Non-synonymous SNPs variants of PRKCG and its association with oncogenes predispose to hepatocellular carcinoma

Fizzah Abid; Khushbukhat Khan; Yasmin Badshah; Naeem Mahmood Ashraf; Maria Shabbir; Arslan Hamid; Tayyaba Afsar; Ali Almajwal; Suhail Razak

doi:10.1186/s12935-023-02965-z

Non-synonymous SNPs variants of PRKCG and its association with oncogenes predispose to hepatocellular carcinoma

Cancer Cell Int. 2023 Jun 21;23(1):123. doi: 10.1186/s12935-023-02965-z.

Authors

Fizzah Abid¹, Khushbukhat Khan¹, Yasmin Badshah¹, Naeem Mahmood Ashraf², Maria Shabbir³, Arslan Hamid⁴, Tayyaba Afsar⁵, Ali Almajwal⁵, Suhail Razak⁶

Affiliations

¹ Department of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, 44010, Pakistan.
² School of Biochemistry and Biotechnology, University of the Punjab, Lahore, 54590, Pakistan.
³ Department of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, 44010, Pakistan. mshabbir@asab.nust.edu.pk.
⁴ LIMES Institute (AG-Netea), University of Bonn, Carl-Troll-Str. 31, 53115, Bonn, Germany.
⁵ Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
⁶ Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia. smarazi@ksu.edu.sa.

Abstract

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.

Keywords: In-silico tools; Non-synonymous SNPs; PKC γ; Protein Kinase C; Therapeutics.