Differential gene expression and network analysis in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a poor prognosis, whose biomarkers have not been studied in great detail. We have collected genomic data of HNSCC patients from The Cancer Genome Atlas (TCGA) and analyzed them to get deeper insights into the gene expression pattern. Initially, 793 differentially expressed genes (DEGs) were categorized, and their enrichment analysis was performed. Later, a protein-protein interaction network for the DEGs was constructed using the STRING plugin in Cytoscape to study their interactions. A set of 10 hub genes was selected based on Maximal Clique Centrality score, and later their survival analysis was studied. The elucidated set of 10 genes, i.e., PRAME, MAGEC2, MAGEA12, LHX1, MAGEA3, CSAG1, MAGEA6, LCE6A, LCE2D, LCE2C, referred to as potential candidates to be explored as HNSCC biomarkers. The Kaplan-Meier overall survival of the selected genes suggested that the alterations in the candidate genes were linked to the decreased survival of the HNSCC patients. Altogether, the results of this study signify that the genomic alterations and differential expression of the selected genes can be explored in therapeutic interpolations of HNSCC, exploiting early diagnosis and target-propelled therapy.

Impact of non-synonymous mutations on the structure and function of telomeric repeat binding factor 1.

Telomeric repeat binding factor 1 (TRF1) is one of the major components of the shelterin complex. It directly binds to the telomere and controls its function by regulating the telomerase acting on it. Several variations are reported in the TRF1 gene; some are associated with variety of diseases. Here, we have studied the structural and functional significance of these variations in the TRFH domain of TRF1. We have used cutting-edge computational methods such as SIFT, PolyPhen-2, PROVEAN, Mutation Assessor, mCSM, SDM, STRUM, MAESTRO, and DUET to predict the effects of 124 mutations in the TRFH domain of TRF1. Out of 124 mutations, we have identified 12 deleterious mutations with high confidence based on their prediction. To see the impact of the finally selected mutations on the structure and stability of TRF1, all-atom molecular dynamics (MD) simulations on TRF1-Wild type (WT), L79R and P150R mutants for 200 ns were carried out. A significant conformational change in the structure of the P150R mutant was observed. Our integrated computational study provides a comprehensive understanding of structural changes in TRF1 incurred due to the mutations and subsequent function, leading to the progression of many diseases.Communicated by Ramaswamy H. Sarma.

Genomic Variations in the Structural Proteins of SARS-CoV-2 and Their Deleterious Impact on Pathogenesis: A Comparative Genomics Approach.

A continual rise in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection causing coronavirus disease (COVID-19) has become a global threat. The main problem comes when SARS-CoV-2 gets mutated with the rising infection and becomes more lethal for humankind than ever. Mutations in the structural proteins of SARS-CoV-2, i.e., the spike surface glycoprotein (S), envelope (E), membrane (M) and nucleocapsid (N), and replication machinery enzymes, i.e., main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) creating more complexities towards pathogenesis and the available COVID-19 therapeutic strategies. This study analyzes how a minimal variation in these enzymes, especially in S protein at the genomic/proteomic level, affects pathogenesis. The structural variations are discussed in light of the failure of small molecule development in COVID-19 therapeutic strategies. We have performed in-depth sequence- and structure-based analyses of these proteins to get deeper insights into the mechanism of pathogenesis, structure-function relationships, and development of modern therapeutic approaches. Structural and functional consequences of the selected mutations on these proteins and their association with SARS-CoV-2 virulency and human health are discussed in detail in the light of our comparative genomics analysis.