DNA methylation biomarkers predict progression-free and overall survival of metastatic renal cell cancer (mRCC) treated with antiangiogenic therapies

Inga Peters, Natalia Dubrowinskaja, Mahmoud Abbas, Christoph Seidel, Michael Kogosov, Ralph Scherer, Kai Gebauer, Axel S. Merseburger, Markus A. Kuczyk, Viktor Grünwald, Jürgen Serth

32 Zitate (Scopus)

Abstract

VEGF-targeted therapy increases both the progression-free (PFS) and overall survival (OS) of patients with metastasized renal cell cancer (mRCC). Identification of molecular phenotypes of RCC could improve risk-stratification and the prediction of the clinical disease course. We investigated whether gene-specific DNA hypermethylation can predict PFS and OS among patients undergoing anti-VEGF-based therapy. Primary tumor tissues from 18 patients receiving targeted therapy were examined retrospectively using quantitative methylation-specific PCR analysis of CST6 , LAD1, hsa-miR-124-3, and hsa-miR-9-1 CpG islands. PFS and OS were analyzed for first-line and sequential antiangiogenic therapies using the log rank statistics. Sensitivity and specificity were determined for predicting first-line therapy failure. Hypermethylation of CST6 and LAD1 was associated with both a shortened PFS (log rank p = 0.009 and p = 0.004) and OS (p = 0.011 and p = 0.043). The median PFS observed for the high and low methylation groups of CST6 and LAD1 was 2.0 vs.11.4 months. LAD1 methylation had a specificity of 1.0 (95% CI 0.65-1.0) and a sensitivity of 0.73 (95% CI 0.43-0.90) for the prediction of first-line therapy. CST6 and LAD1 methylation are candidate epigenetic biomarkers showing unprecedented association with PFS and OS as well as specificity for the prediction of the response to therapy. DNA methylation markers should be considered for the prospective evaluation of larger patient cohorts in future studies.

OriginalspracheEnglisch
Aufsatznummere91440
ZeitschriftPLoS ONE
Jahrgang9
Ausgabenummer3
DOIs
PublikationsstatusVeröffentlicht - 14.03.2014

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  • Profilbereich: Lübeck Integrated Oncology Network (LION)

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