An NRG Oncology/GOG study of molecular classification for risk prediction in endometrioid endometrial cancer.

Cosgrove CM, Tritchler DL, Cohn DE, Mutch DG, Rush CM, Lankes HA, Creasman WT, Miller DS, Ramirez NC, Geller MA, Powell MA, Backes FJ, Landrum LM, Timmers C, Suarez AA, Zaino RJ, Pearl ML, DiSilvestro PA, Lele SB, Goodfellow PJ
Gynecol Oncol 148 174-180 01/01/2018


OBJECTIVES: The purpose of this study was to assess the prognostic significance of a simplified, clinically accessible classification system for endometrioid endometrial cancers combining Lynch syndrome screening and molecular risk stratification.

METHODS: Tumors from NRG/GOG GOG210 were evaluated for mismatch repair defects (MSI, MMR IHC, and MLH1 methylation), POLE mutations, and loss of heterozygosity. TP53 was evaluated in a subset of cases. Tumors were assigned to four molecular classes. Relationships between molecular classes and clinicopathologic variables were assessed using contingency tests and Cox proportional methods.

RESULTS: Molecular classification was successful for 982 tumors. Based on the NCI consensus MSI panel assessing MSI and loss of heterozygosity combined with POLE testing, 49% of tumors were classified copy number stable (CNS), 39% MMR deficient, 8% copy number altered (CNA) and 4% POLE mutant. Cancer-specific mortality occurred in 5% of patients with CNS tumors; 2.6% with POLE tumors; 7.6% with MMR deficient tumors and 19% with CNA tumors. The CNA group had worse progression-free (HR 2.31, 95%CI 1.53-3.49) and cancer-specific survival (HR 3.95; 95%CI 2.10-7.44). The POLE group had improved outcomes, but the differences were not statistically significant. CNA class remained significant for cancer-specific survival (HR 2.11; 95%CI 1.04-4.26) in multivariable analysis. The CNA molecular class was associated with TP53 mutation and expression status.

CONCLUSIONS: A simple molecular classification for endometrioid endometrial cancers that can be easily combined with Lynch syndrome screening provides important prognostic information. These findings support prospective clinical validation and further studies on the predictive value of a simplified molecular classification system.

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