Identification and Characterization of SNP Mutation in Genes Related to Non-small Cell Lung Cancer

克拉斯 单核苷酸多态性 SNP公司 肺癌 基因 生物 癌症基因组测序 癌症 SNP阵列 计算生物学 遗传学 表型 突变 肿瘤科 外显子组测序 医学 基因型
作者
Neelambika Basavaraj Hiremath,P Dayananda
出处
期刊:Current Signal Transduction Therapy [Bentham Science]
卷期号:16 (3): 253-261 被引量:1
标识
DOI:10.2174/1574362415999200819202218
摘要

Background and Objective: The advent of Next Generation Sequencing (NGS) has created a high throughput platform, to identify disease traits and phenotypic characteristics using RNASeq Sequencing analysis in humans. Non-small cell lung cancer (NSCLC), a lethal disease accounts for 85 percent of most lung cancers with very small window ofsurvival rate. The decision of tumour image bio marker impression can be improved by gene profile. Hence there is a need to characterise the variants in the disease manifestation. Methods: To understand the SNP’s in the major genes responsible for NSCLC, RNASeq data of patients aged above 50 years, were downloaded from SRA database. The quality matrix analysis is mapped to Genome reference consortium human build 38 (GRCh38) to call the variants and identify SNP’s with the tuxedo protocol. Results: The SNPs and the patterns of variants were analysed to see the comparison between healthy individuals and NSCLC patients, and in between patients of different age. Oncogenes commonly associated with the NSCLC like KRAS, EGFR, ALK, BRAF and HER2 were mainly analysed to see the SNPs and their characterisations with respect to the functional change done. Conclusion: The SNPs with the greater quality scores belonging to the above-said genes were identified, which gives us a baseline to understand the NSCLC at the Genomic level. Further fold change of these genes to the frequency of variants can be mapped to understand the NSCLC at a greater depth.

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