Background
Congenital cataract is causing one‐third of blindness worldwide. Congenital cataract is heterogeneous in its inheritance patterns. The current study is aimed to explore the unknown genetic causes underlying congenital cataracts.
Methods
Blood samples from affected and normal individuals of n = 25 Pakistani families identified with congenital cataracts were collected. Genomic DNA was extracted and Sanger sequencing was performed to identify novel pathogenic variants in the
FYCO1
(MIM#607182) gene. Later structural bioinformatics tools and molecular dynamics simulations were performed to analyze the impact of these variants on protein structure and function.
Results
Sanger sequencing resulted in the identification of a novel splice site mutation (NM_024513.3: c.3151‐29_3151‐7del) segregating in an autosomal recessive manner. This novel variant was confirmed to be absent in the n = 300 population controls. Further, bioinformatics tools revealed the formation of a mutant protein with a loss of the Znf domain. In addition, we also found a previously known (c.4127 T > C; p.Leu1376Pro) mutation in four families. We also report a novel heterozygous variant (c.3419G > A; p.Arg1140Gln) in another family.
Conclusions
In conclusion, we report a novel deletion (NM_024513.3: c.3151‐29_3151‐7del) in one family and a frequent homozygous missense mutation (c.4127 T > C; p.Leu1376Pro) in four Pakistani families. The current research highlights the importance of autophagy in lens development and maintaining its transparency.
Ovarian cancer has the highest mortality rate among gynecologic malignancies, owing to its misdiagnosis or late diagnosis. Identification of its genetic determinants could improve disease outcomes. Conventional Protein Kinase C-γ (PKCγ) dysregulation is reported in several cancers. Similarly, its variant rs1331262028 is also reported to have an association with hepatocellular carcinoma. Therefore, the aim of the present study was to analyze the variant rs1331262028 association with ovarian cancer and to determine its impact on PKCγ’s protein interactions. Association of variation was determined through genotyping PCR (cohort size:100). Protein–protein docking and molecular dynamic simulation were carried out to study the variant impact of PKCγ interactions. The study outcome indicated the positive association of variant rs1331262028 with ovarian cancer and its clinicopathological features. Molecular dynamics simulation depicted the potential influence of variation on PKCγ molecular signaling. Hence, this study provided the foundations for assessing variant rs1331262028 as a potential prognostic marker for ovarian cancer. Through further validation, it can be applied at the clinical level.
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.
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