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Eight potential biomarkers for distinguishing between lung adenocarcinoma and squamous cell carcinoma.


ABSTRACT: Lung adenocarcinoma (LADC) and squamous cell carcinoma (LSCC) are the most common non-small cell lung cancer histological phenotypes. Accurate diagnosis distinguishing between these two lung cancer types has clinical significance. For this study, we analyzed four Gene Expression Omnibus (GEO) datasets (GSE28571, GSE37745, GSE43580, and GSE50081). We then imported the datasets into the Gene-Cloud of Biotechnology Information online platform to identify genes differentially expressed in LADC and LSCC. We identified DSG3 (desmoglein 3), KRT5 (keratin 5), KRT6A (keratin 6A), KRT6B (keratin 6B), NKX2-1 (NK2 homeobox 1), SFTA2 (surfactant associated 2), SFTA3 (surfactant associated 3), and TMC5 (transmembrane channel-like 5) as potential biomarkers for distinguishing between LADC and LSCC. Receiver operating characteristic curve analysis suggested that KRT5 had the highest diagnostic value for discriminating between these two cancer types. Using the PrognoScan online survival analysis tool and the Kaplan-Meier Plotter, we found that high KRT6A or KRT6B levels, or low NKX2-1, SFTA3, or TMC5 levels correlated with unfavorable prognoses in LADC patients. Further studies will be needed to verify our findings in additional patient samples, and to elucidate the mechanisms of action of these potential biomarkers in non-small cell lung cancer.

SUBMITTER: Xiao J 

PROVIDER: S-EPMC5641087 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Eight potential biomarkers for distinguishing between lung adenocarcinoma and squamous cell carcinoma.

Xiao Jian J   Lu Xiaoxiao X   Chen Xi X   Zou Yong Y   Liu Aibin A   Li Wei W   He Bixiu B   He Shuya S   Chen Qiong Q  

Oncotarget 20170503 42


Lung adenocarcinoma (LADC) and squamous cell carcinoma (LSCC) are the most common non-small cell lung cancer histological phenotypes. Accurate diagnosis distinguishing between these two lung cancer types has clinical significance. For this study, we analyzed four Gene Expression Omnibus (GEO) datasets (GSE28571, GSE37745, GSE43580, and GSE50081). We then imported the datasets into the Gene-Cloud of Biotechnology Information online platform to identify genes differentially expressed in LADC and L  ...[more]

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