Single-nucleotide polymorphism (SNP) analysis to associate cancer risk

Screening of high-risk deleterious missense variations in the CYP1B1 gene implicated in the pathogenesis of primary congenital glaucoma: A comprehensive in silico approach

Background

Primary congenital glaucoma (PCG) is the most common subtype of glaucoma caused by defects in the cytochrome P450 1B1 (CYP1B1) gene. It is developing among infants in more than 80% of cases who exhibit impairments in the anterior chamber angle and the trabecular meshwork. Thus, a comprehensive in silico approach was performed to evaluate the effect of high-risk deleterious missense variations in the CYP1B1 gene.

Material and methods

All the information for CYP1B1 missense variants was retrieved from the dbSNP database. Seven different tools, namely: SIFT, PolyPhen-2, PROVEAN, SNAP2, PANTHER, PhD-SNP, and Predict-SNP, were used for functional annotation, and two packages, which were I-Mutant 2.0 and MUpro, were used to predict the effect of the variants on protein stability. A phylogenetic conservation analysis using deleterious variants was performed by the ConSurf server. The 3D structures of the wild-type and mutants were generated using the I-TASSER tool, and a 50 ns molecular dynamic simulation (MDS) was executed using the GROMACS webserver to determine the stability of mutants compared to the native protein. Co-expression, protein-protein interaction (PPI), gene ontology (GO), and pathway analyses were additionally performed for the CYP1B1 in-depth study.

Results

All the retrieved data from the dbSNP database was subjected to functional, structural, and phylogenetic analysis. From the conducted analyses, a total of 19 high-risk variants (P52L, G61E, G90R, P118L, E173K, D291G, Y349D, G365W, G365R, R368H, R368C, D374N, N423Y, D430E, P442A, R444Q, F445L, R469W, and C470Y) were screened out that were considered to be deleterious to the CYP1B1 gene. The phylogenetic analysis revealed that the majority of the variants occurred in highly conserved regions. The MD simulation analysis exhibited that all mutants' average root mean square deviation (RMSD) values were higher compared to the wild-type protein, which could potentially cause CYP1B1 protein dysfunction, leading to the severity of the disease. Moreover, it has been discovered that CYP1A1, VCAN, HSD17B1, HSD17B2, and AKR1C3 are highly co-expressed and interact with CYP1B1. Besides, the CYP1B1 protein is primarily involved in the metabolism of xenobiotics, chemical carcinogenesis, the retinal metabolic process, and steroid hormone biosynthesis pathways, demonstrating its multifaceted and important roles.

Discussion

This is the first comprehensive study that adds essential information to the ongoing efforts to understand the crucial role of genetic signatures in the development of PCG and will be useful for more targeted gene-disease association studies.

In silico screening and exploration into phenotypic alterations of deleterious oncogenic single nucleotide polymorphisms in HSPB1 gene

A small heat shock protein, HSP27, encoded by HSPB1 gene strongly favors survival, proliferation and metastasis of cancer cells and its expression is dependent on post-translational modifications like phosphorylation. This study performed an extensive in silico screening of 20 deleterious non-synonymous SNPs in the coding region of HSPB1 gene, among which four were identified to be cancer associated. The SNP variant I181S introduced a new phosphorylation site in position 181, which might elevate the protein's activation potential. Emergence of other post-translational modifications was also observed in SNP variants: L144P and E130K.Significant conformational changes were observed in I181S, L144P and E130K SNP variants with respect to wild-type HSP27. These SNPs appear in one among 10⁵ individuals, making them more susceptible towards cancer. This study would therefore, instigate development of novel biomarkers for cancer risk detection and would provide a detailed understanding towards varied cancer susceptibility of human population.

Exploring Single Nucleotide Polymorphisms in ITGAV for Gastric, Pancreatic and Liver Malignancies: An Approach Towards the Discovery of Biomarker

BACKGROUND

Integrin αV, encoded by ITGAV gene, is one of the most studied protein subunits, closely associated with liver, pancreatic and stomach cancer progression and metastasis via regulation of angiogenesis. The occurrence of Single Nucleotide Polymorphisms (SNPs) in cancer- associated proteins is a key determinant for varied susceptibility of an individual towards cancer.

METHODOLOGY

The study investigated the deleterious effects of these cancer-associated SNPs on the protein's structure, stability and cancer causing potential using an in silico approach. Numerous computational tools were employed that identified the most deleterious cancer-associated SNPs and those to get actively involved in post-translational modifications. The impact of these SNPs on the protein structure, function and stability was also examined. Conclusion and Future Scope: A total 63 non-synonymous SNPs in ITGAV gene were observed to be associated in these three gastrointestinal cancers and among this, 63, 19 were the most deleterious ones. The structural and functional importance of residues altered by most damaging SNPs was analyzed through evolutionary conservation and solvent accessibility. The study also elucidated three-dimensional structures of the 19 most damaging mutants. The analysis of conformational variation identified 5 SNPs (D379Y, G188E, G513V, L950P, and R540L) in integrin αV, which influence the protein's structure. Three calcium binding sites were predicted at residues: D379, G384 and G408 and a peptide binding site at residue: R369 in integrin αV. Therefore, SNPs D379Y, G384C, G408R and R369W have the potential to alter the binding properties of the protein. Screening and characterization of deleterious SNPs could advance novel biomarker discovery and therapeutic development in the future.

First Proposal of Minimum Information About a Cellular Assay for Regenerative Medicine

: Advances in stem cell research have triggered scores of studies in regenerative medicine in a large number of institutions and companies around the world. However, reproducibility and data exchange among laboratories or cell banks are constrained by the lack of a standardized format for experiments. To enhance information flow in stem cell and derivative cell research, here we propose a minimum information standard to describe cellular assay data to facilitate practical regenerative medicine. Based on the existing Minimum Information About a Cellular Assay, we developed Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), which allows for the description of advanced cellular experiments with defined taxonomy of human cell types. By using controlled terms, such as ontologies, MIACARM will provide a platform for cellular assay data exchange among cell banks or registries that have been established at more than 20 sites in the world.

SIGNIFICANCE

Currently, there are more than 20 human cell information storage sites around the world. However, reproducibility and data exchange among different laboratories or cell information providers are usually inadequate or nonexistent because of the lack of a standardized format for experiments. This study, which is the fruit of collaborative work by scientists at stem cell banks and cellular information registries worldwide, including those in the U.S., the U.K., Europe, and Japan, proposes new minimum information guidelines, Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), for cellular assay data deposition. MIACARM is intended to promote data exchange and facilitation of practical regenerative medicine.

New technologies in the genetic approach to sudden cardiac death in the young

Sudden cardiac death (SCD) is a major health problem and constitutes one of the most important unsolved challenges in the practice of forensic pathology due to the failure to determine the cause of death. Particularly, an important number of previously healthy young people who have died suddenly and unexpectedly are consequence of genetic heart disorders, either structural cardiomyopathies or arrhythmogenic abnormalities. The technological approach to analyze this type of genetically heterogeneous disorders is far from easy but nowadays the variety of chemistries and methodologies improves choice. This review offers to the reader a state of the art of the available technologies for the study of genetics of sudden cardiac death, including mutation screening approaches, genome wide association studies, and the recently developed next-generation sequencing.