Application of RBSN detection reagent in preparation of colorectal cancer detection / prognosis prediction product

Abstract

The invention discloses application of an RBSN detection reagent in preparation of a colorectal cancer detection / prognosis prediction product, and belongs to the technical field of colorectal cancer diagnosis markers. It is found through information generation analysis that compared with normal tissue, the expression level of RBSN in colorectal cancer tumor tissue is lower, and patients with high expression of RBSN have longer lifetime than patients with low expression of RBSN. RBSN expression differential genes are obviously enriched on related paths such as digestion and absorption of protein, ECM receptor interaction, proteoglycan in diabetic cardiomyopathy, oxidative phosphorylation, adherence, cancer, thermogenesis, chemical carcinogenesis of active oxygen and the like, and are positively correlated with immune infiltration. Immunohistochemical experiments prove that the coding protein Rabinosyn-5 of the RBSN is expressed in tumor tissues and para-carcinoma normal tissues of the colorectal cancer and is mainly expressed in cytoplasm, the expression of the RBSN is obviously related to the prognosis of the colorectal cancer patient, and the prognosis lifetime of the colorectal cancer patient with high expression of the RBSN is longer.

Description

Technical Field

[0001] The present invention belongs to the technical field of colorectal cancer diagnostic markers, and specifically relates to the application of RBSN detection reagents in the preparation of colorectal cancer detection / prognosis prediction products. Background Art

[0002] Colorectal cancer (CRC) is a malignant disease that seriously endangers human health and imposes a serious burden on society. According to the latest statistics from the American Cancer Institute in 2023, CRC is currently the fourth most common malignant tumor after prostate cancer (male), breast cancer (female) and lung cancer, and it ranks second among all carcinogenic causes of death. In recent years, due to the early prevention and screening of CRC, the improvement of surgical methods, the progress of liver metastasis treatment, and the development and optimization of immunotherapy and targeted therapy, the survival time of patients with advanced CRC has been significantly prolonged. In addition, indicators for the diagnosis and treatment of colorectal cancer, including p53, CEA, CA199, vascular endothelial growth factor (VEGF) and APC, have also been gradually applied in clinical practice. The expression levels of these tumor indicators can understand the degree of differentiation and invasiveness of tumor tissues, and are also conducive to the early diagnosis, disease judgment, and prognosis evaluation of CRC, providing a reference for the precise and individualized treatment of patients. Despite the clinical application and popularization of these tumor markers, the diagnosis and treatment of CRC in clinical practice is still limited, and the high recurrence and metastasis rates after CRC surgery are still difficult to overcome. Therefore, there is an urgent need to find more effective tumor biological indicators to achieve the long-term survival goals of CRC patients. Finding therapeutic targets and prognostic indicators for colorectal cancer remains the focus of current experimental research.

[0003] The RBSN gene is located on chromosome 3p25.1 and contains 10 exons. It is ubiquitously expressed in the brain (RPKM10.8), thyroid (RPKM6.4) and 25 other tissues. Its encoded protein, Rabenosyn-5, is a member of the FYVE protein family and is 110 kDa in size. Rabenosyn-5 is a novel protein found in a novel Rab5 effector complex associated with endosomal fusion. It mainly interacts directly with Rab5. The complex also has another protein, the Sec1-like protein hVPS45. These two proteins interact with RAS-related proteins that regulate membrane transport. Rabenosyn-5 consists of a C2H2 and a FYVE domain, both of which are located near its N-terminal region, in addition to a central coiled region and five asparagine-proline-phenylalanine (NPF) motifs in its C-terminal region. The function of the C2H2 zinc finger domain is still unclear, while the FYVE domain mainly binds to phosphatidylinositol-3-phosphate (PI3P). Rabenosyn-5 is recruited to membrane structures rich in phosphatidylinositol-3-phosphate and participates in many biological processes, such as membrane transport, cytoskeleton regulation, apoptosis and receptor signal transduction, among which the FYVE domain is the most important functional domain. Rabenosyn-5 can bind to the Sec1 / Munc18-like protein VPS45, which is the molecular connection between VPS45 and Rab5. After binding, they can promote the homotypic fusion of vesicles, and in turn stabilize the activity of endosomal soluble attachment protein receptors, regulating the endosomal transport system of multicellular organisms.

[0004] RBSN plays an important role in intracellular transport, so its mutation or abnormal expression is associated with a variety of human diseases. For example, loss of RBSN function can lead to a severe congenital myelofibrosis syndrome (PMID: 29784638); Rabenosyn-5 can significantly promote the turnover of nephrotic protein by interacting with neuronal protein kinase C casein kinase substrate 2 (PMID: 28550045); new Mendelian diseases related to RBSN and multi-organ diseases in children caused by RBSN mutations have also been reported (PMID: 35652444, 25233840); studies have also found that Rabenosyn-5 is a potential urinary biomarker for upper gastrointestinal cancer (PMID: 25644331). However, studies on RBSN in colorectal cancer have not yet been reported. Therefore, there is still a need to develop new methods for the diagnosis, precancerous warning and prognosis of colorectal cancer. Summary of the invention

[0005] In order to overcome the above-mentioned shortcomings of the prior art, the object of the present invention is to provide the use of a detection reagent of RBSN in the preparation of a colorectal cancer detection / prognosis prediction product.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: The first aspect of the present invention discloses the use of a detection reagent of RBSN in the preparation of a colorectal cancer detection / prognosis prediction product.

[0007] Preferably, the product is a preparation, a chip or a kit.

[0008] Preferably, the expression level of RBSN is downregulated in colorectal cancer patients.

[0009] Preferably, colorectal cancer patients with high RBSN expression have a longer prognosis survival.

[0010] Preferably, the mRNA and protein expression levels of RBSN in colorectal cancer tissues are significantly reduced.

[0011] The second aspect of the present invention discloses a kit for colorectal cancer detection / prognosis prediction, comprising a reagent for detecting the expression level of RBSN.

[0012] The third aspect of the present invention discloses the application of RBSN in constructing a computational model for colorectal cancer detection / prognosis prediction.

[0013] A fourth aspect of the present invention discloses a colorectal cancer detection / prognosis prediction system, comprising: Data storage device: used to store the expression information of RBSN; Data analysis device: Calculate the risk of colorectal cancer / colorectal cancer prognosis based on the expression information of RBSN; Result output device: outputs the result of the data analysis device.

[0014] Preferably, the expression level of RBSN is significantly downregulated, which is judged as a high risk of colorectal cancer.

[0015] Preferably, the expression level of RBSN in colorectal cancer patients after surgery is significantly downregulated, which is judged as a poor prognosis for colorectal cancer.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The application of the RBSN detection reagent provided by the present invention in the preparation of colorectal cancer detection / prognosis prediction products, through bioinformatics analysis, found that compared with normal tissues, RBSN has a lower expression level in colorectal cancer tumor tissues, and patients with high RBSN expression have a longer survival period than patients with low expression, and RBSN differentially expressed genes are significantly enriched in protein digestion and absorption, ECM receptor interaction, diabetic cardiomyopathy, oxidative phosphorylation, adhesion, proteoglycans in cancer, thermogenesis, and chemical carcinogenesis of reactive oxygen species, and are positively correlated with immune infiltration. Immunohistochemical experiments have shown that the encoding protein Rabenosyn-5 of RBSN is expressed in both colorectal cancer tumor tissues and adjacent normal tissues, and is mainly expressed in the cytoplasm, and the expression of RBSN is significantly correlated with the prognosis of colorectal cancer patients, and colorectal cancer patients with high RBSN expression have a longer prognosis survival period. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The expression of RBSN and the prognosis survival curve are shown in Figure 1. A is the difference in mRNA expression of RBSN in CRC cancer and adjacent normal tissues in the UALCAN-TCGA database, and B is the relationship between the prognosis of colorectal cancer patients and the expression of RBSN. Figure 2 The volcano plot of RBSN differentially expressed genes; Figure 3 This is the heat map of RBSN differentially expressed genes; Figure 4 This is the GO enrichment analysis diagram of RBSN differentially expressed genes; Figure 5 This is the KEGG enrichment analysis diagram of RBSN differentially expressed genes; Figure 6 The figure is a correlation analysis diagram between RBSN gene expression and immune infiltration; A, B, and C are the correlation analysis between stromal, immune, and ESTIMATE scores of CRC patients including COAD, COADREAD, and READ and RBSN expression, respectively; Figure 7 This is a correlation analysis diagram between RBSN gene expression and immune cells; Figure 8 This is a correlation analysis diagram between RBSN gene expression and immune checkpoints; Fig. 9 RBSN in normal tissue adjacent to CRC cancer ( 20 times) and cancer tissue ( 20 times) middle IHC result picture; Fig.10 This is the difference in expression of RBSN in CRC cancer tissues and adjacent normal tissues detected by immunohistochemistry; Fig.11 The expression of RNSN and the Kaplan-Meier survival curve of CRC patients after surgery; Fig.12 The univariate COX model is used to analyze the risk factors for the prognosis of patients with colorectal cancer; Fig.13 The multivariate COX model was used to analyze the risk factors for the prognosis of patients with colorectal cancer; Fig.14 A schematic diagram of a detection system for colorectal cancer; Fig.15 Schematic diagram of the prognostic evaluation system for patients with colorectal cancer. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to understand the characteristics and effects of the present invention, the following is a general description and definition of the terms and expressions mentioned in the specification and claims. Unless otherwise specified, all technical and scientific terms used in the text are the common meanings understood by those skilled in the art for the present invention. In the event of a conflict, the definition in this specification shall prevail.

[0019] The theories or mechanisms described and disclosed herein, whether correct or incorrect, should not limit the scope of the present invention in any way, that is, the present invention can be implemented without being limited by any specific theory or mechanism.

[0020] In this article, all features such as values, quantities, contents and concentrations defined in the form of numerical ranges or percentage ranges are for simplicity and convenience only. Accordingly, the description of numerical ranges or percentage ranges should be considered to have included and specifically disclosed all possible secondary ranges and individual values ​​within the range (including integers and fractions).

[0021] In this document, unless otherwise specified, “includes,” “including,” “contains,” “has,” or similar terms cover the meanings of “consisting of” and “mainly consisting of,” for example, “A includes a” covers the meanings of “A includes a and other” and “A only includes a.”

[0022] In this document, in order to make the description concise, not all possible combinations of various technical features in various embodiments or examples are described. Therefore, as long as there is no contradiction in the combination of these technical features, the various technical features in various embodiments or examples can be combined arbitrarily, and all possible combinations should be considered to be within the scope of this specification.

[0023] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0024] The following examples use conventional instruments and equipment in the art. The experimental methods in the following examples without specifying specific conditions are usually carried out under conventional conditions or under conditions recommended by the manufacturer. The various raw materials used in the following examples, unless otherwise specified, are conventional commercial products, and their specifications are conventional specifications in the art.

[0025] Example 1 Bioinformatics Analysis Log in to the TCGA database website through the browser: https: / / portal.gdc.cancer.gov / ; select Access TCGA Data to enter the TCGA database data download page, click Repository to enter the data download settings page, click Cases to enter the keyword RBSN in the Project column, check TCGA-COAD and READ to select the data source, then click Files to check transcriptome profiling in the Data Category column to select the data as transcriptome data, then click Add All Files to Cart to add the file to Cart, package and download the Cart file in the background, and download the metadata file at the same time. Unzip the Cart file, use Perl to extract the gene name and expression level in the single sample file, and finally merge it into an expression matrix, and identify the sample attributes through the metadata file, put the paracancerous group in front of the matrix, and the cancer group in the back of the matrix. The downloaded COAD data set includes 41 normal samples and 471 tumor samples, and the READ data set includes 10 normal samples and 167 tumor samples. The expression profiles of rectal cancer and colon cancer were merged according to the classification of the disease, and the merged CRC data matrix was de-batched using the limma / R package and the sva / R package.

[0026] 1. Expression of RBSN in colorectal cancer and its relationship with prognosis Based on paired samples in the TCGA database, the expression of RBSN in colorectal cancer was analyzed. A total of 51 paired COADREAD samples were included. The results showed that the expression of RBSN in colorectal cancer tumor tissues and normal tissues was significantly different (P<0.05). Compared with normal tissues, the expression level in colorectal cancer tumor tissues was lower ( Figure 1In addition, a survival prognosis analysis was performed on 368 colorectal cancer cases with prognostic information screened from the TCGA data, and the Kaplan-Meier survival curve was drawn. The results showed that patients with high RBSN expression in CRC had a longer survival period than those with low RBSN expression ( Figure 1 (B) That is, high expression of RNSN in CRC is associated with a good prognosis (P<0.05).

[0027] 2. Analysis of differentially expressed genes in RBSN Normal tissue samples in colorectal cancer were deleted, and tumor samples were divided into high-expression RBSN group and low-expression RBSN group according to the expression of RBSN gene. The R / limma package was used to analyze the differentially expressed genes in the RBSN high-expression group and the RBSN low-expression group. The screening indicators were the fold change (FC) of gene expression and the corrected P value (FDR). Genes with log|FC|>0.585 and P Value<0.05 were differentially expressed genes. The R / pheatmap package was used to draw the volcano map and heat map of differentially expressed genes ( Figure 2 , Figure 3 ), a total of 82 genes were screened out through the volcano map, of which 36 were upregulated (indicated by red dots) and 46 were downregulated (indicated by green dots). The genes screened out through the heat map mainly include TOP2B, CHCHD5, NDUFA11, NDUFA13, NDUFS7, MTLN, AHNAK, GOLGA4, MCRIP2, etc.

[0028] The differentially expressed genes in the RBAN high expression group and RBSN low expression group in colorectal cancer were collected, and the GO and KEGG enrichment analysis bubble charts were drawn using R / clusterProfiler, R / org.Hs.eg.db, R / enrichplot and R / ggplot2 packages. When pvalue < 0.05, the pathway is considered to be enriched, and the horizontal axis represents the proportion of genes enriched in a certain pathway. Finally, GO (BP, CC, MF) outputs the most significant 10 enriched pathways, and KEGG outputs the most significant 10 enriched pathways. GO enrichment analysis of RBSN differentially expressed genes is shown in Figure 2. Figure 4 As shown in Figure 2, the biological processes (BPs) of RBSN were significantly enriched in the regulation of complement activation, humoral immune response mediated by circulating immunoglobulins, B cell-mediated immunity, phagocytic system, and cell membrane invagination process ( Figure 4 ); Cellular components (CC) mainly include immunoglobulin complexes, extracellular matrix, outer side of plasma membrane, collagen trimer complexes, endoplasmic reticulum lumen, and components of fibrous collagen trimers, etc. ( Figure 4); The molecular functions (MF) of genes mainly include antigen binding, extracellular matrix structure, collagen binding, immunoglobulin receptor binding, glycosaminoglycan binding, growth factor binding, protease binding, etc. ( Figure 4 ). KEGG enrichment analysis showed that RBSN differentially expressed genes were significantly enriched in pathways related to protein digestion and absorption, ECM receptor interaction, diabetic cardiomyopathy, oxidative phosphorylation, focal adhesion, proteoglycans in cancer, thermogenesis, and chemical carcinogenesis of reactive oxygen species ( Figure 5 ).

[0029] 3. RBSN expression immunoassay The gene expression profiles of all tumor samples were extracted, and then the stromal, immune and ESTIMATE scores of all samples were calculated based on gene expression using the R software package ESTIMATE. The immune infiltration scores of 373 tumor samples in COAD, READ and COADREAD were obtained. The Pearson correlation coefficient between the RBSN gene expression level and the immune infiltration score was calculated using the corr.test function. The final results showed that the expression of the RBSN gene in COAD, READ and COADREAD was positively correlated with immune infiltration ( P <0.05), such as Figure 6 shown.

[0030] The infiltration scores of 64 immune cells, including Adipocytes, aDCs, Astrocytes, B-cells, Basophils, CD4+_memory_T-cells, CD4+_naive_T-cells, and CD4+_T-cells, were re-evaluated for each patient in all CRCs based on gene expression using the deconvo_xCell method of the R software package IOBR. The Pearson correlation coefficients between RBSN expression and immune cell infiltration scores in COAD, READ, and COADREAD were calculated using the corr.test function of the R software package psych. The results showed that in CRC, the expression of RBSN was correlated to varying degrees with 36 immune cells, including aDC, B-cells, Basophils, iDC, Keratinocytes, Macrophages, Macrophages_M1 / CD4+_memory_T-cells, CD4+_naive_T-cells, Chondrocytes, Class-switched_memory_B-cells, CMP, Epithelial_cells, Erythrocytes, GMP, Hepatocytes, Megakaryocytes, and Memory_B-cells ( Figure 7 ).

[0031] The expression data of RBSN gene and 60 marker genes of immune checkpoint pathways in all samples were further extracted from the COAD, READ, and COADREAD datasets downloaded from the TCGA database, and the Pearson correlation between RBSN and marker genes (60) of the two immune pathways was calculated. The results are shown in Figure 8 As shown, the expression of RBSN was significantly correlated with 32 immune pathway marker genes including VEGFA, IL12A, EDNRB, CD274, HAVCR2, HMGB1, CD28, and TLR4 ( P <0.05), indicating that RBSN may be involved in regulating cellular immune function in CRC patients.

[0032] Example 2 Immunohistochemistry Experiment Verification 1. Research objects, materials and methods Patients who underwent radical resection for colorectal cancer in the Department of General Surgery of Shaanxi Provincial People's Hospital from January 2017 to December 2018 were retrospectively analyzed. Finally, 183 cases of CRC were included in the study. We collected postoperative paraffin specimens from these 183 patients from the Department of Pathology, including 183 cases of CRC cancer tissue and 120 cases of colorectal tissue adjacent to CRC cancer (at least 5 cm away from the edge of the tumor). Among them, 101 males (55.19%) and 82 females (44.81%) were aged 29 to 89 years, with an average age of 66 years. The clinical data of these 183 cases were complete, and their degree of tissue differentiation, clinical pathological diagnosis, and pathological staging were all supported by pathological histological examination evidence from the Department of Pathology of our hospital. Written informed consent was obtained from each participant before the experimental procedures began. The study procedures have been approved by the Ethics Committee of Shaanxi Provincial People's Hospital and conform to the Declaration of Helsinki.

[0033] Inclusion criteria for study specimens: All patients were primary CRC patients diagnosed by electronic colonoscopy biopsy; patients who underwent radical surgery for CRC and had negative resection margins; complete clinical data, medical records, and follow-up data. Exclusion criteria: patients with incomplete clinical data, pathological data, and follow-up data; patients with other malignant diseases; and patients who died of other accidents (not directly or indirectly caused by CRC).

[0034] The CRC patients included in the study were followed up by telephone, with death or loss of follow-up as the end point of the follow-up. The follow-up period was from January 1, 2022 to December 31, 2023, and the follow-up frequency was once every 6 months. The patient's survival status and cause of death were recorded in detail. The time from CRC surgery to death was the overall survival. The number of cases with complete prognostic information was 183. Immunohistochemistry was used to detect the expression of RBSN encoding protein (Rabenosyn-5) in CRC tumor tissues and adjacent normal tissues of the study subjects, and the results were statistically analyzed by statistical software SSPS26.0, and GraphPad Prism 8.4.3 software was used for drawing. When the measurement data of the inter-group comparison conformed to the normal distribution, the paired sample T test was used, and when it did not conform to the normal distribution, the rank sum test of the two related samples was used; the quantitative data were expressed as x±s, and the count data were assigned a uniform value (negative = 0, positive = 1). The data were tested by chi-square test. The correlation of RBSN expression in CRC was analyzed by Spearman rank correlation analysis. According to the results of univariate analysis, the variables of related risk factors (P < 0.05) were included in the multivariate COX regression model to calculate the relative risk RR value and 95% confidence interval of the variables. The KM (Kaplan-Meier) method was used to calculate the survival rate, and the Log-rank test was used to test the significance of the difference in survival rate. The influencing factors of survival analysis were analyzed by stepwise COX proportional hazard regression model. (P < 0.05 was statistically significant.) 2. Basic process of immunohistochemistry 1) Dewaxing: Before dewaxing, bake the tissue sections in a biomedical oven at 70°C for 20 min until the wax block on the slide softens. Then, soak the slide in xylene solution for 10 min, then soak it in new xylene for 10 min. Finally, soak the paraffin sections in 100% anhydrous ethanol, 85% ethanol, and 75% ethanol for 3 min each.

[0035] 2) Washing: Wash the slides 3 times with PBS solution, 3 min each time.

[0036] 3) Antigen repair: First, heat the sodium citrate solution in a microwave at high heat until it boils, then immerse the entire tissue section in the boiling sodium citrate buffer, continue heating at medium-low heat for 20 minutes, and then cool naturally at room temperature for about 2 hours.

[0037] 4) Washing: Remove the tissue sections from the cooled sodium citrate buffer and wash the sections with PBS solution three times, 3 min each time.

[0038] 5) Antigen blocking: Wipe the liquid around the tissue on the slice dry, draw a circle slightly outside the tissue with an immunohistochemistry pen, add an appropriate amount of peroxidase blocking solution, make sure the blocking solution does not leak out, place in a humidified box at room temperature away from light for 10 minutes to keep the tissue moist. Discard the peroxidase blocking solution after 10 minutes.

[0039] 6) Washing: Wash the slides three times with PBS buffer, 3 min each time.

[0040] 7) Add the RBSN primary antibody diluted according to the instructions, add 100 μL of the primary antibody dilution solution on the tissue section (the optimal antibody concentration for the experiment was 1:500 after preliminary experiments), and then place it in a 4°C refrigerator overnight.

[0041] 8) After incubation, wash the slides three times with PBS buffer for 3 min each time. After drying the sections, add PV8000 secondary antibody and incubate in a humidified box at 37°C for 30 min. Then wash the slides three times with PBS solution for 3 min each time.

[0042] 9) Color development: Add an appropriate amount of DAB color development solution to the tissue circle of the slice. The DAB preparation ratio is 1 mL of buffer solution plus 40-50 µL of color development solution (prepare and use immediately). When the tissue slice appears brown, rinse with tap water for 3-5 minutes.

[0043] 10) Counterstain with hematoxylin for 1 min, soak in tap water for 3 min, then 1% hydrochloric acid alcohol (75% alcohol) for 3 s, rinse with tap water and place in ammonia water (0.5%) for 3 s to return to blue. After counterstaining, dehydrate with 75%, 85%, and 100% anhydrous ethanol in a gradient manner. After air drying, add a drop of neutral resin on the tissue section, cover with a slide, and apply slight pressure with tweezers to eliminate bubbles and ensure complete sealing.

[0044] 11) Interpretation of results: Place the stained sections under a microscope after sealing and read the sections, and calculate the specific IHC score at the same time. A positive result is the appearance of brown-yellow staining in the field of view of the pathological tissue on the slide, and the relative expression level of the protein is quantified according to the area and intensity percentage of the staining. According to the staining intensity, 0, 1, 2, and 3 points are assigned from no staining, weak staining, moderate staining, and strong staining, respectively; according to the staining area, 0~25%, >25%~50%, >50%~75%, and >75%~100%, respectively, 0, 1, 2, and 3 points are assigned. The final score is the product of the scores of the staining area and intensity. Finally, the average of the scores scored by the two pathologists is the final result, ≥3 points for high expression, and <3 points for low expression.

[0045] 3. Experimental results 1) Immunohistochemistry test results We used IHC to detect the expression of RBSN protein (Rabenosyn-5) in 183 CRC tumor tissues and 120 CRC adjacent normal tissues. The results showed that Rabenosyn-5 was expressed in both CRC tumor tissues and adjacent normal tissues, and was mainly expressed in the cytoplasm ( Fig. 9 Specifically, the positive rate of RBSN in CRC cancer tissues was 51.9% (95 / 183), while the positive rate in CRC adjacent normal tissues was 69.2% (83 / 120) (Table 1). Among the 120 pairs of CRC cancer tissues and adjacent normal tissues, the expression of Rabenosyn-5 in CRC adjacent normal tissues was higher than that in tumor tissues, and the difference was statistically significant (P<0.05, Fig.10 ).

[0046] Table 1 Expression of RBSN protein in CRC and adjacent normal tissues

[0047] 2) Relationship between RBSN protein expression and clinicopathological characteristics of CRC patients The results of statistical analysis are shown in Table 2. The expression of RBSN protein in colorectal cancer tissues was not significantly related to the patient's gender (P=0.187), age (P=0.074), site of occurrence (P=0.073), degree of differentiation (P=0.146), T tumor invasion depth (P=0.289), lymph node metastasis (P=0.916), distant metastasis (P=0.931), clinical stage (P=0.224), MMR status (P=0.764), vascular invasion (P=0.217), and nerve invasion (P=0.838), and the difference was not statistically significant (P>0.05).

[0048] Table 2 Relationship between RBSN protein expression and clinical pathological parameters in colorectal cancer tissues

[0049] 3) Relationship between RBSN expression level and prognosis of CRC patients According to the survival data of 183 CRC patients followed up by telephone, the KM survival curve results showed that the overall survival of CRC patients with high RBSN expression was significantly higher than that of those with low RBSN expression (P < 0.015, see Fig.11 ), indicating that the expression of RBSN is significantly correlated with the prognosis of CRC patients.

[0050] 4) Analysis of risk factors for prognosis in CRC patients Univariate COX model analysis showed that clinical stage (P < 0.05), lymph node metastasis (p < 0.05), and RBSN expression in cancer tissue (P < 0.05) of CRC patients were associated with the prognosis of patients (see Fig.12 ); Multivariate COX model analysis showed that RBSN expression in tumor tissue (P < 0.05) was a risk factor affecting the prognosis of CRC patients, further indicating that decreased expression of RBSN coding protein was an independent risk factor for poor prognosis in colorectal cancer patients (see Fig.13 ).

[0051] In summary, after in-depth research, using bioinformatics technology and immunohistochemistry technology to detect a larger sample of clinical specimens, it was found that compared with normal colorectal tissue, the mRNA and protein expression of RBSN in colorectal cancer tissue was significantly reduced; the reduced expression level of RBSN protein is an independent risk factor for poor prognosis in patients with colorectal cancer and can be used as a prognostic indicator for colorectal cancer.

[0052] Example 3 A kit for detecting colorectal cancer includes reagents for detecting RBSN expression levels, and specific components can be selected according to specific experimental methods, and the specific experimental method can be immunohistochemistry. In addition, there can also be standards and controls (such as quantitatively standardized normal human tissue samples, etc.) and normal reference values.

[0053] Example 4 A colorectal cancer detection system, such as Fig.14 As shown, including: Data storage module: used to store the expression information of RBSN; Data analysis module: Calculate the risk of colorectal cancer based on the expression information of RBSN; Result output module: outputs the results of the data analysis module.

[0054] It can be understood that the colorectal cancer detection system provided by the present invention corresponds to the down-regulated expression level of RBSN in colorectal cancer patients provided in the aforementioned Examples 1 and 2, and can be used for colorectal cancer diagnosis.

[0055] Example 5 A prognostic assessment system for patients with colorectal cancer, such as Fig.15 As shown, including: Data storage module: used to store the expression information of RBSN; Data analysis module: Calculate the prognosis and survival of colorectal cancer patients based on the expression information of RBSN; Result output module: outputs the results of the data analysis module.

[0056] It can be understood that the colorectal cancer patient prognosis evaluation system provided by the present invention corresponds to the long prognosis survival period of colorectal cancer patients with high RBSN expression provided in the aforementioned Examples 1 and 2, and can be used for colorectal cancer prognosis prediction.

[0057] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. Application of RBSN detection reagents in the preparation of colorectal cancer detection / prognosis prediction products.

2. The use according to claim 1, characterized in that: The product is a preparation, a chip or a kit.

3. The use according to claim 1 or 2, characterized in that: The expression level of RBSN is downregulated in patients with colorectal cancer.

4. The use according to claim 1 or 2, characterized in that: Colorectal cancer patients with high RBSN expression have a longer survival prognosis.

5. The use according to claim 1 or 2, characterized in that: The mRNA and protein expression levels of RBSN in colorectal cancer tissues were significantly reduced.

6. A kit for colorectal cancer detection / prognosis prediction, characterized in that: Included are reagents for detecting RBSN expression levels.

7. Application of RBSN in constructing a computational model for colorectal cancer detection / prognosis prediction.

8. A colorectal cancer detection / prognosis prediction system, characterized in that: include: Data storage device: used to store the expression information of RBSN; Data analysis device: Calculate the risk of colorectal cancer / colorectal cancer prognosis based on the expression information of RBSN; Result output device: outputs the result of the data analysis device.

9. The colorectal cancer detection / prognosis prediction system according to claim 8, characterized in that: The expression level of RBSN was significantly downregulated, indicating a high risk of colorectal cancer.

10. The colorectal cancer detection / prognosis prediction system according to claim 8, characterized in that: The expression level of RBSN in patients with colorectal cancer was significantly downregulated after surgery, which was judged as a poor prognosis for colorectal cancer.

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