Abstract 5301: Integrative protein-marker prognostic model for early-stage endometrioid endometrial carcinoma

Abstract

Abstract Endometrioid endometrial carcinoma (EEC) is the major histological type of endometrial cancer, the most prevalent gynecologic malignancy in USA. EEC recurrence or metastasis is associated with an abysmal prognosis. Early-stage EEC is generally curable, but a subset has high risk of recurrence or metastasis. Prognosis estimation for early-stage EEC mainly relies on clinicopathological characteristics, but is unreliable. We aimed to identify patients with high-risk early-stage EEC who are most likely to benefit from more extensive surgery and adjuvant therapy by building a prognostic model that integrates clinical variables and protein markers. We employed two large, independent EEC datasets as training and validation cohorts, and generated the levels of 186 proteins and phosphoproteins using reverse-phase protein arrays. Using the training samples, we developed a predictive model containing two clinical factors and 18 protein markers and optimized the risk group classification. Kaplan-Meier survival analyses in the validation cohort confirmed an improved prognostic power. Compared with clinical variables (stage, grade, and patient age), only the risk groups defined by the integrative model were consistently significant in both univariate and multivariate analyses across both cohorts. Our prognostic model is potentially of high clinical value for stratifying patients with early-stage EEC and optimizing their treatment strategies. Note: This abstract was not presented at the meeting. Citation Format: Han Liang, UT MD Anderson RPPA/TCGA working group. Integrative protein-marker prognostic model for early-stage endometrioid endometrial carcinoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5301. doi:10.1158/1538-7445.AM2015-5301