Gastric cancer prognosis marker and application thereof

Abstract

The application provides a gastric cancer prognosis marker and application thereof, and belongs to the technical field of biotechnology.The survival analysis is carried out to explore the prognosis correlation of m6A "writer" RBM15 in gastric cancer.The results prove that RBM15 is a prognosis marker related to better clinical results, and can be used to judge the prognosis of gastric cancer patients.The application verifies the relationship among RBM15, ECT2 and EMT signal pathway, and the results prove that RBM15 mediates the m6A methylation of ECT2 through IGF2BP3, influences the stability of ECT2 RNA, thereby influences the expression of ECT2, and simultaneously regulates the EMT signal pathway.The application also discloses the mechanism that RBM15 influences the proliferation, invasion, migration and sensitivity to 5-fluorouracil chemotherapy of gastric cancer cells, and provides a new treatment target for gastric cancer treatment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of biotechnology, and particularly relates to a gastric cancer prognosis marker and application thereof. BACKGROUND

[0002] Gastric cancer (GC) is one of the most common digestive tract tumors in the world, with more than 1 million new cases each year. It is the third leading cause of cancer-related mortality worldwide. The clinical stage at the time of GC diagnosis is a key determinant of patient prognosis and survival. Currently available biomarkers for early detection of GC, such as carcinoembryonic antigen (CEA), alpha-fetoprotein (AFP), carbohydrate antigen 19-9 (CA19-9), CA72-4, CA125, etc., lack sufficient sensitivity and specificity, and there is an urgent need for new biomarkers to improve early detection and prognosis of GC.

[0003] M6A is involved in almost all aspects of RNA metabolism, including translation, degradation, import, export and folding. Key components of the m6A methyltransferase complex include METTL3, METTL14, WTAP, METTL16, VIRMA and RBM15. Among them, RBM15 can promote the progression of laryngeal squamous cell carcinoma, and its knockdown is proved to inhibit the development of colorectal cancer. However, the expression and mechanism of RBM15 in gastric cancer are still unclear.

[0004] Epithelial cell transformation sequence 2 (ECT2) is a guanine nucleotide exchange factor (GEF) of Rho GTPase, including RhoA, Rac1 and Cdc42

[23] . ECT2 is related to malignant transformation, tumorigenesis and metastasis of tumors. Current research on ECT2 mainly focuses on its role in other tumors. For example, ECT2 promotes malignant phenotype by activating AKT / mTOR pathway and helps cisplatin resistance in cervical cancer. ECT2 also drives the progression of lung adenocarcinoma by affecting extracellular matrix dynamics and focal adhesion signals. Its oncogenic effect is affected by its subcellular localization. However, the role of ECT2 in gastric cancer is still largely unexplored. SUMMARY

[0005] The present application aims to provide a gastric cancer prognosis marker and application thereof, and the gastric cancer marker is RBM15, which can be used for predicting the prognosis effect of gastric cancer and also can be used as a therapeutic target for treating gastric cancer.

[0006] In order to achieve the above-mentioned application purposes, the present application provides the following technical solutions:

[0007] The present application provides a gastric cancer prognosis marker, and the gastric cancer prognosis marker is RBM15.

[0008] The application further provides application of the gastric cancer prognosis marker RBM15 in predicting the prognosis effect of gastric cancer.

[0009] Further, the marker RBM15 high expression is determined as good prognosis, and the marker RBM15 low expression is determined as poor prognosis.

[0010] The application further provides application of the gastric cancer prognosis marker RBM15 as a therapeutic target in preparation of a gastric cancer treatment drug.

[0011] Further, the gastric cancer treatment drug is a drug for promoting RBM15 high expression.

[0012] Further, the drug for promoting RBM15 high expression comprises an RBM15 activator or an RBM15 overexpression recombinant lentivirus.

[0013] Further, the drug for promoting RBM15 high expression can mediate m6A methylation modification of ECT2 through IGF2BP3, and regulate an EMT signal pathway.

[0014] Further, the drug for promoting RBM15 high expression can inhibit gastric cancer cell proliferation, migration and invasion.

[0015] Further, the drug for promoting RBM15 high expression can enhance drug sensitivity of gastric cancer cells.

[0016] Compared with the prior art, the application has the following beneficial effects:

[0017] (1) The application performs survival analysis to explore the prognosis correlation of the m6A "writer" RBM15 in gastric cancer. The results prove that RBM15 is a prognosis marker related to better clinical results, and can be used to judge the prognosis of gastric cancer patients.

[0018] (2) The application verifies the relationship among RBM15, ECT2 and the EMT signal pathway, and the results prove that RBM15 mediates m6A methylation of ECT2 through IGF2BP3, affects the stability of ECT2 RNA, thereby affecting the expression of ECT2, and regulates the EMT signal pathway. The application also reveals the mechanism of RBM15 affecting gastric cancer cell proliferation, invasion, migration and sensitivity to 5-fluorouracil chemotherapy, and provides a new therapeutic target for gastric cancer treatment. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed in the embodiments will be briefly introduced as follows. Obviously, the accompanying drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0020] Figure 1-1 Survival analysis of RBM15 in human gastric cancer in Example 1 of the present application, wherein A is a meta-analysis of 23 m6A regulatory molecules, highlighting the enriched pathways and prognosis; B is the prognostic significance of 23 m6A regulatory molecules; C is the RFS forest plot of 23 m6A regulatory molecules in the TCGA database; D is the OS forest plot of 23 m6A regulatory molecules in the TCGA database, E is the OS forest plot of 23 m6A regulatory molecules in the ACRG database; F is the RFS forest plot of 23 m6A regulatory molecules in the ACRG database; G is the survival analysis of 84 gastric cancer patients based on RBM15 expression;

[0021] Figure 1-2 Survival analysis of RBM15 in human gastric cancer in Example 1 of the present application, wherein H is a Kaplan-Meier curve showing that RBM15 expression high and low are stratified PFS and OS in the TCGA database; I is a comprehensive analysis of the relationship between RBM15 expression and prognosis PFS; PPS and OS are studied in GC patients in the GC chip data sets GSE14210, GSE15459, GSE22377, GSE29272, GSE51105 and GSE62254; J is the RBM15 expression of different subtypes CIN, EBV, GS and MSI in the TCGA database; K is the RBM15 expression of different subtypes CIN, EBV, GS and MSI in the TCGA database; L is the RBM15 expression of different subtypes EMT, MSI, MSS / TP53-, MSS / TP53+ in the ACRG database; M is the RBM15 expression of different subtypes EMT, MSI, MSS / TP53-, MSS / TP53+ in the ACRG database;

[0022] Figure 2 Analysis of 23 m6A related genes in cancer in Example 1 of the present application, wherein A is that 23 m6A related genes in 115 samples of 437 samples have occurred mutations, B is the co-occurrence analysis of 23 m6A related genes; C is the correlation analysis of 23 m6A related genes in the TCGA database; D is the correlation analysis of 23 m6A related genes in the ACRG database;

[0023] Figure 3-1A. Quantitative PCR and Western-blot analysis confirmed the knockdown of RBM15 in AGS cells or the overexpression of RBM15 in MKN-45 cells; B. Cell proliferation assay (CCK-8) results of RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells or MKN-45 vector control or RBM15 overexpression cells; C. Cell proliferation assay (CCK-8) line graph of RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells or MKN-45 vector control or RBM15 overexpression cells; D. Cell migration and invasion assay results of RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells; E. Cell migration and invasion assay results of RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells; F. Cell migration and invasion assay results of MKN-45 cells under the action of vector (vector control) or RBM15 overexpression; G. Cell migration and invasion assay results of MKN-45 cells under the action of vector (vector control) or RBM15 (RBM15 overexpression); H. Cell migration and invasion assay column chart of RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells; I. Cell migration and invasion assay column chart of MKN-45 cells under the action of vector (vector control) or RBM15 (RBM15 overexpression);

[0024] Figure 3-2Figure 1 is a diagram showing the results of cell migration experiments for RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells; Figure 2 is a diagram showing the results of cell migration experiments for RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells; Figure 3 is a diagram showing the results of cell migration experiments for MKN-45 cells under Vector (Vector control) or RBM15 (RBM15 overexpression); Figure 4 is a diagram showing the results of lymphatic vessel formation ability for RBM15-scr, shRBM15-1, shRBM15-2 RBM15 knockdown HLEC cells co-cultured with AGS cells; Figure 5 is a diagram showing the results of lymphatic vessel formation ability for HLEC cells co-cultured with MKN-45 cells under Vector (Vector control) or RBM15 (RBM15 overexpression); Figure 6 is a diagram showing the results of migration of HLEC cells co-cultured with RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells by transwell method; Figure 7 is a diagram showing the results of migration of HLEC cells co-cultured with MKN-45 cells under Vector (Vector control) or RBM15 (RBM15 overexpression) by transwell method; Figure 8 is a diagram showing the results of cell migration experiments for RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells; Figure 9 is a diagram showing the results of cell migration experiments for RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells; Figure 10 is a diagram showing the results of cell migration experiments for MKN-45 cells under Vector (Vector control) or RBM15 (RBM15 overexpression); Figure 11 is a diagram showing the results of lymphatic vessel formation ability for RBM15-scr, shRBM15-1, shRBM15-2 RBM15 knockdown HLEC cells co-cultured with AGS cells; Figure 12 is a diagram showing the results of lymphatic vessel formation ability for HLEC cells co-cultured with MKN-45 cells under Vector (Vector control) or RBM15 (RBM15 overexpression); Figure 13 is a diagram showing the results of migration of HLEC cells co-cultured with RBM15-scr, shRBM15-1, shRBM15-2 (RBM15 knockdown) AGS cells by transwell method; and Figure 14 is a diagram showing the results of migration of HLEC cells co-cultured with MKN-45 cells under Vector (Vector control) or RBM15 (RBM15 overexpression) by transwell method.

[0025] Figure 4-1RBM15 modulates EMT pathway in Example 1 of the present application; A is in ACRG database, based on KEGG pathway dataset; B is in ACRG database, based on REACTOME pathway dataset; C is in ACRG database, based on HALLMARK pathway dataset; D is to analyze the correlation between RBM15 and emt related genes using Spearman; E is to analyze the correlation between RBM15 and Vim using Spearman; F is the flow chat map of RNA sequence; G is KEGG analysis of shRBM15 gene AGS cell RNA-seq; H is Western-blot analysis of the expression level of CDH1, CDH2, CTNNB1 and Vimentin in RBM15 gene knockdown AGS cells;

[0026] Figure 4-2 RBM15 modulates EMT pathway in Example 1 of the present application; wherein, I is to analyze the expression level of CDH1, CDH2, CTNNB1 and Vimentin in RBM15 gene knockdown AGS cells using quantitative pcr q-PCR; J is shRBM15 immunofluorescence assay of E-cadherin in AGS cells; K is shRBM15 immunofluorescence assay of N-cadherin in AGS cells; L is shRBM15 immunofluorescence assay of Vimentin in AGS cells;

[0027] Figure 5-1 Analysis results in Example 1 of the present application, wherein A is the correlation analysis of ARBM15 and CDH1; B is the correlation analysis of RBM15 and CDH2; C is the correlation analysis of RBM15 and TWIST2; D is the correlation analysis of RBM15 and ZEB2; E is the correlation analysis of RBM15 and SNAI2; F is to detect the expression level of CDH1, CDH2, CTNNB1 and Vimentin in MKN-45 cells overexpressing RBM15 by Western blot analysis; G is to detect the expression level of CDH1, CDH2, CTNNB1 and Vimentin in MKN-45 cells overexpressing RBM15 by quantitative PCR (q-PCR); H is immunofluorescence analysis of E-cadherin in MKN-45 cells overexpressing RBM15; I is immunofluorescence analysis of N-cadherin in MKN-45 cells overexpressing RBM15; J is immunofluorescence analysis of Vimentin in MKN-45 cells overexpressing RBM15;

[0028] Figure 5-2The results are from the analysis in Example 1 of this invention, where K is the volcano plot of RBM15 differentially expressed genes in the TCGA database; L is the volcano plot of RBM15 differentially expressed genes in the ACRG database; and M is the volcano plot of RBM15 differentially expressed genes in RNA-seq.

[0029] Figure 6-1 In Example 1 of this invention, RBM15 mediates the EMT signaling pathway through regulated ECT2; A is a Venn diagram of the differentially expressed RBM15 gene in RNA-seq, TCGA, and ACRG databases; B is a Western blot analysis of AGS cells after RBM15 knockout; C is a q-PCR analysis of AGS cells after RBM15 knockout; D is a q-PCR and Western blot analysis of treated AGS cells; E is a q-PCR and Western blot analysis of treated MKN-45 cells; F and G are survival analyses of ECT2 in the ACRG and TCGA databases; H is a joint survival analysis of RBM15 and ECT2 in the ACRG cohort.

[0030] Figure 6-2 In Embodiment 1 of this invention, RBM15 mediates the EMT signaling pathway through regulated ECT2; I represents the joint survival analysis of RBM15 and ECT2 in the TCGA cohort; J represents the correlation between ECT2 and RBM15 in ACRG patients; K represents the correlation analysis of RBM15 in the ACRG database; L represents the enrichment analysis of ECT2 expression based on the KEGG database; M represents the enrichment analysis of ECT2 expression based on the HALLMARK database; and N represents the enrichment analysis of ECT2 expression based on the REACTOME database.

[0031] Figure 7-1 This is an example of animal experiments and tissue microarrays in Example 1 of the present invention; A shows a mouse model and mouse tumor images; the top shows the vector group, and RBM15 is the RBM15 group overexpressing RBM15; B shows the volume of mouse tumors after injection of MKN-45 cells; C shows the weight of mouse tumors after injection of MKN-45 cells; D shows the expression levels of RBM15, ECT2, CDH1, CDH2, CTNNB1, and Vimentin in mouse tumor tissues detected by Vimentin (q-PCR); E shows the expression levels of RBM15, ECT2, CDH1, CDH2, CTNNB1, and Vimentin in mouse tumor tissues detected by CTNNB1.

[0032] Figure 7-2 The images show animal experiments and tissue microarrays in Example 1 of this invention; F represents the expression levels of RBM15, ECT2, CDH1, CDH2, CTNNB1, and Vimentin in mouse tumor tissue detected by immunohistochemistry.

[0033] Figure 7-3 Figure 87 is a representative image of high or low expression of RBM15, ECT2, E-cadherin, β-catenin, and vimentin in 87 GC tumor tissues in the animal experiment and tissue chip of Example 1 of the present application; each scale bar represents 20 μm;

[0034] Figure 8-1 Figure 87 is a representative image of high or low expression of RBM15, ECT2, E-cadherin, β-catenin, and vimentin in 87 GC tumor tissues in the animal experiment and tissue chip of Example 1 of the present application; each scale bar represents 20 μm;

[0035] Figure 8-2 Figure 87 is a representative image of high or low expression of RBM15, ECT2, E-cadherin, β-catenin, and vimentin in 87 GC tumor tissues in the animal experiment and tissue chip of Example 1 of the present application; each scale bar represents 20 μm;

[0036] Figure 9-1 Figure 87 is a representative image of high or low expression of RBM15, ECT2, E-cadherin, β-catenin, and vimentin in 87 GC tumor tissues in the animal experiment and tissue chip of Example 1 of the present application; each scale bar represents 20 μm;

[0037] Figure 9-2RBM15 regulates the methylation modification of ECT2 dependent IGF2BP3 in Example 1 of the present application; I is that RIP-qPCR of MKN-45 cells shows that IGF2BP3 binds to ECT2 m6A modification sites; J is that RIP-qPCR of AGS cells shows that IGF2BP3 binds to ECT2 m6A modification sites; K is that RIP-qPCR of MKN-45 cells shows that IGF2BP3 binds to ECT2 m6A modification sites; L is the luciferase activity of 293T cells co-transfected with ECT2-WT or ECT2-Mut and vector or IGF2BP3; M is that RNA stability analysis of AGS cells shows that different transfection groups have different effects on the half-life of ECT2 mRNA; N is that RNA stability analysis of MKN-45 cells shows that different transfection groups have different effects on the half-life of ECT2 mRNA;

[0038] Figure 10-1 Results in Example 1 of the present application, wherein A is a forest plot of the OS Overall Survival and RFS Relapse-Free Survival of GC patients after ACRG database XP chemotherapy and TCGA database 5-FU chemotherapy by 23 m6A regulatory molecules; B is survival analysis of OS and RFS of XP chemotherapy in the ACRG database;

[0039] Figure 10-2 Results in Example 1 of the present application, wherein C is a comprehensive analysis of the relationship between RBM15 and the prognosis of OS, FPS, and PPS of GC patients using the GEO dataset of 5-fluorouracil; D is the IC50 of 5-FU in MKN-45 cells after treatment detected by CCK-8 method; E is the IC50 of 5-FU in AGS cells after treatment detected by CCK-8 method;

[0040] Figure 10-3 Results in Example 1 of the present application, wherein F is a mode diagram of GC organoids; G is western blot detection of the expression of RBM15 and ECT2 in organoids; H is CCK-8 method for detecting the cell viability of 5-FU treated CTRL: control, 5-FU: 5-fluorouracil 20μM after organoids; I is that tumor organoid drug sensitivity test detects the organoid diameter size of RBM15 high group and RBM15 low group at different time points after drug treatment CTRL: control, 5-FU: 5-fluorouracil 20μM; J is a flowchart of the present study. DETAILED DESCRIPTION

[0041] A number of illustrative embodiments of the present application will now be described in detail with reference to the drawings. The detailed description should be considered in connection with the accompanying drawings, which are not drawn to scale, and are provided to assist in understanding the present application.

[0042] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. Additionally, for a range of values of a parameter, unless otherwise stated, each intervening value of the parameter is also specifically included within the scope of the present application. The intervening values of the parameter are combined with a stated value of the parameter in range form. These are only exemplary of the various values that can be used, and others will suggest themselves to those skilled in the art upon a reading of the disclosure. Also, various "combinations" can be included within the scope of the application. These combinations refer to the various intervening values of the parameters included within the scope of the present application, as well as if such interventions are to be repeated with the same or different values of the parameters. The combinations are either periodic or non-periodic in their occurrence.

[0043] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice of the present application, the preferred methods and materials are described herein. All patents, patent applications, publications, and descriptions mentioned herein are incorporated by reference to disclose and describe the methods and / or materials in connection with which the patents, patent applications, publications, and descriptions are cited.

[0044] Many modifications and variations of this application can be made in the light of the above teachings without departing from the spirit and scope thereof. Additional implementations of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. The examples and embodiments described herein are exemplary and are not intended to be limiting of the application.

[0045] As used herein, the terms "comprise", "comprising", "include", "including", "have", "having" and the like are open-ended and do not exclude additional elements or steps.

[0046] Example 1

[0047] Example 1 of the present application verifies the effect of BM15 as a potential therapeutic target for GC treatment, and the specific steps are as follows:

[0048] (1) Tissue specimens and patient data: The first group was 84 gastric cancer tissue samples obtained from tissue microarray provided by Shanghai Xinsuobio Technology Co., Ltd. (China, Shanghai) from January 2011 to December 2012. The second group included 29 gastric cancer tissue samples from patients who underwent gastrectomy at Shandong Provincial Hospital (China, Shandong) from January 2019 to December 2022. Human materials were obtained with the informed consent of the patients, and the study was approved by the Clinical Research Ethics Committee (National Natural Science Foundation: NO. 2021-529). Prior to the present invention, all patients had not received neoadjuvant chemotherapy. (2) Collection and preprocessing of publicly available datasets: Gene expression profile data and clinical annotations of gastric cancer samples were retrospectively collected from NCBI-GEO (https: / / www.ncbi.nlm.nih.gov / geo / ) and TCGA (https: / / cancergenome.nih.gov / ) publicly accessible datasets. The datasets included GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, and GSE62254 (ACRG) datasets. The RNA sequencing data of TCGA was in FPKM format, downloaded from the UCSC Xena database (https: / / gdc.xenahubs.net / download / TCGA-STAD.htseq_fpkm.tsv.gz).

[0049] (3) RBM15 and prognosis analysis of gastric cancer: metscape and gene set enrichment analysis (GSEA)

[0050] This invention screened a group of 23 m6A modification-related genes (Chong, W., et al., m(6)Aregulator-based methylation modification patterns characterized by distinct tumor microenvironment immune profiles in colon cancer.). Protein-protein interaction enrichment analysis was then performed using Metascape. Furthermore, this invention employed the GSEA algorithm and utilized the R package “clusterProfiler” to examine biological process changes in different RBM15 expression subgroups. Well-defined biomarkers were obtained from Hallmark, Reactome, and KEGG gene sets, which were downloaded from the MSigDB database v7.1 (Chen, H., et al., Molecular characterization and clinical relevance of metabolic signature subtypes in gastric cancer).

[0051] Metascape analysis of 23 m6A regulatory molecules revealed that these factors are mainly involved in pathways related to mRNA modification, transport, destabilization, and progression. Figure 1-1 To elucidate the interactions and prognostic significance of these m6A regulatory factors in gastric cancer, this invention performed correlation and prognostic analyses ( ). Figure 1-1 (B, C, D, E, F). Notably, in both the ACRG and TCGA cohorts, patients with high RBM15 expression showed significantly better prognoses.

[0052] Mutation spectrum analysis showed that RBM15 had a mutation frequency of 3% in GC, ranking among the top three in the m6A molecule. Figure 2 Further analysis of the co-mutation rates of 23 m6A regulatory factors revealed significant differences in the co-mutation rates of RBM15 with ELAVL1, IGF2BP2, YTHDC2, and YTHDF1 / 2. Figure 2 Correlation analysis using data from the TCGA and ACRG databases revealed that RBM15 is closely correlated with several other m6A regulatory factors, indicating that it plays a key role in the m6A regulatory network. Figure 2C and D in Section 1-1). Previous studies have identified several GC molecular subtype nomenclatures based on transcriptomic and genomic analyses. The present application further performed tissue microarray analysis on 84 gastric cancer patients and found that the RBM15 high expression subgroup patients had better prognosis. In addition, by integrating microarray data from multiple GEO databases (including GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, GSE62254), the present application further verified that the high expression of RBM15 was associated with the long-term survival of gastric cancer patients Figure 1-2 H and I in Section 1). The present application also explored the relationship between RBM15 expression and previously identified molecular subtypes Figure 1-2 J in Section 1). In the TCGA cohort, RBM15 was highly expressed in the EBV and MSI subtypes, both of which were associated with good prognosis Figure 1-2 K in Section 1). Similarly, in the ACRG cohort, RBM15 was upregulated in the MSI and MSS / TP53+ subtypes Figure 1-2 L and M in Section 1).

[0053] (2) RBM15 inhibits the proliferation, migration and invasion of GC cells: To explore the functional role of RBM15 in gastric cancer cells, the present application performed a series of experiments: A, cell culture and transfection

[0054] AGS cells and MKN-45 cells were purchased from the American Type Culture Collection (ATCC). AGS and MKN-45 cells were cultured in RPMI 1640 medium (Gibco) containing 10% fetal bovine serum (PAN), penicillin (10 U / mL, Thermo) and streptomycin (10 U / mL, Thermo). Cells were cultured in a 37°C, 5% CO2 saturated humidity incubator. For experiments, AGS and MKN-45 cells were seeded in 6-well plates at a density of 2x10 5 RBM15 and ECT2 knockdown or overexpression lentiviral vectors were prepared, as well as their respective blank control vectors, from Genechem (Shanghai). Transfection was performed according to the transfection reagent instructions. After transfection, cells were selected with puromycin (0.5 μg / ml, MedChemExpress) for 7 days. siRNA targeting IGF2BP3 was purchased from Keyybio (Shandong, China).

[0055] B, CCK-8 assay: One day before the experiment, cells were seeded in 96-well plates at a density of 5x10 3Cells were seeded at a density per well in 96-well plates. Cell proliferation assays were performed using the Cell Counting Kit-8 (DojinDo, Japan) according to the manufacturer's instructions. Absorbance was measured at 0 h, 24 h, 48 h, 72 h, and 96 h to assess cell viability and proliferation.

[0056] C. Clonogenesis experiment: Cells were inoculated at a rate of 2 × 10⁻⁶ 3 The cells were seeded at a density of 1 cell per well in 6-well plates and incubated at 37°C for 7 days, with the culture medium changed every 4 days. After the incubation period, colonies containing more than 50 cells were observed and counted under an optical microscope.

[0057] D. Transwell assay: To perform cell invasion and migration analysis, 200 μL of cell suspension in serum-free medium (migration: 3 × 10⁻⁶) was used. 5 / mL, invasion: 5×10 5 Cells were inoculated onto Transwell inserts (Corning) at a density of 1 / mL. For invasion assays, the inserts were pre-coated with Matrigel, while for migration assays, no Matrigel coating was applied. The lower cavity was filled with 600 μl of intact culture medium. After hatching, cells on the Transwell inserts were fixed in PBS with 4% paraformaldehyde for 30 minutes. Subsequently, they were stained with crystal violet (Sigma-Aldrich) for 30 minutes.

[0058] E. Wound Healing Assay: Cells were seeded in 6-well plates and cultured until confluence exceeded 95%. The monolayer was then scraped along the central axis using a sterile plastic tip, and loose cells were washed with PBS. The culture medium was replaced with low-serum medium (1%). Cell motility was quantified by measuring the distance between cell edges at three randomly selected microscopic fields (×100 magnification) at each time point (0h, 24h, 48h).

[0059] In clone formation experiments ( Figure 3-1 (B) and Cell Counting Kit-8 (CCK-8) Experiment ( Figure 3-1 In the study (C), knockdown of RBM15 in AGS cells led to a significant increase in cell proliferation, while overexpression of RBM15 in MKN-45 cells led to a significant decrease in cell proliferation.

[0060] In addition, the Transwell experiment ( Figure 3-1 D, E, H) and wound healing experiment ( Figure 3-2 The results showed that RBM15 knockdown significantly enhanced cell migration and invasion, while RBM15 overexpression inhibited these behaviors. Figure 3-1 F, G, I and Figure 3-2(L, M). Further co-culture experiments with HLECs revealed that knocking down RBM15 increased the lymphangiogenic capacity of HLECs. Figure 3-2 In the middle N and O), overexpression of RBM15 weakened lymphangiogenesis ( Figure 3-2 (P and Q). Furthermore, knocking down RBM15 improved the migration ability of HLECs (P and Q). Figure 3-2 In the middle R and S), overexpression of RBM15 inhibited the migration ability of HLECs (R and S), while overexpression of RBM15 inhibited the migration ability of HLECs (R and S). Figure 3-2 Middle T, U).

[0061] In summary, these findings highlight the role of RBM15 as a tumor suppressor in gastric cancer, emphasizing its important function in regulating the proliferation, migration, and invasion of gastric cancer cells in vitro.

[0062] (3) RBM15 regulates the EMT pathway

[0063] To investigate the biological significance of RBM15 dysregulation, this invention performed gene set enrichment analysis (GSEA) to compare high- and low-expression subgroups of RBM15 in the ACRG database. Using the KEGG, REACTOME, and HALLMARK pathway datasets, GSEA revealed that RBM15 is involved in the regulation of m6A methylation-related functions, including RNA processing and splicing. Furthermore, RBM15 is also involved in the regulation of EMT, cell adhesion, and TGF-β signaling pathways. Figure 4-1 (A, B, C). Molecular subtype analysis further confirmed that RBM15 expression was downregulated in the EMT subtype. Figure 1-2 (Middle L and M).

[0064] Correlation analysis showed that RBM15 was significantly negatively correlated with matrix markers such as CDH2 (N-cadherin), VIM, ZEB2, TWIST, and SNAI2 in GC, while it was significantly positively correlated with epithelial markers such as CDH1 (E-cadherin). Figure 4-1 D, E and Figure 5-1 (A, B, C, D, E)

[0065] To further elucidate its mechanism, this invention performed RNA-seq on RBM15-knockdown GC cells. Figure 4-1 (China F). GSEA results reinforce the involvement of RBM15.

[0066] In pathways related to focal adhesion, ecm receptor interaction, etc. Figure 4-1 (G). qPCR analysis showed that RBM15 knockdown led to decreased CDH1 RNA levels and increased levels of CDH2, CTNNB1, and Vimentin. Figure 4-1 (H). Conversely, RBM15 overexpression has the opposite effect (H).Figure 4-1 Western blot and immunofluorescence (IF) detection confirmed these findings, showing similar trends Figure 4-2 Western blot and immunofluorescence (IF) detection confirmed these findings, showing similar trends Figure 5-1 Western blot and immunofluorescence (IF) detection confirmed these findings, showing similar trends

[0067] (4) RBM15 mediates EMT signaling pathway through regulated ECT2

[0068] A, Real-time quantitative PCR (qPCR)

[0069] Total RNA was extracted from cells with Trizol reagent (Vazyme, China). Then RNA was reverse transcribed into cDNA using HiScript III RT SuperMix for qPCR (Vazyme, China) according to the manufacturer's instructions. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed on an Applied Biosystems QuantStudio1 real-time PCR system (Applied Biosystems, ThermoFish) using ChamQ Universal SYBR qPCR Master Mix (Vazyme, China) to detect mRNA expression levels. The primer sequences used for qRT-PCR are shown in Table S1. GAPDH was used as an internal control gene for mRNA normalization. The relative expression of mRNA was calculated using the 2-ΔΔCt method, and a higher 2-ΔΔCt value indicates a higher gene expression level.

[0070] B, Western blot analysis and antibody detection

[0071] Briefly, total cell lysate was prepared using cell lysis buffer and then denatured by boiling. Protein concentration was determined using a BCA protein assay kit (Solarbio). Equal amounts of protein were separated by SDS-PAGE at 80V for 2.5h and then transferred to a PVDF membrane for 1.5h. After transfer, the membrane was washed with 1% TBST for 3 times, 5 minutes each time.

[0072] Primary antibodies RBM15 (Proteintech, 10587-1-AP), ECT2 (Santa Cruz, sc- 514750), E-cadherin (Proteintech, 60335-1-Ig), N-cadherin (Proteintech, 66119-1-ig), Vimentin (Proteintech, 60330-1-Ig), β-catenin (Proteintech, 66379-1-Ig), IGF2BP3 (Proteintech, 14642-1-AP) and β-actin (Proteintech, 20536-1-AP) were incubated with membranes overnight at 4°C. Then membranes were incubated with secondary antibodies (Proteintech, SA00001 and SA00002) according to standard protocols.

[0073] C. In vivo experiments

[0074] Balb / c male nude mice, 4-5 weeks old, weighing 20-25 g, were purchased from Vital River Laboratories (Beijing, China). In the tumor growth study, 10 mice per group were used to evaluate the effect of RBM15 overexpression and its respective control vector. Each mouse was subcutaneously injected with 100 μl of transfected lentivirus tumor cells (5 x 10 6 ). Tumor volume was measured every 2 days. After 4 weeks, the tumor was collected, the volume and weight were measured, and the photograph was taken. This study was approved by the Clinical Research Ethics Committee (NSFC: NO. 2021-529).

[0075] C. Transwell assay

[0076] For cell invasion and migration analysis, cell suspensions in 200 μL serum-free medium (migration: 3 x 10 5 / mL, invasion: 5 x 10 5 / mL) were seeded onto Transwell inserts (Corning). For invasion assays, the inserts were pre-coated with a Matrigel coating, while for migration assays, they were not coated with Matrigel. The lower chamber was filled with 600 μL complete medium. After incubation, the cells on the transwell inserts were fixed with 4% paraformaldehyde in PBS for 30 minutes. Subsequently, they were stained with crystal violet (Sigma-Aldrich) for 30 minutes.

[0077] To determine the potential regulatory targets of RBM15 in GC, the inventors performed a joint analysis of differentially expressed genes (DEGs) in RBM15 knockdown cells combined with data from TCGA and ACRG databases.

[0078] This analysis identified 604 RBM15-associated DEGs, including ECT2, ARHGAP5, HIPK2, TJP2, COL17A1, and MATR3, among others Figure 6-1 A and Figure 5-2 K, L, M). qPCR and western blot assays confirmed that ECT2 is a downstream target of RBM15 Figure 6-1 B and C). RBM15 knockdown or overexpression altered the RNA and protein levels of ECT2 Figure 6-1 D, E). Survival analysis showed that GC patients with high ECT2 expression had improved prognosis in both ACRG and TCGA databases Figure 6-1 F, G). By integrating RBM15 and ECT2 expression subgroups, the inventors classified GC samples into four categories: RBM15-low / ECT2-low, RBM15-low / ECT2-high, RBM15-high / ECT2-high, and found that the RBM15-low / ECT2-low subgroup had the worst prognosis Figure 6-1 H, I in 6-2). Correlation analysis showed that ECT2 was significantly positively correlated with RBM15 Figure 6-2 J), and significantly negatively correlated with emt-related molecules CDH2, VIM, ZEB2, TWIST, and SNAI2 Figure 6-2 K). Enrichment analysis based on the differential expression of ECT2 also highlighted its role in inhibiting the EMT process Figure 6-2 L, N). These findings suggest that, like RBM15, ECT2 plays a crucial role in the negative regulation of the EMT process.

[0079] To further assess the effect of RBM15 on the progression of GC cells in vivo, the inventors subcutaneously injected MKN-45 cells overexpressing RBM15 into mice (n=20). As expected, the tumor volume and weight were reduced in the RBM15 overexpression group compared to the vector control group Figure 7-1CDH1 and ECT2 expression increased, while CDH2, CTNNB1 (β-catenin) and vimentin expression decreased in RBM15 overexpression group (D, E in 7-1). Immunohistochemical analysis further confirmed these findings, with stronger staining of RBM15, ECT2 and E-cadherin, and weaker staining of N-cadherin, β-catenin and vimentin in RBM15 overexpression group compared to the vector group (F in 7-2).

[0080] The present application also explored the clinical relevance of RBM15, ECT2, E-cadherin, β-catenin and vimentin in GC through tissue chip analysis (n=29) Figure 7-3 Immunohistochemical analysis showed that ECT2 and E-cadherin expression significantly increased, while β-catenin and vimentin expression significantly decreased in RBM15-high tumor tissues.

[0081] Although the key role of RBM15 in EMT signaling pathway GC development has been established, further studies are needed to determine whether these effects are mediated through ECT2. To explore this, the present application transfected AGS cells with shRBM15 and / or overexpressed ECT2, and transfected MKN-45 cells with RBM15 overexpression and / or shECT2. These modified cells were then subjected to various functional assays. As shown in Figure 8-1 As shown in Figs. 7A and 7B, colony formation experiments and CCK-8 experiments showed that ECT2 overexpression restored the proliferative capacity of GC cells caused by RBM15 knockdown. Conversely, shECT2 reversed the reduced cell proliferation caused by RBM15 overexpression.

[0082] Transwell experiments further showed that ECT2 overexpression restored the migration and invasion capacity of GC cells reduced by RBM15 overexpression, while shECT2 restored the migration and invasion capacity of RBM15 overexpression cells Figure 8-1 Figs. 7C and 7D, Figure 8-2 Fig. 7E, Figure 8-2 Fig. 7F). In addition, ECT2 overexpression counteracted the upregulation of N-cadherin and vimentin and the downregulation of E-cadherin induced by RBM15 knockdown. Conversely, ECT2 knockdown reversed the inhibitory effect of RBM15 overexpression on the EMT process Figure 8-2 Figs. 7G and 7H).

[0083] (5) RBM15 mediates ECT2 methylation and regulates EMT through IGF2BP3

[0084] A, MeRIP experiment

[0085] RNA extraction was performed as previously described, 2 μg of total RNA was used for MeRIP-PCR (P-9018-24, EpigenTek) following the manufacturer's protocol. 1% agarose gel was prepared and run at 100 V for 1 h to detect the methylation level of RNA.

[0086] B, Luciferase reporter assay

[0087] 293T cells were seeded in 24-well plates and transfected with luciferase reporter or Renilla reporter, and RBM15 overexpression plasmid or control vector. Absorbance was measured within 48 h after transfection.

[0088] C, RIP-qPCR and RNA pulldown experiment

[0089] RIP-qPCR: Cells were lysed with tris-triton buffer and incubated with protein A / G magnetic beads pre-coupled with IGF2BP3 antibody. After overnight incubation, magnetic beads were washed and the bound RNA on the beads was detected by qPCR.

[0090] RNA pulldown: Biotin-labeled ECT2 transcript was incubated with streptavidin magnetic beads. Then cell lysate prepared with tris-triton buffer was incubated with magnetic beads for 6 h. Western blot was used to detect the IGF2BP3 protein level.

[0091] To investigate the molecular mechanism of RBM15 regulating m6A modification in GC, the inventors quantified the m6A methylation level in GC cells with RBM15 knockdown or overexpression using EpiQuik m6A RNA Methylation Quantification Kit. The results showed that the m6A methylation level was significantly reduced after RBM15 inhibition, and the methylation level was increased after RBM15 overexpression (Figures 6A and 6B). Further analysis using the SRAMP methylation prediction website identified potential m6A sites (Figure 6C). MeRIP analysis showed that RBM15 downregulation reduced the m6A modification of ECT2 mRNA, while RBM15 overexpression enhanced this modification (Figures 6D and 6E). Based on SRAMP analysis, the inventors mutated the AAAC T sequence at 2909 bp of the 3'UTR to AACCT and performed luciferase assay. The results showed that RBM15 overexpression significantly increased the relative luciferase activity of WT-ECT2, while the mutt-ECT2 group was resistant to the effect of RBM15 overexpression (Figure 6F). Figure 9-1 Figure 9-1 Figure 9-1 Figure 9-1

[0092] ​​​​The regulatory role of “m6A readers” in m6A-modified transcripts is crucial. This invention first used an RNA pull-down assay to detect the enrichment of IGF2BP3 binding to ECT2 mRNA. Figure 9-1 (G). RIP-qPCR assay confirmed that IGF2BP3 binds to ECT2 mRNA in AGS and MKN-45 cells. Figure 9-1 H, Figure 9-2 (I). Furthermore, RIP-qPCR showed that RBM15 knockdown attenuated the direct interaction between IGF2BP3 and ECT2 mRNA in GC cells, while RBM15 overexpression enhanced this interaction. Figure 9-2 (J, K).

[0093] Further luciferase assays with the AGACA 3'UTR 2887bp mutation showed that WT-ECT2 luciferase activity significantly increased with IGF2BP3 overexpression, while the mutt-ect2 group exhibited resistance to the effects of IGF2BP3. Figure 9-2 (L). Furthermore, actinomycin treatment showed that ECT2 stability was decreased in the shRBM15 group compared to the control group, while ECT2 stability was increased in the RBM15 overexpression group compared to the vector control. Figure 9-2 (N).

[0094] In summary, these findings further confirm that RBM15-mediated ECT2 modification via m6A enhances ECT2 stability through IGF2BP3.

[0095] (6) RBM15 enhances the 5-fluorouracil sensitivity of gastric cancer cells.

[0096] Gastric cancer tissue from a patient with gastric GC after gastrectomy; the GC tissue is approximately 0.5 cm in size. 3 Rinse three times in DPBS containing antibiotics, then cut into 1mm pieces. 3The fragments were incubated in 10-15 ml of the digestion solution at 37 °C for 30 min to 1 h. The resulting suspension was filtered through a purification mesh and centrifuged at 2000 G for 5 min at 4 °C. The cell pellet was resuspended in red blood cell lysis buffer and the cells were collected by centrifugation again. The cell pellet was then mixed 1 : 1 with Matrigel (BD Biosciences, California, USA) and seeded into a 24-well plate. After the digestion of the organoids, 50 organoid fragments (containing 250 cells) were mixed with 10 ul Matrigel and seeded into each well of a 96-well plate. The average diameter of the PDOs was allowed to grow to 50 μΜ, and 10 μΜ of 5-Fu (selleckchem, USA) was dissolved in DMSO for treatment. The images of the PDOs were taken every 3 days. After 9 days, the cell viability was measured using the CellTiter-Lumi™ Luminescent 3D Cell Viability Assay Kit (Beyotime, Shanghai, China). Briefly, the organoids were mixed with 100 μL of CellTiter-Glo® 3D Reagent, shaken for 5 min, and incubated at room temperature for 30 min. The average diameter was analyzed using the brightfield images of the images J. by fluorescence absorption method using a spectrophotometer.

[0097] To further investigate the role of RBM15 in regulating drug sensitivity, the present application analyzed sequencing data of GC patients treated with 5-fluorouracil in ACRG and TCGA cohorts. The ACRG database includes 91 GC patients treated with XP regimen (5-fluorouracil and cisplatin), while the TCGA cohort includes 68 patients treated with 5-fluorouracil chemotherapy. Cox regression analysis of 23 m6A regulatory molecules showed that GC patients with high expression of RBM15 had improved prognosis after 5-fluorouracil chemotherapy, suggesting that 5-fluorouracil chemotherapy can provide greater benefit to patients Figure 10-1 Kaplan-Meier survival analysis further showed that GC patients with high expression of RBM15 had longer OS and RFS when receiving XP chemotherapy Figure 10-1 Figure 10-2 This finding was confirmed by independent GEO datasets, indicating that patients with high expression of RBM15 can benefit from 5-fluorouracil treatment Figure 10-2 In contrast, RBM15 knockdown reduced the sensitivity of GC cells to 5-fluorouracil treatment Figure 10-2

[0098] The present application proposes to establish gastric cancer organoids from patients Figure 10-3 ​​Fig. 6C. These organoids reflect the complex dynamics of the response to chemotherapy. It can provide a valuable tool for improving personalized treatment and predicting the response of individual patients to chemotherapy. In the organoid culture, the present application divided the samples into RBM15-high group and RBM15-low group according to the expression of RBM15. The RBM15-high group included #1, #2 and #3, while the RBM15-low group included #4, #5, #6. Western blot analysis showed that the RBM15 and ECT2 expression levels of the RBM15-high expression group were higher than those of the RBM15-low expression group Figure 10-3 Fig. 6D. CCK-8 test found that the RBM15-high group had higher sensitivity to 5-fluorouracil than the RBM15-low group Figure 10-3 Fig. 6E. In addition, tumor organoid drug sensitivity test showed that the organoids of the RBM15-high group were smaller in diameter than those of the RBM15-low group after 5-fluorouracil treatment Figure 10-3 Fig. 6F. In summary, these findings suggest that RBM15 enhances the sensitivity of GC cells to 5-fluorouracil.

[0099] The above description is only preferred embodiments of the present application, and it should be pointed out that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. Use of a recombinant lentivirus overexpressing RBM15 in the preparation of a medicament for enhancing the sensitivity of gastric cancer cells to 5-fluorouracil.

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