Ankita Mehta, Yasha Hasija
Department of Biotechnology, Delhi Technological University (Formerly Delhi College of Engineering), Shahbad Daulatpur, Main Bawana Road, Delhi-110042, India.
ABSTRACT
Cancer has been one of the common causes of morbidity and mortality worldwide. Also, geographic localization of cancers affecting certain groups of populations is well known. However, the interplay of genetic susceptibility, lifestyle factors and infections in carcinogenesis is still poorly understood. An analysis of genome-wide genetic variations changes in cancer may provide a holistic view of cancer genes for any cancer type. Besides these rare mutations, commonly occurring single nucleotide polymorphisms (SNPs) have also been shown to incrementally contribute to cancer risk. In this study, an attempt has been made to study the inter-relations between SNPs and cancers for identifying common factors that may influence the susceptibility of individuals to cancer phenotypes. For this, the dataset was taken from COSMIC (Catalogue of Somatic Mutations in Cancer) release 53. Of the 1,31,271 SNPs in 11127 genes found to be associated with 42 types of cancer, the highest number (25%) of SNPs was associated with hematopoitic and lymphoid tissue. Moreover, maximum numbers of SNPs were found to be on chromosome 9, suggestive of the role of this chromosome in cancers. Of all the 1,31271 nucleotide changes, 75000 were transversions, of which the maximum were G to T changes, the total count being 40,519. Likewise, when analysis on amino acid mutation was done, Valine to Phenylalanine change was maximum, followed by valine to glutamic acid. These SNPs were analyzed using Polyphen 2, to predict the possible impact of an amino acid substitutions on the structure and function of human proteins. It was found that out of all the SNPs associated with cancer, 83,705 were predicted to be probably damaging, 14756 benign, 10,605 possibly damaging, while 22,204 were unknown. When gene ontology analysis was done, it was found that majority of the genes were related to transmembrane signaling receptor activity, Thus, we presume that further SNP analysis may prove to be an invaluable approach for deciphering the genetic variations responsible for the development of cancer, thereby promising to assist in the identification of novel cancer-related genes, as well as in the development of novel diagnostic tests for predicting an individual’s likelihood for developing cancer. Read More …
