Bioinformatic analysis of key genes and pathways for Lung cancer as a therapeutic target

Background and Aim: Lung cancer is the leading cause of death among men and second leading cause of death among women worldwide, long cancer rate varies by sex, age, race, socioeconomic state and geography. Factors such as genetic susceptibility, poor diet, air pollution and smocking contribute as a risk factor in lung cancer. Lung cancer survival rate is about ten years for patients that received proper treatment and underwent surgical process. Also, early diagnosis of the cancer significantly has positive effects of patient’s treatment and survival rate. Those genes that their expression significantly change through cancer state and also regulates other genes can be considered as biomarker genes that helps to early diagnosis of lung cancer disease.Methods: The microarray gene expression data downloaded from GEO datasets (GSE۱۳۰۷۷۹). The raw data is from single channel Agilent platform. R statistical language limma package were used for statistical analysis and. Quality control performed before and after data normalization with boxplot, density plot, RLE plot, and hierarchal clustering then removing background reads from data. Analysis performed and deferential expression genes were determined with log fold change.Results: Top ۱۰۰ genes were determined those with P-value<۰.۰۵ are considered significant (۳۶ upregulated and ۶۴ downregulated according to their foldchange and P-value). Then using gene pathway analysis and gene-gene interactions performed by FunRich software. ۵ Genes that have most interactions with other genes are considered significant and those with biomarker values. Then biological functions of those key genes are determined.Conclusion: Cav۱, CADPS, A۲M, EGR۱, and GAB۳ are considered biomarker genes that they are contributing in various cellular processes. Caveolin۱ shows an inhibition activity in cell proliferation thus it is shown that the expression of this gene declined in our data. A۲M role is to inhibit growth promoting tumors pathways such as PI۳K/AKT, SMAD and upregulating PTEN to inhibit cell proliferation, thus in our results its expression significantly decreased during long cancer. EGR۱ arrest cell mobility and inhibit cell migration it is shown that this increase level of EGR۱ gene expression influence the expression of genes such as CDKN۱C, CDC۲۷ and PRKDC, in our results it is shown that expression level of this gene significantly declined compare to normal samples. GAB۳ gene is a protein coding gene and it is associated with pathways like MAPK and Mitogen stimulation pathway which in fact it shows upregulation in cancers such as lung. In our study GAB۳ gene is upregulated during lung cancer in patients compared to normal samples. Our study shows the significant of these genes as a therapeutic target and biomarker discovery for early diagnosis of lung cancer.

Keywords:

Lung cancer , Micro-array , Biomarker , R Language