A biomarker panel associated with distant metastasis in prostate cancer patients treated with radiotherapy as prognostic for DM in a large cohort of prostatectomy patients.

Authors

null

Alan Pollack

Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL

Alan Pollack , Nicholas Erho , Roshan Noronha , Lucia L.C. Lam , Christine Buerki , Sakhi Abraham , Eric A. Klein , R. Jeffrey Karnes , Robert Benjamin Den , Adam Dicker , Adrian Ishkanian , Elai Davicioni , Felix Yi-Chung Feng , Radka Stoyanova

Organizations

Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, GenomeDx Biosciences, Inc., Vancouver, BC, Canada, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, Department of Urology, Mayo Clinic, Rochester, MN, Rochester, MN, Department of Radiation Oncology, The Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA, Department of Radiation Oncology, University of Michigan Health System, Ann Arbor, MI

Research Funding

No funding sources reported

Background: A number of biomarkers related to cell cycle, angiogenesis or apoptosis have been found to be associated with patient outcome in tissue samples from men treated with first line radiation therapy in RTOG clinical trials using immunohistochemical staining and analysis. In a prior study, four biomarkers (Ki-67, MDM2, p16 and Cox-2) and clinical covariates were included in a model of distant metastasis (DM; Pollack et al, Clin Cancer Res, 2014 [epub ahead of print]) risk. The current study tested the hypothesis that these genes are prognostic for DM in men treated primarily with total prostatectomy using RNA expression profiling. Methods: RNA fromprostatectomy samples from Cleveland Clinic (CC, n=182); Mayo Clinic (MC)-I (n = 545) and II (n=235); Memorial Sloan Kettering Cancer Center (MSKCC, n=131); Erasmus Medical Center (EMC, n=48) and Thomas Jefferson University (TJU, n=130) were profiled using 1.4 million RNA features. A Cox proportional hazards model was built on the MC-I training set to combine the 4 biomarkers into a prognostic risk score (4BMSig). 4BMSig was subsequently evaluated for its prognostic significance separately and in combination with clinical risk factors (biopsy Gleason Score, cT-category and Preop-PSA) for DM. Results: 4BMSig was found to discriminate DM patients significantly for the MC-II (AUC = 0.66, p < 0.001), CCF (AUC = 0.68, p < 0.001), and MSKCC (AUC = 0.71, p = 0.04) datasets, and achieved borderline significance for EMC (AUC = 0.70, p = 0.06). 4BMSig did not discriminate DM in the TJU dataset (only 10 DM events). Pooled multivariable analysis (n = 726) with clinical covariates revealed that 4BMSig is a strong independent prognostic covariate for DM (p < 0.001) and prostate cancer specific mortality (p = 0.005). Conclusions: The four genes identified previously as being associated with DM in radiotherapy patients were incorporated herein into 4BMSig, which was found to have potential as a pretreatment prognostic DM risk assessment tool for men treated with prostatectomy. Further validation would consist of testing 4BMSig from RNA in diagnostic tissue from prostate cancer patients prior to prostatectomy.

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Abstract Details

Meeting

2015 Genitourinary Cancers Symposium

Session Type

Poster Session

Session Title

General Poster Session A: Prostate Cancer

Track

Prostate Cancer

Sub Track

Prostate Cancer - Localized Disease

Citation

J Clin Oncol 33, 2015 (suppl 7; abstr 8)

DOI

10.1200/jco.2015.33.7_suppl.8

Abstract #

8

Poster Bd #

A14

Abstract Disclosures

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