Bin Yang1, Jinghua Xie2, Zhiguo Li3, Dan Su2, Longfa Lin2, Xiaofeng Guo2, Zhiqiang Fu2, Quanbo Zhou2, Yanan Lu4. 1. Department of Gastrointestinal Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. 2. Department of Pancreatobiliary Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. 3. Department of Thoracic Surgery, the Second People Hospital of Foshan, Foshan, China. 4. Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Abstract
BACKGROUND: The aim of the present study was to construct a novel gene signature on the tumor microenvironment (TME) to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: We downloaded gene expression profiles and clinical information of PDAC from The Cancer Genome Atlas (TCGA) datasets, as well as Gene Expression Omnibus (GEO) datasets (GSE78229, GSE62452, and GSE28735). Differentially expressed genes were generated by comparing high versus low score groups of immune/stromal subgroups based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Subsequently, a prognostic risk score model was constructed and validated through univariate and multivariate Cox regression analyses. Finally, functional enrichment analysis and protein-protein interactions were performed to predict the functional implication of the prognostic model. RESULTS: We picked out 1,797 upregulated genes in immune groups and stromal groups. Through further analysis, we constructed a 7-gene signature on the TME. The risk score from the model effectively differentiated patients into high-risk and low-risk groups with different overall survival and was validated by GEO datasets. A functional analysis suggested that 7 selected genes and their co-expressed genes were mainly enriched in immune response, extracellular structure organization, and cell adhesion molecule binding. CONCLUSIONS: Our results showed that the 7-gene model on the TME can be used to assess the prognosis of patients with PDAC. 2021 Gland Surgery. All rights reserved.
BACKGROUND: The aim of the present study was to construct a novel gene signature on the tumor microenvironment (TME) to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: We downloaded gene expression profiles and clinical information of PDAC from The Cancer Genome Atlas (TCGA) datasets, as well as Gene Expression Omnibus (GEO) datasets (GSE78229, GSE62452, and GSE28735). Differentially expressed genes were generated by comparing high versus low score groups of immune/stromal subgroups based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Subsequently, a prognostic risk score model was constructed and validated through univariate and multivariate Cox regression analyses. Finally, functional enrichment analysis and protein-protein interactions were performed to predict the functional implication of the prognostic model. RESULTS: We picked out 1,797 upregulated genes in immune groups and stromal groups. Through further analysis, we constructed a 7-gene signature on the TME. The risk score from the model effectively differentiated patients into high-risk and low-risk groups with different overall survival and was validated by GEO datasets. A functional analysis suggested that 7 selected genes and their co-expressed genes were mainly enriched in immune response, extracellular structure organization, and cell adhesion molecule binding. CONCLUSIONS: Our results showed that the 7-gene model on the TME can be used to assess the prognosis of patients with PDAC. 2021 Gland Surgery. All rights reserved.
Entities:
Keywords:
Gene Expression Omnibus (GEO); Pancreatic cancer; The Cancer Genome Atlas (TCGA); overall survival (OS); tumor microenvironment (TME)