Nonsynonymous mutations in VEGF receptor binding domain alter the efficacy of bevacizumab treatment.

Vascular endothelial growth factor (VEGF) mediated angiogenesis is crucial for tumor progression. Isoforms of VEGF bind to different VEGF receptors (VEGFRs) to initiate angiogenesis specific cellular signaling. Inhibitors that target both the receptors and ligands are in clinical use to impede angiogenesis. Bevacizumab, a monoclonal antibody (mAb) approved by the Food and Drug Administration (FDA), binds in the VEGF receptor binding domain (RBD) of all soluble isoforms of VEGF and inhibits the VEGF-VEGFR interaction. Bevacizumab is also used in combination with other chemotherapeutic agents for a better therapeutic outcome. Understanding the intricate polymorphic character of VEGFA gene and the influence of missense or nonsynonymous mutations in the form of nonsynonymous polymorphisms (nsSNPs) on RBD of VEGF may aid in increasing the efficacy of this drug. This study has identified 18 potential nsSNPs in VEGFA gene that affect the VEGF RBD structure and alter its binding pattern to bevacizumab. The mutated RBDs, modeled using trRosetta, in addition to the changed pattern of secondary structure, post translational modification and stability compared to the wild type, have shown contrasting binding affinity and molecular interaction pattern with bevacizumab. Molecular docking analysis by ClusPro and visualization using PyMol and PDBsum tools have detected 17 nsSNPs with decreased binding affinity to bevacizumab and therefore may impact the treatment efficacy. Whereas VEGF RBD expressed due to rs1267535717 (R229H) nsSNP of VEGFA has increased affinity to the mAb. This study suggests that genetic characterization of VEGFA before bevacizumab mediated cancer treatment is essential in predicting the appropriate efficacy of the drug, as the treatment efficiency may vary at individual level.

Analysis of the Compositional Features and Codon Usage Pattern of Genes Involved in Human Autophagy.

Autophagy plays an intricate role in paradigmatic human pathologies such as cancer, and neurodegenerative, cardiovascular, and autoimmune disorders. Autophagy regulation is performed by a set of autophagy-related (ATG) genes, first recognized in yeast genome and subsequently identified in other species, including humans. Several other genes have been identified to be involved in the process of autophagy either directly or indirectly. Studying the codon usage bias (CUB) of genes is crucial for understanding their genome biology and molecular evolution. Here, we examined the usage pattern of nucleotide and synonymous codons and the influence of evolutionary forces in genes involved in human autophagy. The coding sequences (CDS) of the protein coding human autophagy genes were retrieved from the NCBI nucleotide database and analyzed using various web tools and software to understand their nucleotide composition and codon usage pattern. The effective number of codons (ENC) in all genes involved in human autophagy ranges between 33.26 and 54.6 with a mean value of 45.05, indicating an overall low CUB. The nucleotide composition analysis of the autophagy genes revealed that the genes were marginally rich in GC content that significantly influenced the codon usage pattern. The relative synonymous codon usage (RSCU) revealed 3 over-represented and 10 under-represented codons. Both natural selection and mutational pressure were the key forces influencing the codon usage pattern of the genes involved in human autophagy.