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 SNP’s and the patterns of variants were analysed to see the comparison between healthy individual 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 SNP’s and their characterisations with respect to the functional
change was done.
Conclusion:
The SNP’s 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 variant can
be mapped to understand the NSCLC at a greater depth.
RNA-sequencing analysis identifies downstream genes of TCF4 involved in the development of non-small cell lung cancer.