Microarray profile of human kidney from diabetes, renal cell carcinoma and renal cell carcinoma with diabetes
Adam Kosti2, Hung-I Harry Chen4, Sumathy Mohan3, Sitai Liang2, Yidong Chen4,5 and Samy L. Habib1,2
1 Geriatric Research, Education and Clinical Center, South Texas Veterans Healthcare System, University of Texas Health Science Center, San Antonio, Texas, USA
2 Department of Cellular & Structural Biology, University of Texas Health Science Center, San Antonio, Texas, USA
3 Department of Pathology, University of Texas Health Science Center, San Antonio, Texas, USA
4 Department of Greehey Children’s Cancer Research Institute, University of Texas Health Science Center, San Antonio, Texas, USA
5 Department of Epidemiology and Biostatistics, University of Texas Health Science Center, San Antonio, Texas, USA
Correspondence:
Samy L Habib, email:
Keywords: microarray, renal, diabetes, RCC
Received: November 25, 2014 Accepted: February 13, 2015 Published: February 14, 2015
Abstract
Recent study from our laboratory showed that patients with diabetes are at a higher risk of developing kidney cancer. In the current study, we have screened whole human DNA genome from healthy control, patients with diabetes or renal cell carcinoma (RCC) or RCC+diabetes. We found that 883 genes gain/163 genes loss of copy number in RCC+diabetes group, 669 genes gain/307 genes loss in RCC group and 458 genes gain/38 genes loss of copy number in diabetes group, after removing gain/loss genes obtained from healthy control group. Data analyzed for functional annotation enrichment pathways showed that control group had the highest number (280) of enriched pathways, 191 in diabetes+RCC group, 148 in RCC group, and 81 in diabetes group. The overlap GO pathways between RCC+diabetes and RCC groups showed that nine were enriched, between RCC+diabetes and diabetes groups was four and between diabetes and RCC groups was eight GO pathways. Overall, we observed majority of DNA alterations in patients from RCC+diabetes group. Interestingly, insulin receptor (INSR) is highly expressed and had gains in copy number in RCC+diabetes and diabetes groups. The changes in INSR copy number may use as a biomarker for predicting RCC development in diabetic patients.
