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Identification and validation of key genes associated with non-small-cell lung cancer.
Ma, Qiang; Xu, Yuan; Liao, Hebin; Cai, Yan; Xu, Lei; Xiao, Dan; Liu, Chang; Pu, Wenjie; Zhong, Xiaowu; Guo, Xiaolan.
Afiliação
  • Ma Q; Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
  • Xu Y; Translational Medicine Research Center, North Sichuan Medical College, Nanchong, China.
  • Liao H; Department of Laboratory Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.
  • Cai Y; Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
  • Xu L; Translational Medicine Research Center, North Sichuan Medical College, Nanchong, China.
  • Xiao D; Department of Laboratory Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.
  • Liu C; Translational Medicine Research Center, North Sichuan Medical College, Nanchong, China.
  • Pu W; Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
  • Zhong X; Translational Medicine Research Center, North Sichuan Medical College, Nanchong, China.
  • Guo X; Department of Laboratory Medicine, North Sichuan Medical College, Nanchong, Sichuan, China.
J Cell Physiol ; 234(12): 22742-22752, 2019 12.
Article em En | MEDLINE | ID: mdl-31127628
ABSTRACT
Non-small-cell lung cancer (NSCLC) is one of the main causes of death induced by cancer globally. However, the molecular aberrations in NSCLC patients remain unclearly. In the present study, four messenger RNA microarray datasets (GSE18842, GSE40275, GSE43458, and GSE102287) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NSCLC tissues and adjacent lung tissues were obtained from GEO2R and the overlapping DEGs were identified. Moreover, functional and pathway enrichment were performed by Funrich, while the protein-protein interaction (PPI) network construction were obtained from STRING and hub genes were visualized and identified by Cytoscape software. Furthermore, validation, overall survival (OS) and tumor staging analysis of selected hub genes were performed by GEPIA. A total of 367 DEGs (95 upregulated and 272 downregulated) were obtained through gene integration analysis. The PPI network consisted of 94 nodes and 1036 edges in the upregulated DEGs and 272 nodes and 464 edges in the downregulated DEGs, respectively. The PPI network identified 46 upregulated and 27 downregulated hub genes among the DEGs, and six (such as CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M) of that have not been identified to be associated with NSCLC so far. Moreover, the expression differences of the mentioned hub genes were consistent with that in lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. Further analysis showed that all the six hub genes were associated with tumor staging except MYH11, while only the upregulated DEG CENPE was associated with the worse OS of patients with NSCLC. In conclusion, the current study showed that CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M might be the key genes contributed to tumorigenesis or tumor progression in NSCLC, further functional study is needed to explore the involved mechanisms.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biomarcadores Tumorais / Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biomarcadores Tumorais / Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article