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Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification.

ABSTRACT: 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 (15/17 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.

SUBMITTER: Takahashi M

PROVIDER: S-EPMC55525 | biostudies-literature | 2001 Aug

REPOSITORIES: biostudies-literature

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Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification.

Takahashi M M Rhodes D R DR Furge K A KA Kanayama H H Kagawa S S Haab B B BB Teh B T BT

Proceedings of the National Academy of Sciences of the United States of America 20010807 17

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 rel ...[more]

PMID: 11493696

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Project description:Gene expression profiling has been shown to provide prognostic information on patients with solitary sporadic renal cell carcinoma. To our knowledge there is no reliable way to differentiate synchronous renal metastasis from bilateral primary tumors in patients with bilateral renal cell carcinoma. We present data using a custom kidney cancer cDNA array that can predict the outcome in patients with unilateral and bilateral renal cell carcinoma.Fresh frozen tissue from 38 clear cell renal cell carcinomas was analyzed using a cancer cDNA array containing 3,966 genes relevant to cancer or kidney development. Median followup was 5.3 years. Cancer recurred in 12 patients (43%) and 11 (39%) had died by the last followup.Using a training data set of 8 tumors a 44 gene expression profile distinguishing aggressive and indolent clear cell renal cell carcinoma was identified. Of 29 single clear cell renal cell carcinomas 16 and 13 were predicted to be indolent and aggressive, respectively, by the gene expression profile. Recurrence-free survival at 5 years was 68% and 42% in these 2 groups, respectively (p = 0.032). Clear cell renal cell carcinoma classified as indolent or aggressive according to SSIGN (stage, size, grade and necrosis) score showed a 5-year recurrence-free survival rate of 78% and 42%, respectively (p = 0.021). On Cox proportional hazards analysis the gene expression profile was not an independent predictor of recurrence-free survival after accounting for SSIGN score. Gene expression profile classification correlated with cancer specific survival at 5 years in 4 of 4 patients with metachronous clear cell renal cell carcinoma but in only 2 of 4 with bilateral synchronous clear cell renal cell carcinoma.Gene expression profiling using a kidney cancer relevant cDNA array can differentiate between aggressive and indolent clear cell renal cell carcinomas. Gene expression profile results may be most useful for unilateral clear cell renal cell carcinoma when results are discordant with predictions of tumor behavior based on standard clinicopathological features. In addition, gene expression profiling can provide prognostic information that may help characterize tumors of unknown clinical stage, such as bilateral metachronous clear cell renal cell carcinoma.

Project description:Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of malignancy in adults. However, the clinical significance of tumor suppressor genes (TSG) is largely elusive. Herein, the expression profile TSGs and its clinical response in ccRCC were investigated. A total of 603 ccRCC samples from two cohorts (TCGA and ICGC) were retrieved in this study. Three molecular subtypes (C1, C2, and C3) were identified based on the TSGs expression profile in the TCGA dataset. Through Weighted Gene Correlation Network Analysis (WGCNA), six modules associated with three subtypes were identified. Pathway enrichment for the modules revealed that crucial pathways including p53 signaling and immune-related pathways were significantly enriched. We further focused on the relationship between immune infiltration level and subtypes, and found that subtype C1 was associated with higher immune infiltration level, subtype C2 was corresponding with medium immune infiltration level, whereas subtype C3 was correlated with lower immune infiltration level. Interestingly, C2 have a better survival outcome, while C1 and C3 showed a poor prognosis. Considering their survival difference, we then performed a differentially expression analysis between C2 and C1&3, and a total of 99 differentially expressed tumor suppressor genes (DETSGs) were identified. According to these DETSGs, 59 potential compounds with 28 mechanisms of action (MOA) were predicted using the Connectivity Map (CMap) database. Among these compounds, leflunomide, naftopidil, and ribavirin were the most prospective compounds for the treatment of ccRCC. In addition, we found that subtype C2 is more sensitive to sorafenib and sunitinib drugs, and C2 have more likelihood to be responded to immunotherapy. In summary, the three subtypes hinged on the tumor suppressor gene expression for ccRCC might contribute to understanding the underlying molecular mechanisms of ccRCC. Also, its potential compounds might offer guidelines for developing a novel treatment strategy of ccRCC.

Project description:Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of RCC; however, prognostic prediction tools for ccRCC are scant. Developing mRNA or long non-coding RNA (lncRNA)-based risk assessment tools may improve the prognosis in patients with ccRCC. RNA-sequencing and prognostic data from patients with ccRCC were downloaded from The Cancer Genome Atlas and the European Bioinformatics Institute Array database at the National Center for Biotechnology Information. Differentially expressed (DE) RNAs (DERs) and prognostic DERs were screened between less favorable and favorable prognoses using the limma package in R 3.4.1, and analyzed using univariate and multivariate Cox regression analyses, respectively. Risk score models were constructed using optimal combinations of DEmRNAs and DElncRNAs identified using the Least Absolute Shrinkage And Selection Operator Cox regression model of the penalized package. Associations between risk score models and overall survival time were evaluated. Independent prognostic clinical factors were screened using univariate and multivariate Cox regression analyses, and nomogram models were constructed. Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted using the clusterProfiler package in R3.4.1. A total of 451 DERs were identified, including 404 mRNAs and 47 lncRNAs, between less favorable and favorable prognoses, and 269 DERs, including 233 mRNAs and 36 lncRNAs, were identified as independent prognostic factors. Optimal combinations including 10 DEmRNAs or 10 DElncRNAs were screened using four risk score models based on the status or expression levels of the 10 DEmRNAs or 10 DElncRNAs. The model based on the expression levels of the 10 DEmRNAs had the highest prognostic power. These prognostic DEmRNAs may be involved in biological processes associated with the inflammatory response, complement and coagulation cascades and neuroactive ligand-receptor interaction pathways. The present validated risk assessment tool based on the expression levels of these 10 DEmRNAs may help to identify patients with ccRCC at a high risk of mortality. These 10 DEmRNAs in optimal combinations may serve as prognostic biomarkers and help to elucidate the pathogenesis of ccRCC.

Dataset Information

Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification.

Publications

Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification.

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