Gene expression profiling of clear cell renal cell carcinoma: Gene identification and prognostic classification (original) (raw)
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Gene expression profile of renal cell carcinoma clear cell type
International braz j urol : official journal of the Brazilian Society of Urology
The determination of prognosis in patients with renal cell carcinoma (RCC) is based, classically, on stage and histopathological aspects. The metastatic disease develops in one third of patients after surgery, even in localized tumors. There are few options for treating those patients, and even the new target designed drugs have shown low rates of success in controlling disease progression. Few studies used high throughput genomic analysis in renal cell carcinoma for determination of prognosis. This study is focused on the identification of gene expression signatures in tissues of low-risk, high-risk and metastatic RCC clear cell type (RCC-CCT). We analyzed the expression of approximately 55,000 distinct transcripts using the Whole Genome microarray platform hybridized with RNA extracted from 19 patients submitted to surgery to treat RCC-CCT with different clinical outcomes. They were divided into three groups (1) low risk, characterized by pT1, Fuhrman grade 1 or 2, no microvascula...
Gene expression profiling of clear cell renal cell carcinoma with sarcomatoid transformation
International Journal of Urology, 2019
To better understand the molecular mechanisms that underlie the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC), we studied the gene expression profiles of 29 ccRCC tumors obtained from patients with diverse clinical outcomes by using 21,632 cDNA microarrays. We identified gene expression alterations that were both common to most of the ccRCC studied and unique to clinical subsets. There was a significant distinction in gene expression profile between patients with a relatively nonaggressive form of the disease [100% survival after 5 years with the majority (15͞17 or 88%) having no clinical evidence of metastasis] versus patients with a relatively aggressive form of the disease (average survival time 25.4 months with a 0% 5-year survival rate). Approximately 40 genes most accurately make this distinction, some of which have previously been implicated in tumorigenesis and metastasis. To test the robustness and potential clinical usefulness of this molecular distinction, we simulated its use as a prognostic tool in the clinical setting. In 96% of the ccRCC cases tested, the prediction was compatible with the clinical outcome, exceeding the accuracy of prediction by staging. These results suggest that two molecularly distinct forms of ccRCC exist and that the integration of expression profile data with clinical parameters could serve to enhance the diagnosis and prognosis of ccRCC. Moreover, the identified genes provide insight into the molecular mechanisms of aggressive ccRCC and suggest intervention strategies.
2016
PURPOSE: Evaluation of 12 ccRCC publicly-available ccRCC gene expression datasets showed that previously proposed discrete molecular subtypes are unstable. To reflect the continuous nature of gene expression observed, we developed a quantitative score (Continuous Linear Enhanced Assessment of Renal cell carcinoma, or CLEAR) using expression analysis founded on pathologic parameters. MATERIALS AND METHODS: 265 ccRCC gene expression profiles were used to develop the CLEAR score, representing a genetic correlate of the continuum of morphological tumor grade. A signature derivation method based on correlation of CLEAR score with gene expression ranking was used to derive an 18-transcript signature. External validation was conducted in multiple public expression datasets. Results: As a measure of intertumoral gene expression heterogeneity, the CLEAR score demonstrated both superior prognostic estimates (94% vs 83% adequacy index in TCGA dataset) and inverse correlation with anti-angiogen...
Cancers, 2021
The Identification of reliable Biomarkers able to predict the outcome after nephrectomy of patients with clear cell renal cell carcinoma (ccRCC) is an unmet need. The gene expression analysis in tumor tissues represents a promising tool for better stratification of ccRCC subtypes and patients’ evaluation. Methods: In our study we retrospectively analyzed using Next-Generation expression analysis (NanoString), the expression of a gene panel in tumor tissue from 46 consecutive patients treated with nephrectomy for non-metastatic ccRCC at two Italian Oncological Centres. Significant differences in expression levels of selected genes was sought. Additionally, we performed a univariate and a multivariate analysis on overall survival according to Cox regression model. Results: A 17-gene expression signature of patients with a recurrence-free survival (RFS) < 1 year (unfavorable genomic signature (UGS)) and of patients with a RFS > 5 years (favorable genomic signature (FGS)) was iden...
Vol 22, No 3, October-December (Autumn) 2020, Pages: 386-393, 2020
Objective: We aimed to explore potential molecular mechanisms of clear cell renal cell carcinoma (ccRCC) and provide candidate target genes for ccRCC gene therapy. Material and Methods: This is a bioinformatics-based study. Microarray datasets of GSE6344, GSE781 and GSE53000 were downloaded from Gene Expression Omnibus database. Using meta-analysis, differentially expressed genes (DEGs) were identified between ccRCC and normal samples, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) function analyses. Then, protein-protein interaction (PPI) networks and modules were investigated. Furthermore, miRNAs-target gene regulatory network was constructed. Results: Total of 511 up-regulated and 444 down-regulated DEGs were determined in the present gene expression microarray data meta-analysis. These DEGs were enriched in functions like immune system process and pathways like Toll-like receptor signaling pathway. PPI network and eight modules were further constructed. A total of 10 outstanding DEGs including TYRO protein tyrosine kinase binding protein (TYROBP), interferon regulatory factor 7 (IRF7) and PPARG co-activator 1 alpha (PPARGC1A) were detected in PPI network. Furthermore, the miRNAs-target gene regulation analyses showed that miR-412 and miR-199b respectively targeted IRF7 and PPARGC1A to regulate the immune response in ccRCC. Conclusion: TYROBP, IRF7 and PPARGC1A might play important roles in ccRCC via taking part in the immune system process. expression microarray data meta-analysis identifies candidate genes and molecular mechanism associated with clear cell renal cell carcinoma. Cell J. 2020; 22(3): 386-393. doi: 10.22074/cellj.2020.6561. This open-access article has been published under the terms of the Creative Commons Attribution Non-Commercial 3.0 (CC BY-NC 3.0).
International Journal of Oncology, 2006
In order to clarify the molecular mechanism involved in renal carcinogenesis, and to identify molecular targets for diagnosis and treatment, we analyzed genome-wide gene expression profiles of 15 surgical specimens of clear cell renal cell carcinoma (RCC), compared to normal renal cortex, using a combination of laser microbeam microdissection (LMM) with a cDNA microarray representing 27,648 genes. We identified 257 genes that were commonly up-regulated and 721 genes that were down-regulated in RCCs. None of top 24 up-regulated genes that showed most significant differences in informative RCC-cases were included in previous reports describing expression profiles of RCC using RNAs isolated from bulk tissues. These findings suggest that it is important to purify as much as possible the populations of cancerous and normal epithelial cells obtained from surgical specimens. Among the significantly-transactivated genes, we focused on Semaphorin 5B (SEMA5B) and knocked-down its expression in RCC cells by small-interfering RNA (siRNA). Effective downregulation of its expression levels in RCC cells significantly attenuated RCC cell viability. In conclusion, our data should be helpful for a better understanding of the tumorigenesis of RCC and should contribute to the development of diagnostic tumor markers and molecular-targeting therapy for patients with RCC.
Scientific Reports
Kidney renal clear cell carcinoma (KIRC) is the most common renal cell carcinoma (RCC). However, patients with KIRC usually have poor prognosis due to limited biomarkers for early detection and prognosis prediction. In this study, we analysed key genes and pathways involved in KIRC from an array dataset including 26 tumour and 26 adjacent normal tissue samples. Weighted gene co-expression network analysis (WGCNA) was performed with the WGCNA package, and 20 modules were characterized as having the highest correlation with KIRC. The upregulated genes in the tumour samples are involved in the innate immune response, whereas the downregulated genes contribute to the cellular catabolism of glucose, amino acids and fatty acids. Furthermore, the key genes were evaluated through a protein-protein interaction (PPI) network combined with a co-expression network. The comparatively lower expression of AGXT, PTGER3 and SLC12A3 in tumours correlates with worse prognosis in KIRC patients, while h...
Modern Pathology, 2013
Clear cell papillary renal cell carcinoma is a distinct variant of renal cell carcinoma that shares some overlapping histological and immunohistochemical features of clear cell renal cell carcinoma and papillary renal cell carcinoma. Although the clear cell papillary renal cell carcinoma immunohistochemical profile is well described, clear cell papillary renal cell carcinoma mRNA expression has not been well characterized. We investigated the clear cell papillary renal cell carcinoma gene expression profile using previously identified candidate genes. We selected 17 clear cell papillary renal cell carcinoma, 15 clear cell renal cell carcinoma, and 13 papillary renal cell carcinoma cases for molecular analysis following histological review. cDNA from formalin-fixed paraffinembedded tissue was prepared. Quantitative real-time PCR targeting alpha-methylacyl coenzyme-A racemase (AMACR), BMP and activin membrane-bound inhibitor homolog (BAMBI), carbonic anhydrase IX (CA9), ceruloplasmin (CP), nicotinamide N-methyltransferase (NNMT), schwannomin-interacting protein 1 (SCHIP1), solute carrier family 34 (sodium phosphate) member 2 (SLC34A2), and vimentin (VIM) was performed. Gene expression data were normalized relative to 28S ribosomal RNA. Clear cell papillary renal cell carcinoma expressed all eight genes at variable levels. Compared with papillary renal cell carcinoma, clear cell papillary renal cell carcinoma expressed more CA9, CP, NNMT, and VIM, less AMACR, BAMBI, and SLC34A2, and similar levels of SCHIP1. Compared with clear cell renal cell carcinoma, clear cell papillary renal cell carcinoma expressed slightly less NNMT, but similar levels of the other seven genes. Although clear cell papillary renal cell carcinoma exhibits a unique molecular signature, it expresses several genes at comparable levels to clear cell renal cell carcinoma relative to papillary renal cell carcinoma. Understanding the molecular pathogenesis of clear cell papillary renal cell carcinoma will have a key role in future sub-classifications of this unique tumor.
Gene expression-based biomarkers for discriminating early and late stage of clear cell renal cancer
Scientific reports, 2017
In this study, an attempt has been made to identify expression-based gene biomarkers that can discriminate early and late stage of clear cell renal cell carcinoma (ccRCC) patients. We have analyzed the gene expression of 523 samples to identify genes that are differentially expressed in the early and late stage of ccRCC. First, a threshold-based method has been developed, which attained a maximum accuracy of 71.12% with ROC 0.67 using single gene NR3C2. To improve the performance of threshold-based method, we combined two or more genes and achieved maximum accuracy of 70.19% with ROC of 0.74 using eight genes on the validation dataset. These eight genes include four underexpressed (NR3C2, ENAM, DNASE1L3, FRMPD2) and four overexpressed (PLEKHA9, MAP6D1, SMPD4, C11orf73) genes in the late stage of ccRCC. Second, models were developed using state-of-art techniques and achieved maximum accuracy of 72.64% and 0.81 ROC using 64 genes on validation dataset. Similar accuracy was obtained on...