Integrative meta-analysis of multiple gene expression profiles in acquired gemcitabine-resistant cancer cell lines to identify novel therapeutic biomarkers.

摘要: In molecular-targeted cancer therapy, acquired resistance to gemcitabine is a major clinical problem that reduces its effectiveness, resulting in recurrence and metastasis of cancers. spite great efforts reveal the overall mechanism resistance, no definitive genetic factors have been identified are absolutely responsible for process. Therefore, we performed cross-platform meta-analysis three publically available microarray datasets cell lines with using R-based RankProd algorithm, were able identify total 158 differentially expressed genes (DEGs; 76 up- 82 down-regulated) potentially involved gemcitabine. Indeed, top 20 down-regulated DEGs largely associated common process carcinogenesis many cells. For 50 DEGs, conducted integrated analyses gene regulatory network, co-expression protein-protein interaction network. The functionally enriched via Gene Ontology hierarchy Kyoto Encyclopedia Genes Genomes pathway analyses. By systemic combinational analysis molecular networks, could condense number final seven genes. Notably, GJA1, LEF1, CCND2 contained within lists or DEGs. Our study represents comprehensive overview expression patterns theoretical support further therapeutic studies.