Dataset Information

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma.

ABSTRACT: The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. In an independent validation of set of 47 patients with mCCRCC, transcript expression of the 18 candidate genes were quantified using a customized NanoString probeset. Cox regression multivariate analysis confirmed that two of the candidate genes were significantly associated with overall survival. Higher expression of BAG1 [hazard ratio (HR) of 0.14, p < 0.0001, 95% confidence interval (CI) 0.04-0.36] and NOP56 (HR 0.13, p < 0.0001, 95% CI 0.05-0.34) were associated with better prognosis. A prognostic model incorporating expression of BAG1 and NOP56 into the MSKCC score improved prognostication significantly over a model using the MSKCC prognostic score only (p < 0.0001). Prognostic value of using whole blood mRNA gene profiling in mCCRCC is feasible and should be prospectively confirmed in larger studies.

SUBMITTER: Giridhar KV

PROVIDER: S-EPMC5713295 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma.

Giridhar Karthik V KV Sosa Carlos P CP Hillman David W DW Sanhueza Cristobal C Dalpiaz Candace L CL Costello Brian A BA Quevedo Fernando J FJ Pitot Henry C HC Dronca Roxana S RS Ertz Donna D Cheville John C JC Donkena Krishna Vanaja KV Kohli Manish M

International journal of molecular sciences 20171103 11

The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. ...[more]

PMID: 29099775

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Project description:ObjectivesTo predict CTLA4 expression levels and prognosis of clear cell renal cell carcinoma (ccRCC) by constructing a computed tomography-based radiomics model and establishing a nomogram using clinicopathologic factors.MethodsThe clinicopathologic parameters and genomic data were extracted from 493 ccRCC cases of the Cancer Genome Atlas (TCGA)-KIRC database. Univariate and multivariate Cox regression and Kaplan-Meier analysis were performed for prognosis analysis. Cibersortx was applied to evaluate the immune cell composition. Radiomic features were extracted from the TCGA/the Cancer Imaging Archive (TCIA) (n = 102) datasets. The support vector machine (SVM) was employed to establish the radiomics signature for predicting CTLA4 expression. Receiver operating characteristic curve (ROC), decision curve analysis (DCA), and precision-recall curve were utilized to assess the predictive performance of the radiomics signature. Correlations between radiomics score (RS) and selected features were also evaluated. An RS-based nomogram was constructed to predict prognosis.ResultsCTLA4 was significantly overexpressed in ccRCC tissues and was related to lower overall survival. A higher CTLA4 expression was independently linked to the poor prognosis (HR = 1.458, 95% CI 1.13-1.881, p = 0.004). The radiomics model for the prediction of CTLA4 expression levels (AUC = 0.769 in the training set, AUC = 0.724 in the validation set) was established using seven radiomic features. A significant elevation in infiltrating M2 macrophages was observed in the RS high group (p < 0.001). The predictive efficiencies of the RS-based nomogram measured by AUC were 0.826 at 12 months, 0.805 at 36 months, and 0.76 at 60 months.ConclusionsCTLA4 mRNA expression status in ccRCC could be predicted noninvasively using a radiomics model based on nephrographic phase contrast-enhanced CT images. The nomogram established by combining RS and clinicopathologic factors could predict overall survival for ccRCC patients. Our findings may help stratify prognosis of ccRCC patients and identify those who may respond best to ICI-based treatments.

Dataset Information

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma.

Publications

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma.

Similar Datasets

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