Integration of network pharmacology, metabolomics and lipidomics for clarifying the role of sphingolipid metabolism in the treatment of liver cancer by regorafenib.

Aims: Regorafenib, an FDA-approved drug for advanced primary liver cancer (PLC), could provide survival benefits for patients. However, markers for its therapeutic sensitivity are lacking. This study seeks to identify sensitive targets of regorafenib in PLC from the perspective of small molecular metabolites.

Development of Prognostic Features of Hepatocellular Carcinoma Based on Metabolic Gene Classification and Immune and Oxidative Stress Characteristic Analysis.

Background: The molecular classification of HCC premised on metabolic genes might give assistance for diagnosis, therapy, prognosis prediction, immune infiltration, and oxidative stress in addition to supplementing the limitations of the clinical staging system. This would help to better represent the deeper features of HCC.

Methods: TCGA datasets combined with GSE14520 and HCCDB18 datasets were used to determine the metabolic subtype (MC) using ConsensusClusterPlus.

Safety and efficacy of S1 monotherapy or combined with nab-paclitaxel in advanced elderly pancreatic cancer patients: A meta-analysis.

Objective: To evaluate the therapeutic efficacy and safety of S1 monotherapy or combination with nab-paclitaxel for the treatment of elderly patients with metastatic or locally advanced pancreatic adenocarcinoma.

Method: PubMed, Embase, Cochrane Central Library, China Biology Medicine, and China National Knowledge Infrastructure databases were searched without time limits according to the inclusion criteria. RevMan (Version 5.

HDNA methylation data-based molecular subtype classification related to the prognosis of patients with hepatocellular carcinoma.

Background: DNA methylation is a common chemical modification of DNA in the carcinogenesis of hepatocellular carcinoma (HCC).

Methods: In this bioinformatics analysis, 348 liver cancer samples were collected from the Cancer Genome Atlas (TCGA) database to analyse specific DNA methylation sites that affect the prognosis of HCC patients.

Results: 10,699 CpG sites (CpGs) that were significantly related to the prognosis of patients were clustered into 7 subgroups, and the samples of each subgroup were significantly different in various clinical pathological data.

Identification of a long non‑coding RNA‑mediated competitive endogenous RNA network in hepatocellular carcinoma.

The present study was designed to identify the endogenous RNA regulatory networks involved in hepatocellular carcinoma (HCC) by bioinformatic analysis. Both miRNA interaction network‑based correlation analysis and expression‑based Spearman correlation coefficients were utilized to identify potential mRNA‑lncRNA interactions. Then, a competitive endogenous (ce)RNA network was constructed from these interactions, and network topology and Gene Ontology enrichment analyses were conducted to mine potential functions of ceRNAs.