Investigation of transcriptional and immunological disparities among patient groups with varied prognostic risk factors in cholangiocarcinoma.

Background: This study explores molecular features associated with better prognosis in cholangiocarcinoma (CCA).

Methods And Results: The transcriptomic and whole-exome sequencing data obtained from paired tissues of 70 were analyzed, grouping them based on progression-free survival (PFS), differentiation degree, and lymph node metastasis. Among the 70 patients, the TP53 gene mutation frequency was the highest (53%), while FLG gene mutation occurred exclusively in the long PFS group.

Exploration of prognostic and treatment markers in hepatocellular carcinoma via GPCR-related genes analysis.

Background: G protein-coupled receptors (GPCRs), the biggest family of signaling receptors, account for 34 % of all the drug targets approved by the Food and Drug Administration (FDA). It has been gradually recognized that GPCRs are of significance for tumorigenesis, but in-depth studies are still required to explore specific mechanisms. In this study, the role of GPCRs in hepatocellular carcinoma (HCC) was elucidated, and GPCR-related genes were employed for building a risk-score model for the prognosis and treatment efficacy prediction of HCC patients.

Immune checkpoint inhibitor-related molecular markers predict prognosis in extrahepatic cholangiocarcinoma.

Background: Therapeutic approaches for extrahepatic cholangiocarcinoma (EHCC) are limited, due to insufficient understanding to biomarkers related to prognosis and drug response. Here, we comprehensively assess the molecular characterization of EHCC with clinical implications.

Methods: Whole-exome sequencing (WES) on 37 tissue samples of EHCC were performed to evaluate genomic alterations, tumor mutational burden (TMB) and microsatellite instability (MSI).

Gene signature and connectivity mapping to assist with drug prediction for pancreatic ductal adenocarcinoma.

Introduction: The prognosis of patients with pancreatic ductal adenocarcinoma (PDAC) is highly variable and there is a paucity of effective treatment options for patients with PDAC. Genome-wide analyses may allow for potential drugs to be identified using differentially expressed genes, as well as constructing protein interaction networks and molecule-gene connectivity mapping.

Methods: Microarray data of RNA expression profiling of PDAC and normal pancreas tissues were downloaded from the Gene Expression Omnibus (GEO).

Novel Drug Candidate Prediction for Intrahepatic Cholangiocarcinoma via Hub Gene Network Analysis and Connectivity Mapping.

Intrahepatic cholangiocarcinoma (ICC) is an aggressive malignancy, and there is a need for effective systemic therapies. Gene expression profile-based analyses may allow for efficient screening of potential drug candidates to serve as novel therapeutics for patients with ICC. The RNA expression profile of ICC and normal biliary epithelial cells were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases.