Synuclein-γ in uterine serous carcinoma impacts survival: An NRG Oncology/Gynecologic Oncology Group study.

Winder AD, Maniar KP, Wei JJ, Liu D, Scholtens DM, Lurain JR, Schink JC, Buttin BM, Filiaci VL, Lankes HA, Ramirez NC, Park K, Singh M, Lieberman RW, Mannel RS, Powell MA, Backes FJ, Mathews CA, Pearl ML, Secord AA, Peace DJ, Mutch DG, Creasman WT, Kim JJ
Cancer 123 1144-1155 01/01/2017


BACKGROUND: Synuclein-γ (SNCG) is highly expressed in advanced solid tumors, including uterine serous carcinoma (USC). The objective of the current study was to determine whether SNCG protein was associated with survival and clinical covariates using the largest existing collection of USCs from the Gynecologic Oncology Group (GOG-8023).

METHODS: High-density tissue microarrays (TMAs) of tumor tissues from 313 patients with USC were stained by immunohistochemistry for SNCG, p53, p16, FOLR1, pERK, pAKT, ER, PR, and HER2/neu. Associations of SNCG and other tumor markers with overall and progression-free survival were assessed using log-rank tests and Cox proportional-hazards models, which also were adjusted for age, race, and stage.

RESULTS: The overall survival at 5 years was 46% for women with high SNCG expression and 62% for those with low SNCG expression (log-rank P = .021; hazard ratio [HR], 1.31; 95% confidence interval [CI], 0.91-1.9 in adjusted Cox model). The progression-free survival rate at 5 years was worse for women who had high SNCG expression, at 40%, compared with 56% for those who had low SNCG expression (log-rank P = .0081; HR, 1.36; 95% CI, 0.96-1.92 in adjusted Cox model). High levels of both p53 and p16 were significantly associated with worse overall survival (p53: HR, 4.20 [95% CI, 1.54-11.45]; p16: HR, 1.95 [95% CI, 1.01-3.75]) and progression-free survival (p53: HR, 2.16 [95% CI, 1.09-4.27]; p16: HR, 1.53 [95% CI, 0.87-2.69]) compared with low levels.

CONCLUSIONS: This largest collection of USCs to date demonstrates that SNCG was associated with poor survival in univariate analyses. SNCG does not predict survival outcome independent of p53 and p16 in models that jointly consider multiple markers. Cancer 2017;123:1144-1155. © 2016 American Cancer Society.

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