Two novel PRKCI polymorphisms and prostate cancer risk in an Eastern Chinese Han population

Exploring the prognostic significance of PKCε variants in cervical cancer

BACKGROUND

Protein Kinase C-epsilon (PKCε) is a member of the novel subfamily of PKCs (nPKCs) that plays a role in cancer development. Studies have revealed that its elevated expression levels are associated with cervical cancer. Previously, we identified pathogenic variations in its different domains through various bioinformatics tools and molecular dynamic simulation. In the present study, the aim was to find the association of its variants rs1553369874 and rs1345511001 with cervical cancer and to determine the influence of these variants on the protein-protein interactions of PKCε, which can lead towards cancer development and poor survival rates.

METHODS

The association of the variants with cervical cancer and its clinicopathological features was determined through genotyping analysis. Odds ratio and relative risk along with Fisher exact test were calculated to evaluate variants significance and disease risk. Protein-protein docking was performed and docked complexes were subjected to molecular dynamics simulation to gauge the variants impact on PKCε's molecular interactions.

RESULTS

This study revealed that genetic variants rs1553369874 and rs1345511001 were associated with cervical cancer. Smad3 interacts with PKCε and this interaction promotes cervical cancer angiogenesis; therefore, Smad3 was selected for protein-protein docking. The analysis revealed PKCε variants promoted aberrant interactions with Smad3 that might lead to the activation of oncogenic pathways. The data obtained from this study suggested the prognostic significance of PRKCE gene variants rs1553369874 and rs1345511001.

CONCLUSION

Through further in vitro and in vivo validation, these variants can be used at the clinical level as novel prognostic markers and therapeutic targets against cervical cancer.

Elucidating the role of missense SNP of protein kinase C epsilon in HCV-induced hepatocellular carcinoma

BACKGROUND

The protein kinase C (PKC) family of serine/threonine kinases contains more than ten isozymes that are involved in multiple signaling pathways, including cell cycle regulation and carcinogenesis. The PKCε isozyme is an oncogene known to be upregulated in various signaling pathways involved in hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC). However, there is no known association of missense SNPs in PKCε with this disease, which can be a potential biomarker for early diagnosis and treatment. This research reveals a novel missense SNP in PKCε that is associated with HCV-induced HCC in the Pakistani population.

METHODS

The PKCε SNP with amino acid substitution of E14K was chosen for wet lab analysis. Tetra ARMS-PCR was employed for the identification of high-risk SNP in PKCε of HCV-induced HCC patients. Liver function testing was also performed for comparison between the liver condition of the HCC patient and control group, and the viral load of HCC patient samples was evaluated to determine any alteration in the viral infectivity between different genotypes of the selected high-risk PKCε variant SNP.

RESULTS

Frequency distribution of the homozygous GG genotype was found to be highest among HCV-induced HCC patients and was also found to be significantly associated with disease development and progression. The p values of comparative data obtained for the other two genotypes, heterozygous AG and homozygous AA, of the SNP also showed the significance of the data for these alleles. Still, their odds ratio and relative risk analysis did not indicate their association with HCV-induced HCC.

CONCLUSION

The distribution of a genotype GG of PKCε has been found in HCV- induced HCC patients. Therefore, these PKCε SNP have the potential to be biomarkers for HCV-induced HCC. Further investigation using a larger sample size would provide additional insight into these initial data and open a new avenue for a better prognosis of this disease.

Protein Kinase C (PKC) Isozymes as Diagnostic and Prognostic Biomarkers and Therapeutic Targets for Cancer

Protein kinase C (PKC) is a large family of calcium- and phospholipid-dependent serine/threonine kinases that consists of at least 11 isozymes. Based on their structural characteristics and mode of activation, the PKC family is classified into three subfamilies: conventional or classic (cPKCs; α, βI, βII, and γ), novel or non-classic (nPKCs; δ, ε, η, and θ), and atypical (aPKCs; ζ, ι, and λ) (PKCλ is the mouse homolog of PKCι) PKC isozymes. PKC isozymes play important roles in proliferation, differentiation, survival, migration, invasion, apoptosis, and anticancer drug resistance in cancer cells. Several studies have shown a positive relationship between PKC isozymes and poor disease-free survival, poor survival following anticancer drug treatment, and increased recurrence. Furthermore, a higher level of PKC activation has been reported in cancer tissues compared to that in normal tissues. These data suggest that PKC isozymes represent potential diagnostic and prognostic biomarkers and therapeutic targets for cancer. This review summarizes the current knowledge and discusses the potential of PKC isozymes as biomarkers in the diagnosis, prognosis, and treatment of cancers.

PRKCE non-coding variants influence on transcription as well as translation of its gene

Untranslated regions of the gene play a crucial role in gene expression regulation at mRNA and protein levels. Mutations at UTRs impact expression by altering transcription factor binding, transcriptional/translational efficacy, miRNA-mediated gene regulation, mRNA secondary structure, ribosomal translocation, and stability. PKCε, a serine/threonine kinase, is aberrantly expressed in numerous diseases such as cardiovascular disorders, neurological disorders, and cancers; its probable cause is unknown. Therefore, in the current study, the influence of PRKCE 5'-and 3'UTR variants was explored for their potential impact on its transcription and translation through several bioinformatics approaches. UTR variants data was obtained through different databases and initially evaluated for their regulatory function. Variants with regulatory function were then studied for their effect on PRKCE binding with transcription factors (TF) and miRNAs, as well as their impact on mRNA secondary structure. Study outcomes indicated the regulatory function of 73 5'UTR and 17 3'UTR variants out of 376. 5'UTR variants introduced AP1 binding sites and promoted the PRKCE transcription. Four 3'UTR variants introduced a circular secondary structure, increasing PRKCE translational efficacy. A region in 5'UTR position 45,651,564 to 45,651,644 was found where variants readily influenced the miRNA-PRKCE mRNA binding. The study further highlighted a PKCε-regulated feedback loop mechanism that induces the activity of TFs, promoting its gene transcription. The study provides foundations for experimentation to understand these variants' role in diseases. These variants can also serve as the genetic markers for different diseases' diagnoses after validation at the cell and population levels.