Hub Genes in Non-Small Cell Lung Cancer Regulatory Networks

Abstract

There are currently no accurate biomarkers for optimal treatment selection in early-stage non-small cell lung cancer (NSCLC). Novel therapeutic targets are needed to improve NSCLC survival outcomes. This study systematically evaluated the association between genome-scale regulatory network centralities and NSCLC tumorigenesis, proliferation, and survival in early-stage NSCLC patients. Boolean implication networks were used to construct multimodal networks using patient DNA copy number variation, mRNA, and protein expression profiles. T statistics of differential gene/protein expression in tumors versus non-cancerous adjacent tissues, dependency scores in in vitro CRISPR-Cas9/RNA interference (RNAi) screening of human NSCLC cell lines, and hazard ratios in univariate Cox modeling of the Cancer Genome Atlas (TCGA) NSCLC patients were correlated with graph theory centrality metrics. Hub genes in multi-omics networks involving gene/protein expression were associated with oncogenic, proliferative potentials and poor patient survival outcomes (p < 0.05, Pearson’s correlation). Immunotherapy targets PD1, PDL1, CTLA4, and CD27 were ranked as top hub genes within the 10th percentile in most constructed multi-omics networks. BUB3, DNM1L, EIF2S1, KPNB1, NMT1, PGAM1, and STRAP were discovered as important hub genes in NSCLC proliferation with oncogenic potential. These results support the importance of hub genes in NSCLC tumorigenesis, proliferation, and prognosis, with implications in prioritizing therapeutic targets to improve patient survival outcomes.

Investigation of Diagnostic and Prognostic Value of CLEC4M of Non-Small Cell Lung Carcinoma Associated with Immune Microenvironment

“…Through the enriched function analysis, we found that CLEC4M may play an important role in the activation and response of immune cells, comprising T cells, lymphocytes, myeloid leucocytes, macrophages, further confirming the crucial role of CLEC4M in immune activity, and uncovered the potential mechanism by which CLEC4M affected NSCLC microenvironment. Recently, Ye et al 49 integrated CNV-mediated transcriptional networks, mRNA co-expression, and protein co-expression networks to reveal associations between multi-omics network centrality and NSCLC oncogenesis, proliferation, and patient survival, demonstrating the immunotherapy targets including PD1, PDL1, CTLA4 and CD27, were the top hub genes in most of the constructed multi-omics networks in NSCLC tumors. In Yu’s study, 50 SPP1 was identified as a biomarker of NSCLC, which has significant coexpression relation to PD1 and PDL1, and acted as an immune-related target.…”