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A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance)

Authors :
Hyung L. Kim
Susan Halabi
Ping Li
Greg Mayhew
Jeff Simko
Andrew B. Nixon
Eric J. Small
Brian Rini
Michael J. Morris
Mary-Ellen Taplin
Daniel George
Source :
EBioMedicine, Vol 2, Iss 11, Pp 1814-1820 (2015)
Publication Year :
2015
Publisher :
Elsevier, 2015.

Abstract

Background: Prognosis associated with metastatic renal cell carcinoma (mRCC) can vary widely. Methods: This study used pretreatment nephrectomy specimens from a randomized phase III trial. Expression levels of candidate genes were determined from archival tumors using the OpenArray® platform for TaqMan® RT-qPCR. The dataset was randomly divided at 2:1 ratio into training (n = 221) and testing (n = 103) sets to develop a multigene prognostic signature. Findings: Gene expressions were measured in 324 patients. In the training set, multiple models testing 424 candidate genes identified a prognostic signature containing 8 genes plus MSKCC clinical risk factors. In the testing set, the time dependent (td) AUC for a prognostic model containing the 8 genes with and without MSKCC risk factors were 0.72 and 0.69, respectively. The tdAUC for the clinical risk factors alone was 0.61. Additional primary mRCCs from patients with mRCC (n = 12) were sampled in multiple sites and standard deviations of gene expressions within a tumor were used as a measure of heterogeneity. All 8 genes in the final prognostic model met our criteria for minimal heterogeneity. Conclusions: A molecular prognostic signature based on 8 genes was developed and is ready for external validation in this patient population and other related settings such as nonmetastatic RCC.

Details

Language :
English
ISSN :
23523964
Volume :
2
Issue :
11
Database :
Directory of Open Access Journals
Journal :
EBioMedicine
Publication Type :
Academic Journal
Accession number :
edsdoj.5879eb1e7af417fb8d9f7606801fad6
Document Type :
article
Full Text :
https://doi.org/10.1016/j.ebiom.2015.09.012