Prognostic role of transcription factor in patients with endometrial cancer of no specific molecular profile (NSMP) subtype.

Objective: As more than 50% of newly diagnosed endometrial cancers remain classified as 'no specific molecular subtype' (NSMP) due to a lack of established biomarkers to further improve molecular subtyping, this study aims to evaluate the prognostic value of in endometrial cancers of NSMP subtype.

Methods: Prospectively collected molecular profiling data of all consecutive patients with endometrial cancer who underwent primary surgery at our department between August 2017 and June 2022 and for whom both molecular profiling and clinical follow-up data were available were retrospectively evaluated. Tumor specimens were evaluated by combined mismatch repair protein immunohistochemistry and targeted next-generation hotspot sequencing. mutational status, as defined by full-length gene sequencing, was matched with risk of recurrence, progression-free and disease-specific survival within the NSMP cohort.

Results: A total of 127 patients with endometrial cancer were included. Among 72 patients with tumors of NSMP subtype (56.7%), mutations were identified in 24 cases (33.3%). mutations were significantly associated with a higher risk of recurrence (37.5% vs 12.5%, OR 4.20, 95% CI 1.28 to 13.80, p=0.018) and impaired progression-free survival (HR 3.96, 95% CI 1.41 to 11.15, p=0.009), but not with disease-specific survival. The results for both risk of recurrence (OR 3.70, 95% CI 1.04 to 13.13, p=0.043) and progression-free survival (HR 3.19, 95% CI 1.10 to 9.25, p=0.033) were confirmed in multivariable analysis compared with advanced tumor stage International Federation of Gynecology and Obstetrics (2009) (FIGO ≥III) and impaired Eastern Clinical Oncology Group performance status (ECOG ≥1).

Conclusion: appears to identify patients with endometrial cancer of NSMP subtypes with a higher risk of recurrence and could be used as a future prognostic biomarker. After clinical validation, assessment could help to further sub-classify selected endometrial cancers and improve personalized treatment strategies.