scholarly journals Identification of key genes and evaluation of clinical outcomes in lung squamous cell carcinoma using integrated bioinformatics analysis

2019 ◽  
Author(s):  
Yangfeng Shi ◽  
Yeping Li ◽  
Chao Yan ◽  
Hua Su ◽  
Kejing Ying
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Clinical Outcomes ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
Key Genes

scholarly journals Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis

2020 ◽  
Vol 21 (8) ◽  
pp. 2994
Author(s):  
Miaomiao Gao ◽  
Weikaixin Kong ◽  
Zhuo Huang ◽  
Zhengwei Xie
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Good Prediction ◽  
Good Prediction Accuracy ◽  
Key Genes

Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.

scholarly journals Association of ERBB Mutations With Clinical Outcomes of Afatinib- or Erlotinib-Treated Patients With Lung Squamous Cell Carcinoma

JAMA Oncology ◽  
2018 ◽  
Vol 4 (9) ◽  
pp. 1189 ◽  
Author(s):  
Glenwood D. Goss ◽  
Enriqueta Felip ◽  
Manuel Cobo ◽  
Shun Lu ◽  
Konstantinos Syrigos ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Clinical Outcomes ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma
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