Unravelling Prognostic Potential of PKC Gamma in Hepatocellular Carcinoma

Abstract

Hepatocellular Carcinoma (HCC) is a major malignancy that affects millions worldwide. Owing to the recurrence and drug resistance of HCC, there is a need to search for the potential prognostic and therapeutic targets that can make cancer cells respond better to treatment. Therefore, the current study has set its direction towards the identification of a unique gene, (Protein Kinase C Gamma type (PKC γ), which is the member of conventional PKCs. Its notable role in a few cancers is reported, however, there is insufficient data from literature that can explicitly untangle its role in HCC. The current study has covered both computational and experimental approaches for determining the central role played by PKC Gamma in carcinogenesis. Tetramethoxyflavone (2-(2,6-Dimethoxyphenyl)-5,6-dimethoxy-chrome-4-one) against HCC was assessed. Its pharmacokinetics properties were determined that highlighted the drug as being highly potent for cancer. Docking was performed that showed Tetramethoxyflavone interacted with PKC Gamma. Molecular Dynamic (MD) simulations revealed the significant association of the Tetramethoxyflavone with PKC Gamma at molecular level. Moreover, Tetramethoxyflavone inhibited colony formation, migratory capacity and cell viability of liver cancer cells that included human hepatoblastoma (HepG2) and hepatoma (Huh7) cells. Reverse Transcription Polymerase Chain Reaction (RT-PCR) analysis of genes expression in HepG2 and Huh7 cells revealed the upregulation of PKC Gamma, AKT (Protein kinase B), HIF-1 alpha (Hypoxia Inducible Factor 1 subunit-alpha), Vascular Endothelial Growth Factor (VEGF) and downregulation of SOCS3 (Suppressor of Cytokine Signaling 3) relative to Beta-actin. At protein level, the western blotting revealed the similar expression pattern of PKC Gamma, AKT, SOCS3 and VEGF as revealed during mRNA expression analysis when compared with GAPDH (Glyceraldehyde 3-Phosphate-Dehydrogenase). The study was carried out at mRNA, protein, and metabolomics level. Gas Chromatography-Mass Spectroscopy (GC-MS) was done for identifying metabolites that associate with pathways, which are cancer drivers. Both the PKC Gamma coding and xxxiii non-coding Single Nucleotide Polymorphisms (SNPs) reference cluster IDs (rsIDs) were retrieved and the effect on the translated protein i.e. PKC Gamma was analyzed. The impact of PKC Gamma 3′-UTR SNP linkage with miRNA on cancer risk was determined that indicated the mutations at 3′-UTR regions lead to disruption of interaction with miRNAs, because of which the resulting protein shows differential expression that provokes cancer onset. The effect on mutations on mRNA secondary structures was also observed. Moreover, splice variants were identified that could significantly affect the splicing mechanism. In total 16 non-synonymous (ns) SNPs were narrowed down and analyzed further. nsSNPs positions were mapped across different PKC Gamma exons. The molecular mechanisms disruption and structural and functional changes because of nsSNPs were discerned. Analysis of mutations effect on PKC Gamma stability was determined through Molecular Dynamic (MD) simulations that revealed the significant fluctuations within mutant structures when the comparison was drawn with the wild. PKC Gamma sequence analysis highlighted the highly conserved residues that could alter the PTMs and regulatory pathways. Its high expression ratio in cytoplasm revealed its soluble nature and its ability to influence pathways that connect with cytoplasm, nucleus, and membrane. To add to this, the PKC Gamma expression during pathological stages and co-relation with survival was assessed. It was observed that as the cancer stage increases, so does the PKC Gamma expression that resulted in reduced survival rate. 2 nsSNPs (rs1331262028 and rs386134171) out of 16 were selected for genotypic analysis. A comparison of nsSNPs rs1331262028 and rs386134171 related genotypes AA, GG, and AG within patients and controls and between males and females was done that showed the AA genotype was associated with HCC risk. The blood-based mRNA expression analysis was done on the same genes as done in-vitro within HepG2 and Huh7 cells that indicated the upregulation of oncogenes and downregulation of tumor suppressor genes. The pathway was also constructed that specified the interconnection between genes. This study is central and holds importance as it revolves around finding an effective prognostic and genetic marker that can unfold new dimensions in HCC treatment.