Correlation between circadian rhythm related genes, type 2 diabetes, and cancer: Insights from metanalysis of transcriptomics data

摘要

Clock genes work as an auto-regulated transcription-translational loop of circadian genes that drives the circadian rhythms in each cell and they are essential to physiological requests. Since metabolism is a dynamic process, it involves several physiological variables that circadian cycling. The clock genes alterations can affect multiple systems concomitantly, because they constitute the promoter factors for relevant metabolic pathways. Considering the intertwined structure of signaling, regulatory, and metabolic processes within a cell, we employed a genome-scale biomolecular network. Accordingly, a meta-analysis of diabetic-associated transcriptomic datasets was performed, and the core information on differentially expressed genes (DEGs) was obtained by statistical analyses. In the current study, meta-analysis was performed on type 2 diabetes, circadian rhythm-related genes, and breast, bladder, liver, pancreas, colon and rectum cancer-associated transcriptome data using the integration of gene expression profiles with genome-scale biomolecular networks in diabetes samples. First, we detected downregulated and upregulated DEGs in mouse cortex and hypothalamus samples of mice with sleep deprivation. In summary, upregulated genes active genes associated with oxidative phosphorylation, cancer and diabetes, mainly in hypothalamus specimens. In cortex, we observed mainly downregulation of immune system. DEGs were combined with 214 circadian rhythm related genes to type 2 DM and cancer samples. We observed that several common genes deregulated in both diseases. Klf10, Ntkr3, Igf1, Usp2, Ezh2 were both downregulated in type 2 DM and cancer samples, while Arntl2 and Agrp were upregulated. It seems that the changes in mRNA are contributing to the phenotypic changes in type 2 DM, resulting in phenotypic changes associated with the malignant transformation. Taking those genes to perform a survival analysis, we found only Igf1, Usp2 and Arntl2 genes associated with patient outcomes. While Igf1 and Usp2 downregulation had a negative impact, Arntl2 upregulation was associated with poor survival both in BLCA and BRCA cancer samples. Our data stimulate efforts in news studies to achieve the experimental and clinical validation about these biomolecules.