|Year : 2023 | Volume
| Issue : 2 | Page : 93-102
Collagen type V alpha 2 promotes the development of gastric cancer via M2 macrophage polarization
Xin Guo, Xiaoqian Bu, Li Yuan, Lina Ji
Department of Digestive Oncology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi; Department of Digestive Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
|Date of Submission||01-Sep-2022|
|Date of Decision||20-Nov-2022|
|Date of Acceptance||22-Nov-2022|
|Date of Web Publication||27-Mar-2023|
Dr. Lina Ji
Department of Digestive Oncology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, No. 99, Longcheng Avenue, Xiaodian District, Taiyuan, Shanxi
Source of Support: None, Conflict of Interest: None
Gastric cancer is a type of digestive tract cancer with a high morbidity and mortality, which leads to a major health burden worldwide. More research into the functions of the immune system will improve therapy and survival in gastric cancer patients. We attempted to identify potential biomarkers or targets in gastric cancer via bioinformatical analysis approaches. Three gene expression profile datasets (GSE79973, GSE103236, and GSE118916) of gastric tissue samples were obtained from the Gene Expression Omnibus database. There were 65 overlapping differentially expressed genes (DEGs) identified from three microarrays. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway were carried out for the key functions and pathways enriched in the DEGs. Then, ten hub genes were identified by protein–protein interaction network. In addition, we observed that collagen type V alpha 2 (COL5A2) was linked to gastric cancer prognosis as well as M2 macrophage infiltration. Furthermore, COL5A2 enhanced gastric cancer cell proliferation through the PI3K-AKT signaling pathway and polarized M2 macrophage cells. Therefore, in this study, we found that COL5A2 was associated with the development of gastric cancer which might function as a potential therapeutic target for the disease.
Keywords: Bioinformatic analysis, cell differentiation, collagen type V alpha 2, gastric cancer, M2 macrophage
|How to cite this article:|
Guo X, Bu X, Yuan L, Ji L. Collagen type V alpha 2 promotes the development of gastric cancer via M2 macrophage polarization. Chin J Physiol 2023;66:93-102
|How to cite this URL:|
Guo X, Bu X, Yuan L, Ji L. Collagen type V alpha 2 promotes the development of gastric cancer via M2 macrophage polarization. Chin J Physiol [serial online] 2023 [cited 2023 May 29];66:93-102. Available from: https://www.cjphysiology.org/text.asp?2023/66/2/93/374408
| Introduction|| |
Gastric cancer is a type of digestive tract cancer with a high morbidity and mortality.,, With an overall 5-year survival rate of fewer than 20%, most of gastric cancer patients have a poor prognosis. The limited incidence of early diagnosis of gastric cancer is largely due to the lack of symptoms in the early stages. Thus, the majority of patients have advanced-stage stomach cancer with a bad prognosis. Therefore, there is a growing interest in improving treatment of advanced gastric cancer.
Microarray is a useful strategy for discovering more about the heterogeneity of disease tissues, identifying the potential predictive biomarkers for disease diagnosis, and uncovering the novel targets for disease treatment.,, However, due to the heterogeneity of specimens, the employment of multiple detection platforms and data processing techniques may lead to conflicting results. The gene expression omnibus (GEO) database contains a large and comprehensive collection of various tumor gene expression profiles. This public database can be used to develop new hypotheses and gain understanding about diseases by combining and evaluating a variety of gene expression data, in addition to serving as a priceless source of publicly available gene expression profiles.
Collagen type V alpha 2 (COL5A2) is one of the collagen types. Emerging research shows that COL5A2 is involved in immune system modulation, angiogenesis, and tumor metastasis.,, Currently, Tan et al. reported that gastric cancer tissues showed the increased expression level of COL5A2, suggesting an involvement of COL5A2 in the development of gastric cancer. As yet, it is not known what molecular mechanism COL5A2 plays in the progression and prognosis of gastric cancer.
In this report, we attempted to discover potential biomarkers or targets in gastric cancer via bioinformatical analysis approaches. Using GEO database, we obtained three gene chip expression profiles (GSE79973, GSE103236, and GSE118916) and identified 65 overlapping differentially expressed genes (DEGs) in gastric cancer. Moreover, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and gastric cancer-related protein–protein interaction (PPI) network analysis were performed based on the overlapping DEGs. Then, ten hub genes were identified. Furthermore, COL1A10 and COL5A2 were discovered to be linked to gastric cancer prognosis. We then chose COL5A2 to further explore its effect on gastric cancer. Moreover, we validated that COL5A2 promoted gastric cancer cell proliferative capability and M2 macrophage cell polarization. Therefore, we found that COL5A2 was associated with the development of gastric cancer, which might function as a potential therapeutic target for the disease.
| Materials and Methods|| |
In this study, there were three gastric cancer microarray dataset (GSE79973, GSE103236, and GSE118916) matrix files obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). Raw data of three datasets were preprocessed and normalized using the Limma package in R software. The log2 transformation was performed on all gene expression data. The number of samples used and detailed information of three microarray datasets are included in [Table 1].
|Table 1: Detail information of three gastric cancer microarrays downloaded from gene expression omnibus database|
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Differentially expressed genes identification
A differential analysis of gastric cancer tissue in relation to normal tissue was conducted using the R package Limma (|Log2Fold Change| >1, and adjusted P < 0.05). Volcano plots and heatmap were generated by R package ggplot2. The overlapping DEG was obtained by Venn Diagram package of R language.
Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis
Using the Enrichr database (https://maayanlab.cloud/Enrichr/enrich#), functional analysis and pathway enrichment analyses of GO and KEGG pathways were conducted on DEGs as previously described.
Network analysis of protein–protein interactions
The overlapping DEGs were entered into the STRING (https://string-db.org/) database for PPI analysis. Following that, we screened STRING for the top 10 hub genes with the highest number of nodes in the PPI network.
The association between overall survival and hub gene expression level
The expression levels of the top 5 hub genes (COL1A10, COL5A2, Thrombospondin-2 (THBS2), Biglycan (BGN) and Tissue inhibitor of metalloproteinase 1 (TIMP1)) were examined by Gene Expression Profiling Interactive Analysis (GEPIA) (http://gepia.cancer-pku.cn/). In addition, the gastric cancer patients' clinical information was also downloaded from GEPIA to analyze the association between overall survival and these genes expression as described before.
The association between immune cell infiltration and hub gene expression level
In order to investigate the interaction between immune cells and key gene expression of cancer, the association between immune cell infiltration and key gene expression was carried out using the tumor immune estimation resource (TIMER) webserver (https://cistrome.shinyapps.io/timer/) as reported previously.
Cell culture and transfection
Human gastric cancer cell lines (AGS cells and MKN45 cells) and human monocytic cell line (THP-1 cells) were supplied from American Type Culture Collection (Manassas, VA, USA) and were maintained in RPMI 1640 (Thermo Fisher Scientific, Waltham, MA, USA) containing 10% fetal bovine serum (FBS) (Thermo Fisher Scientific) and 100 U/ml of penicillin/streptomycin (Thermo Fisher Scientific) in a humidified incubator.
AGS and MKN45 cells were transfected with COL5A2-short interference RNA (siRNA), negative control (NC)-siRNA, COL5A2 plasmid vector (Thermo Fisher Scientific), and control vectors as previously described. When cells were 60%–80% confluence, cells were then incubated with Lipofectamine transfection reagent (Thermo Fisher Scientific) for 12 h as directed by the manufacturer.
THP-1 cells were incubated with phorbol-12-myristate-13-acetate (PMA) (100 ng/mL; Sigma, St Louis, MO, USA) for 24 h to differentiate into M0 macrophages, which were followed by incubation with 20 ng/mL of interleukin 4 (IL-4) (20 ng/ml; R and D system, Minneapolis, MN, USA) for 72 h to polarize toward M2 macrophages. AGS and MKN45 cells were transfected with COL5A2-siRNA, NC-siRNA, and COL5A2 plasmid vector. After transfection, 1 × 105 AGS or MKN45 cells were seeded in Transwell chambers (Corning, NY, USA) for coculture experiments. Then, the chamber was cocultured with differentiated THP-1 cells in a 6-well plate for 48 h.
Cells were collected and were lysed in RIPA buffer with protease and phosphatase inhibitors. The protein concentrations of supernatant were detected by bicinchoninic acid protein detection kit (Servicebio, Wuhan, China). Equal amounts of protein were loaded and separated by 4%–12% SDS-PAGE and transferred to PVDF membranes. After blocking, the blots were incubated with primary antibodies. Second antibodies (Thermo Fisher Scientific) were added for 1-hour incubation. Following that, ECL was applied to develop the blots. The detailed information of primary antibodies used in Western blotting is listed in [Table 2].
Colony formation assay
After the cells were digested with trypsin, AGS and MKN45 cells were inoculated into 12-well plates and cultured in a cell incubator at 37°C for 14 days. Then, the cells were fixed with methanol and stained with crystal violet for 10 min. The quantity of cell colonies stained with crystal violet was photographed and counted.
Cell counting Kit-8 assay
The cell viability was evaluated using CCK-8 assay as instructed by the manufacturer. After the cells were digested with trypsin, AGS and MKN45 cells were seeded into 96-well plates and then 10 μL CCK-8 solution (Sigma, St. Louis, MO, USA) was added for 2-h incubation. At a wavelength of 450 nm, optical density values were determined using a microplate reader (Bio-Rad, Richmond, VA, USA).
After cocultured with gastric cancer cells, fixable viability stain 700 (BD Bioscience, San Jose, CA, USA) was used to stain THP-1 cells to remove dead cells. Then, fluorescein-labeled CD163 (BD Bioscience) and CD206 (BD Bioscience) were directly incubated for 30 min at 4°C in dark. Then, the cells were enumerated using a BD-FACS Canto II (BD Bioscience) instrument and the data were analyzed using FlowJo software (TreeStar, Ashland, OR, USA).
In this study, all data analysis and visualization were carried out using GraphPad Prism software (version 9.0.2 for windows, San Diego, CA, USA). The data were expressed as the mean ± standard deviation. Normality of the data was assessed using the Shapiro-Wilk test. If the data were normally distributed, ANOVA in combination with a Tukey's post hoc test for multiple comparisons and a Student's t-test for binary comparisons were applied. Otherwise, a Kruskal–Wallis test in combination with a Dunn's post hoc test for multiple comparisons and a Mann–Whitney U test for binary comparisons were performed. For correlation analysis, the Spearman rank test was applied. The Kaplan–Meier method was used for the survival analysis, and log rank was used to test the hypothesis. P < 0.05 was considered statistically significant.
| Results|| |
Differentially expressed genes in microarrays of gastric cancer from public database
After downloading and normalizing the GSE79973, GSE103236, and GSE118916 datasets, we identified the DEGs (|Log2Fold Change| >1 and adjusted P < 0.05) of gastric cancer tissue in relation to normal tissue in three microarray datasets. Volcano plots showed the DEGs of gastric cancer tissue in relation to normal tissue [Figure 1]a. Heatmap based on the DEGs indicated different expression patterns existing in the gastric cancer and control groups [Figure 1]b. Then, Venn diagram showed that 65 overlapping DEGs were identified from three microarray datasets [Figure 1]c.
|Figure 1: Differentially expressed genes in microarrays of gastric cancer from public database. (a) Volcano plots showing the DEGs between gastric cancer tissues and normal tissues in three microarrays. (b) Heatmap showing the DEGs between gastric cancer tissues and normal tissues in three microarrays. (c) Venn diagram showing the overlapping DEGs among three microarrays. DEGs: Differentially expressed genes.|
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Pathway enrichment analysis and network analysis of protein–protein interactions
Based on the overlapping DEGs in gastric cancer, GO functional analysis and KEGG pathway enrichment analysis were performed. The top 10 GO items in biological process and top 10 KEGG pathways were visualized [Figure 2]a. The GO items in biological processes were enriched in extracellular matrix (ECM) organization, collagen fibril organization, and extracellular structure organization. The KEGG pathways were associated with protein digestion and absorption, cytokine-cytokine receptor interaction, and ECM-receptor interaction. Alternatively, the protein kinase B (Akt) signaling pathway was enriched in the top 10 KEGG pathways.
|Figure 2: Pathway enrichment analysis and Network analysis of PPIs. (a) Bar graph showing the top 10 GO items in biological process and top 10 KEGG pathways. (b) PPI network analysis and the top 10 hub genes were illustrated. GO: Gene ontology, KEGG: Kyoto Encyclopedia of Genes and Genomes, PPI: Protein–protein interaction.|
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Furthermore, according to the overlapping DEGs in gastric cancer, we next constructed PPI network analysis and the top 10 hub genes were illustrated [Figure 2]b. COL1A10, COL5A2, THBS2, BGN, and TIMP1 were the top 5 hub genes which were crucial nodes in the PPI network.
Prognosis significance of the expression of key genes in gastric cancer
To further verify the expression of key genes and prognosis significance in gastric cancer, the mRNA expression of COL1A10, COL5A2, THBS2, BGN, and TIMP1 in gastric tissue samples and clinical data of patients with gastric cancer were downloaded from GEPIA tool. Further analysis confirmed the higher expression of COL1A10, COL5A2, THBS2, BGN, and TIMP1 in the gastric cancer group than that of the control group [Figure 3]a. Of note, we found that the higher expression of COL1A10 and COL5A2 in gastric cancer tissues was correlated with poor prognosis in gastric cancer patients [Figure 3]b. Thus, these data suggested that COL1A10 and COL5A2 had a role in the prognosis of gastric cancer patients.
|Figure 3: Prognosis significance of the expression of key genes in gastric cancer. (a) Scatter plots showing the mRNA expression of COL1A10, COL5A2, THBS2, BGN and TIMP1 in gastric cancer tissues and normal tissues derived from GEPIA tool. (b) Kaplan-Meier graphs showed the survival rates of high COL1A10, COL5A2, THBS2, BGN and TIMP1 expression group and low COL1A10, COL5A2, THBS2, BGN and TIMP1 expression group. COL1A10: Collagen type I alpha 10, COL5A2: Collagen type V alpha 2, THBS2: Thrombospondin-2, TIMP1: Tissue inhibitor of metalloproteinase 1; BGN: Biglycan. *P < 0.05.|
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An association between collagen type V alpha 2 and M2 macrophage infiltration in gastric cancer
We then focused our investigation on COL5A2 because of its greater prognosis significance. Recently, there is increasing evidence that the development and prognosis of gastric cancer are relevant to immune function. Subsequently, we investigated the underlying association between COL5A2 and immune infiltration via the online tool, TIMER. These results indicated a positive link between COL5A2 and macrophage infiltrations in gastric cancer tissues [Figure 4]a. Further analysis on the prognosis significance of multiple immune cell subsets and COL5A2 showed that a worse prognosis was linked to greater COL5A2 expression and macrophage infiltration in patients with gastric cancer [Figure 4]b.
|Figure 4: COL5A2 is related to M2 macrophage infiltration in gastric cancer. (a) Correlations between COL5A2 expression and immune cell (B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, dendritic cell) infiltration in gastric cancer. (b) Kaplan-Meier graphs showed the survival rates of more immune cell (B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, dendritic cell) infiltration group and less immune cell (B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, dendritic cell) infiltration as well as high COL5A2 expression group and low COL5A2 expression group. (c) Correlation between COL5A2 expression and M2 macrophage in gastric cancer. (d) Correlations between COL5A2 expression and the expression of M2 macrophage marker, CD163 and MRC-1. COL5A2: Collagen type V alpha 2; MRC-1: Mannose receptor C-type 1.|
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Moreover, gastric cancer tissues showed a correlation between COL5A2 expression and M2 macrophage infiltration [Figure 4]c. Further investigation revealed that the levels of the M2 macrophage marker, CD163 and Mannose receptor C-type 1 (MRC-1; also known as CD206) were positively correlated with COL5A2 expression [Figure 4]d. Thereby, these data suggested that macrophage was an involvement in the development of gastric cancer and COL5A2 might promote the differentiation of M2 macrophage in gastric cancer.
Silencing collagen type V alpha 2 inhibits the proliferative capacity of gastric cancer cells
To investigate the involvement of COL5A2 in gastric cancer, AGS and MKN45 cells were transfected with siRNA and plasmid vector. Western blotting showed that silencing COL5A2 led to a reduction of COL5A2 protein expression in both AGS cell line and MKN45 cell line, while COL5A2 overexpression increased the COL5A2 protein expression [Figure 5]a and [Figure 5]b. Colony formation assay and CCK8 test indicated that silencing COL5A2 decreased the proliferative capability of gastric cancer cells, which was promoted by COL5A2 overexpression [Figure 5]c and [Figure 5]d. In addition, we found that COL5A2 overexpression promoted PI3K-AKT signaling pathway activation, which was inhibited by COL5A2 silence [Figure 5]e and [Figure 5]f. Taken together, we showed that COL5A2 regulated the proliferative capacity of gastric cancer cells via the PI3K-AKT signaling pathway.
|Figure 5: Silencing COL5A2 inhibits the proliferative capacity of gastric cancer cells. (a) Representative graph of Western blotting experiment indicating the protein expression of COL5A2 in both AGS cell line and MKN45 cell line with or without si-COL5A2 and COL5A2 plasmid transfection. (b) Histogram showing the protein levels of COL5A2 in both AGS cell line (n = 3) and MKN45 cell line (n = 3) with or without si-COL5A2 and COL5A2 plasmid transfection. (c) Colony formation assay detecting the mean colony number in both AGS cell line (n = 3) and MKN45 cell line (n = 3) with or without si-COL5A2 and COL5A2 plasmid transfection. (d) CCK8 test showing the viability of AGS cell line (n = 3) and MKN45 cell line (n = 3) with or without si-COL5A2 and COL5A2 plasmid transfection. (e) Representative graph of Western blotting experiment indicating the protein expression of PI3K, phosphorylated PI3K, AKT and phosphorylated AKT in both AGS cell line and MKN45 cell line with or without si-COL5A2 and COL5A2 plasmid transfection. (f) Histogram showing the protein levels of PI3K, phosphorylated PI3K, AKT and phosphorylated AKT in both AGS cell line (n = 3) and MKN45 cell line (n = 3) with or without si-COL5A2 and COL5A2 plasmid transfection. COL5A2: Collagen type V alpha 2; siRNA: Small interference RNA, NC: Negative control. *P < 0.05, **P < 0.01 and ***P < 0.001 versus the vector group; ^^P < 0.01 and ^^^P < 0.001 versus the si-NC group.|
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Collagen type V alpha 2 promotes M2 macrophage polarization
We observed that COL5A2 expression was specifically associated with M2 macrophage infiltration as well as M2 macrophage gene signatures (CD163 and CD206) [Figure 4]a and [Figure 4]c. We further explored whether COL5A2 could induce M2 macrophage polarization. THP-1 cells were incubated with PMA to induce differentiation into M0 macrophages. Then, M0 macrophage was treated with IL-4 and cocultured with AGS and MKN45 cells which were transfected with siRNA or plasmid vector. Flow cytometry showed that the expression level of the M2 macrophage markers (CD163 and CD206) was significantly increased in the COL5A2 vector group compared to the blank vector group [Figure 6]. Meanwhile, the expression of CD163 and CD206 was obviously decreased in the si-COL5A2 group in relation to the si-NC group [Figure 6]. Overall, these findings implied that COL5A2 was involved in the polarization of M2 macrophage in gastric cancer microenvironment.
|Figure 6: COL5A2 promotes the polarization of M2 macrophage. Flow cytometry indicating the expression of CD163 and CD206 on macrophages which were cocultured with AGS cell line (n = 3) and MKN45 cell line (n = 3) with or without si-COL5A2 and COL5A2 plasmid transfection. siRNA: Small interference RNA, NC: Negative control. *P < 0.05 and **P < 0.01 versus the vector group; ^^P < 0.01 versus the si-NC group.|
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| Discussion|| |
Gastric cancer is one of the most prevalent malignant tumors in the world; it ranks fifth for cancer incidence and the third most common cause of cancer death globally. The prevalence of gastric cancer among youngsters is constantly rising. Thus, gastric cancer is a huge public health burden around the world. Despite breakthroughs in surgical operations,, radiation, immunotherapy, and neoadjuvant therapy, gastric cancer remains the third leading cause of death among all cancers. More research into the functions of the immune system will improve therapy and survival in gastric cancer patients. Using bioinformatic analysis approaches, we identified COL5A2 as the key gene that was highly expressed in gastric cancer tissues and that was associated with gastric cancer prognosis as well as M2 macrophage infiltration. Furthermore, we found that COL5A2 played a role in the proliferative capability of gastric cancer cells and M2 macrophage polarization.
COL5A2 is a component of collagen family. According to several lines of evidence, COL5A2 was found to be involved in the progression of inflammation, angiogenesis, fibroblast proliferation, collagen production, and ECM remodeling.,, In this study, we found an increase in COL5A2 expression of gastric cancer tissues in relation to normal tissues, which was linked to a poor prognosis. Alternatively, we observed that COL5A2 overexpression promoted gastric cancer cell proliferation, while COL5A2 silence inhibited this promotion. Thus, our data suggested that COL5A2 regulated the proliferative capacity of gastric cancer cells.
Furthermore, we observed that COL5A2 overexpression enhanced the activation of the PI3K-AKT signaling pathway, whereas COL5A2 silence suppressed it. The PI3K-AKT signaling pathway modulates multiple essential biological activities, including cell growth, death, and metastasis, which then contributes to the development of cancer.,, Several studies have found that the PI3K-AKT signaling pathway contributes to poor prognosis in a variety of malignancies, including renal carcinoma, cervical cancer, and colon cancer. Prior research discovered that the PI3K-AKT signaling pathway had an effect on the progression of gastric cancer. In line with previous study, the PI3K-AKT signaling pathway was enriched in KEGG enrichment pathway in our report, which implied a role of this pathway in gastric cancer. Taken together, these findings revealed that by activating the PI3K-AKT signaling pathway, COL5A2 was implicated in gastric cancer.
Macrophage is one of the most common immune-related stromal cells within or surrounding tumors. Distinct stimuli can polarize macrophages into M1 macrophages or M2 macrophages. Tumor-associated macrophages (TAMs), which are M2-like, present inside the tumor microenvironment and regulate tumor metastasis via communicating with cancer cells.,,, Until now, the interaction between cancer cells and M2 macrophages has been widely studied. By inducing macrophages to produce growth factors and cytokines, M2 polarization of TAMs is crucial for regulating tumor development, migration, and angiogenesis.,,, In this study, COL5A2 was determined to be linked to macrophage infiltration, especially M2 macrophage infiltration in gastric cancer microenvironment. In addition, when cocultured with gastric cancer cells possessing higher COL5A2 expression, more macrophages differentiated toward M2 macrophages. In light of this, our findings showed that COL5A2 increased M2 macrophage polarization through the interaction of gastric cancer cells and macrophages.
In the present report, using bioinformatic analysis approaches, we identified the key gene COL5A2 in gastric cancer tissues. The prognosis of gastric cancer and macrophage infiltration were discovered to be related to COL5A2 expression. And, COL5A2 regulated the proliferative capacity of gastric cancer cells via the PI3K-AKT signaling pathway. Moreover, COL5A2 promoted M2 macrophage polarization in gastric cancer. Thus, these findings indicated that COL5A2 was involved in both the proliferation of gastric cancer cells and the differentiation of M2 macrophages. This finding may contribute to understanding and gastric cancer therapy in the future.
| Conclusion|| |
We discovered COL5A2 as an important target for gastric cancer, which is highly expressed, enhances gastric cancer cell proliferation, and promotes M2 macrophage differentiation in gastric cancer.
Availability of data and materials
All data generated or analyzed during this study are included in this published article.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
[Table 1], [Table 2]