A novel algorithm to implement the molecular classification according to the new ESGO/ESTRO/ESP 2020 guidelines for endometrial cancer.

Endometrial Neoplasms Pathology

Journal

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society
ISSN: 1525-1438
Titre abrégé: Int J Gynecol Cancer
Pays: England
ID NLM: 9111626

Informations de publication

Date de publication:
22 Jun 2022
Historique:
entrez: 22 6 2022
pubmed: 23 6 2022
medline: 23 6 2022
Statut: aheadofprint

Résumé

To compare the risk class attribution with We conducted a retrospective study including all consecutive patients with endometrial cancer undergoing surgery and comprehensive molecular analyses between April 2019 and December 2021. Molecular analyses including immunohistochemistry for p53 and mismatch repair (MMR) proteins, and DNA sequencing for POLE exonuclease domain were performed to classify tumors as POLE-mutated (POLE), MMR-deficient (MMR-d), p53 abnormal (p53abn), or non-specific molecular profile (NSMP). The two risk classifications of the ESGO/ESTRO/ESP 2020 guidelines were compared to estimate the proportion of patients in which the molecular analysis was able to change the risk class attribution. We developed a novel algorithm where the molecular analyses are reserved only for patients in whom incorporation of the molecular classification could change the risk class attribution. A total of 278 patients were included. Molecular analyses were successful for all cases, identifying the four subgroups: 27 (9.7%) POLE, 77 (27.7%) MMR-d, 49 (17.6%) p53abn, and 125 (45.0%) NSMP. Comparison of risk class attribution between the two classification systems demonstrated discordance in the risk class assignment in 19 (6.8%, 95% CI 4.2% to 10.5%) cases. The application of our novel algorithm would have led to a reduction in the number of POLE sequencing tests by 67% (95% CI 61% to 73%) and a decrease of p53 immunohistochemistry by 27% (95% CI 22% to 33%), as compared with the application of molecular classification to all patients. Molecular categorization of endometrial cancer allows the reallocation of a considerable proportion of patients in a different risk class. Furthermore, the application of our algorithm enables a reduction in the number of required tests without affecting the risk classification.

Identifiants

pubmed: 35732351
pii: ijgc-2022-003480
doi: 10.1136/ijgc-2022-003480
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© IGCS and ESGO 2022. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Ilaria Betella (I)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy ilaria.betella@ieo.it.

Caterina Fumagalli (C)

Clinical Unit of Oncogenomics, European Institute of Oncology (IEO), IRCCS, Milan, Italy.
Department of Diagnostic Services, Division of Pathology, Azienda Socio Sanitaria Territoriale della Valle Olona, Gallarate, Italy.

Paola Rafaniello Raviele (P)

Department of Pathology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Gabriella Schivardi (G)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.
Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, New York, USA.

Luigi Antonio De Vitis (LA)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Maria Teresa Achilarre (MT)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Alessia Aloisi (A)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Annalisa Garbi (A)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Matteo Maruccio (M)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Vanna Zanagnolo (V)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Giovanni Aletti (G)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.
Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy.

Elena Guerini-Rocco (E)

Department of Pathology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.
Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy.

Andrea Mariani (A)

Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, New York, USA.

Angelo Maggioni (A)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Massimo Barberis (M)

Department of Pathology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Nicoletta Colombo (N)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.
Faculty of Medicine and Surgery, Universita degli Studi di Milano-Bicocca, Milan, Italy.

Francesco Multinu (F)

Department of Gynecology, European Institute of Oncology (IEO), IRCCS, Milan, Italy.

Classifications MeSH