Whole blood mRNA expression-based prognosis of metastatic renal cell carcinoma

Karthik V. Giridhar, Carlos P. Sosa, David W. Hillman, Cristobal Sanhueza, Candace L. Dalpiaz, Brian A. Costello, Fernando J. Quevedo, Henry C. Pitot, Roxana S. Dronca, Donna Ertz, John C. Cheville, Krishna Vanaja Donkena, Manish Kohli

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish (US)
Article number2326
JournalInternational journal of molecular sciences
Volume18
Issue number11
DOIs
StatePublished - Nov 3 2017

Keywords

  • Metastatic renal cell carcinoma
  • Prognostic biomarkers
  • Whole blood mrna gene expression

ASJC Scopus subject areas

  • Catalysis
  • Molecular Biology
  • Spectroscopy
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Inorganic Chemistry

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