Familiarity Breeds Strategy: In Silico Untangling of the Molecular Complexity on Course of Autoimmune Liver Disease-to-Hepatocellular Carcinoma Transition Predicts Novel Transcriptional Signatures

Abstract

Autoimmune liver diseases (AILD) often lead to transformation of the liver tissues into hepatocellular carcinoma (HCC). Considering the drawbacks of surgical procedures in such cases, need of successful non-invasive therapeutic strategies and treatment modalities for AILD-associated-HCC still exists. Due to the lack of clear, sufficient knowledge about factors mediating AILD-to-HCC transition, an in silico approach was adopted to delineate the underlying molecular deterministic factors. Parallel enrichment analyses on two different public microarray datasets (GSE159676 and GSE62232) pinpointed the core transcriptional regulators as key players. Correlation between the expression kinetics of these transcriptional modules in AILD and HCC was found to be positive primarily with the advancement of hepatic fibrosis. Most of the regulatory interactions were operative during early (F0–F1) and intermediate fibrotic stages (F2–F3), while the extent of activity in the regulatory network considerably diminished at late stage of fibrosis/cirrhosis (F4). Additionally, most of the transcriptional targets with higher degrees of connectivity in the regulatory network (namely DCAF11, PKM2, DGAT2 and BCAT1) may be considered as potential candidates for biomarkers or clinical targets compared to their low-connectivity counterparts. In summary, this study uncovers new possibilities in the designing of novel prognostic and therapeutic regimen for autoimmunity-associated malignancy of liver in a disease progression-dependent fashion.

Keywords

• autoimmune liver disease
• hepatocellular carcinoma
• HCC transcriptomics
• hepatic fibrosis
• liver cirrhosis
• gene regulatory network