Application of VIRMA as prognosis biomarker and treatment target of gastric cancer

Abstract

The invention relates to the technical field of biological medicine, in particular to application of VIRMA as a prognosis biomarker and a treatment target of gastric cancer. The invention discovers that the VIRMA can be used as a prognosis biomarker and a treatment target of the gastric cancer, a new thought is provided for monitoring prognosis of the gastric cancer, and the VIRMA can play a positive role in treatment of the gastric cancer by inhibiting overexpression of the VIRMA and utilizing a VIRMA inhibitor drug.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to the application of VIRMA as a prognostic biomarker and therapeutic target for gastric cancer. Background Art

[0002] Gastric cancer is the fifth most common cancer in the world and the fourth leading cause of cancer-related death. Patients with gastric cancer are often diagnosed in an advanced stage, and gastric cancer is characterized by extensive metastasis, which significantly worsens their prognosis. Despite great progress in the treatment of gastric cancer, including neoadjuvant therapy, immunotherapy, targeted therapy, etc., a portion of patients with advanced gastric cancer still do not respond to these treatments, resulting in unsatisfactory treatment results and poor prognosis. In recent years, tumor research has penetrated into the molecular and other microscopic levels in order to discover and decipher the mechanisms of tumor development. In view of this background, it is crucial to further study the changes in biological functions driven by genetic alterations in gastric cancer and their related therapeutic targets. Such studies may promote the development of targeted treatment strategies, enhance the personalization and efficacy of treatment, and thus improve the prognosis of gastric cancer patients.

[0003] N6-methyladenosine (m6A) modification is the most abundant modification in eukaryotic mRNA and is involved in regulating almost all RNA metabolic processes. The role of m6A modification includes, but is not limited to, regulating mRNA stability, splicing, translocation, localization and translation, and RNA-protein interactions. This modification is dynamically reversible and mainly depends on the interaction between methyltransferases, demethylases, and methylation reader proteins. Specific methyltransferases, such as METTL3 / 4, WTAP, and VIRMA, promote m6A motif conversion and directly or indirectly affect RNA function. Recent studies have shown that m6A modification can affect RNA function by affecting RNA splicing, translation, stability, and degradation. Viral-like m6A methyltransferase-associated protein (VIRMA) functions as part of a methyltransferase complex. It is thought to act as a scaffold for the methyltransferase complex, guiding the installation of m6A at specific sites and modifying coding and non-coding RNAs. With the deepening of research on VIRMA, its role in various cancers, including liver cancer, lung cancer, colon cancer, etc., has been increasingly discovered. However, a review of existing studies suggests that the relationship between VIRMA and gastric cancer remains underexplored.

[0004] Cysteine- and glycine-rich protein 1 (CSRP1) belongs to the cysteine-rich protein family, which is characterized by a unique dual zinc finger motif and plays a vital role in cell differentiation. CSRP1 is associated with various processes of tumorigenesis and cell transformation. The expression of CSRP1 is significantly increased in breast cancer and is associated with RNA binding function. Studies on colon cancer have shown that high expression of CSRP1 promotes the growth of colon adenocarcinoma and is associated with poor prognosis. However, the mechanism of CSRP1 in the occurrence and development of gastric cancer remains largely unexplored. Summary of the invention

[0005] The technical problem to be solved by the present invention is that in view of the deficiencies of the above-mentioned prior art, the present invention aims to study the role of VIRMA in gastric cancer and to clarify its potential mechanism for promoting lymphatic metastasis. Our results show that the expression of VIRMA in gastric cancer is significantly upregulated and is associated with poor survival outcomes. Both in vitro and in vivo experiments have shown that VIRMA can enhance the proliferation and metastasis of gastric cancer cells. Mechanistically, VIRMA stabilizes its mRNA in an m6A-YTHDF1-dependent manner and thus upregulates CSRP1 expression. These results identify VIRMA as a potential prognostic biomarker and a promising therapeutic target in gastric cancer.

[0006] In order to achieve the purpose of the present invention, the following technical scheme is adopted: Application of VIRMA as a prognostic biomarker and therapeutic target for gastric cancer.

[0007] VIRMA is a prognostic biomarker for gastric cancer. VIRMA expression affects gastric cancer progression and lymph node metastasis. The expression of VEGF-C, a marker of lymph node metastasis, increases with VIRMA overexpression.

[0008] As a prognostic biomarker for gastric cancer, VIRMA affects the proliferation, migration, and invasion of gastric cancer cells by regulating CSRP1.

[0009] As a prognostic biomarker for gastric cancer, VIRMA mediates the methylation of CSRP1 through m6A modification and regulates the expression profile of CSRP1 through YTHDF1, affecting the malignant progression of gastric cancer.

[0010] VIRMA, as a prognostic biomarker for gastric cancer, regulates Hippo-YAP signaling by interacting with CSRP1. When VIRMA is overexpressed, Hippo-YAP signaling is promoted.

[0011] As a specific technical solution of the present invention: an application of VIRMA as a prognostic biomarker for gastric cancer in the preparation of a kit for prognosis monitoring of gastric cancer.

[0012] Preferably, the kit further comprises other gastric cancer prognosis monitoring reagents.

[0013] Another specific technical solution of the present invention is: use of a VIRMA inhibitor in the preparation of drugs related to the treatment of gastric cancer, wherein the drug targets VIRMA and inhibits overexpression of VIRMA.

[0014] Preferably, the drug further comprises other possible acceptable carriers.

[0015] Preferably, the drug works in any of the following ways: a. Inhibit the proliferation, migration and invasion of gastric cancer cells; b. Regulate or inhibit lymph node metastasis in gastric cancer.

[0016] Compared with the prior art, the present invention achieves the following technical effects: The present invention finds that VIRMA can be used as a prognostic biomarker and therapeutic target for gastric cancer, providing a new idea for monitoring the prognosis of gastric cancer, and can have a positive effect on the treatment of gastric cancer by inhibiting the overexpression of VIRMA and using VIRMA inhibitor drugs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] For ease of explanation, the present invention is described in detail with reference to the following specific embodiments and the accompanying drawings.

[0018] Figure 1 shows the involvement of VIRMA in regulating lymph node metastasis in gastric cancer, including (A) the interaction network of VIRMA and various m6A-related genes; (B) schematic diagram of the two domains of VIRMA: N-terminus (1-1130aa) and C-terminus (1131-1812aa), which are involved in m6A RNA methylation. (C) Comparison of VIRMA expression levels in GC tissues and non-tumor tissues.

[0019] Figure 2 Figure 2 shows Kaplan-Meier analysis and co-mutation rate and correlation analysis between VIRMA and common m6A modification molecules. (D) Kaplan-Meier analysis of overall survival (OS) and post-progression survival (PPS) of GC patients, stratified by VIRMA mRNA expression level; (E) Co-mutation rate and correlation between VIRMA and common m6A modification molecules in the TCGA GC cohort.

[0020] Figure 3Pathway enrichment analysis and box plots for VIRMA, where (F) Pathway enrichment analysis of VIRMA in GC using KEGG, REACTOME, and HALLMARK datasets; (G) Box plots showing VIRMA expression in negative (LN (-)) and positive (LN (+) metastatic lymph nodes; the left panel compared all gastric cancer patients (p = 0.041), and the right panel focused on T3 and T4 stage patients (p = 0.0055); higher VIRMA expression was associated with lymph node metastasis, especially in advanced gastric cancer; (H) Correlation between VIRMA expression and the total number of lymph nodes and the number of positive lymph nodes.

[0021] Figure 4 Figures are immunohistochemical analysis, where (I) Immunohistochemical analysis shows the expression of VIRMA in cancer and adjacent noncancerous tissues and in negative and positive lymph nodes on microarray.

[0022] Figure 5 Figure 1 shows the effects of VIRMA overexpression and knockdown on GC cells, where (A) quantitative PCR (qPCR) and Western blot analysis confirmed the efficacy of VIRMA knockdown and overexpression. (B) Representative images of colony formation assays show the effects of VIRMA manipulation on GC cell colony formation. (C) GC cell proliferation assessed by CCK-8 assay after VIRMA overexpression and knockdown. (D) Scratch healing assay illustrates the effects of VIRMA on wound healing of GC cells.

[0023] Figure 6 Figure 3 (E) Representative images of migration and invasion assays in VIRMA-overexpressed and -knocked-down GC cells.

[0024] Figure 7 The figures are micrographs, wherein (F) micrographs show tubule formation of HLEC cells treated with conditioned medium of VIRMA-overexpressing or -knockdown GC cells; (G) micrographs show migration of HLEC cells treated with conditioned medium of VIRMA-overexpressing or -knockdown GC cells.

[0025] Figure 8Figure 3 shows the effects of VIRMA knockdown in vitro and in vivo, where (A) quantitative PCR (qPCR) analysis confirmed the efficacy of VIRMA knockdown in GC cells; (B) Western blot analysis confirmed the efficacy of VIRMA knockdown in GC cells; (C) representative images of colony formation assay, showing the effect of VIRMA knockdown on GC cell colony formation; (D) GC cell proliferation assessed by CCK-8 assay after VIRMA knockdown; (E) scratch healing assay illustrates the effect of VIRMA knockdown on GC cell wound healing.

[0026] Fig. 9 Representative images of migration and invasion assays in VIRMA-knockdown GC cells and diagram of established xenograft model, where (F) Representative images of migration and invasion assays in VIRMA-knockdown GC cells; (G) Xenograft model was established in BALB / c mice by axillary injection of HGC-27 / shNC and HGC-27 / shVIRMA cells (n=5 / group).

[0027] Fig.10 Figure 2 is a graph of tumor weight and volume, where (H) tumor weight of xenograft mice was measured; (I) tumor volume of xenograft mice was measured.

[0028] Fig.11 Figure 2 shows the immunohistochemical analysis of xenograft tumors. (J) Immunohistochemical analysis of VIRMA, Ki-67, VEGF-C and LYVE-1 expression in xenograft tumors.

[0029] Fig.12 Figures for the analysis of CSRP1 as a downstream regulatory target of VIRMA, where (A) Venn diagram showing downregulated genes after VIRMA knockdown, star plot illustrating the distribution of genes with differential (high or low) methylation levels (Y-axis; |fold change|≥2) and differential (up or down) gene expression levels (X-axis; |fold change|≥2) in shVIRMA compared with the control group; (B) heat map showing representative gene expression in response to VIRMA knockdown.

[0030] Fig.13 The expression analysis diagram of downstream genes after VIRMA overexpression and knockdown is shown in Figure 1, where (C) quantitative PCR (qPCR) was performed to verify the expression of downstream genes after VIRMA overexpression and knockdown; (D) Western blot was performed to verify the expression of downstream genes after VIRMA overexpression and knockdown.

[0031] Fig.14 Figure 2 Effects of VIRMA expression changes, where (E) attenuation of VIRMA reduces the m6A modification of CSRP1 mRNA in GC cells; (F) Top sequence motifs identified from MeRIP-seq peaks in shNC and shVIRMA cells; (G) MeRIP assay was performed to verify the effect of VIRMA expression changes on the m6A modification of CSRP1 mRNA.

[0032] Fig.15 Figure 2 shows the correlation analysis of relative luciferase activity and ‘reader’ protein and gene expression, including: (H) relative luciferase activity of wild-type (WT) or mutant (Mut) (A to G mutation) CSRP1 luciferase reporter gene in vector and VIRMA overexpression cell lines; (I) correlation analysis of ‘reader’ protein and gene expression in the ACRG database.

[0033] Fig.16 RNA pull-down assay and RIP-qPCR show the binding of YTHDF1 to CSRP1 mRNA, where (J) RNA pull-down assay confirmed the binding of CSRP1 to the “reader” protein in GC cells. (K) RIP-qPCR shows the binding of YTHDF1 to CSRP1 mRNA and the enrichment of m6A modification sites.

[0034] Fig.17 Figure 2 shows the results of VIRMA regulating GC cell behavior by regulating CSRP1, including: (A) quantitative PCR (qPCR) analysis to verify the overexpression and knockdown efficiency of CSRP1 in gastric cancer cells; (B) Western blot analysis to verify the overexpression and knockdown efficiency of CSRP1 in gastric cancer cells; (C) representative images of colony formation analysis; (D) quantification of gastric cancer cell proliferation using CCK-8 assay.

[0035] Fig.18 Figure 2 shows the analysis of the scratch wound healing assay, where (E) Representative images of the scratch wound healing assay in CSRP1 overexpressed and knocked-down gastric cancer cells.

[0036] Fig.19 Figure 2 shows the analysis of migration and invasion assays after overexpression and knockdown of CSRP1. (F) Representative images of migration and invasion assays after overexpression and knockdown of CSRP1 in gastric cancer cells.

[0037] Fig. 20Figure 2 shows the tubule formation of HLEC cells, where (G) Micrographs depict tubule formation of HLEC cells treated with culture medium of gastric cancer cells transfected with oe-CSRP1 and siCSRP1.

[0038] Fig.21 Figure 2 shows the tubule migration of HLEC cells, where (H) Micrographs depict the migration of HLEC cells treated with culture medium of gastric cancer cells transfected with oe-CSRP1 and siCSRP1.

[0039] Fig. 22 Figure 3. VIRMA promotes lymphatic metastasis by activating the Hippo-YAP pathway in GC cells, where (A) the VIRMA expression score was generated using transcriptome data from 33 paired cancer and adjacent non-tumor samples; (B) phosphoproteomic analysis of the 33 paired samples was performed to examine the correlation between VIRMA protein levels and p-YAP; (C-D) Western blot analysis was performed to explore the relationship between VIRMA and CSRP1 expression and Hippo-YAP pathway activation; (E) Flowchart of this study (provided by Figdraw). DETAILED DESCRIPTION

[0040] The following are specific embodiments of the present invention and are combined with the attached Figure 1-22 , the technical solution of the present invention is further described, but the present invention is not limited to these embodiments; in the following description, specific details such as specific configurations are provided only to help fully understand the embodiments of the present invention.

[0041] Example This example uses several user-friendly databases and tools for analysis, including the Cancer Genome Atlas (TCGA) database (https: / / portal.gdc.cancer.gov), the Human Protein Atlas (https: / / www.proteinatlas.org / ), StarBase (https: / / starbase.sysu.edu.cn / ), the Kaplan-Meier plotter (KMplot) (http: / / kmplot.com) and the Venn diagram (http: / / bioinfogp.cnb.csic.es / tools / venny / index.html). The genetic profile data and clinical data of gastric cancer patients were downloaded from the TCGA database, and clinical data such as survival time and survival status were extracted and merged using Perl software. The "Limma" R package was used to analyze the differences in gene expression between patients. Subsequently, the Annotation, Visualization and Integrated Discovery Database (www.david.niaid.nih.gov) and the KEGG database (http: / / www.genome.jp / kegg / ) were used for gene ontology and pathway analysis, respectively.

[0042] 1.1 Human gastric cancer tissue This example was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Ethics Committee of Shandong Provincial Hospital (NO.2023-497). Written informed consent was obtained from all enrolled patients. Tumor tissue, adjacent normal tissue, and lymphoid tissue were collected from 33 + 29 gastric cancer patients who underwent radical surgery at Shandong Provincial Hospital. Samples from 33 gastric cancer patients were used for multi-omics sequencing analysis, while samples from 29 gastric cancer patients were used for microarray manufacturing and data analysis. All patients did not receive local or systemic treatment before surgery. Fresh tumors and corresponding normal tissues were frozen in liquid nitrogen and stored at -80 °C until use. The remaining specimens were fixed in formalin and embedded in paraffin for histopathological analysis.

[0043] 1.2 Cell culture and treatment Human gastric cancer cell lines MKN-45 and HGC-27 and AGS were purchased from Guangzhou Saiye Biotechnology Co., Ltd. (Guangzhou, China), and human lymphatic endothelial cells (HLECs) were purchased from ScienCell Research Laboratories (CA, USA). MKN45, AGS, and HGC-27 were cultured in RPMI 1640 medium (Gibco, CA, USA), while HLECs were cultured in ECM medium (ScienCell, CA, USA). The culture medium for gastric cancer cell lines was supplemented with 10% fetal bovine serum (FBS, PAN), 100 U / mL penicillin (Solarbio), 50 μg / mL gentamicin (Solarbio), and 0.1 mg / mL streptomycin (Solarbio). For HLECs, the culture medium was supplemented with 10% fetal bovine serum (ScienCell), endothelial cell growth factor (ECGS, ScienCell), and penicillin / streptomycin solution (ScienCell). All cells were cultured in an incubator at 37°C and 5% CO 2 MKN-45, AGS, and HGC-27 cells were infected with the corresponding lentivirus for 24 h and then selected with the selective antibiotic G418 (1 mg / ml, MCE) or puromycin (0.5 μg / ml, MCE).

[0044] 1.3 Western Blot Analysis Cells were lysed using RIPA buffer (Solarbio) containing 1% PMSF and 1% phosphatase inhibitors. Protein concentration was measured using a BCA protein assay kit (Solarbio). Protein samples were mixed with an equal volume of 1× loading buffer and denatured in a metal bath at 100°C for 10 min. Proteins were separated on a 10% SDS-polyacrylamide gel and then transfected onto a PVDF membrane. The membrane was blocked with 5% skim milk for 1 h at room temperature and then incubated with primary antibodies overnight at 4°C. The next day, the membrane was incubated with the corresponding secondary antibodies for 1 h at room temperature. Protein bands were visualized using an ECL detection kit (Vazyme, China) and imaged using an Amersham ImageQuant 800 system. The primary antibodies used in this study included VIRMA (1:1000, 88358S, CST), β-Acitin (1:1000, 66009-1-AP, PTG), CSRP1 (1:1000, 13432-1-AP, PTG), VEGF-C (1:1000, 22601-1-AP, PTG), YAP (1:1000, 14074S, CST), and p-YAP (1:1000, 13008S, CST).

[0045] 1.4 RNA extraction and real-time PCR (qPCR) analysis Total RNA was extracted using Trizol reagent (Vazyme, China) and then reverse transcribed into cDNA using HiScripIII RTSuperMix for qPCR (Vazyme, China). qRT-PCR was performed using the Universal SYBRGreen Master Kit (Vazyme, China) on an Applied Biosystems QuantStudio 1 Real-Time PCR System (Applied Biosystems, Thermo Fisher). -ΔΔCt Methods Relative expression levels were calculated, and GAPDH was used as an internal reference for mRNA normalization.

[0046] 1.5 Colony formation assay Cells were seeded in 6-well plates at a density of 1000 cells per well and cultured in complete medium at 37°C for 2-4 weeks until individual colonies reached a size of 2-5 mm. Colonies were then fixed with 4% paraformaldehyde for 30 minutes and stained with 0.5% crystal violet for 30 minutes at room temperature. After the plates were dried, colonies were photographed and counted using Image J software. All experiments were performed in triplicate.

[0047] 1.6 CCK-8 assay Well-growing cells were seeded in 96-well plates at a density of 2000 cells per well and incubated at 37 °C. After the cells adhered to the wells, the medium was replaced with 110 μL of freshly prepared CCK-8 solution (DojinDo, Japan) per well every 24 hours, followed by incubation at 37 °C for 2 hours. The absorbance was measured at 450 nm every day for 5 days using a Multiskan Sky microplate reader (ThermoFisher). Cell viability was calculated and plotted using GraphPad prism 8 software. All experiments were repeated 3 times.

[0048] 1.7 Transwell assay Cell suspensions were prepared by digesting the cells and resuspending them in serum-free medium. For migration assays, 200 μL of cell suspension was added to the inner chamber of Transwell (Corning, USA). For invasion assays, the inner chamber membrane was coated with Matrigel extracellular matrix (BD Bioscience, USA) before adding 200 μL of cell suspension. In both experiments, 600 μL of complete medium containing FBS was added to the outer chamber as a chemoattractant. After 24 h of incubation, the chamber was removed and the cells on the membrane were fixed with 4% paraformaldehyde for 30 min. The cells were then stained with 0.5% crystal violet solution for 30 min, and the excess stain was carefully removed from the inner chamber with a cotton swab. Finally, 5 random fields of view were captured under a microscope, and the number of migrating or invading cells was counted. Each experiment was repeated 3 times.

[0049] 1.8 Wound healing assay Cells were seeded in 6-well plates, and when they reached optimal density (>95% confluence), three parallel scratches were created on the cell monolayer using a pipette tip. Detached cells were washed with phosphate-buffered saline (PBS), and medium containing 1% serum was added. Wound healing was monitored and photographed in multiple randomly selected microscopic fields (×10 magnification) at different time points (0 h, 24 h, 48 h, and 72 h). The percentage of wound closure was quantified using ImageJ (National Institutes of Health, USA) software.

[0050] 1.9 Tubule formation assay The supernatant of 1640 complete medium cultured with VIRMA-transfected MKN-45 and AGS cells was collected, and the medium was centrifuged at 500r for 10 minutes. 3 mL of supernatant was collected and added to the culture dish containing HLEC cells for co-culture for 48 hours. 50 μL of Matrigel extracellular matrix (BD Bioscience, USA) was added to the 96-well plate and incubated at 37°C for 1 hour. The HLEC cells were then resuspended in culture medium supplemented with 1% microvascular growth factor and MKN-45 or AGS cells, and 100 μL of the cell suspension was evenly distributed on the Matrigel in each well. After the HLEC cells formed lymphatic vessels, photos were taken at specific time intervals to evaluate the structure and number of lymphatic vessels. The number of branches and total branch length were measured using ImageJ software to evaluate the extent of in vitro angiogenesis.

[0051] 1.10 Methylated RNA immunoprecipitation sequencing (MeRIP-seq) m6A motifs were identified using RMVar (https: / / rmvar.renlab.org / ). For MeRIP-PCR, 2 μg of RNA from each group (knockout control and VIRMA knockout AGS cells and overexpression control and VIRMA overexpression MKN45 cells) was treated with the EpiQuik CUT&RUN m6A RNA Enrichment MeRIP Kit (P-9018-24, EpigenTek). PCR products were subjected to gel electrophoresis, and bands were visualized using the Tanon 3500 Gel Imaging System (Shanghai Tanon Life Sciences Co., Ltd.).

[0052] 1.11 RNA pull-down and RIP-qPCR RNA pull-down: Biotinylated transcripts of CSRP1 were bound to streptavidin magnetic beads. Cells lysed with Tris-triton buffer were incubated with these beads for 6 hours. The protein level of YTHDF1 bound to the beads was then detected by western blot.

[0053] RIP-qPCR: Lysed cells are incubated with protein A / G magnetic beads that have been pre-incubated with YTHDF1 antibody overnight. After washing the beads, RNA bound to the beads is extracted and analyzed.

[0054] 1.12 Dual luciferase reporter gene assay In this example, plasmid constructs pGL3-CSRP1-WT and pGL3-CSRP1-MUT were designed based on the MeRIP results. 293T cells were transfected with oe-VIRMA or vector plasmid and Renilla luciferase plasmid for 48 hours, and the cells were harvested and analyzed using the dual-luciferase reporter gene assay system (Promega, Madison, USA) according to the manufacturer's instructions. The ratio of firefly luciferase activity to Renilla luciferase activity was calculated to evaluate the effect of the mutation site.

[0055] 1.13 RNA immunoprecipitation assay RNA immunoprecipitation was performed using antibodies or IgG specific for the target protein or as a control, which were used to bind RNA from control or shVIRMA lysates to protein A / G magnetic beads. After immunoprecipitation, RNA was purified and analyzed by RT-qPCR. The enrichment of the corresponding gene was calculated by normalization to the input RNA.

[0056] 1.14 Immunohistochemistry (IHC) analysis Immunohistochemical staining was performed using an IHC kit (ZSGB-BIO, PV-8000, China) according to the manufacturer's instructions. Immunohistochemical scoring was performed after tissue embedding, sectioning, dewaxing, antibody incubation, staining, and scanning. IHC scores were calculated as the product of frequency and intensity. The frequency was graded as 0, 1, 2, 3, and 4 (<5%, 5%-25%, 25%-50%, 50%-75%, and >75%, respectively) according to the proportion of positive cells. The staining intensity was divided into 0 (negative), 1 (weak), (moderate), and 3 (strong). The integrated optical density (IOD) of the stained sections was measured using ImageJ software, and the mean IOD (MOD) was calculated as IOD / area. The primary antibodies used included VIRMA (1:500, 88358S, CST), VEGF-C (1:100, 22601-1-AP, PTG), Ki-67 (1:200, ab15580, abcam), and LYVE-1 (1:40, 28321-1-AP, PTG).

[0057] 1.15 Animals and Animal Models Animal studies were approved by the Institutional Ethics Committee of Shandong Provincial Hospital (NSFC2023-497). BALB / c male nude mice (4–5 weeks old) were purchased from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China) in a pathogen-free facility. For tumor xenograft models, VIRMA knockout and negative control HGC27 cells (5 × 10 6 ) were injected subcutaneously into the right axilla of nude mice (n = 6 per group). Tumor length (L) and width (W) were measured weekly using a vernier caliper and the formula V = (L × W 2 ) × 0.5 to calculate tumor volume. Tumor growth and volume were assessed every 2 days. If tumor weight exceeded 10% of body weight or weight loss exceeded 20%-25%, the experiment was terminated and mice were euthanized by cervical dislocation. Tumors were weighed, photographed, and fixed in 4% paraformaldehyde or frozen for further analysis.

[0058] 2. Results 2.1 Overexpression of VIRMA in gastric cancer and its prognostic value VIRMA is the largest component of the m6A methyltransferase complex and plays a scaffolding role in the m6A methyltransferase complex, connecting the catalytic core of METTL3 / METTL14 / WTAP to the RNA substrate (Figure 1A). VIRMA is a large molecular protein that contains two domains, the N-terminus (1-1130aa) and the C-terminus (1131-1812aa), in which the N-terminal domain specifically affects the catalytic effect of m6A at a specific location (Figure 1B). We used the TCGA public database to analyze the expression of VIRMA in various tumors and found that its expression level in gastric cancer was significantly higher than that in normal gastric tissue ( Figure 1 C). In addition, gastric cancer patients with high VIRMA expression had shorter overall survival (OS) and post-progression survival (PPS) (Figure 2D). In addition, we examined the correlation between common m6A methylation modifier genes and found that VIRMA interacted with multiple modifier genes to jointly promote tumor development (Figure 2E). Pathway enrichment analysis across multiple databases showed that VIRMA was mainly enriched in pathways related to extracellular matrix, cell adhesion, and VEGF (Figure 3F), indicating that it is involved in tumor cell adhesion and lymph metastasis. Based on this consideration, we compared the expression of VIRMA in gastric cancer lymph nodes using public databases and found that its expression in lymph node-positive cells was significantly increased, especially in T3 / 4 stage gastric cancer with higher infiltration depth ( Figure 3 G). The relationship between VIRMA expression and the total number of lymph nodes and the number of positive lymph nodes was also analyzed. The results showed that the total number of lymph nodes and positive lymph nodes was higher in the VIRMA high expression group, and this relationship was more obvious in the T3 and T4 stages (Figure 3H). Immunohistochemical staining of pathological tissues of gastric cancer patients showed that VIRMA expression was significantly increased in gastric cancer tissues compared with normal gastric tissues, and the expression in positive lymph nodes was higher than that in negative lymph nodes, indicating that VIRMA expression may affect gastric cancer progression and lymph node metastasis (Figure 4).

[0059] 2.2 VIRMA affects the proliferation, migration and invasion of gastric cancer cells in vitro and in vivo To evaluate the functional role of VIRMA in gastric cancer, we selected MKN45 cells to establish a VIRMA overexpression model, and selected HGC-27 and AGS cells to construct a VIRMA knockdown model.

[0060] Compared with the control group, oe-VIRMA transfection significantly promoted the expression of VIRMA mRNA and protein in gastric cancer cells. In contrast, VIRMA mRNA and protein expression were significantly decreased in gastric cancer cells treated with shVIRMA (Figure 5A). Overexpression of VIRMA enhanced cell growth in both colony formation assay (Figure 5B) and cell counting kit 8 (CCK-8) assay (Figure 5C). Similarly, overexpression of VIRMA promoted cell survival in MKN45 cells, while knockdown of VIRMA in AGS cells significantly reduced cell proliferation. Wound healing assay ( Figure 5 D) shows that cells in the overexpression group showed extended migration distance. In addition, in the Transwell assay ( Figure 6 ), increased VIRMA expression promoted cell migration and invasion. In contrast, gastric cancer cells treated with VIRMA knockdown exhibited significantly shorter migration distances in wound healing assays and reduced migration and invasion abilities in Transwell assays. Co-culture experiments of human lymphatic endothelial cells (HLECs) and gastric cancer cell culture media showed that overexpression of VIRMA increased the lymphatic vessel formation ability of HLEC cells, while knockdown of VIRMA reduced this ability ( Figure 7 F). In addition, overexpression of VIRMA enhanced the migration ability of HLEC cells, while knockdown of VIRMA inhibited their migration ability ( Figure 7 G). To investigate the carcinogenic effect of VIRMA in gastric cancer, we performed functional experiments using the HGC-27 cell line and constructed a subcutaneous tumor model for in vivo experiments. VIRMA significantly reduced the expression of VIRMA mRNA and protein in HGC-27 cells ( Figure 8 AB). This knockdown resulted in a significant reduction in colony formation and cell viability, as well as wound healing ( Figure 8 CE) and reduced migration and invasion abilities in Transwell assays (Figure 9F). In in vivo experiments, the volume and weight of xenograft tumors in knockout mice were significantly reduced ( Fig. 9 G. Fig.10 ). In addition, IHC staining and scoring of tumor tissues showed that the expression of Ki-67, LYVE-1, VEGF-C, and VIRMA was significantly reduced in xenograft tumors formed by shVIRMA cells (Figure 11). These results indicate that VIRMA plays a crucial role in promoting gastric cancer tumor growth in vitro and in vivo.

[0061] 2.3 Transcriptome sequencing and m6A sequencing confirmed that CSRP1 is a direct target of VIRMA To understand the regulatory effect of VIRMA on comprehensive gene expression, we performed MeRIP-seq to compare the overall distribution of m6A target genes between control cells and VIRMA stable knockdown cells. We used RNA-seq to compare the expression profiles between control cells and stable VIRMA-inhibited cells. Since VIRMA mainly mediates m6A modification, we focused on mRNA transcripts with reduced m6A peaks. We sorted out the genes that were differentially expressed (P < 0.05) in stable VIRMA-inhibited cells in MeRIP-seq and RNA-seq. As mentioned previously, most genes in gastric cancer cells undergo m6A demethylation modification. We then analyzed the differentially expressed genes in the two sets of sequencing data, filtering for 2-fold differences in m6A peak expression (fold change, FC > 2). The intersected and integrated datasets identified 7 candidate genes, including CSRP1 ( Figure 12-13 We verified the mRNA and protein expression of these 7 downstream genes in the VIRMA overexpression and knockout groups. The results showed that CSRP1 may be a downstream gene of VIRMA ( Figure 13-14 ).

[0062] To investigate the molecular mechanism of VIRMA regulating m6A modification in gastric cancer, we further analyzed the m6A sites using the SRAMP methylation prediction website ( Fig.14 F). MeRIP was used to detect the m6A modification status of CSRP1. The results showed that overexpression of VIRMA led to an increase in the m6A modification of CSRP1 mRNA, while downregulation of VIRMA led to a corresponding decrease in the m6A modification of CSRP1 mRNA ( Fig.14 G). Based on the previous SRAMP site analysis and MeRIP experimental results, we identified a 2937 bp CCACA sequence located in the 3'UTR of CSRP1 and mutated it to CCGCA for dual-luciferase assay. The results showed that the relative luciferase activity of WT-CSRP1 was significantly increased after VIRMA overexpression. In contrast, the relative luciferase activity of the Mut-CSRP1 group was resistant to the effect of VIRMA overexpression (Figure 15H).

[0063] Methylation reader proteins (“Readers”) play a crucial role in the regulation of m6A-modified transcripts. First, we analyzed the correlation between common readers with VIRMA and CSRP1 using the public database ACRG ( Fig.15I, and used RNA pull-down assays to detect the enrichment of each reader for CSRP1 m6A binding ( Fig.16 J). We found that YTHDF1 is enriched in CSRP1 mRNA binding. In MKN45 cells, RIP-qPCR experiments confirmed the binding of CSRP1 mRNA to YTHDF1 ( Fig.16 K).

[0064] The above results confirmed that VIRMA mediated the methylation of CSRP1 through m6A modification and regulated the expression profile of CSRP1 through YTHDF1.

[0065] 2.4 VIRMA affects gastric cancer cell proliferation, migration and invasion by regulating CSRP1 To elucidate whether VIRMA affects gastric cancer progression by regulating CSRP1 expression, we designed oe-CSRP1 and shCSRP1 constructs. CSRP1 gene knockdown and overexpression and VIRMA knockdown were performed in gastric cancer cells overexpressed with VIRMA, and the expression of VIRMA, CSRP1 mRNA and protein was measured ( Fig.17 AB). oe-CSRP1 was able to rescue the decreased colony formation and proliferation of gastric cancer cells caused by VIRMA knockout, while si-CSRP1 inhibited the function of gastric cancer cells after VIRMA overexpression ( Fig.17 CD). Compared with control cells containing an empty vector, the proliferation of gastric cancer cells was reduced after VIRMA knockdown. oe-CSRP1 restored wound healing ability, and overexpression of CSRP1 significantly improved the migration and invasion ability of gastric cancer cells. The enhanced wound healing and migration and invasion abilities observed after overexpression in gastric cancer cells were attenuated upon CSRP1 inhibition ( Figure 18-19 ). Similarly, in the culture medium of gastric cancer cells containing oe-CSRP1, the tube formation and migration of HLECs were enhanced. In contrast, in the culture medium of gastric cancer cells containing si-CSRP1, the function of HLECs was significantly reduced, and the tube formation and migration abilities were significantly decreased ( Figure 20-21 ).

[0066] The above experimental results indicate that VIRMA affects the malignant progression of gastric cancer by regulating the expression of CSRP1.

[0067] 2.5 VIRMA regulates Hippo-YAP signaling by interacting with CSRP1 To mechanistically understand how VIRMA affects gastric cancer disease progression through CSRP1 regulation, we analyzed transcriptome data from 33 pairs of tumors and adjacent tissues. We found that the Hippo signaling pathway score increased with the increase of VIRMA expression ( Fig. 22 A). Phosphoproteomics data showed a negative correlation between VIRMA protein levels and p-YAP serine 109 [p-YAP (S109)] ( Fig. 22 B), indicating that VIRMA may regulate the Hippo-YAP signaling pathway. The results showed that the expression of the core components of the Hippo-YAP pathway, including YAP and p-YAP (S109), changed significantly in the VIRMA knockdown and overexpression groups. After VIRMA overexpression, CSRP1 protein expression increased and phosphorylation of the core components of the Hippo-YAP pathway decreased, indicating that Hippo-YAP signaling was promoted ( Fig. 22 B). In addition, the expression of VEGF-C, a marker of lymph node metastasis, increased with VIRMA overexpression. In contrast, in the VIRMA knockdown group, the reduction of VIRMA led to a decrease in the expression of CSRP1 and VEGF-C, while the expression of p-YAP (S109) increased. The inhibitory effect on p-YAP (S109) was weakened with the decrease in CSRP1 expression ( Fig. 22 CD).

Claims

1. Application of VIRMA as a prognostic biomarker and therapeutic target for gastric cancer, characterized in that: VIRMA expression affects gastric cancer progression and lymph node metastasis, and the expression of VEGF-C, a marker of lymph node metastasis, increases with VIRMA overexpression.

2. The use according to claim 1, characterized in that: VIRMA affects the proliferation, migration and invasion of gastric cancer cells by regulating CSRP1.

3. The use according to claim 1, characterized in that: VIRMA mediates methylation of CSRP1 through m6A modification and regulates the expression profile of CSRP1 through YTHDF1, affecting the malignant progression of gastric cancer.

4. The use according to claim 1, characterized in that: VIRMA overexpression regulates Hippo-YAP signaling by interacting with CSRP1.

5. Use of VIRMA as claimed in claim 1 as a prognostic biomarker for gastric cancer in the preparation of a kit for prognosis monitoring of gastric cancer.

6. The use according to claim 5, characterized in that: The kit also includes other gastric cancer prognosis monitoring reagents and a buffer solution.

7. Use of the inhibitor of VIRMA as claimed in claim 1 in the preparation of drugs for treating gastric cancer, wherein the drug targets VIRMA and inhibits overexpression of VIRMA.

8. The use according to claim 7, characterized in that: The medicament may also include other acceptable carriers.

9. The use according to claim 7 or 8, characterized in that: The drug works by either: a. Inhibit the proliferation, migration and invasion of gastric cancer cells; b. Regulate or inhibit lymph node metastasis in gastric cancer.

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