Integrated analysis of long non-coding RNAs and mRNA profiles reveals potential sex-dependent biomarkers of bevacizumab/erlotinib response in advanced lung cancer

Background While lung cancer patient outcomes are well-recognized to vary as a function of patient sex, there has been insufficient research regarding the relationship between patient sex and EGFR(Epidermal growth factor receptor) response efficacy. The present study therefore sought to identify novel sex-related biomarkers of bevacizumab/erlotinib (BE) responses in non-small cell lung cancer (NSCLC) patients. Methods The exon array data in the Gene Expression Omnibus (GEO) dataset were analyzed in order to identify patterns of mRNA and lncRNA expression associated with BE resistance in NSCLC. These differentially expressed (DE) lncRNAs and mRNAs were identified via DE Analysis Filtering. These DE mRNAs were then assessed for their potential functional roles via pathway enrichment analyses, with overlapping functions possibly associated with the BE resistance. The mRNAs in these overlapping groups were then assessed for their correlations with patient survival, and lncRNA-mRNA co-expression networks were generated for each patient subset. A protein-protein interaction (PPI) network was also generated based upon these DE mRNAs. Results In females we identified 172 DE lncRNAs and 1766 DE mRNAs associated with BE responses, while in males we identified 78 DE lncRNAs and 485 DE mRNAs associated with such responses. Based on the overlap between these two datasets, we identified a total of 37 GO functions and 18 pathways associated with BE responses. Co-expression and PPI networks suggested that the key lncRNAs and mRNAs associated with these BE response mechanisms weredifferent in the male and female patients. Conclusions This work is the first to conduct a global profiling of the relationship between lncRNA and mRNA expression patterns, patient sex, and BE responses in individuals suffering from NSCLC. Together these results suggest that the integrative lncRNA-mRNA expression analyses may offer invaluable new therapeutic insights that can guide the tailored treatment of lung cancer in order to ensure optimal BE responses.