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MicroRNA expression profiles predict clinical phenotypes and prognosis in chromophobe renal cell carcinoma.

ABSTRACT: Chromophobe renal cell carcinoma (chRCC) is the third most common subtype of kidney cancers. In the present study, we identified 58 treatment-naïve primary chRCC patients from The Cancer Genome Atlas dataset and analyzed the genome-wide microRNA (miRNA) expression profiles, with the aim to assess the relationship of miRNA expression with the progression and prognosis of chRCC. Overall, a total of 105 miRNAs were found to be differentially expressed between tumor and the adjacent normal tissues from 22 chRCC patients. In the unpaired condition (58 chRCC vs. 22 normal tissues), 77 (96.3%) samples were distinguished correctly by the signatures. In the progression-related profiles, 27 miRNAs were selected for pathologic T and 9 for lymph node involvement. In the survival analyses, the expression levels of mir-191, mir-19a, mir-210, and mir-425 were significantly associated with both recurrence-free survival (RFS) and overall survival, while mir-210 was proven as an independent prognostic factor in terms of RFS. In summary, miRNAs are expressed differentially in chRCC, and unique expression of miRNAs is associated with the progression and prognosis of chRCC.

SUBMITTER: Ge YZ

PROVIDER: S-EPMC4434887 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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MicroRNA expression profiles predict clinical phenotypes and prognosis in chromophobe renal cell carcinoma.

Ge Yu-Zheng YZ Xin Hui H Lu Tian-Ze TZ Xu Zheng Z Yu Peng P Zhao You-Cai YC Li Ming-Hao MH Zhao Yan Y Zhong Bing B Xu Xiao X Zhou Liu-Hua LH Wu Ran R Xu Lu-Wei LW Wu Jian-Ping JP Li Wen-Cheng WC Zhu Jia-Geng JG Jia Rui-Peng RP

Scientific reports 20150518

Chromophobe renal cell carcinoma (chRCC) is the third most common subtype of kidney cancers. In the present study, we identified 58 treatment-naïve primary chRCC patients from The Cancer Genome Atlas dataset and analyzed the genome-wide microRNA (miRNA) expression profiles, with the aim to assess the relationship of miRNA expression with the progression and prognosis of chRCC. Overall, a total of 105 miRNAs were found to be differentially expressed between tumor and the adjacent normal tissues f ...[more]

PMID: 25981392

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Project description:Numerous studies have shown that microRNA (miRNA) serves as key regulatory factors in the origin and development of cancers. However, the biological mechanisms of miRNAs in kidney renal clear cell carcinoma (KIRC) are still unknown. It is necessary to construct an effective miRNA-clinical model to predict the prognosis of KIRC. In this study, 94 differentially expressed miRNAs were found between para-tumor and tumor tissues based on the Cancer Genome Atlas (TCGA) database. Seven miRNAs (hsa-miR-21-5p, hsa-miR-3613-5p, hsa-miR-144-5p, hsa-miR-376a-5p, hsa-miR-5588-3p, hsa-miR-1269a, and hsa-miR-137-3p) were selected as prognostic indicators. According to their cox coefficient, a risk score formula was constructed. Patients with risk scores were divided into high- and low-risk groups based on the median score. Kaplan-Meier curves analysis showed that the low-risk group had a better survival probability compared to the high-risk group. The area under the ROC curve (AUC) value of the miRNA model was 0.744. In comparison with clinical features, the miRNA model risk score was considered as an independent prognosis factor in multivariate Cox regression analysis. In addition, we built a nomogram including age, metastasis, and miRNA prognostic model based on the results of multivariate Cox regression analysis. The decision curve analysis (DCA) revealed the clinical net benefit of the prognostic model. Gene set enrichment analysis (GSEA) results suggested that several important pathways may be the potential pathways for KIRC. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the target genes of 7 miRNAs revealed that miRNAs may participate in KIRC progression via many specific pathways. Additionally, the levels of seven prognostic miRNAs showed a significant difference between KIRC tissues and adjacent non-tumorous tissues. In conclusion, the miRNA-clinical model provides an effective and accurate way to predict the prognosis of KIRC.

Project description:BACKGROUND: Chromophobe renal cell carcinoma (chRCC) and renal oncocytoma are two distinct but closely related entities with strong morphologic and genetic similarities. While chRCC is a malignant tumor, oncocytoma is usually regarded as a benign entity. The overlapping characteristics are best explained by a common cellular origin, and the biologic differences between chRCC and oncocytoma are therefore of considerable interest in terms of carcinogenesis, diagnosis and clinical management. Previous studies have been relatively limited in terms of examining the differences between oncocytoma and chromophobe RCC. METHODS: Gene expression profiling using the Affymetrix HGU133Plus2 platform was applied on chRCC (n = 15) and oncocytoma specimens (n = 15). Supervised analysis was applied to identify a discriminatory gene signature, as well as differentially expressed genes. High throughput single-nucleotide polymorphism (SNP) genotyping was performed on independent samples (n = 14) using Affymetrix GeneChip Mapping 100 K arrays to assess correlation between expression and gene copy number. Immunohistochemical validation was performed in an independent set of tumors. RESULTS: A novel 14 probe-set signature was developed to classify the tumors internally with 93% accuracy, and this was successfully validated on an external data-set with 94% accuracy. Pathway analysis highlighted clinically relevant dysregulated pathways of c-erbB2 and mammalian target of rapamycin (mTOR) signaling in chRCC, but no significant differences in p-AKT or extracellular HER2 expression was identified on immunohistochemistry. Loss of chromosome 1p, reflected in both cytogenetic and expression analysis, is common to both entities, implying this may be an early event in histogenesis. Multiple regional areas of cytogenetic alterations and corresponding expression biases differentiating the two entities were identified. Parafibromin, aquaporin 6, and synaptogyrin 3 were novel immunohistochemical markers effectively discriminating the two pathologic entities. CONCLUSIONS: Gene expression profiles, high-throughput SNP genotyping, and pathway analysis effectively distinguish chRCC from oncocytoma. We have generated a novel transcript predictor that is able to discriminate between the two entities accurately, and which has been validated both in an internal and an independent data-set, implying generalizability. A cytogenetic alteration, loss of chromosome 1p, common to renal oncocytoma and chRCC has been identified, providing the opportunities for identifying novel tumor suppressor genes and we have identified a series of immunohistochemical markers that are clinically useful in discriminating chRCC and oncocytoma.

Dataset Information

MicroRNA expression profiles predict clinical phenotypes and prognosis in chromophobe renal cell carcinoma.

Publications

MicroRNA expression profiles predict clinical phenotypes and prognosis in chromophobe renal cell carcinoma.

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