Implementation of the ProMisE classifier and validation of its prognostic impact in Brazilian endometrial carcinomas.

PURPOSE

Molecular classification of endometrial cancer (EC) has emerged as a key approach to individualize therapy and define prognostic outcomes. This study aimed to implement the traditional ProMisE classification in a Brazilian population, compared with a molecular setting of ProMisE biomarkers, and evaluate its impact on patients' prognosis.

PATIENT AND METHODS

A prospective cohort of 114 patients with primary EC treated at Barretos Cancer Hospital (BCH) between October 2020 and December 2022 was conducted. Pathology diagnosis, staging, treatment, and follow-up data were collected. The traditional ProMisE methodology was carried out by hotspot sequencing and immunohistochemistry (IHC) for p53 and mismatch repair (MMR) proteins. We further evaluate the MMR and status by molecular approach, namely microsatellite instability (MSI) by PCR-based and mutation analysis by next-generation sequencing (NGS). The results of the 4 molecular groups in both methodologies were compared regarding agreement accuracy and survival outcomes.

RESULTS

Among the 114 cases, the traditional ProMisE groups were: mut 15.8%, MMRd 28.1%, p53abn 27.2%, and no specific molecular profile (NSMP) 28.9%. Considering the molecular classification approach, we observed a mut group , MSI group of 23.7%, mutation of 27.2%, and NSMP of 33.3%. The concordance rate of both approaches was 86.8% (99/114 cases) with an overall accuracy of 0.87. Importantly, both traditional and molecular ProMisE approaches were associated with significant distinct overall survival (OS) and progression-free survival (PFS) outcomes, with mut patients exhibiting a better prognosis (93.8% OS, at 24 months), whereas the p53abn having a worse survival time (68.9% of OS, at 24 months).

CONCLUSION

We reported for the first time the Brazilian profile of the ProMisE classification of endometrial cancer and demonstrated the prognostic impact of the traditional and molecular ProMisE classification on patient outcomes.