Comprehensive RNA-Seq Gene Co-Expression Analysis Reveals Consistent Molecular Pathways in Hepatocellular Carcinoma across Diverse Risk Factors

Abstract

Simple Summary The molecular heterogeneity of hepatocellular carcinoma (HCC) and its range of potential etiologies contribute to the complexities in treating this disease. Additionally, inter-sample molecular variability can mean the involvement of different prognostic genes or utilization of distinct molecular pathways in HCC development. This paper examines the genes and pathways most involved in different histological grades of HCC across various pre-cancer risk factors using publicly available bulk transcriptomics data and a systems biology approach. It identifies shared pathways among HCCs of varying grades and risk factors, as well as genes common to these pathways. Furthermore, this study highlights gene clusters preserved across risk factors, which may indicate shared targets for general treatment and gene clusters specific to viral or non-viral etiologies. Overall, this research reveals common and differing molecular pathways across risk factors and similarities in gene expression between histological grades. It provides a framework for understanding HCC development respective of risk factors and underscores the molecular pathways and genes involved.Abstract Hepatocellular carcinoma (HCC) has the highest mortality rate and is the most frequent of liver cancers. The heterogeneity of HCC in its etiology and molecular expression increases the difficulty in identifying possible treatments. To elucidate the molecular mechanisms of HCC across grades, data from The Cancer Genome Atlas (TCGA) were used for gene co-expression analysis, categorizing each sample into its pre-existing risk factors. The R library BioNERO was used for preprocessing and gene co-expression network construction. For those modules most correlated with a grade, functional enrichments from different databases were then tested, which appeared to have relatively consistent patterns when grouped by G1/G2 and G3/G4. G1/G2 exhibited the involvement of pathways related to metabolism and the PI3K/Akt pathway, which regulates cell proliferation and related pathways, whereas G3/G4 showed the activation of cell adhesion genes and the p53 signaling pathway, which regulates apoptosis, cell cycle arrest, and similar processes. Module preservation analysis was then used with the no history dataset as the reference network, which found cell adhesion molecules and cell cycle genes to be preserved across all risk factors, suggesting they are imperative in the development of HCC regardless of potential etiology. Through hierarchical clustering, modules related to the cell cycle, cell adhesion, the immune system, and the ribosome were found to be consistently present across all risk factors, with distinct clusters linked to oxidative phosphorylation in viral HCC and pentose and glucuronate interconversions in non-viral HCC, underscoring their potential roles in cancer progression.