scholarly journals Identification of key genes in non-small cell lung cancer by bioinformatics analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8215 ◽  
Author(s):  
Li Zhang ◽  
Rui Peng ◽  
Yan Sun ◽  
Jia Wang ◽  
Xinyu Chong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Candidate Genes ◽  
Cell Lung Cancer ◽  
Malignant Tumors ◽  
Small Cell ◽  
Ppi Network ◽  
Small Cell Lung ◽  
Key Genes

Background Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors in the world, and it has become the leading cause of death of malignant tumors. However, its mechanisms are not fully clear. The aim of this study is to investigate the key genes and explore their potential mechanisms involving in NSCLC. Methods We downloaded gene expression profiles GSE33532, GSE30219 and GSE19804 from the Gene Expression Omnibus (GEO) database and analyzed them by using GEO2R. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. We constructed the protein-protein interaction (PPI) network by STRING and visualized it by Cytoscape. Further, we performed module analysis and centrality analysis to find the potential key genes. Finally, we carried on survival analysis of key genes by GEPIA. Results In total, we obtained 685 DEGs. Moreover, GO analysis showed that they were mainly enriched in cell adhesion, proteinaceous extracellular region, heparin binding. KEGG pathway analysis revealed that transcriptional misregulation in cancer, ECM-receptor interaction, cell cycle and p53 signaling pathway were involved in. Furthermore, PPI network was constructed including 249 nodes and 1,027 edges. Additionally, a significant module was found, which included eight candidate genes with high centrality features. Further, among the eight candidate genes, the survival of NSCLC patients with the seven high expression genes were significantly worse, including CDK1, CCNB1, CCNA2, BIRC5, CCNB2, KIAA0101 and MELK. In summary, these identified genes should play an important role in NSCLC, which can provide new insight for NSCLC research.

Integrative genomic and gene expression analysis of chromosome 7 identified novel oncogene loci in non-small cell lung cancer

Genome ◽  
2008 ◽  
Vol 51 (12) ◽  
pp. 1032-1039 ◽  
Author(s):  
Jennifer M. Campbell ◽  
William W. Lockwood ◽  
Timon P.H. Buys ◽  
Raj Chari ◽  
Bradley P. Coe ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Chromosome 7 ◽  
Normal Lung ◽  
Clinical Samples ◽  
Small Cell Lung ◽  
Key Genes

Lung cancer accounts for over a quarter of cancer deaths, with non-small cell lung cancer (NSCLC) accounting for approximately 80% of cases. Several genome studies have been undertaken in both cell models of NSCLC and clinical samples to identify alterations underlying disease behaviour, and many have identified recurring aberrations of chromosome 7. The presence of recurring chromosome 7 alterations that do not span the well-studied oncogenes EGFR (at 7p11.2) and MET (at 7q31.2) has raised the hypothesis of additional genes on this chromosome that contribute to tumourigenesis. In this study, we demonstrated that multiple loci on chromosome 7 are indeed amplified in NSCLC, and through integrative analysis of gene dosage alterations and parallel gene expression changes, we identified new lung cancer oncogene candidates, including FTSJ2, NUDT1, TAF6, and POLR2J. Activation of these key genes was confirmed in panels of clinical lung tumour tissue as compared with matched normal lung tissue. The detection of gene activation in multiple cohorts of samples strongly supports the presence of key genes involved in lung cancer that are distinct from the EGFR and MET loci on chromosome 7.

p53-regulated GML gene expression in non-small cell lung cancer: Relation to cisplatin chemosensitivity

Lung Cancer ◽  
2000 ◽  
Vol 29 (1) ◽  
pp. 193
Author(s):  
M Higashiyama ◽  
K Kodama ◽  
H Yokouchi ◽  
K Takami ◽  
Y Miyoshi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung

Effects of fine air particulates on gene expression in non-small-cell lung cancer

2017 ◽  
Vol 62 (2) ◽  
pp. 295-301 ◽  
Author(s):  
Biao Yang ◽  
Xinming Li ◽  
Dongmei Chen ◽  
Chunling Xiao
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung

scholarly journals Cell-autonomous immune gene expression is repressed in pulmonary neuroendocrine cells and small cell lung cancer

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ling Cai ◽  
Hongyu Liu ◽  
Fang Huang ◽  
Junya Fujimoto ◽  
Luc Girard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Neuroendocrine Cells ◽  
Immune Gene ◽  
Small Cell Lung ◽  
Immune Gene Expression ◽  
Pulmonary Neuroendocrine Cells

AbstractSmall cell lung cancer (SCLC) is classified as a high-grade neuroendocrine (NE) tumor, but a subset of SCLC has been termed “variant” due to the loss of NE characteristics. In this study, we computed NE scores for patient-derived SCLC cell lines and xenografts, as well as human tumors. We aligned NE properties with transcription factor-defined molecular subtypes. Then we investigated the different immune phenotypes associated with high and low NE scores. We found repression of immune response genes as a shared feature between classic SCLC and pulmonary neuroendocrine cells of the healthy lung. With loss of NE fate, variant SCLC tumors regain cell-autonomous immune gene expression and exhibit higher tumor-immune interactions. Pan-cancer analysis revealed this NE lineage-specific immune phenotype in other cancers. Additionally, we observed MHC I re-expression in SCLC upon development of chemoresistance. These findings may help guide the design of treatment regimens in SCLC.

scholarly journals Predicting Diagnostic Gene Biomarkers for Non-Small-Cell Lung Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Bin Liang ◽  
Yang Shao ◽  
Fei Long ◽  
Shu-Juan Jiang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Association Network ◽  
Small Cell Lung ◽  
Functional Association ◽  
Functional Association Network ◽  
Gene Modules

Lung cancer is the primary reason for death due to cancer worldwide, and non-small-cell lung cancer (NSCLC) is the most common subtype of lung cancer. Most patients die from complications of NSCLC due to poor diagnosis. In this paper, we aimed to predict gene biomarkers that may be of use for diagnosis of NSCLC by integrating differential gene expression analysis with functional association network analysis. We first constructed an NSCLC-specific functional association network by combining gene expression correlation with functional association. Then, we applied a network partition algorithm to divide the network into gene modules and identify the most NSCLC-specific gene modules based on their differential expression pattern in between normal and NSCLC samples. Finally, from these modules, we identified genes that exhibited the most impact on the expression of their functionally associated genes in between normal and NSCLC samples and predicted them as NSCLC biomarkers. Literature review of the top predicted gene biomarkers suggested that most of them were already considered critical for development of NSCLC.

scholarly journals Prognostic significance of epigenetic regulatory gene expression in patients with non-small-cell lung cancer

Aging ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 7397-7415
Author(s):  
Zegui Tu ◽  
Xiancheng Chen ◽  
Tian Tian ◽  
Guo Chen ◽  
Meijuan Huang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Regulatory Gene ◽  
Prognostic Significance ◽  
Small Cell ◽  
Small Cell Lung
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