Development and validation of a RNAseq signature for prognostic stratification in endometrial cancer

Guillaume Beinse (1, 2) , Marie-Aude Le Frere Belda (2) , Pierre-Alexandre Just (2, 3) , Nahina Bekmezian (2, 3) , Meriem Koual (2, 3) , Simon Garinet (2, 1) , Karen Leroy (2, 3) , Franck Letourneur (4, 5) , Adèle Lusson (2) , Claire Mulot (1, 6) , Delphine Le Corre (1) , Marie Metairie (1) , Nicolas Delanoy (2) , Helene Blons (2) , Claire Gervais (2, 3) , Catherine Durdux (2, 3) , Charles Chapron (2, 3) , François Goldwasser (2) , Benoit Terris (2, 3) , Cecile Badoual (2, 3) , Valerie Taly (1) , Pierre Laurent-Puig (2, 1) , Bruno Borghese (2, 1) , Anne-Sophie Bats (2, 1) , Jérôme Alexandre (2, 1)

1 CRC (UMR_S_1138 / U1138) - Centre de Recherche des Cordeliers
2 SIRIC CARPEM - Cancer Research and Personalized Medicine - CARPEM [Paris]
3 UPCité - Université Paris Cité
4 IC UM3 (UMR 8104 / U1016) - Institut Cochin
5 GENOM'IC - Plateforme de genomique
6 Epigenetec

Background: Despite recent advances in endometrial carcinoma (EC) molecular characterization, its prognostication remains challenging. We aimed to assess whether RNAseq could stratify EC patient prognosis beyond current classification systems.Methods: A prognostic signature was identified using a LASSO-penalized Cox model trained on TCGA (N = 543 patients). A clinically applicable polyA-RNAseq-based work-flow was developed for validation of the signature in a cohort of stage I-IV patients treated in two Hospitals [2010-2017]. Model performances were evaluated using time-dependent ROC curves (prediction of disease-specific-survival (DSS)). The additional value of the RNAseq signature was evaluated by multivariable Cox model, adjusted on high-risk prognostic group (2021 ESGO-ESTRO-ESP guidelines: non-endometrioid histology or stage III-IVA orTP53-mutated molecular subgroup).Results: Among 209 patients included in the external validation cohort, 61 (30%), 10 (5%), 52 (25%), and 82 (40%), had mismatch repair-deficient, POLE-mutated, TP53-mutated tumors, and tumors with no specific molecular profile, respectively. The 38-genes signature accurately predicted DSS (AUC = 0.80). Most disease-related deaths occurred in high-risk patients (5-years DSS = 78% (95% CI = [68%-89%]) versus 99% [97%-100%] in patients without high-risk). A composite classifier accounting for the TP53-mutated subgroup and the RNAseq signature identified three classes independently associated with DSS: RNAseq-good prognosis (reference, 5-years DSS = 99%), non-TP53 tumors but with RNAseq-poor prognosis (adjusted-hazard ratio (aHR) = 5.75, 95% CI[1.14-29.0]), and TP53-mutated subgroup (aHR = 5.64 [1.12-28.3]). The model accounting for the high-risk group and the composite classifier predicted DSS with AUC = 0.84, versus AUC = 0.76 without (p = 0.01).Conclusion: RNA-seq profiling can provide an additional prognostic information to established classification systems, and warrants validation for potential RNAseq-based therapeutic strategies in EC.

Mots clés: Endometrial carcinoma; Molecular characterization; Personalized medicine; Prognostic stratification; Transcriptome analysis

Domaines: Cancer

Guillaume Beinse, Marie-Aude Le Frere Belda, Pierre-Alexandre Just, Nahina Bekmezian, Meriem Koual, et al.. Development and validation of a RNAseq signature for prognostic stratification in endometrial cancer. Gynecologic Oncology, 2022, 164 (3), pp.596-606. ⟨10.1016/j.ygyno.2022.01.005⟩. ⟨inserm-03857908⟩