Sravanthi Davuluri1, Akhilesh Kumar Bajpai1, Kavitha Thirumurugan2, Kshitish K Acharya3. 1. Structural Biology Lab, Centre for Biomedical Research, School of Bio Sciences & Technology (SBST), Vellore Institute of Technology (VIT) University, Vellore 632014, Tamil Nadu, India; Shodhaka Life Sciences Pvt. Ltd., Electronic City, Phase I, Bengaluru (Bangalore) 560100, Karnataka, India. 2. Structural Biology Lab, Centre for Biomedical Research, School of Bio Sciences & Technology (SBST), Vellore Institute of Technology (VIT) University, Vellore 632014, Tamil Nadu, India. 3. Shodhaka Life Sciences Pvt. Ltd., Electronic City, Phase I, Bengaluru (Bangalore) 560100, Karnataka, India; Insitute of Bioinformatics and Applied Biotechnology (IBAB), Phase I, Electronic City, Bengaluru (Bangalore) 560 100, Karnataka, India. Electronic address: juneindia@gmail.com.
Abstract
AIMS: Gender disparities exist in smoking-related lung cancer epidemiology, but the molecular basis has not been explored so far. We aimed at identifying genes with gender-bias expression pattern in smoking lung cancer patients for understanding the molecular basis of gender bias in smokers using meta-analysis of microarray gene expression data. MATERIALS AND METHODS: Transcriptome of around 1100 samples from 13 studies were used in the meta-analysis to identify 'Lung Cancer genes specific to Female-Smokers' (LCFS) and 'Lung Cancer genes specific to Male-Smokers' (LCMS). The expression profiles of these genes were validated with an independent microarray report and TCGA-RNA-sequencing data. The molecular interactions, pathway, and other functional annotations were portrayed for the key genes identified. KEY FINDINGS: We identified 1159 gender-biased genes in smoking lung cancer patients. Of these, 400 and 474 genes showed differential expression in cancerous compared to normal lung of women (LCFS) and men (LCMS), respectively. While many up-regulated LCFS were involved in 'immune responses' including T-cell activation, leukocyte cell-cell adhesion, the LCMS were mainly involved in 'positive regulation of gene expression', signaling pathways including RAS, VEGF, insulin-receptor signaling, and 'cell cycle'. SIGNIFICANCE: The strategic-method identified genes, particularly, SNX20, GIMAP6, MTMR2, FAM171B, IDH1, MOBP, FBXO17, LPXN and WIPF1, which were consistently differentially expressed in at least 4 studies, and in agreement with RNA-Seq data. Exploring their functions could be beneficial to the gender-based diagnosis, prognosis, and treatment of lung cancer in smokers. The current meta-analysis supports existing knowledge of sexual-dimorphism of immune responses in cancer.
AIMS: Gender disparities exist in smoking-related lung cancer epidemiology, but the molecular basis has not been explored so far. We aimed at identifying genes with gender-bias expression pattern in smoking lung cancerpatients for understanding the molecular basis of gender bias in smokers using meta-analysis of microarray gene expression data. MATERIALS AND METHODS: Transcriptome of around 1100 samples from 13 studies were used in the meta-analysis to identify 'Lung Cancer genes specific to Female-Smokers' (LCFS) and 'Lung Cancer genes specific to Male-Smokers' (LCMS). The expression profiles of these genes were validated with an independent microarray report and TCGA-RNA-sequencing data. The molecular interactions, pathway, and other functional annotations were portrayed for the key genes identified. KEY FINDINGS: We identified 1159 gender-biased genes in smoking lung cancerpatients. Of these, 400 and 474 genes showed differential expression in cancerous compared to normal lung of women (LCFS) and men (LCMS), respectively. While many up-regulated LCFS were involved in 'immune responses' including T-cell activation, leukocyte cell-cell adhesion, the LCMS were mainly involved in 'positive regulation of gene expression', signaling pathways including RAS, VEGF, insulin-receptor signaling, and 'cell cycle'. SIGNIFICANCE: The strategic-method identified genes, particularly, SNX20, GIMAP6, MTMR2, FAM171B, IDH1, MOBP, FBXO17, LPXN and WIPF1, which were consistently differentially expressed in at least 4 studies, and in agreement with RNA-Seq data. Exploring their functions could be beneficial to the gender-based diagnosis, prognosis, and treatment of lung cancer in smokers. The current meta-analysis supports existing knowledge of sexual-dimorphism of immune responses in cancer.