotope, enzyme, fluorescent molecule, or chemiluminescent reagent.

[0032] Preferably, the detection reagent for mRNA expression level includes reagents used in the following methods: PCR-based detection method, Southern hybridization method, Northern hybridization method, dot hybridization method, fluorescence in situ hybridization method, DNA microarray method, ASO method, and high-throughput sequencing platform method.

[0033] Preferably, the reagent for detecting mRNA expression levels includes specific primers and / or probes.

[0034] Preferably, the primers and / or probes can be DNA, RNA, DNA-RNA chimeras, RNA, or other derivatives. The length of the probe is not limited; any length is acceptable as long as specific hybridization and binding to the target nucleotide sequence are achieved. The probe length can be as short as 25, 20, 15, 13, or 10 base pairs. Similarly, the probe length can be as long as 60, 80, 100, 150, 300 base pairs or longer, even the entire gene. Since different probe lengths have different effects on hybridization efficiency and signal specificity, the probe length is typically at least 14 base pairs, and generally does not exceed 30 base pairs. The optimal length for complementarity with the target nucleotide sequence is 15-25 base pairs. The probe's own complementary sequence should preferably be less than 4 base pairs to avoid affecting hybridization efficiency.

[0035] Preferably, the probe includes hybridization probes and hydrolysis probes (Taqman probes).

[0036] On the other hand, the present invention provides the application of reagents for detecting the methylation level of SEMA6B or its promoter in the preparation of products for diagnosing colorectal cancer;

[0037] The SEMA6B methylation level was reduced in the patients.

[0038] Preferably, the reagents used for detecting the degree of methylation are reagents used in one or more of the following methods, wherein the methylation detection methods include: pyrosequencing, bisulfite sequencing, methylation-specific PCR (MS-PCR), bisulfite-specific PCR, methylation-sensitive restriction endonuclease-PCR / Southern assay, combined bisulfite restriction enzyme analysis (COBRA), digital polymerase chain reaction, restriction marker genome scanning, single nucleotide primer extension, CpG island microarray, single nucleotide primer extension SNUPE, and methylation profiling.

[0039] Therapeutic applications

[0040] On the other hand, the present invention provides the application of SEMA6B inhibitors in the treatment of colorectal cancer.

[0041] Preferably, the SEMA6B inhibitor includes drugs that specifically target SEMA6B, specific antibodies, siRNA, or reagents that reduce the expression level of SEMA6B through gene editing technology.

[0042] Preferably, the drug includes, but is not limited to, chemical drugs.

[0043] Preferably, the specific antibody includes a complete antibody molecule, any fragment of an antibody, or a modification thereof, such as a chimeric antibody, scFv, Fab, F(ab')2, Fv, etc., as long as the fragment retains its ability to bind to the aforementioned marker.

[0044] Preferably, the gene editing technology includes CRISPR technology, ZFN technology, and TALEN technology.

[0045] Preferably, the inhibitor of SEMA6B is siRNA;

[0046] More preferably, the siRNA sequence of the SEMA6B is shown in SEQ ID NO.:1 and SEQ ID NO.:2.

[0047] Preferably, the treatment includes inhibiting the expression of immunosuppressive molecules, inhibiting cell proliferation, inhibiting cell migration, inhibiting cell invasion, and inhibiting the formation of an immunosuppressive microenvironment.

[0048] Preferably, the immunosuppressive molecules include EDNRB, TGFB2, IL1B, IL6ST, BTLA, PD-L1, LGALS1, ICAM1, and HAVCR2.

[0049] Diagnostic and prognostic reagent kits

[0050] On the other hand, the present invention provides a kit for diagnosing colorectal cancer and predicting the prognosis of colorectal cancer patients, the kit comprising the reagents used for detecting SEMA6B expression level and / or methylation level.

[0051] Preferably, the kit may further include any one or more of the following: mRNA expression level auxiliary detection reagents, protein expression level auxiliary detection reagents, mRNA expression level auxiliary detection instruments, and protein expression level auxiliary detection instruments.

[0052] Preferably, the mRNA expression level auxiliary detection reagent includes, but is not limited to: reaction reagents that visualize the amplicon corresponding to the primer, such as reagents that visualize the amplicon by agarose gel electrophoresis, enzyme-linked gel electrophoresis, chemiluminescence, in situ hybridization, fluorescence detection, etc.; RNA extraction reagents; reverse transcription reagents; cDNA amplification reagents; standards used to prepare standard curves; positive controls; and negative controls.

[0053] Preferably, the auxiliary reagents for detecting protein expression levels include, but are not limited to: blocking solution, antibody dilution solution, washing buffer, colorimetric stop solution, and standards for preparing standard curves.

[0054] Prognostic system

[0055] On the other hand, the present invention provides a system for predicting the prognosis of colorectal cancer patients, the system including a calculation device for calculating the prognosis based on the detection results of SEMA6B expression level / index combination;

[0056] Preferably, the system includes an input device for inputting the expression level and / or index combination results of the aforementioned SEMA6B.

[0057] Preferably, the system may further include a collection device for collecting information.

[0058] Preferably, the information includes the results of SEMA6B expression level detection, T staging results, M staging results, N staging results, and other clinical demographic information.

[0059] Preferably, the system may further include an output device for outputting results.

[0060] Preferably, the system may further include a detection device for detecting mRNA and / or protein expression levels.

[0061] Preferably, the system further includes an assessment result sending unit, which can send the assessment results of the subject to an information communication terminal device that can be viewed by the patient or medical staff.

[0062] Preferably, the calculation of predicting patient prognosis based on a combination of indicators can be based on... Figure 9 Calculations are performed using the nodal graph shown in Figure A.

[0063] Pharmaceutical Composition

[0064] On the other hand, the present invention provides a pharmaceutical composition for treating colorectal cancer, the pharmaceutical composition comprising an inhibitor of SEMA6B.

[0065] Preferably, the pharmaceutical composition further includes a pharmaceutically acceptable carrier, diluent, or excipient.

[0066] Preferably, the pharmaceutically acceptable carrier, diluent, or excipient includes, but is not limited to, any adjuvant, carrier, excipient, gliding agent, sweetener, diluent, preservative, dye / coloring agent, flavor enhancer, surfactant, wetting agent, dispersant, suspending agent, stabilizer, isotonic agent, solvent, surfactant, or emulsifier that has been approved by the U.S. Food and Drug Administration or the China Food and Drug Administration for use in humans or livestock.

[0067] Preferably, the pharmaceutical composition can be a tablet, pill, powder, granule, capsule, lozenge, syrup, liquid, emulsion, suspension, controlled release formulation, aerosol, film, injection, intravenous infusion, transdermal absorption formulation, ointment, lotion, adhesive formulation, suppository, pill, nasal preparation, pulmonary preparation, eye drops, etc., or an oral or parenteral preparation.

[0068] method

[0069] On the other hand, the present invention provides a method for diagnosing colorectal cancer, the method comprising determining whether a subject has colorectal cancer based on the expression level or methylation level of SEMA6B.

[0070] On the other hand, the present invention provides a method for predicting the prognosis of colorectal cancer patients, the method comprising predicting patient prognosis based on the expression level of SEMA6B.

[0071] On the other hand, the present invention provides a treatment method for colorectal cancer, the method comprising inhibiting the expression of SEMA6B.

[0072] Preferably, the inhibition is achieved through siRNA technology.

[0073] The implementation of the "method or system" described in this invention may include performing or completing the selected task manually, automatically, or in combination thereof.

[0074] Furthermore, the actual instruments and equipment according to the embodiments of the methods and systems of the present invention can implement multiple selected tasks by means of hardware, by means of software, or by means of firmware or by means of a combination of them using an operating system. Attached Figure Description

[0075] Figure 1 These are the results of SEMA6B differential analysis and ROC curve analysis. A: Expression profile of SEMA6B mRNA in tumor and normal samples from TCGA and GEO colorectal cancer datasets; B: Protein expression level of SEMA6B in colorectal cancer tumor and normal samples; C: ROC curve of SEMA6B mRNA in the GEO dataset for diagnosing colorectal cancer.

[0076] Figure 2This is a graph showing the results of SEMA6B DNA methylation level analysis. A: Differential analysis of SEMA6B methylation in normal and tumor samples in the TCGA colorectal cancer dataset; B: Methylation analysis of SEMA6B at different sites in the TCGA colorectal cancer dataset; C: ROC curve of SEMA6B methylation level for diagnosing colorectal cancer.

[0077] Figure 3 This is a graph showing the results of somatic mutation and SEMA6B mutation status analysis of colorectal cancer samples.

[0078] Figure 4 This is a graph showing the correlation analysis results between SEMA6B expression levels and clinicopathological features of colorectal cancer patients.

[0079] Figure 5 This is a graph showing the relationship between SEMA6B expression levels and prognostic effects in colorectal cancer. A: TCGA dataset, B: GSE39582 dataset.

[0080] Figure 6 This is a graph analyzing the prognostic effects of SEMA6B expression levels in various cancers. A: Breast cancer, B: Esophageal adenocarcinoma, C: Esophageal cell carcinoma, D: Gastric cancer, E: Liver cancer, F: Lung adenocarcinoma, G: Lung squamous cell carcinoma, H: Ovarian cancer.

[0081] Figure 7 This is a graph showing the results of univariate and multivariate Cox regression analyses of SEMA6B in colorectal cancer patients. A: Cox regression analysis of progression-free survival from the TCGA dataset; B: Cox regression analysis of disease-free survival from the GSE17538 dataset.

[0082] Figure 8 This is a graph showing the results of univariate and multivariate Cox regression analyses of SEMA6B in overall survival of colorectal cancer patients. Figure 9 This is a graph showing the validation results of SEMA6B in predicting the prognosis of colorectal cancer. A: Nonograph of 3-year and 5-year progression-free survival prediction for colorectal cancer patients; B: Calibration curve of the nonograph; C: ROC curve predicting overall survival for colorectal cancer patients; D: ROC curve predicting progression-free survival for colorectal cancer patients.

[0083] Figure 10This is a graph showing the results of an analysis of how SEMA6B siRNA knockdown inhibits the malignant biological behavior of colon cancer cells and downregulates the expression of immunosuppressive molecules. A: Expression level of SEMA6B mRNA in different colon cancer cell lines; B: Expression levels of immunosuppressive molecules such as SEMA6B, EDNRB, TGFB2, IL1B, IL6ST, BTLA, PD-L1, 12LGALS1, ICAM1, and HAVCR2 in colon cancer cells after SEMA6B siRNA treatment; C: Proliferative capacity of colon cancer cells after SEMA6B siRNA treatment; D: Migration capacity of colon cancer cells after SEMA6B siRNA treatment; E: Invasive capacity of colon cancer cells after SEMA6B siRNA treatment.

[0084] Figure 11 This is a graph showing the correlation between SEMA6B mRNA expression and immunosuppressive cell infiltration levels in colorectal cancer samples. Detailed Implementation

[0085] The present invention will be further described below with reference to embodiments. The following description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make equivalent modifications to the disclosed technical content to create equivalent embodiments. Any simple modifications or equivalent changes made to the following embodiments based on the technical essence of the present invention without departing from the scope of the invention are all within the protection scope of the present invention.

[0086] Example 1: SEMA6B expression level is upregulated in CRC.

[0087] Data sources and analysis methods

[0088] The data used in this invention include RNA sequencing data from the TCGA colon adenocarcinoma (TCGA-COAD) and TCGA rectal adenocarcinoma (TCGA-READ) cohorts, comprising 638 CRC samples and 51 normal tissue samples downloaded from a public database (https: / / portal.gdc.cancer.gov / ). The downloaded information includes the corresponding clinicopathological characteristics for each patient, including age, sex, race, tumor location, disease type, tumor stage, tumor lymph node metastasis (TNM) classification, venous invasion, lymph node invasion, pretreated CEA level, and survival information. This invention only includes patients with available survival information and expression data.

[0089] Additionally, mRNA expression profiles of 308 adjacent normal tissue samples were obtained from GTEx (https: / / www.gtexportal.org / home / datasets). The TCGA and GTEx data were normalized to TPM format using the R / Bioconductor software package for subsequent comparative analysis, and genes with expression levels ≤0.3 were removed from the expression matrix.

[0090] In this study, six GEO database datasets were downloaded for external validation: GSE41258, GSE44076, GSE37182, GSE20842, GSE83889, and GSE39582, along with survival information. Normalized expression matrices from the GEO databases were directly applied for analysis. Immunohistochemical data from the HPA database (http: / / www.proteinatlas.org / ) were used to detect the protein expression levels of SEMA6B in clinical specimens from cancer patients and normal tissues.

[0091] Experimental results

[0092] Based on RNA sequencing data from the TCGA colorectal cancer dataset and the GTEx project, SEMA6B mRNA expression in CRC tissues (n=638) was significantly higher than that in normal colorectal tissues (n=359; P<0.001).

[0093] In the GEO datasets: GSE41258 (P<0.001), GSE44076 (P<0.001), GSE37182 (P<0.001), GSE20842 (P=0.003), and GSE83889 (P=0.015), the upregulation of SEMA6B mRNA levels in CRC tissues was also verified. Figure 1 A).

[0094] Furthermore, immunohistochemical staining obtained from the HPA database showed that the protein expression level of SEMA6B was consistent with its transcriptional level compared to the protein expression level in normal tissues. Figure 1 B).

[0095] The effectiveness of SEMA6B in diagnosing CRC was validated on the GSE37182 and GSE44076 datasets. The ROC curves are shown below. Figure 1 C.

[0096] Example 2: SEMA6B is regulated by methylation

[0097] Methylation analysis

[0098] To investigate expression regulation related to the SEMA6B expression profile, DNA mutation and methylation analyses were explored using online databases. Specifically, somatic mutation information was determined using the cBioPortal platform (www.cBioPortal.org). Methylation changes of SEMA6B in CRC and adjacent normal tissues were compared using UALCAN (http: / / ualcan.path.uab.edu / index.html) (Chandrashekar et al. 2017) and Wanderer (http: / / maplab.imppc.org / wanderer / , Díez-Villanueva et al. 2015).

[0099] Experimental results

[0100] Further investigation into the role of methylation in regulating SEMA6B expression revealed that, compared to normal samples, the DNA methylation level of SEMA6B in colorectal cancer tissues was significantly downregulated (P<0.001). Figure 2 A). For example Figure 2 As shown in B, the data from the Wanderer web tool were similar (P<0.05; normal n=44, tumor n=400), with most SEMA6B probes in the 450 methylation array showing significant differences between colorectal cancer and normal specimens, and very few SEMA6B mutations or somatic copy number alterations were observed in cancer tissue. Figure 3 ROC analysis showed that the DNA methylation level of the SEMA6B gene could clearly distinguish between tumor tissue and normal tissue. The AUC value predicted by overall SEMA6B gene methylation was 0.951, and the AUC value predicted by promoter methylation was 0.911.

[0101] Example 3: Patients with high SEMA6B expression have poor prognosis

[0102] Survival Analysis

[0103] Kaplan-Meier curves were plotted to compare overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and recurrence-free survival (RFS). These curves were generated using the `survfit` function in the R package `survminer` with the optimal cutoff value for SEMA6B mRNA expression, and a log-rank test was performed to compare differences in survival status. Univariate and multivariate Cox analyses were performed to obtain hazard ratios (HRs) with 95% confidence intervals (CI) and statistical significance; results were illustrated using forest plots in GraphPad Prism 8. A nomogram model for PFS was constructed based on the multivariate Cox regression results. Calibration curves were plotted, and the concordance index (C-index) was calculated to assess the predictive power of the nomogram. Furthermore, the prognostic value of SEMA6B expression in breast, esophageal, gastric, liver, lung, and ovarian cancers was assessed using the Kaplan-Meier plotter (www.kmplot.com) with the optimal cutoff value, and HRs with 95% CI and log-rank P-values ​​were calculated.

[0104] Experimental results

[0105] Continue using the TCGA-CRC dataset to assess the correlation between SEMA6B expression and clinicopathological features in CRC patients. Figure 4 As shown, SEMA6B expression levels were significantly associated with venous invasion, T stage, MSI, KRAS mutation, and CMS. However, SEMA6B expression was not significantly associated with other clinicopathological features, including age, sex, tumor location, lymphatic invasion, M stage, N stage, pathological stage, and patient status.

[0106] To assess the prognostic value of SEMA6B, cancer patients were divided into high and low SEMA6B expression groups based on the optimal cutoff value for SEMA6B levels. Kaplan-Meier survival curve analysis showed that, compared with colorectal cancer patients with low SEMA6B expression, colorectal cancer patients with high SEMA6B expression had shorter overall survival (OS) (P = 0.040), five-year survival (P = 0.042), disease-free survival (DFS) (P = 0.002), and progression-free survival (P < 0.001). Figure 5 A).

[0107] Further validation of the prognostic significance of SEMA6B using another GEO cohort (GSE39582) yielded results consistent with those in the TCGA dataset, showing lower survival rates in the high SEMA6B expression group (OS: P = 0.022; RFS: P = 0.050). Figure 5 B).

[0108] Subsequently, the prognostic potential of SEMA6B in different cancers was analyzed using database analysis. Further investigation revealed that high SEMA6B expression levels were associated with poor overall survival (OS) in lung adenocarcinoma and squamous cell carcinoma. Figure 6 SEMA6B expression has a smaller prognostic impact on other types of cancer.

[0109] Example 4: CRC prognostic model including SEMA6B

[0110] Experimental results

[0111] Furthermore, to explore the clinical prognostic significance of SEMA6B in colorectal cancer, Cox regression analysis was performed to determine PFS and OS. Univariate Cox regression analysis showed that in CRC patients derived from the TCGA dataset, SEMA6B, venous invasion, N stage, pretreatment CEA, T stage, and M stage were significantly associated with PFS (P<0.05). Figure 7 A, above figure). Meanwhile, multivariate Cox regression analysis showed that SEMA6B, T stage, and M stage were independent prognostic factors for PFS in CRC patients (P<0.05). Figure 7 A, Figure below). For OS, univariate Cox regression analysis showed that SEMA6B, age, venous invasion, pretreatment CEA, T stage, N stage, and M stage were statistically significant; however, in the multivariate analysis of OS, SEMA6B expression was not an independent prognostic factor (P>0.05). Figure 8 Furthermore, in the GSE17538 validated colorectal cancer dataset, SEMA6B was an independent prognostic factor for disease-free survival (DFS) in multivariate Cox regression analysis (P<0.05). Figure 7 B).

[0112] Based on the results of multivariate Cox regression analysis, independent prognostic features of SEMA 6B, M stage, and N stage were incorporated to establish a nomogram model. Figure 9 A) predicts the three-year and five-year progression-free survival (PFS) probability for each patient in clinical practice. The C-index of this model is 0.72 (95% CI, 0.70–0.75). Furthermore, the calibration curve ( Figure 9 B) shows that the nomogram model's predicted three-year and five-year PFS rates are highly consistent with actual observations. These results indicate that the nomogram model has good prognostic ability for predicting PFS.

[0113] Furthermore, ROC analysis showed that the predictive model, which included pathological M stage, N stage, T stage, and SEMA6B expression, improved the predicted overall survival (OS) from 0.639 to 0.759 and the progression-free survival (PFS) from 0.641 to 0.719. Figure 9 C and 9D) indicate that SEMA6B has an additive predictive value compared to known prognostic factors.

[0114] Example 4: Knocking out SEMA6B can inhibit cell proliferation, migration, and invasion.

[0115] Experimental methods

[0116] Cell viability analysis

[0117] The mRNA expression level of SEMA6B in different colon cancer cell lines was detected using the Encyclopedia of Cancer Cell Lines (CCLE) website (https: / / sites.broadinstitute.org / ccle). Based on the survey, we selected two colon cancer cell lines with high SEMA6B expression levels (HCT116 and LoVo cells) for follow-up studies. Cell counting kit 8 (CCK8) was used to measure cell proliferation. HCT116 and LoVo cells were cultured in 96-well plates at 1500 cells per well and then interfered with SEMA6B- and NC-siRNA for 0, 24, 48, or 72 hours. After interference, the supernatant was removed, and 100 μL of DMEM or DMEM F12K was added in the presence of 10 μL of CCK8, and the cells were cultured at 37°C for 4 hours. Then, the absorbance at 450 nm was measured.

[0118] Cell migration and invasion assay cells

[0119] Cells were transfected with NC- or SEMA6B siRNA for 48 hours. Specifically, the siRNA sequence was: sense strand (SEQ ID NO.: 1): 5'-GCGAGUGUCGAAACUUCGUAATT-3', antisense strand (SEQ ID NO.: 2): 5'-UUACGAAGUUUCGACACUCGCTT-3'.

[0120] The efficacy of cells in the migration and invasion phases was evaluated using an invasion chamber with 8 μm wells (Matrigel invasion chamber; Corning, NY, USA). For the invasion assay, 2 × 10⁶ cells were used. 5 Cells in serum-free medium were added to the upper chamber. Then, 500 μL of 10% DMEM or DMEM F12K was added to the lower chamber, and the number of cells that migrated after 48 hours was quantified by counting five random regions under a microscope (IX70; Olympus Corporation, Tokyo, Japan). A similar method was used for migration assays, except that 1 × 10⁶ cells were added. 5 Cells were added to the upper cavity without Matrigel coating. Seven random regions were calculated in each chamber.

[0121] Experimental results

[0122] The mRNA levels of SEMA6B in different colon cancer cell lines were investigated using the CCLE dataset. Bar plots show that HCT116, SW480, LoVo, SW620, GP2D, and LS513 were the top six colon cancer cell lines with high SEMA6B expression. Figure 10 A). HCT116 and LoVo cell lines were selected for further study. QRT-PCR analysis showed that, compared with the corresponding control group, SEMA6B silencing not only significantly reduced SEMA6B expression but also decreased the mRNA levels of immunosuppressive molecules EDNRB, TGFB2, IL1B, IL6ST, BTLA, PD-L1, 12LGALS1, ICAM1, and HAVCR2 in the selected cell lines. Figure 10 B), the above mRNA measurements were performed using an RNA isolation kit (Beyotime, Shanghai, China), and the primers are shown in Table 1. According to CCK-8 analysis, knockout of SEMA6B significantly reduced the proliferation of both cell lines. Figure 10 C). Furthermore, according to the results of the Transwell migration assay, the number of cells migrating across the membrane was significantly reduced in the SEMA6B silencing groups of both cell lines. Figure 10 D). The Transwell invasion assay also showed that SEMA6B silencing significantly reduced the invasiveness of both colon cancer cell lines (D). Figure 10 E).

[0123] These data indicate that SEMA6B gene knockout can reduce the growth and progression of colon cancer cells and inhibit the formation of an immunosuppressive microenvironment.

[0124] Table 1. Primers used in this invention

[0125]

[0126] sequence list <120> Use of biomarker SEMA6B in the preparation of products for colorectal cancer diagnosis and prognosis prediction <140> 202111320742.9 <141> 2021-11-09 <160> 20 <170> SIPOSequenceListing 1.0 <210> 1 <211> twenty three <212> RNA <213> Artificial Sequence <400> 1 gcgagugucg aaacuucgua auu 23 <210> 2 <211> twenty three <212> RNA <213> Artificial Sequence <400> 2 uuacgaaguu ucgacacucg cuu 23 <210> 3 <211> 19 <212> DNA <213> Artificial Sequence <400> 3 ggaagctcag caactcgaa 19 <210> 4 <211> 18 <212> DNA <213> Artificial Sequence <400> 4 cccaagcgct ttccatga 18 <210> 5 <211> 19 <212> DNA <213> Artificial Sequence <400> 5 ctgaggtttg gtggagaga 19 <210> 6 <211> twenty one <212> DNA <213> Artificial Sequence <400> 6 ttgcaccccc aaatctaagg a 21 <210> 7 <211> 18 <212> DNA <213> Artificial Sequence <400> 7 ggaaattccg gcagtgcc 18 <210> 8 <211> 20 <212> DNA <213> Artificial Sequence <400> 8 tgacagctgg tggcattcaa 20 <210> 9 <211> 20 <212> DNA <213> Artificial Sequence <400> 9 cgctaagagc ttcgtgctga 20 <210> 10 <211> 18 <212> DNA <213> Artificial Sequence <400> 10 cgttgagcga ggttgaag 18 <210> 11 <211> 19 <212> DNA <213> Artificial Sequence <400> 11 cctgagtcgc cagtgaaat 19 <210> 12 <211> 19 <212> DNA <213> Artificial Sequence <400> 12 gtcggagatt cgtagcgga 19 <210> 13 <211> 19 <212> DNA <213> Artificial Sequence <400> 13 ggccacacag acttacaga 19 <210> 14 <211> twenty two <212> DNA <213> Artificial Sequence <400> 14 rgtcaggaag aagtgggcct tt 22 <210> 15 <211> 19 <212> DNA <213> Artificial Sequence <400> 15 ctctgctgcc ggatccaaa 19 <210> 16 <211> 18 <212> DNA <213> Artificial Sequence <400> 16 gtcccctggg taagcatc 18 <210> 17 <211> 19 <212> DNA <213> Artificial Sequence <400> 17 aggtgctatc gttcaacta 19 <210> 18 <211> 16 <212> DNA <213> Artificial Sequence <400> 18 tagcacttag caacaa 16 <210> 19 <211> 20 <212> DNA <213> Artificial Sequence <400> 19 taccaccttt ccgattgccc 20 <210> 20 <211> 16 <212> DNA <213> Artificial Sequence <400> 20 tggcctgact tgtgtt 16

Claims

1. Application of reagents for detecting SEMA6B expression levels in the preparation of products for diagnosing colon cancer.

2. The application as described in claim 1, characterized in that, The expression levels include protein expression levels and / or mRNA expression levels.

3. The application as described in any one of claims 1-2, wherein the product further comprises reagents for collecting and / or processing samples.

4. The application of SEMA6B inhibitors in the preparation of drugs for treating colon cancer, wherein the SEMA6B inhibitor is siRNA, and the sequence of the siRNA is: sense strand: 5'-GCGAGUGUCGAAACUUCGUAATT-3', antisense strand: 5'-UUACGAAGUUUCGACACUCGCTT-3'.

5. A pharmaceutical composition for treating colon cancer, said pharmaceutical composition comprising an inhibitor of SEMA6B; The inhibitor of SEMA6B is siRNA, and the sequence of the siRNA is: sense strand: 5'-GCGAGUGUCGAAACUUCGUAATT-3', antisense strand: 5'-UUACGAAGUUUCGACACUCGCTT-3'.

6. The pharmaceutical composition according to claim 5, characterized in that, The pharmaceutical composition also includes a pharmaceutically acceptable carrier.

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