Background HCC is a major health concern worldwide. PKC gamma, a member of the conventional PKC subclass, is involved in many cancer types, but the protein has received little attention in the context of single nucleotide polymorphisms and HCC. Therefore, the study aims to investigate the association of PKC gamma missense SNP with HCV-induced hepatocellular carcinoma. Methods The PKC gamma nsSNPs were retrieved from the ENSEMBL genome browser and the deleterious nsSNPs were filtered out through involvingPredictSNP2, CADD, DANN, FATHMM, FunSeq2 and GWAVA. Among the filtered nsSNPs, nsSNP rs1331262028 was identified to be the most pathogenic one. Through involving I-TASSER, ProjectHOPE, I-Mutant, MUpro, mCSM, SDM, DynaMut and MutPred, the influence of SNP rs1331262028 on protein structure, function and stability was estimated. A molecular Dynamic simulation was run to determine the conformational changes in mutant protein structure compared to wild. The blood samples were collected for genotyping analysis and for assessing ALT levels in the blood. Results The study identified for the first time an SNP (rs1331262028) of PRKCG to strongly decrease protein stability and induce HCC. The RMSD, RMSF, and Rg values of mutant and wild types found were significantly different. Based on OR and RR values of 5.194 and 2.287, respectively, genotype analysis revealed a higher correlation between the SNP homozygous wild Typeform, AA, and the disease while patients with genotype AG have higher viral load. Conclusion Outcomes of the current study delineated PKC gamma SNP rs1331262028 as a genetic marker for HCV-induced HCC that could facilitate disease management after further validation.

Background PRKCG encodes PKC γ, which is categorized under the classical protein kinase C family. No studies have specifically established the relationship between PRKCG nsSNPs with structural and functional variations in PKC γ in the context of hepatocellular carcinoma (HCC). The present study aims to uncover this link through in-silico and experimental studies. Methods The 3D structure of PKC γ was predicted. Molecular Dynamic (MD) Simulations were run and estimates were made for interactions, stability, conservation and post-translational alterations between wild and mutant structures. The association of PRKCG levels with HCC survival rate was determined. Genotyping analyses were conducted to investigate the deleterious PRKCG nsSNP association with HCC. mRNA expression of PKC γ, HIF-1 alpha, AKT, SOCS3 and VEGF in the blood of controls and HCC patients was analyzed and a genetic cascade was constructed depicting these interactions. Results The expression level of studied oncogenes was compared to tumour suppressor genes. Through Alphafold, the 3D structure of PKC γ was explored. Fifteen SNPs were narrowed down for in-silico analyses that were identified in exons 5, 10 and 18 and the regulatory and kinase domain of PKC γ. Root mean square deviation and fluctuation along with the radius of gyration unveiled potential changes between the wild and mutated variant structures. Mutant genotype AA (homozygous) corresponding to nsSNP, rs386134171 had more frequency in patients with OR (2.446), RR (1.564) and P-values (< 0.0029) that highlights its significant association with HCC compared to controls in which the wild genotype GG was found more prevalent. Conclusion nsSNP rs386134171 can be a genetic marker for HCC diagnosis and therapeutic studies. This study has laid down a road map for future studies to be conducted on HCC.