Gene Expression Profiling with Transcriptomic Data Analysis In Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is aggressive due to fast tumor development, early metastatic dissemination, and genetic instability. In this study, the RNA sequencing method was applied to the selected experimental data set for gene expression analysis in lung tissue samples of SCLC using Array Express functional genomic data. Array Express is a public repository for transcriptomic and related data that aims to store MIAME-compliant data in accordance with MGED recommendations. We wanted to look into the genomic sequence data (GSE60052) of 7 healthy controls and 75 SCLC patients through the GEO2R platform and the NCBI Gene Expression Omnibus (GEO) using the accession number E-GEOD-60052. The GSE60052 dataset of the genomic expression study was found on the GEO2R platform using the Illumina HiSeq 2000 RNA sequencing method in lung tissue samples from 75 SCLC patients and 7 controls. This was done to find out how the gene profile in SCLC were being expressed. In patients both in the SCLC and the control group, it was identified through the Volcano plot graph that HOXD10, FAM83A, HOXB1, ECEL1, GATA4, DMRT3, TGM3, CHP2, and PPP1R1A genes were down-regulated (log2(fold change) < -5), while PGC, SFTPC, SLC6A4, and CSF3 genes were up-regulated (log2 (fold change > +5). We share the view that SCLC is a type of neuroendocrine tumor with high malignancy and a poor prognosis, and identifying significant genes through expression profiling in lung tissue samples may be effective in elucidating the complex mechanisms underlying SCLC and determining their effect on the prognosis of the disease. The use of related genes as possible prognostic biomarkers in targeted therapy in SCLC could be enables the determination of the effects of the tumor microenvironment on immune cells and stromal cells.