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Role of the tumor microenvironment in the pathogenesis of gastric carcinoma.

ABSTRACT: Gastric carcinoma (GC) is the 4(th) most prevalent cancer and has the 2(nd) highest cancer-related mortality rate worldwide. Despite the incidence of GC has decreased over the past few decades, it is still a serious health problem. Chronic inflammatory status of the stomach, caused by the infection of Helicobacter pylori (H. pylori) and through the production of inflammatory mediators within the parenchyma is suspected to play an important role in the initiation and progression of GC. In this review, the correlation between chronic inflammation and H. pylori infection as an important factor for the development of GC will be discussed. Major components, including tumor-associated macrophages, lymphocytes, cancer-associated fibroblasts, angiogenic factors, cytokines, and chemokines of GC microenvironment and their mechanism of action on signaling pathways will also be discussed. Increasing our understanding of how the components of the tumor microenvironment interact with GC cells and the signaling pathways involved could help identify new therapeutic and chemopreventive targets.

SUBMITTER: Chung HW

PROVIDER: S-EPMC3930967 | biostudies-other | 2014 Feb

REPOSITORIES: biostudies-other

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Role of the tumor microenvironment in the pathogenesis of gastric carcinoma.

Chung Hye Won HW Lim Jong-Baeck JB

World journal of gastroenterology 20140201 7

Gastric carcinoma (GC) is the 4(th) most prevalent cancer and has the 2(nd) highest cancer-related mortality rate worldwide. Despite the incidence of GC has decreased over the past few decades, it is still a serious health problem. Chronic inflammatory status of the stomach, caused by the infection of Helicobacter pylori (H. pylori) and through the production of inflammatory mediators within the parenchyma is suspected to play an important role in the initiation and progression of GC. In this re ...[more]

PMID: 24587646

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Project description:Background: Gastric carcinoma (GC) is a carcinoma with a high incidence rate, and it is a deadly carcinoma globally. An effective tool, that is, able to predict different survival outcomes for GC patients receiving individualized treatments is deeply needed. Methods: In total, data from 975 GC patients were collected from TCGA-STAD, GSE15459, and GSE84437. Then, we performed a comprehensive unsupervised clustering analysis based on 54 TGFβ-pathway-related genes and correlated these patterns with tumor microenvironment (TME) cell-infiltrating characteristics. WGCNA was then applied to find the module that had the closest relation with these patterns. The least absolute shrinkage and selection operator (LASSO) algorithm was combined with cross validation to narrow down variables and random survival forest (RSF) was used to create a risk score. Results: We identified two different TGFβ regulation patterns and named them as TGFβ Cluster 1 and Cluster 2. TGFβ Cluster 1 was linked to significantly poorer survival outcomes and represented an inflamed TME subtype of GC. Using WGCNA, a module (magenta) with the closest association with the TGFβ clusters was identified. After narrowing down the gene list by univariate Cox regression analysis, the LASSO algorithm and cross validation, four of the 243 genes in the magenta module were applied to build a risk score. The group with a higher risk score exhibited a considerably poorer survival outcome with high predictive accuracy. The risk score remained an independent risk factor in multivariate Cox analysis. Moreover, we validated this risk score using GSE15459 and GSE84437. Furthermore, we found that the group with a higher risk score represented an inflamed TME according to the evidence that the risk score was remarkably correlated with several steps of cancer immunity cycles and a majority of the infiltrating immune cells. Consistently, the risk score was significantly related to immune checkpoint genes and T cell-inflamed gene expression profiles (GEPs), indicating the value of predicting immunotherapy. Conclusions: We have developed and validated a TGFβ-associated signature, that is, capable of predicting the survival outcome as well as depicting the TME immune characteristics of GC. In summary, this signature may contribute to precision medicine for GC.

Project description:BackgroundGastric cancer (GC) still represents the third leading cause of cancer-related death worldwide. Peritoneal relapse (PR) is the most frequent metastasis occurring among patients with advanced gastric cancer. Increasingly more evidence have clarified the tumor immune microenvironment (TIME) may predict survival and have clinical significance in GC. However, tumor-transcriptomics based immune signatures derived from immune profiling have not been established for predicting the peritoneal recurrence of the advanced GC.MethodsIn this study, we depict the immune landscape of GC by using transcriptome profiling and clinical characteristics retrieved from GSE62254 of Gene Expression Omnibus (GEO). Immune cell infiltration score was evaluated via single-sample gene set enrichment (ssGSEA) analysis algorithm. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was used to select the valuable immune cells and construct the final model for the prediction of PR. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to check the accuracy of PRIs. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to explore the molecular pathways associated with PRIs.ResultsA peritoneal recurrence related immune score (PRIs) with 10 immune cells was constructed. Compared to the low-PRIs group, the high-PRIs group had a greater risk. The upregulation of the focal adhesion signaling was observed in the high-PRIs subtype by GSEA and KEGG. Multivariate analysis found that both in the internal training cohort and the internal validation cohort, PRIs was a stable and independent predictor for PR. A nomogram that integrated clinicopathological features and PRIs to predict peritoneal relapse was constructed. Subgroup analysis indicated that the PRIs could obviously distinguish peritoneal recurrence in different molecular subtypes, pathological stages and Lauren subtypes, in which PRIs of Epithelial-Mesenchymal Transitions (EMT) subtype, III-IV stage and diffuse subtype are higher respectively.ConclusionOverall, we performed a comprehensive evaluation of the immune landscape of GC and constructed a predictive PR model based on the immune cell infiltration. The PRIs represents novel promising feature of predicting peritoneal recurrence of GC and sheds light on the improvement of the personalized management of GC patients after surgery.

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Role of the tumor microenvironment in the pathogenesis of gastric carcinoma.

Publications

Role of the tumor microenvironment in the pathogenesis of gastric carcinoma.

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