TY - JOUR
T1 - Development and validation of a RNAseq signature for prognostic stratification in endometrial cancer
AU - Beinse, Guillaume
AU - Le Frere Belda, Marie Aude
AU - Just, Pierre Alexandre
AU - Bekmezian, Nahina
AU - Koual, Meriem
AU - Garinet, Simon
AU - Leroy, Karen
AU - Letourneur, Franck
AU - Lusson, Adèle
AU - Mulot, Claire
AU - Le Corre, Delphine
AU - Metairie, Marie
AU - Delanoy, Nicolas
AU - Blons, Helene
AU - Gervais, Claire
AU - Durdux, Catherine
AU - Chapron, Charles
AU - Goldwasser, François
AU - Terris, Benoit
AU - Badoual, Cecile
AU - Taly, Valerie
AU - Laurent-Puig, Pierre
AU - Borghese, Bruno
AU - Bats, Anne Sophie
AU - Alexandre, Jérôme
N1 - Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/3/1
Y1 - 2022/3/1
N2 - 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.
AB - 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.
KW - Endometrial carcinoma
KW - Molecular characterization
KW - Personalized medicine
KW - Prognostic stratification
KW - Transcriptome analysis
UR - http://www.scopus.com/inward/record.url?scp=85122962964&partnerID=8YFLogxK
U2 - 10.1016/j.ygyno.2022.01.005
DO - 10.1016/j.ygyno.2022.01.005
M3 - Article
C2 - 35033379
AN - SCOPUS:85122962964
SN - 0090-8258
VL - 164
SP - 596
EP - 606
JO - Gynecologic Oncology
JF - Gynecologic Oncology
IS - 3
ER -