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Current Signal Transduction Therapy

Editor-in-Chief

ISSN (Print): 1574-3624
ISSN (Online): 2212-389X

Meta-Analysis

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

Author(s): Neelambika B. Hiremath and P. Dayananda*

Volume 16, Issue 3, 2021

Published on: 19 August, 2020

Page: [253 - 261] Pages: 9

DOI: 10.2174/1574362415999200819202218

Price: $65

Abstract

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 a very small window of survival rate. The decision of tumour image biomarker impression can be improved by gene profile. Hence there is a need to characterise the variants in the disease manifestation.

Methods: To understand the SNPs in the major genes responsible for NSCLC, RNASeq data of patients aged above 50 years were downloaded from the SRA database. The quality matrix analysis is mapped to Genome reference consortium human build 38 (GRCh38) to call the variants and identify SNPs 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.

Keywords: Non-small cell lung cancer, KRAS, EGFR, RNASeq, mutation, next generation sequencing.

Graphical Abstract

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