Dataset Information

Microarray profile of human kidney from diabetes, renal cell carcinoma and renal cell carcinoma with diabetes.

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.

SUBMITTER: Kosti A

PROVIDER: S-EPMC4362485 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Microarray profile of human kidney from diabetes, renal cell carcinoma and renal cell carcinoma with diabetes.

Kosti Adam A Harry Chen Hung-I HI Mohan Sumathy S Liang Sitai S Chen Yidong Y Habib Samy L SL

Genes & cancer 20150101 1-2

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 obtai ...[more]

PMID: 25821562

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Project description:Background: Circular RNAs (circRNAs), a novel class of endogenous noncoding RNAs, are involved in a variety of diseases, including several types of cancers. We hypothesized that circRNAs are involved in the tumorigenesis and development of clear cell renal cell carcinoma (ccRCC). Methods: To verify our hypothesis, we explored the circRNA expression profiles in 4 pairs of ccRCC tissues and their adjacent non-carcinoma tissues via microarray analysis. Selected circRNAs were further validated by qPCR. Moreover, hsa_circ_0005875 was selected for further study and the potential clinical values of hsa_circ_0005875 were investigated in 60 pairs of ccRCC tissues and adjacent normal controls. In addition, the role of hsa_circ_0005875 in ccRCC progression were performed using colony formation assay, Transwell assay and Martrigel-Transwell assay respectively. Finally, interactions between the circRNAs and miRNAs were predicted using Arraystar's miRNA target prediction software. Luciferase reporter assays were performed to evaluate the interaction between hsa_circ_0005875 and hsa_miR-145-5p. Results: The microarray data showed 1988 circRNAs were significantly dysregulated circRNAs, including 1033 upregulated and 955 downregulated ones in the ccRCC tissues. Hsa_circ_0005875 was confirmed to be significantly upregulated in the ccRCC tumor tissues and renal carcinoma cells. Further analysis revealed that hsa_circ_0005875 expression was associated with tumor size, pathological TNM stage, histological differentiation, and lymphatic metastasis. Functional experiments demonstrated that overexpression of hsa_circ_0005875 increased proliferation, migration and invasion abilities. Moreover, bioinformatics analysis and luciferase reporter assays suggest that hsa_circ_0005875 may serve as a ceRNA (competing endogenous RNA) of miR-145-5p to relieve the repressive effect of miR-145-5p on target ZEB2. Conclusions: These data indicate that hsa_circ_0005875 might play a role in promoting tumor growth and metastasis and be a potential biomarker of ccRCC.

Project description:Renal cell carcinoma (RCC) is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays.Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC.Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR). Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved.This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most notably, genes involved in cell adhesion were dominantly up-regulated whereas genes involved in transport were dominantly down-regulated. This study reveals significant gene expression alterations in key biological pathways and provides potential insights into understanding the molecular mechanism of renal cell carcinogenesis.

Dataset Information

Microarray profile of human kidney from diabetes, renal cell carcinoma and renal cell carcinoma with diabetes.

Publications

Microarray profile of human kidney from diabetes, renal cell carcinoma and renal cell carcinoma with diabetes.

Similar Datasets

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