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Identification of immune cells and mRNA associated with prognosis of gastric cancer.

ABSTRACT: BACKGROUND:The clinical success demonstrates the enormous potential of immunotherapy in cancer treatment. METHODS:This article presented research linking gastric cancer to immune cells, based on RNA-seq data of Stomach adenocarcinoma (STAD) and gene expression profile of GSE84437, 24 kinds of tumor-infiltrating immune cells were quantified by single-sample gene set enrichment analysis. RESULTS:Th2 cells, T helper cells, and Mast cells were identified as prognostic immune cells in both TCGA and GEO groups. Then SUPV3L1 and SLC22A17 were identified as hub genes which may affect immune cell infiltration by correlation analysis. Survival analysis further proved that hub genes and prognostic immune cells are associated with the prognosis of gastric cancer. In gastrointestinal tumors, hub genes and prognostic immune cells also found differences in non-tumor and tumor tissues. CONCLUSIONS:We found that three immune cells infiltration are associated with the prognosis of gastric cancer and further identify two hub genes. These two key genes may affect immune cell infiltration, result in the different prognosis of patients.

SUBMITTER: Wang M

PROVIDER: S-EPMC7068972 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Identification of immune cells and mRNA associated with prognosis of gastric cancer.

Wang Mingming M Li Zedong Z Peng Yu Y Fang Jianyu J Fang Tao T Wu Jiajia J Zhou Jun J

BMC cancer 20200312 1

<h4>Background</h4>The clinical success demonstrates the enormous potential of immunotherapy in cancer treatment.<h4>Methods</h4>This article presented research linking gastric cancer to immune cells, based on RNA-seq data of Stomach adenocarcinoma (STAD) and gene expression profile of GSE84437, 24 kinds of tumor-infiltrating immune cells were quantified by single-sample gene set enrichment analysis.<h4>Results</h4>Th2 cells, T helper cells, and Mast cells were identified as prognostic immune ce ...[more]

PMID: 32164594

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Project description:Background Gastric cancer (GC) is a highly heterogeneous disease. In recent years, the prognostic value of the mRNA expression-based stemness index (mRNAsi) across cancers has been reported. We intended to identify stemness index-associated genes (SI-genes) for clinical characteristic, gene mutation status, immune response, and tumor microenvironment evaluation as well as risk stratification and survival prediction. Methods The correlations between the mRNAsi and GC prognosis, clinical characteristics, gene mutation status, immune cell infiltration and tumor microenvironment were evaluated. Weighted gene correlation network analysis (WGCNA) was performed to identify SI-genes from differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA). Single-sample gene set enrichment analysis (ssGSEA) was employed to calculate the sample SI-gene-based ssGSEA score according to the SI-genes. Then, the correlations between the ssGSEA score and GC prognosis, clinical characteristics, gene mutation status, immune cell infiltration and tumor microenvironment were analyzed. Finally, the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was used to construct a prognostic signature with prognostic SI-genes. The ssGSEA score and prognostic signature were validated using the Gene Expression Omnibus (GEO) database. Results The mRNAsi could predict overall survival (OS), clinical characteristics, the gene mutation status, immune cell infiltration, and the tumor microenvironment composition. Fourteen positive SI-genes and 178 negative SI-genes were screened out using WGCNA. The ssGSEA score, similar to the mRNAsi, was found to be closely related to OS, clinical characteristics, the gene mutation status, immune cell infiltration, and the tumor microenvironment composition. Finally, a prognostic signature based on 18 prognostic SI-genes was verified to more accurately predict GC 1-year, 3-year, and 5-year OS than traditional clinical prediction models. Conclusion The ssGSEA score and prognostic signature based on 18 prognostic SI-genes are of great value for immune response evaluation, risk stratification and survival prediction in GC and suggest that stemness features are crucial drivers of GC progression.

Project description:Objective: Immune cells infiltrating has been proved to be associated with prognosis in gastric cancer (GC) by studies. This study aims to explore the prognosis value of infiltrating immune cells in gastric cancer. Methods: In our study, the CIBERSORT algorithm was used to calculate the fraction of 22 tumor-infiltrating immune cells (TIIC) in 100 normal and 300 tumor samples from the GEO cohort and 30 normal and 344 tumor samples from the TCGA cohort. Univariate and multivariate Cox regression were used to construct an immune risk score model. Multivariate cox regression was also used to validate whether our risk score model could predict prognosis in GC independently. Furthermore, the model was validated in different patient subgroups to test its independence. P<0.05 was considered statistically significant. Results: The results showed that the fraction of 3 immune cells increased in tumor tissues compared with normal tissues in both the GEO and TCGA cohort. Univariate cox regression analysis showed four cells significantly correlated with survival rate in GC (P<0.05). The immune risk score model was constructed based on the four cells through multivariate cox regression and further validated. The KM survival curve suggested that patients with high risk had poor prognosis than patients with low risk (P<0.05). ROC curve indicated the model was reliable (AUC= 0.67 in the GEO cohort, AUC = 0.65 in the TCGA cohort). Furthermore, multivariate Cox regression showed the model was an independent factor for overall survival predicting in GC (hazard ratio (HR) = 2.35, 95% confidence interval (CI) = 1.63~3.40 in the GEO cohort, HR = 2.87, 95% CI = 1.94~4.25 in the TCGA cohort). Finally, we validated the model in patient subgroups by the KM survival curve. Conclusion: In summary, tumor-infiltrating immune cells play an essential role in GC progression and affect the outcome of GC patients. The immune risk score can predict overall survival for GC independently, and high immune risk score is associated with poor prognosis.

Project description:BackgroundGastric cancer (GC) is one of the most common cancers, with a wide range of symptoms and outcomes. Cancer-associated fibroblasts (CAFs) are newly identified in the tumor microenvironment (TME) and associated with GC progression, prognosis, and treatment response. A novel CAF-associated prognostic model is urgently needed to improve treatment strategies.MethodsThe detailed data of GC samples were downloaded from The Cancer Genome Atlas (TCGA), GSE62254, GSE26253, and GSE84437 datasets, then obtained 18 unique CAF-related genes from the research papers. Eight hundred eight individuals with GC were classified as TCGA or GSE84437 using consensus clustering by the selected CAF-related genes. The difference between the two subtypes revealed in this study was utilized to create the "CAF-related signature score" (CAFS-score) prognostic model and validated with the Gene Expression Omnibus (GEO) database.ResultsWe identified two CAF subtypes characterized by high and low CAFS-score in this study. GC patients in the low CAFS-score group had a better OS than those in the high CAFS-score group, and the cancer-related malignant pathways were more active in the high CAFS-score group, compared to the low CAFS-score group. We found that there was more early TNM stage in the low CAFS-score subgroup, while there was more advanced TNM stage in the high CAFS-score subgroup. The expression of TMB was significantly higher in the low CAFS-score subgroup than in the high CAFS-score subgroup. A low CAFS-score was linked to increased microsatellite instability-high (MSI-H), mutation load, and immunological activation. Furthermore, the CAFS-score was linked to the cancer stem cell (CSC) index as well as chemotherapeutic treatment sensitivity. The patients in the high CAFS-score subgroup had significantly higher proportions of monocytes, M2 macrophages, and resting mast cells, while plasma cells and follicular helper T cells were more abundant in the low-risk subgroup. The CAFS-score was also highly correlated with the sensitivity of chemotherapeutic drugs. The low CAFS-score group was more likely to have an immune response and respond to immunotherapy. We developed a nomogram to improve the CAFS-clinical score's usefulness.ConclusionThe CAFS-score may have a significant role in the TME, clinicopathological characteristics, prognosis, CSC, MSI, and drug sensitivity, according to our investigation of CAFs in GC. We also analyzed the value of the CAFS-score in immune response and immunotherapy. This work provides a foundation for improving prognosis and responding to immunotherapy in patients with GC.

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Identification of immune cells and mRNA associated with prognosis of gastric cancer.

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Identification of immune cells and mRNA associated with prognosis of gastric cancer.

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