Power Domination Set-based Algorithm for Identification of KeyGenes in Lung Adenocarcinoma

Lung cancer is responsible for ۱۸% of cancer-related deaths. The most common lung cancer is Lung adenocarcinoma, whose patients are increasing especially among non-smokers, women and younger people . Despite all these facts, the factors of its development are not yet known precisely. The present study was conducted with the aim of identifying key genes in the development or prognosis of lung adenocarcinoma. So far, the concept of power dominating set (PDS) has not been used to identify or predict important genes in any type of biological network, and this study is the first research in this case. It is necessary to mention that a set of vertices that eventually monitors, using special rules, all the vertices of a graph is called a PDS . Here, we considered six microarray datasets related to lung adenocarcinoma from the Gene Expression Omnibus database , each set containing several control and tumor samples. Then, we extracted ۱۴۳ di↵erentially expressed genes using the GEO۲R and considering p-value<۰.۰۵ and | logfc| >۱. To validate these genes, we used ۵۷۴ datasets of The Cancer Genome Atlas (https://www.cancer.gov/tcga), which included ۵۱۵ tumor and ۵۹ normal samples. After analyzing these samples, we reached ۳۷۴۴ di↵erentially expressed genes. We calculated the intersection of these genes and ۱۴۳ genes obtained from GEO and finally, ۱۳۳ genes were obtained. Then, we obtained the network corresponding to these ۱۳۳ genes using STRING and tried to find PDS in this network. Our algorithm identified four pairs of genes {SPARCL۱, CDH۵}, {CLEC۱۴A۱, CAV۱}, {CDH۵, VWF} and {RHOJ, VWF} as four PDSs. Upon analysis of their functions within various biological processes and pathways, we have reached the conclusion that these genes apparently play a crucial role and may be highly correlated with lung adenocarcinoma.

کلیدواژه ها:

Power dominating set ، Lung adenocarcinoma ، Gene expression ، Graph theory