Abstract

Background Lung cancers are classified as squamous cell carcinoma (SQ), adenocarcinoma (AC) and small cell lung carcinoma (SCLC). SQ is the major subtype of lung cancer. Currently, there are no targeted therapies for SQ due to lack of understanding its driving oncogenes. In this study, we validated an SQ specific biomarker hsa-miR-205 in Chinese patients with lung cancer and screened its candidate target genes for further functional studies to enrich knowledge in SQ target therapies. Methods Quantitative reverse-transcription PCR (quantitative RT-PCR) was performed on 197 macro-dissected (cancerous cells >75%) surgical lung tissues (45 SQ, 44 AC, 54 SCLC and 54 adjacent normal tissues) to validate the expression profiles of miR-205. Furthermore, the targets of this microRNA were predicted through the gateway miRecords and mapped to lung cancer-associated pathways using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. Then quantitative RT-PCR was performed on an independent cohort of 44 snap-frozen surgical lung tissues to concurrently assess the expression profiles of miR-205 and its 52 putative targeted genes. Results MicroRNA-205 yielded high diagnostic accuracy in discriminating SQ from AC with an area under the curve (AUC) of 0.985, and discriminating SQ from SCLC with an AUC of 0.978 in formalin-fixed paraffin-embedded (FFPE) surgical lung tissues. Predicted targets of miR-205 were associated with 52 key members of lung cancer signaling pathways. Ten target genes (ACSL1, AXIN2, CACNA2D2, FOXO3, PPP1R3A, PRKAG3, RUNX1, SMAD4, STK3 and TBL1XR1) were significantly down-regulated in SQ and had a strong negative correlation with miR-205, while one target gene (CDH3) was up-regulated in SQ and exhibited a strong positive correlation with miR-205. Conclusions We confirmed the high diagnostic accuracy of miR-205 in discriminating SQ from AC and SCLC in Chinese patients. Moreover, we identified 11 significant target genes of miR-205 which could be used for further functional studies as the basis for the development of SQ targeted therapies.

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