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Synuclein-γ (SNCG) expression in ovarian cancer is associated with high-risk clinicopathologic disease

Posted on 2016-11-03 - 05:00
Abstract Background Synuclein gamma (SNCG) expression is associated with advanced disease and chemoresistance in multiple solid tumors. Our goal was to determine if SNCG protein expression in ovarian cancer was correlated with clinicopathologic variables and patient outcomes. Methods Tissue microarrays from primary tumors of 357 ovarian, fallopian tube, and primary peritoneal cancer patients, who underwent primary surgery at Roswell Park Cancer Institute between 1995 and 2007, were immunohistochemically stained for SNCG. A pathologist blinded to patient data scored tumors as positive if ≥10 % of the sample stained for SNCG. Medical records were reviewed for clinicopathologic and demographic variables. Between the positive and negative groups, Wilcoxon rank-sum test was used to compare the median ages and Fisher’s exact test was used to compare groups in categorical variables. Cox proportional hazard models examined associations between SNCG and overall and progression-free survival. Results The median follow-up was 36 months, median overall survival was 39 months, and median progression-free survival was 18 months. SNCG presence was associated with clinical variables of serous histology, grade 3 disease, suboptimal debulking, ascites at surgery, FIGO stage III-IV cancer, or initial CA-125 level >485. There was no significant difference in overall survival (HR 1.06 95 % CI 0.81–1.39 P 0.69) or progression-free survival (HR 1.16 95 % CI 0.89–1.50 P 0.28) for patients with or without SNCG expression. Conclusions SNCG expression in ovarian cancer is frequent in patients with high-risk features, but it does not correlate with chemotherapy response, overall survival, or progression-free survival.

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Journal of Ovarian Research

AUTHORS (13)

Anna Strohl
Kristina Mori
Stacey Akers
Wiam Bshara
Barbara Buttin
Peter Frederick
Irene Helenowski
Carl Morrison
Kunle Odunsi
Julian Schink
Denise Scholtens
Jian-Jun Wei
J. Kim
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