DOI: 10.36347/sjams.2019.v07i02.006

Pages: 447-450

Metastatic lung cancer is difficult to be cured due to easy and wide dissemination of the lung cancer. Here we reported a patient case suffering from small-cell lung cancer (SCLC) by using RNA-seq analysis. In the methodology, we used magnetic-activated cell sorting (MACS) to harvest a pair of the patient lung cancer cells and normal cells and then extracted RNAs for RNA-seq to achieve gene expression files and SNP profile from lung cancer cells and normal control cells. After uncovering gene expression profiles and SNP profile, genomic expression signature (GES) was used to map quantitative network and then GES combined with SNP (single-nucleotide polymorphism) profile was screened to discover driving genes and driving mutations. We successfully discovered that ADAM19, NID1, SLIT3 and SVEP1 abnormally drive EGFR pathway to cause lung cancer although finally no any drug was uncovered target ADAM19, NID1, SLIT3 and SVEP1 related to a personalized therapy. The case with that analysis tells us that pharmacogenomics scientists need develop more targeting genes related to drugs in high expressed EGFR pathway and physicians’ scientists also require extending more methods such as epigenomics, microRNA and non-coding RNA by RNA detection techniques with their therapeutic targeting methods.