Ovarian Cancer Canada

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Predicting Time to Ovarian Carcinoma Recurrence using Protein Markers

“Identification of protein markers linked to disease recurrence may yield insights into tumor biology.” 

Ji-Yeon Yang, Kosuke Yoshihara, Kenichi Tanaka, Masayuki Hatae, Hideaki Masuzaki, Hiroaki Itamochi, The Cancer Genome Atlas Research Network, Masashi Takano, Kimio Ushijima, Janos L. Tanyi, George Coukos, Yiling Lu, Gordon B. Mills and Roel G.W. Verhaak1

Published August 15, 2013. Received for publication December 26, 2012, and accepted in revised form June 6, 2013.


Patients with ovarian cancer are at high risk of tumor recurrence. Prediction of therapy outcome may provide therapeutic avenues to improve patient outcomes. Using reverse-phase protein arrays, we generated ovarian carcinoma protein expression profiles on 412 cases from TCGA and constructed a PRotein-driven index of OVARian cancer (PROVAR). PROVAR significantly discriminated an independent cohort of 226 high-grade serous ovarian carcinomas into groups of high risk and low risk of tumor recurrence as well as short-term and long-term survivors. Comparison with gene expression–based outcome classification models showed a significantly improved capacity of the protein-based PROVAR to predict tumor progression. Identification of protein markers linked to disease recurrence may yield insights into tumor biology. When combined with features known to be associated with outcome, such as BRCA mutation, PROVAR may provide clinically useful predictions of time to tumor recurrence.


This entry was posted on September 3, 2013 by in Research Updates and tagged , , .

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