Screening of Critical Genes in Lung Adenocarcinoma via Network Analysis of Gene Expression Profile

Abstract

Biomarker discovery is of great importance in diagnosis and treatment of diseases. In present study, a number of differentially expressed genes (DEGs) were identified for lung adenocarcinoma via comparative analysis of gene expression data. A gene expression core signature was generated for four types of lung adenocarcinoma (EGFR-mutated, KRAS-mutated, ALK-mutated and triple-negative adenocarcinoma). Functional enrichment analysis with DAVID tools revealed that up-regulated genes were mainly associated with cell cycle while down-regulated genes were mainly involved in vasculature development and cell adhesion. Then it was used to retrieve relevant small molecule drugs with Connectivity map and trichostatin A was predicted to be the top candidate drug for treatment of lung cancer. Network clustering was performed with MCL in cytoscape to identify sub-networks and several hub genes were obtained: CDC25C, ICT1, TK1 and EZH2. These genes play important roles in the progression of lung cancer and some have been suggested as potential biomarkers. Therefore, our findings are beneficial in deepening the understandings about the pathogenesis and providing directions for future researches.

Identification of stage-specific biomarkers in lung adenocarcinoma based on RNA-seq data

“…Pathologic stages of LAC are critical factors for cancer treatment and outcome prediction. A better understanding of LAC staging will pave the way for novel therapies for LAC [5].…”

Knockdown of Immature Colon Carcinoma Transcript 1 Inhibits Proliferation and Promotes Apoptosis of Non–Small Cell Lung Cancer Cells

“…7,25 Network analysis of gene expression by Huang et al shows that ICT1 is a potential biomarker for LC. 10 However, the role of ICT1 in NSCLC cells remains unclear.…”

“…9 ICT1 has been identified as a hug gene for LC and guessed to play an important role in the progression of LC. 10 However, its role in LC has not been further investigated.…”

Identification of suitable genes contributes to lung adenocarcinoma clustering by multiple meta‐analysis methods

“…Huang et al . showed several hub genes, four of which were suggested as potential biomarkers . In this study, we selected the top 20 DE genes detected by each meta‐analysis method, and the DE genes identified by SR method outperformed the others for classification capability.…”