Abstract
Background/Aim: Collagen triple helix repeat containing-1 (CTHRC1) promotes tumor progression by regulating the immunosuppression of the tumor microenvironment. However, the function of CTHRC1 in gastric cancer (GC) and its relationship with tumor-infiltrating immune cells remains unclear. Patients and Methods: Data were downloaded from The Cancer Genome Atlas (TCGA) database. The difference in expression of CTHRC1 in GC and adjacent non-tumor tissues was analyzed by R software and verified by the online database Oncomine. A Kaplan–Meier survival analysis was selected for evaluating the impact of CTHRC1 expression on the survival of GC and verified by the Kaplan–Meier plotter. The relationship between CTHRC1 expression and clinicopathological parameters was assessed by univariate and multivariate Cox regression. The correlation with tumor-infiltrating immune cells was analyzed by Tumor Immune Estimation Resource (TIMER). A gene set enrichment analysis (GSEA) was used to screen the signaling pathways between low and high CTHRC1 expression datasets. Results: The expression of CTHRC1 in GC tissue was higher than that in adjacent non-tumor tissues. The Kaplan–Meier curve showed that patients with higher CTHRC1 expression had a worse prognosis. The univariate and multivariate Cox analyses showed that high expression of CTHRC1 was an important independent predictor of poor overall survival in GC. The TIMER database analysis revealed that CTHRC1 was associated with five tumor immunosuppressive cells in GC. The GSEA indicated that 10 signaling pathways were enriched in samples with a high CTHRC1 expression phenotype. Conclusion: CTHRC1 might be a new prognostic biomarker for CG and might be a potential target for treatment of GC.
Gastric cancer (GC) is one of the most common malignancies, and its mortality rate ranks third worldwide (1). The overall survival rate of gastric cancer is poor. In the United States, the 5-year survival rate of GC is less than 30% (2), and this rate is even lower in developing countries. Metastasis is the main cause of poor prognosis in GC. Immune escape is considered to be an important factor in tumor metastasis (3). Tumor immunotherapy, a treatment strategy that prevents tumor escape, has attracted much attention in recent years (4) and achieved good results in the treatment of certain tumors, such as melanoma (5) and non-small cell lung cancer (6). Immunotherapy is considered to be a new direction in the treatment of GC (7). However, the benefits of tumor immunotherapy in patients with advanced GC is currently extremely limited (8). Studies have shown that lymphocyte infiltration is closely related to the efficacy of gastric cancer tumor immunotherapy (9). Therefore, there is an urgent need to identify new immunologically relevant therapeutic targets for GC.
CTHRC1 is a secreted protein with a molecular weight of 25 kDa, and its coding gene is located on chromosome 8. CTHRC1 was first identified in an injured artery of mice (10). Studies have shown that CTHRC1 promotes cell migration, an important process in wound healing (10). In addition, studies have shown that CTHRC1 is closely related to tumors (11). CTHRC1 is highly expressed in hepatocellular cancer (12), breast cancer (13), pancreatic cancer (14), colorectal cancer (11), cervical cancer (15), lung cancer (16), and other malignant tumors. CTHRC1 has also been shown to be highly expressed in GC, is associated with the prognosis of GC (17), and enhances the ability of GC cells to proliferate, migrate, and infiltrate (18). In addition to the above effects, CTHRC1 is involved in tumor immune cell infiltration. It has been reported that CTHRC1 promotes the immersion of M2 macrophages and M2 macrophages have immunosuppressive effects (19). These findings indicate that CTHRC1 plays a regulatory role in the development and progression of GC. However, the potential function and mechanism of CTHRC1 in the progression of GC and tumor immunology remain unclear.
In this study, we comprehensively analyzed the expression of CTHRC1 and its correlation with the prognosis of patients with GC using the Oncomine, Kaplan–Meier plotter, and other databases. In addition, we investigated the association of CTHRC1 with tumor-infiltrating immune cells in the tumor microenvironment of GC through the Tumor Immune Estimation Resource (TIMER). The findings of this report reveal the important role of CTHRC1 in GC and provide a potential relationship and mechanism between CTHRC1 and tumor immune interactions.
Patients and Methods
TCGA data download. The mRNA and clinical data of 375 samples of GC tissues and 32 samples of adjacent normal tissues of patients with GC were downloaded from the TCGA database on or before April 6, 2020. The details of the clinical data included age, survival time, vital status, sex, grade, pathological stage, T stage, N stage, and M stage. The details of the patients are shown in Table I.
Characteristics of patients with gastric cancer (Data are reported as a %).
CTHRC1 expression analysis and survival analysis. R software was used to sort and merge the downloaded TCGA-SATD original data, extract the CTHRC1 expression data from the dataset by the limma package, and then compare the difference in CTHRC1 expression between adjacent normal tissues and tumor tissues. Perl programming language was used to extract survival data from clinical data for matching with mRNA expression data.
After that, the patients were divided into a high CTHRC1 expression group and a low CTHRC1 expression group according to the median value of CTHRC1 mRNA expression. The survival curves of the high expression group vs. the low expression group were calculated and visualized by R language.
Verification of CTHRC1 expression analysis and survival analysis. The Oncomine database (20, 21), comprising 729 gene expression datasets and the data of 86,733 samples, was used to verify the expression levels of CTHRC1 in GC. The analysis in the Oncomine database was run with the following parameters: p-value<0.001, fold change=2.0.
The Kaplan–Meier plotter (20) was used to verify the correlation between CTHRC1 expression and the prognosis of GC. The Kaplan–Meier plotter database is a tool for the discovery and validation of survival biomarkers. This database includes 1,065 GC samples, which originated from GEO, EGA, and TCGA. The hazard ratio (HR) and log-rank p-value were computed to analyze the prognostic value of the CTHRC1 gene.
Univariate and multivariate Cox regression analyses. A Cox proportional hazard regression model was used for univariate and multivariate analyses. The independent predictive value of clinicopathological features and CTHRC1 expression in GC was quantitatively evaluated by calculating hazard ratios and 95% confidence intervals, and the independent prognostic effect of CTHRC1 on the survival rate of GC was evaluated by adjusting for confounding factors.
Perl language was used to sort and merge the original clinical data, delete the unknown or incomplete clinical information patients, and match the expression data of CTHRC1. Finally, data from 317 patients were obtained and analyzed by univariate and multivariate Cox regression. According to the median expression of CTHRC1, 317 patients were divided into a high-expression group and a low-expression group. The data were analyzed and visualized using R software with the survival package, coxph package, and ggforest package. The data from the univariate and multivariate Cox regression analysis are seen in Table II.
The correlation of collagen triple helix repeat containing-1 (CTHRC1) expression with gastric cancer in COX proportional hazard regression model (Univariate analysis and multivariate).
Immune infiltration estimation. Through the survival analysis, we demonstrated the prognostic value of CTHRC1 in GC. Studies have shown that the CTHRC1 gene is associated with immune cell infiltration in the tumor microenvironment (19). Lymphocytic infiltration in the tumor microenvironment plays an important role in tumor prognosis (22). Therefore, we further studied the relationship between CTHRC1 and immune cell infiltration in the tumor microenvironment of GC through the TIMER database. TIMER contains 10,009 samples of 23 cancer types from TCGA (23). The abundance of B cells, CD4 T cells, CD8 T cells, neutrophils, macrophages, and dendritic cells in the tumor microenvironment was estimated using this website tool. We used the “gene” module of TIMER to evaluate the correlation of CTHRC1 expression level with the abundance of immune infiltrates in GC. In addition, “correlation” modules of TIMER were used to examine the correlations between CTHRC1 expression and gene marker sets of the immune cells that infiltrated the GC microenvironment.
Gene correlation analysis in GEPIA. Tumor-infiltrating lymphocytes (TILs) in the tumor microenvironment can be divided into two types: TILs inhibiting tumor growth and TILs promoting tumor growth. FOXP3+ T cells (Tregs), CD4+ T helper 2 (Th2) cells, M2 macrophages, dendritic cells (DCs), and myeloid-derived suppressor cells (MDSCs) play a role in immunosuppression and participate in tumor immune escape (24).
The online database Gene Expression Profiling Interactive Analysis (GEPIA) is a web server resource of the TCGA and GTEx projects, and includes the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples (25). The GEPIA correlation module was used to generate expression scatter plots between the CTHRC1 and TIL gene sets in GC.
Gene set enrichment analysis. GSEA software (version 4.0) was used to study the signaling pathway of CTHRC1 in GC. According to the median CTHRC1 expression, patients from the TCGA-STAD database were divided into a low CTHRC1 expression group and a high CTHRC1 expression group. GSEA software was used to analyze the gene expression between the two groups. A total of 1,000 gene sets were arranged in each analysis to identify significantly different pathways. Each analysis performed 1,000 genome substitutions to identify significantly different pathways. The normalized enrichment score (NES), nominal p-value, and false discovery rate (FDR) q value indicated the association between gene sets and pathways.
Statistical analysis. The results of CTHRC1 expression generated in Oncomine are displayed with p-values, fold changes, and ranks. The survival curves generated from Kaplan–Meier plots are displayed with HR and p or Cox p-values from a log-rank test. Clinicopathologic characteristics were associated with overall survival in TCGA patients using R (v.4.0.3) in the Cox regression and the Kaplan–Meier method. The correlation of gene expression was evaluated by Spearman’s correlation and statistical significance, and the strength of the correlation was determined using the following guide for the absolute value: 0.00-0.19 “very weak”, 0.20-0.39 “weak”, 0.40-0.59 “moderate”, 0.60-0.79 “strong”, and 0.80-1.0 “very strong”. p-Values <0.05 were considered statistically significant.
Results
CTHRC1 expression levels in gastric cancer. The results of the Oncomine database analysis showed that CTHRC1 mRNA expression was higher in GC tissues than that in normal tissues in seven datasets (Figure 1). Furthermore, these results also revealed that CTHRC1 was highly expressed in the brain and CNS cancer, breast cancer, cervical cancer, colorectal cancer, esophageal cancer, head and neck cancer, leukemia, liver cancer, lung cancer, lymphoma, melanoma, pancreatic cancer, and prostate cancer. In different pathological types of GC, including mucinous gastric adenocarcinoma (Figure 2A, p<0.001, t-test=5.595, fold change=1.164), gastric adenocarcinoma (Figure 2B, p<0.001, t-test=10.937, fold change=1.171), gastric tubular adenocarcinoma (Figure 2C, p<0.001, t-test=4.950, fold change=1.214), gastric intestinal type adenocarcinoma (Figure 2D, p<0.001, t-test=5.888, fold change=1.199), and diffuse gastric adenocarcinoma (Figure 2E, p<0.001, t-test=3.830, fold change=1.142), CTHRC1 mRNA expression increased. We assessed the expression of CTHRC1 in the TCGA-STAD database to further evaluate the expression of CTHRC1 in GC. The results showed that the expression of CTHRC1 in GC was significantly lower than that in adjacent normal tissues (p<0.001) (Figure 2F).
The expression of collagen triple helix repeat containing-1 (CTHRC1) in cancers and in gastric cancer based on Oncomine. (A) The expression of CTHRC1 in different cancer types. (B) The expression levels of CTHRC1 in gastric cancer. Red means higher relative expression compared to normal cells.
The expression of collagen triple helix repeat containing-1 (CTHRC1) in gastric cancer (GC) based on The Cancer Genome Atlas (TCGA) and in different pathological GC based on Oncomine. (A) The expression of CTHRC1 in mucinous gastric adenocarcinoma. (B) The expression of CTHRC1 in gastric adenocarcinoma. (C) The expression of CTHRC1 in gastric tubular adenocarcinoma. (D) The expression of CTHRC1 in gastric intestinal type adenocarcinoma. (E) The expression of CTHRC1 in diffuse gastric adenocarcinoma. (F) The expression of CTHRC1 in gastric cancer based on TCGA-STAD.
CTHRC1 expression level predicts GC prognosis. We assessed the relationship between CTHRC1 expression level and the prognosis of GC via the Kaplan–Meier plotter databases. The results indicated that the higher the expression level of CTHRC1 in patients with GC, the shorter the survival (HR=1.55, 95%CI=1.24-1.94, p<0.001). In addition, the Kaplan–Meier plotter analysis (Figure 3) revealed that the expression levels of CTHRC1 also affected the first progression (FP) and post-progression survival (PPS) of patients with GC. The higher the expression level of CTHRC1, the shorter the time of first progression (HR=1.75, 95%CI=1.38-2.23, p<0.001) and the shorter the post-progression survival (HR=1.61, 95%CI=1.2-2.16, p<0.001). In addition, TCGA data were also used to confirm the prognostic value of CTHRC1 in patients with GC. Based on the mean CTHRC1 expression level, patients with GC were divided into a high expression group and a low expression group. The survival curve was obtained by R software calculation and visualization, and the results were consistent with the Kaplan–Meier plotter databases. Therefore, higher CTHRC1 expression is a risk factor for a poor prognosis in GC.
Kaplan–Meier survival curves of patients with gastric cancer (GC) with high vs. low collagen triple helix repeat containing-1 (CTHRC1) expression. (A) Comparison of the overall survival of GC patients with high CTHRC1 expression and low expression in Kaplan–Meier Plotter Database (HR=1.55, 95%CI=1.24-1.94, p<0.001). (B) Comparison of the first progression of GC patients with high CTHRC1 expression and low expression in Kaplan–Meier Plotter Database (HR=1.75, 95%CI=1.38-2.23, p<0.001). (C) Comparison of the post-progression survival of GC patients with high CTHRC1 expression and low expression in Kaplan–Meier Plotter Database (HR=1.61, 95%CI=1.2-2.16, p<0.01). (D) Comparison of the overall survival of GC patients with high CTHRC1 expression and low expression in The Cancer Genome Atlas (TCGA)-STAD Database (p<0.05).
Univariate and multivariate cox regression analysis. The CTHRC1 expression level was significantly correlated with the overall survival of patients with GC. We used a Cox proportional hazard regression model (Figure 4) to evaluate the influence of CTHRC1 expression and other clinicopathological factors on survival in 317 patients with GC in the TCGA-STAD database, which contains complete clinical data. The univariate regression analysis showed that age, stage, T stage, M stage, and CTHRC1 expression were important predictors of survival. In addition, the multivariate regression analysis was also performed. The results showed that CTHRC1 expression was an important independent predictor of a poor prognosis.
Forest plot for the multivariate COX proportional hazard regression model. Collagen triple helix repeat containing-1 (CTHRC1) is an independent predictor of poor survival rate (HR=1.01, 95%CI=1.00-1.0; p=0.013). *p<0.05, **p<0.01, ***p<0.001.
CTHRC1 is correlated with infiltrating immune cells in the microenvironment of GC. The infiltration of immune cells into the tumor microenvironment is considered an important factor affecting the prognosis of tumors (22-26). To evaluate the relationship between CTHRC1 expression and tumor-infiltrated immune cells in GC, we used TIMER for analysis. The results indicated that CTHRC1 expression had significant negative correlations with GC tumor purity (R=−0.148, p<0.001) (Figure 5A) and the infiltration levels of B cells (R=−0.253, p<0.001) (Figure 5B). The CTHRC1 expression level had significant positive correlations with the infiltration levels of CD8+ T cells (R=0.125, p<0.001) (Figure 5C), macrophages (R=0.405, p<0.001) (Figure 5E), neutrophils (R=0.249, p<0.001) (Figure 5F), and dendritic cells (R=0.315, p<0.001) (Figure 5G). The CTHRC1 expression level had no relationship with CD4+ T cell infiltration (R=0.036, p<0.001) (Figure 5D). This finding suggests that CTHRC1 may affect the prognosis of GC by affecting the infiltration of immune cells.
The correlation between collagen triple helix repeat containing-1 (CTHRC1) and immune cells. (A) The correlation between CTHRC1 expression and tumor purity (Cor=−0.148, p<0.001). (B) The correlation between CTHRC1 expression and B cells (Cor=−0.253, p<0.001). (C) The correlation between CTHRC1 expression and CD8+ T cells (Cor=0.125, p<0.05. (D) The correlation between CTHRC1 expression and CD4+ T cells (Cor=0.036, p=0.491). (E) The correlation between CTHRC1 expression and macrophages (Cor=0.405, p<0.001). (F) The correlation between CTHRC1 expression and neutrophils (Cor=0.249, p<0.001). (G) The correlation between CTHRC1 expression and dendritic cells (Cor=0.315, p<0.001).
The correlation between CTHRC1 expression level and the infiltration of immunosuppressive cells in GC. Immune escape plays an important role in tumor progression and is closely related to tumor prognosis (27, 28). Tumor cell escape of immune destruction is a critical step of tumor progression and is related to the infiltration of immunosuppressive cells in the tumor microenvironment (28). TAMs, M2 monocytes, Th2 cells, and Treg cells were shown to be immunosuppressive cells (29). Immunosuppressive cells were recognized by cell markers, including TAMs, M2 monocytes, Th2 cells, and Tregs, via the website CellMarker (19). We next used the TIMER and GEPIA databases to investigate the relationship between immunosuppressive cell markers and CTHRC1 expression levels to determine whether the expression of CTHRC1 is related to the infiltration of immunosuppressive cells. The TIMER results showed that CTHRC1 was significantly correlated with the infiltration of TAMs, M2 monocytes, Th2 cells, and Tregs, with or without adjustment for purity (Table III). We performed the same analysis to verify this finding in GEPIA, and the same results were obtained (Table IV).
Analysis of the correlation between collagen triple helix repeat containing-1 (CTHRC1) expression and gene markers of immune suppressor cells in Tumor Immune Estimation Resource (TIMER).
Analysis of the correlation between collagen triple helix repeat containing-1 (CTHRC1) expression and gene markers of immune suppressor cells in Gene Expression Profiling Interactive Analysis (GEPIA).
Gene set enrichment analysis in GC. The signaling pathways enriched by GSEA that met the following conditions were considered to be significantly enriched signaling pathways: NES>1, FDR q-value>0.25, and nominal p-value<0.05. In this study, a total of 106 pathways were enriched in the CTHRC1 over-expression group and the top 15 significant signaling pathways enriched were ECM receptor interaction, focal adhesion, hedgehog signalling pathway, TGF beta signalling pathway, glycosaminoglycan biosynthesis chondroitin sulfate, basal cell carcinoma, melanoma, complement and coagulation cascades, dilated cardiomyopathy, hypertrophic cardiomyopathy HCM, pathways in cancer, cytokine-cytokine receptor pathway, cell adhesion molecules (CAMs), lysosome, and leishmanial infection in the high CTHRC1 expression phenotypes (Table V, Figure 6).
Gene sets enriched in the high collagen triple helix repeat containing-1 (CTHRC1) expression phenotype.
Gene set enrichment analysis (GSEA) analysis enriched pathways in gastric cancer (GC). The significantly enriched pathways were ECM receptor interaction, focal adhesion, hedgehog signalling pathway, TGF beta signalling pathway, glycosaminoglycan biosynthesis chondroitin sulphate, basal cell carcinoma, melanoma, complement and coagulation cascades, dilated cardiomyopathy, hypertrophic cardiomyopathy (HCM), pathways in cancer, cytokine-cytokine receptor pathway, cell adhesion molecules (CAMs), lysosome, and leishmanial infection in the high collagen triple helix repeat containing-1 (CTHRC1) expression phenotypes.
Discussion
CTHRC1 is a glycosylated secretory protein initially found to function in vascular injury repair. Its role is to reduce collagen deposition and promote cell migration, which is crucial for wound healing (10). In previous studies, CTHRC1 has been demonstrated to be upregulated in some solid tumors, including hepatocellular carcinoma (12), pancreatic adenocarcinoma (14), gastrointestinal stromal tumor (30), colorectal cancer (31, 32), and breast cancer (33), and is closely associated with these processes. In GC, the upregulation of CTHRC1 has been shown. Wang et al. (33) found that the expression of CTHRC1 is up-regulated in GC and related to the metastasis of GC. In a clinical study, Gu et al. (17) found that CTHRC1 was highly expressed in 108 cases from 166 GC samples, and the expression level of CTHRC1 was related to gastric wall infiltration, lymph node metastasis, recurrence, and other clinical characteristics of GC. In addition, this study found that the overall survival and disease-free survival of GC patients with high CTHRC1 expression were significantly lower (p=0.001 and p=0.002). In our current research, we found that compared with that in adjacent normal tissues, CTHRC1 expression level in GC tissues was significantly higher (p<0.001). In addition, in different pathological types of GC including mucinous gastric adenocarcinoma (p<0.001, t-test=5.595, fold change=1.164), gastric adenocarcinoma (p<0.001, t-test=10.937, fold change=1.171), gastric tubular adenocarcinoma (p<0.001, t-test=4.950, fold change=1.214), gastric intestinal type adenocarcinoma (p<0.001, t-test=5.888, fold change=1.199), and diffuse gastric adenocarcinoma (p<0.001, t-test=3.830, fold change=1.142), CTHRC1 was highly expressed. We also found that patients with high CTHRC1 expression had shorter OS (HR=1.55, p<0.001) (TCGA cohort p=0.013), FP (HR=1.75, 95%CI=1.38-2.23, p<0.001), and PPS (HR=1.61, 95%CI=1.2-2.16, p<0.001). The univariate regression analysis and multivariate regression analysis showed that CTHRC1 expression was an independent risk factor for GC. From the results above, we believe that CTHRC1 is highly expressed in GC, and its expression level is related to the poor prognosis of GC; thus, CTHRC1 can be used as an independent risk factor for GC.
Most patients with GC die of cancer progression. Many studies have already shown that CTHRC1 is associated with tumor progression; in breast cancer, a high expression level of CTHRC1 is associated with bone metastasis (34). In colorectal cancer, CTHRC1 is directly related to peritoneal metastasis (32-34). Similarly, CTHRC1 plays a critical role in the progression of GC (35).
Immune infiltration is a risk factor for tumor progression. Interestingly, some studies have found that CTHRC1 can regulate the polarization and infiltration of M2 macrophages in the tumor microenvironment (36), which indicates that CTHRC1 may modify the infiltration of immune cells in the tumor microenvironment. To evaluate the relationship between CTHRC1 and immune invasion in GC, we calculated the relationship between CTHRC1 expression and six types of infiltrating immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) via the web tool TIMER. The results indicated that CTHRC1 expression had significant negative correlations with GC tumor purity (R=−0.148, p<0.001) (Figure 5A) and the infiltration levels of B cells (R=−0.253, p<0.001) (Figure 5B). The CTHRC1 expression level had significant positive correlations with the infiltration levels of CD8+ T cells (R=0.125, p<0.001) (Figure 5C), macrophages (R=0.405, p<0.001) (Figure 5E), neutrophils (R=0.249, p<0.001) (Figure 5F), and dendritic cells (R=0.315, p<0.001) (Figure 5G), and was not related to the infiltration of CD4+ T cells. These results confirmed that the expression of CTHRC1 is related to the immune infiltration of GC.
Tumor cells escape from the killing effect of the immune system through a series of changes, a phenomenon called tumor immune escape (28). Tumor immune escape is considered to be the key step of tumor metastasis. Immunosuppressive cell infiltration is an important reason for tumor immune escape, and the main immunosuppressive cells in the tumor microenvironment are TAM cells, M2 monocytes, and Tregs (28). Immunosuppressive cells are closely related to tumor progression and the clinical outcome of tumors (28, 37).
Regulatory T cells (Tregs) are a subset of T cells. They are the main immunosuppressive cells in the tumor microenvironment and play a significant role in immune escape (28). The increased infiltration of Tregs has been confirmed to be associated with poor prognosis in ovarian cancer, breast cancer and GC (37). Tregs can inhibit a variety of immunocompetent cells, including CD8+ T cells, natural killer (NK) cells, B cells, and antigen-presenting cells (APCs) (38). Tregs promote immune escape mainly by inhibiting the function of T lymphocytes, and the mechanism is that Tregs can (a) produce IL-10 and TGF-β, which are immunosuppressive cytokines, and (b) consume the cytokine IL-2 (39). In addition, Tregs can inhibit the presentation and expression of tumor-associated antigens and interfere with the function of cytotoxic T cells by inhibiting the release of particles during tumor progression (40).
Macrophages infiltrating around tumors are called tumor-associated macrophages (TAMs), which are divided into M1 macrophages and M2 macrophages. M2 macrophages are important subtypes of TAMs that participate in immune escape (41). M2 macrophages have a weaker antigen presentation ability and can produce IL-10 and TGF-β to inhibit the T cell immune response (42). We verified the correlation between the expression of CTHRC1 and the immune escape of GC through the TIMER and GEPIA databases. The results showed that the expression level of CTHRC1 was positively correlated with the invasion of Tregs, TAM cells, M2 monocytes, and other immunosuppressive cells (Table III and Table IV). Therefore, we believe that CTHRC1 is related to the immune escape of GC.
GSEA was utilized to provide the potential molecular mechanism for CTHRC1 in immune escape. A total of 106 signaling pathways were enriched in GC with high CTHRC1 expression, and the top 15 signaling pathways are listed in Table V. Among these top 15 pathways, the TGF-β signaling pathway is most relevant to tumor immunity. Much evidence indicates that TGF-β is closely related to tumor immunity (43-45). TGF-β can inhibit tumor immunity and is an immunosuppressive factor that can facilitate tumor immune escape mainly through inhibiting Th1 helper cells and cytotoxic T cells, promoting tumor immune escape by inducing and regulating the generation of T cells, inhibiting natural killer cells, changing the function of dendritic cells, and regulating the phenotype of macrophages (43).
Conclusion
In conclusion, our study showed that CTHRC1 is a biomarker for the diagnosis and prognosis of GC, and its high expression is closely related to the immune escape of GC, which may provide a new therapeutic target for immunotherapy in GC. However, the results of this study are from the analysis of bioinformatics, and more clinical trials and laboratory experiments are needed for further validation and clinical application.
Acknowledgements
This work was supported by the Science and Technology Plan Project of Chenzhou Municipal Science and Technology Bureau (No. zdyf201974). The Authors thank the Freescience Editorial Team for language assistance. The Authors acknowledge TCGA, Oncomine database, TIMER, GEPIA databases for the data analysis.
Footnotes
Authors’ Contributions
Zuliang Deng and Zhili Hu designed the study. Yangzhi Hu, Lijuan Huang, Kailai Zhao, Yuan Li, Nathan T. Givens, Aidan J. Heslin, Zuliang Deng, Zhili Hu and Yujiang Fang were involved in data analysis and/or data interpretation. Yangzhi Hu, Lijuan Huang, and Kailai Zhao drafted the manuscript. Nathan T. Givens, Aidan J. Heslin, Zuliang Deng, Zhili Hu and Yujiang Fang performed critical revision.
Conflicts of Interest
TCGA, Oncomine database, TIMER, GEPIA database belong to public databases. The patients involved in the database have obtained ethical approval. Users can download relevant data for free for research and publish relevant articles. Our study is based on open-source data, thus there are no ethical issues or conflicts of interest.
- Received October 29, 2022.
- Revision received November 10, 2022.
- Accepted November 15, 2022.
- Copyright © 2023 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
