ArticleWorld journal of surgical oncology2021
Gene coexpression network approach to develop an immune prognostic model for pancreatic adenocarcinoma.
Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- An integrative pan-cancer analysis of USP37 and functional validation in pancreatic cancer.Frontiers in cell and developmental biology · 2025Article
- Identification of genetic and immune signatures for the recurrence of HER2-positive breast cancer after trastuzumab-based treatment.Breast cancer research and treatment · 2023Article
- Sensory Ion Channel Candidates Inform on the Clinical Course of Pancreatic Cancer and Present Potential Targets for Repurposing of FDA-Approved Agents.Journal of personalized medicine · 2022Article
- Prognostic value of immune-related lncRNA pairs in patients with bladder cancer.World journal of surgical oncology · 2021Article
- The immune checkpoint regulator PD-L1 expression are associated with clinical progression in prostate cancer.World journal of surgical oncology · 2021Article
- Construction and Validation of an Immune-Based Prognostic Model for Pancreatic Adenocarcinoma Based on Public Databases.Frontiers in genetics · 2021Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundPancreatic adenocarcinoma (PAAD) is a nonimmunogenic tumor, and very little is known about the relationship between the host immune response and patient survival. We aimed to develop an immune prognostic model (IPM) and analyze its relevance to the tumor immune profiles of patients with PAAD.
methodsWe investigated differentially expressed genes between tumor and normal tissues in the TCGA PAAD cohort. Immune-related genes were screened from highly variably expressed genes with weighted gene correlation network analysis (WGCNA) to construct an IPM. Then, the influence of IPM on the PAAD immune profile was comprehensively analyzed.
resultsA total of 4902 genes highly variably expressed among primary tumors were used to construct a weighted gene coexpression network. One hundred seventy-five hub genes in the immune-related module were used for machine learning. Then, we established an IPM with four core genes (FCGR2B, IL10RA, and HLA-DRA) to evaluate the prognosis. The risk score predicted by IPM was an independent prognostic factor and had a high predictive value for the prognosis of patients with PAAD. Moreover, we found that the patients in the low-risk group had higher cytolytic activity and lower innate anti-PD-1 resistance (IPRES) signatures than patients in the high-risk group.
conclusionsUnlike the traditional methods that use immune-related genes listed in public databases to screen prognostic genes, we constructed an IPM through WGCNA to predict the prognosis of PAAD patients. In addition, an IPM prediction of low risk indicated enhanced immune activity and a decreased anti-PD-1 therapeutic response.
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