A universal co‐expression gene network and prognostic model for hepatic–biliary–pancreatic cancers identified by integrative analyses. Issue 11 (23rd September 2022)

• Record Type: Journal Article
• Authors: Zhang, Jing; Xiao, Juan; Wang, Yixuan; Zheng, Xiao; Cui, Jiajun; Wang, Chaochen
• Other Names: Rizo Josep guestEditor.
• Is Part Of: FEBS open bio. Volume 12:Issue 11(2022)
• Page Start: 2006
• Page End: 2024
• Publication Date: 2022-09-23
• Subjects: cholangiocarcinoma -- hepatocellular carcinoma -- pancreatic adenocarcinoma -- prognosis -- training cohort -- validation cohort; Molecular biology -- Periodicals; Cytology -- Periodicals; Life sciences -- Periodicals; Biological Science Disciplines -- Periodicals; Molecular Biology -- Periodicals; Cell Biology -- Periodicals; Cytology; Life sciences; Molecular biology; Periodicals; 572.805
• DOI: 10.1002/2211-5463.13478
• Languages: English
• ISSNs: 2211-5463

Abstract

Abstract : Hepatic, biliary and pancreatic cancers are a diverse set of malignancies with poor prognoses. It is possible that common molecular mechanisms are involved in the carcinogenesis of these cancers. Here, we identified LINC01537 and seven protein‐coding genes by integrative analysis of transcriptomes of mRNAs, microRNAs and long non‐coding RNAs from cholangiocarcinoma, hepatocellular carcinoma and pancreatic adenocarcinoma cohorts in TCGA. A predictive model constructed from seven biomarkers was established to successfully predict the survival rate of patients, which was then further verified in external cohorts. Additionally, patients with high‐risk scores in our model were prone to epithelial–mesenchymal transition. Finally, activation of the biomarker PDE2A significantly attenuated migration and epithelial–mesenchymal transition in the HepG2 liver cancer cell line. Abstract : Hepatic, biliary and pancreatic cancers are a diverse set of malignancies with poor prognoses. Here, we established a prognostic model for hepatic–biliary–pancreatic cancers based on ACSM5, ADRA1A, CCL14, DNASE1L3, LILRB5, PDE2A and RBP5 expression. Our prognostic model was predictive of patient survival in both TCGA test cohorts and in two independent validation cohorts.