ArticlePathology oncology research : POR2014
Screening of critical genes in lung adenocarcinoma via network analysis of gene expression profile.
Article in Pathology oncology research : POR, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Identification of stage-specific biomarkers in lung adenocarcinoma based on RNA-seq data.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2015Pooled it
- Evaluating the feasibility of gene replacement strategies to treat MTRFR deficiency.Disease models & mechanisms · 2025Article
- Functional Diversity of Mitochondrial Peptidyl-tRNA Hydrolase ICT1 in Human Cells.Frontiers in molecular biosciences · 2021Review
- Knockdown of Immature Colon Carcinoma Transcript 1 Inhibits Proliferation and Promotes Apoptosis of Non-Small Cell Lung Cancer Cells.Technology in cancer research & treatment · 2017Article
- Detection and screening of small molecule agents for overcoming Sorafenib resistance of hepatocellular carcinoma: a bioinformatics study.International journal of clinical and experimental medicine · 2015Article
- Knockdown of immature colon carcinoma transcript-1 inhibits proliferation of glioblastoma multiforme cells through Gap 2/mitotic phase arrest.OncoTargets and therapy · 2015Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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