Dataset Information

Immune-related gene signature predicts overall survival of gastric cancer patients with varying microsatellite instability status.

ABSTRACT:

Purpose

Gastric cancer (GC) is one of the most common and fatal malignancies globally. While microsatellite instability (MSI) index has earlier been correlated with survival outcome in gastric cancer patients, the present study aims to construct a risk-stratification model based on immune-related genes in GC patients with varying MSI status.

Results

The univariate and multivariate Cox regression analyses identified SEMA7A, NUDT6, SCGB3A1, NPR3, PTH1R, and SHC4 as signature genes, which were used to build the prognostic model for GC patients with microsatellite instability-low (MSI-L) and microsatellite stable (MSS). Whereas, for GC patients with microsatellite instability-high (MSI-H), prognostic model was established with three genes (SEMA6A, LTBP1, and BACH2), based on the univariate and multivariate Cox regression, and Kaplan-Meier survival analyses.

Conclusion

The prognostic immune-related gene signature identified in this study may offer new targets for personalized treatment and immunotherapy for GC patients with MSI-H or MSI-L/MSS status.

Methods

The Cancer Genome Atlas (TCGA) and ImmPort databases were used to extract expression data and to explore prognostic genes from the immune-related genes (IRGs), respectively. Univariate and multivariate Cox regression analysis were applied to identify IRGs correlated with patient prognosis. The regulatory network between prognostic IRGs and TFs were performed using R software.

SUBMITTER: Tian R

PROVIDER: S-EPMC7880323 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Immune-related gene signature predicts overall survival of gastric cancer patients with varying microsatellite instability status.

Tian Ruyue R Hu Jiexuan J Ma Xiao X Liang Lei L Guo Shuilong S

Aging 20201209 2

<h4>Purpose</h4>Gastric cancer (GC) is one of the most common and fatal malignancies globally. While microsatellite instability (MSI) index has earlier been correlated with survival outcome in gastric cancer patients, the present study aims to construct a risk-stratification model based on immune-related genes in GC patients with varying MSI status.<h4>Results</h4>The univariate and multivariate Cox regression analyses identified SEMA7A, NUDT6, SCGB3A1, NPR3, PTH1R, and SHC4 as signature genes, ...[more]

PMID: 33316777

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Project description:BackgroundMicrosatellite instability-high (MSI-H) subgroup of gastric cancer (GC) is characterized by a high tumor mutational burden, increased lymphocytic infiltration, and enhanced inflammatory cytokines. GC patients with MSI-H status have a good response to immune checkpoint blockade management. However, heterogeneity within the subtype and the underlying mechanisms of shaping tumor microenvironments remain poorly understood.MethodsRNA expression levels and clinical parameters of GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The data were analyzed using single-sample Gene Set Enrichment Analysis (ssGSEA), univariate Cox regression, multivariate Cox regression, and Least Absolute Shrinkage Selection Operator (LASSO) regression. In addition, multiplex immunohistochemistry (mIHC) was used in our clinical cohort for the tumor microenvironment study.ResultsBy ssGSEA and survival analysis, the EMT signaling pathway was identified as a representative pathway, which can stratify the patients with MSI-H GC with significant survival predictive power. Then, a novel representative EMT-related five-gene signature (namely CALU, PCOLCE2, PLOD2, SGCD, and THBS2) was established from EMT signaling gene set, which sensitivity and specificity were further validated in the independent GEO database (GSE62254) cohort for disease outcome prediction. Based on public single-cell data and in situ immunohistochemistry, we found that most of these five genes were abundantly expressed in cancer-associated fibroblasts. Furthermore, patients with high or low risk divided by this five-gene signature exhibited a strong correlation of the distinct patterns of tumor immune microenvironment. By mIHC staining of sections from 30 patients with MSI-H status, we showed that the patients with better prognoses had the increased infiltration of CD8+ cells in the primary tumoral tissue.ConclusionOur study developed a simple five-gene signature for stratifying MSI-H GC patients with survival predictive power.

Project description:BackgroundGastric cancer (GC) has a high mortality rate and is one of the most fatal malignant tumours. Male sex has been proven as an independent risk factor for GC. This study aimed to identify immune-related genes (IRGs) associated with the prognosis of male GC.MethodsRNA sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed IRGs between male GC and normal tissues were identified by integrated bioinformatics analysis. Univariate and multivariate Cox regression analyses were applied to screen survival-associated IRGs. Then, GC patients were separated into high- and low-risk groups based on the median risk score. Furthermore, a nomogram was constructed based on the TCGA dataset. The prognostic value of the risk signature model was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index and calibration curves. In addition, the gene expression dataset from the Gene Expression Omnibus (GEO) was also downloaded for external validation. The relative proportions of 22 types of infiltrating immune cells in each male GC sample were evaluated using CIBERSORT.ResultsA total of 276 differentially expressed IRGs were screened, including 189 up-regulated and 87 down-regulated genes. Subsequently, a seven-IRGs signature (LCN12, CCL21, RNASE2, CGB5, NRG4, AGTR1 and NPR3) was identified to be significantly associated with the overall survival (OS) of male GC patients. Survival analysis indicated that patients in the high-risk group exhibited a poor clinical outcome. The results of multivariate analysis revealed that the risk score was an independent prognostic factor. The established nomogram could be used to evaluate the prognosis of individual male GC patients. Further analysis showed that the prognostic model had excellent predictive performance in both TCGA and validated cohorts. Besides, the results of tumour-infiltrating immune cell analysis indicated that the seven-IRGs signature could reflect the status of the tumour immune microenvironment.ConclusionsOur study developed a novel seven-IRGs risk signature for individualized survival prediction of male GC patients.

Dataset Information

Immune-related gene signature predicts overall survival of gastric cancer patients with varying microsatellite instability status.

Purpose

Results

Conclusion

Methods

Publications

Immune-related gene signature predicts overall survival of gastric cancer patients with varying microsatellite instability status.

Similar Datasets

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