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Updated: Jan 20, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Comprehensive analysis of non-small-cell lung cancer microarray datasets identifies several prognostic biomarkers
Xiuxiu Qin1, Ruoshi Chen2, Rui Xiong2
1Department of Anesthesia, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, PR China.
Abstract:
Aim: To find accurate and effective biomarkers for diagnosis of non-small-cell lung cancer (NSCLC) patients. Materials & methods: We downloaded microarray datasets GSE19188, GSE33532, GSE101929 and GSE102286 from the database of Gene Expression Omnibus. We screened out differentially expressed genes (DEGs) and miRNAs (DEMs) with GEO2R. We also performed analyses for the enrichment of DEGs' and DEMs' function and pathway by several tools including database for annotation, visualization and integrated discovery, protein-protein interaction and Kaplan-Meier-plotter. Results: Total 913 DEGs were screened out, among which ten hub genes were discovered. All the hub genes were linked to the worsening overall survival of the NSCLC patients. Besides, 98 DEMs were screened out. MiR-9 and miR-520e were the most significantly regulated miRNAs. Conclusion: Our results could provide potential targets for the diagnosis and treatment of NSCLC.
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