Reactive Oxygen Species and Platelet-Related Prognostic Genes in Hepatocellular Carcinoma
Description
Primary liver cancer (PLC) is a malignant tumor characterized by high histological and biological heterogeneity; it ranks third in mortality among all cancers. Hepatocellular carcinoma (HCC) is the primary pathological subtype of PLC. Currently, overall survival rates for HCC remain suboptimal. Therefore, there is an urgent need to elucidate the molecular mechanisms underlying tumor progression and to develop new targeted therapies to prolong survival in HCC patients. Studies have demonstrated that reactive oxygen species (ROS) and platelets play significant roles in tumor initiation and progression, and that ROS are involved in platelet activation and aggregation. However, the interaction between ROS and platelets in HCC has not been clearly reported to date. This study employs bioinformatics to identify prognostic genes associated with ROS and platelets in HCC, develop a novel risk scoring model to predict patient prognosis, guide clinical treatment, and provide a theoretical basis for clinical decision-making and treatment strategies for HCC. In this study, we identified prognosis-related genes associated with ROS and platelets in HCC and constructed a prognostic model based on transcriptomic and single-cell datasets. We then conducted a series of analyses using these prognosis-related genes and the prognostic model, followed by experimental validation.
Files
Steps to reproduce
This study utilized LIHC samples from the public TCGA database and employed bioinformatics analysis methods to investigate the biological roles of ROS- and platelet-related genes in LIHC, including expression analysis, prognostic analysis, and genetic variant analysis. Through differential analysis and prognostic analysis, we identified prognostic genes associated with LIHC survival and used a random survival forest model to develop a risk score for LIHC patients. We validated the model using LIHC patients from the ICGC database. We then conducted functional analysis, immune cell infiltration analysis, immune microenvironment analysis, drug sensitivity analysis, regulatory network analysis, and single-cell analysis between the high- and low-risk groups.
Institutions
- First Affiliated Hospital of Xinjiang Medical UniversityXinjiang, Ürümqi