Molecular classification improves preoperative risk assessment of endometrial cancer

Silvia Cabrera; Vicente Bebia; Carlos López-Gil; Ana Luzarraga-Aznar; Melek Denizli; Lourdes Salazar-Huayna; Nihed Abdessayed; Josep Castellví; Eva Colas; Antonio Gil-Moreno

doi:10.1016/j.ygyno.2024.07.003

Molecular classification improves preoperative risk assessment of endometrial cancer

Silvia Cabrera^*, Vicente Bebia, Carlos López-Gil, Ana Luzarraga-Aznar, Melek Denizli, Lourdes Salazar-Huayna, Nihed Abdessayed, Josep Castellví, Eva Colas, Antonio Gil-Moreno

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Objective: Ens vam proposar avaluar el rendiment de la classificació molecular del càncer d'endometri per predir malalties extrauterines després de la cirurgia primària en solitari i en combinació amb altres dades clíniques disponibles abans de l'operació. Mètodes: Estudi observacional unicèntric retrospectiu que va incloure pacients amb adenocarcinoma endometrial tractats amb cirurgia primària entre desembre del 1994 i maig del 2022. Es van fer perfils moleculars usant immunohistoquímica de p53, MLH1, PMS2, MSH2 i MSH6; i genotipificació KASP de les 6 mutacions més comunes del gen POLE. Es va revisar la informació clínica, patològica i d'imatges. Es van fer tècniques de regressió logística, arbres de regressió i classificació aleatòria (CART). Resultats: Vam inscriure a 658 pacients, 47 amb tumors ECMut (7.1%), 234 amb MMRd (35.6%), 95 amb p53abn (14.4%) i 282 amb NSMP (42.8%). Es va diagnosticar malaltia extrauterina després de la cirurgia primària en l'11,7% dels pacients; els tumors ECMut van mostrar una major disseminació extrauterina (34.1%) i afectació ganglionar (30.1%) (p < .001). En anàlisi multivariada, només el subgrup p53abn (aOR = 16.0, CI95% = 1.5-165.1) i la sospita radiològica de malaltia extrauterina (aOR = 24.2, CI95% = 12.2-48.2) van predir independentment el diagnòstic de malaltia extrauterina després de la cirurgia primària. En pacients amb malaltia uterina confinada preoperativa, l'afectació profunda del miometri i cervical en l'avaluació radiològica i el subtipus molecular p53abn van ser les millors variables per identificar els pacients en risc d'ocultació extrauterina després de la cirurgia. Conclusió: La classificació molecular EC és més precisa que l'histotip o grau en biòpsies preoperatives per predir malaltia avançada, i juntament amb proves radiològiques són la informació preoperatòria més fiable. Aquest treball proporciona un marc inicial per a l'ús d'informació molecular preoperativa per adaptar el tractament quirúrgic

Idioma original	Anglès
Pàgines (de-a)	56-63
Nombre de pàgines	8
Revista	Gynecologic Oncology
Volum	189
DOIs	https://doi.org/10.1016/j.ygyno.2024.07.003
Estat de la publicació	Publicada - d’oct. 2024

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10.1016/j.ygyno.2024.07.003

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@article{8a71b1c3a987488586249d81912f7b1b,

title = "Molecular classification improves preoperative risk assessment of endometrial cancer",

abstract = "Objective: We aimed to evaluate the performance of endometrial cancer (EC) molecular classification in predicting extrauterine disease after primary surgery alone and in combination with other clinical data available in preoperative setting. Methods: Retrospective single-center observational study including patients with endometrial adenocarcinoma treated with primary surgery between December 1994 and May 2022. Molecular profiling was performed using immunohistochemistry of p53, MLH1, PMS2, MSH2 and MSH6; and KASP genotyping of the 6 most common mutations of POLE gene. Clinical, pathological and imaging information was reviewed. Logistic regression, regression trees and random forest classification techniques (CART) were performed. Results: We enrolled 658 patients, 47 with POLEmut (7.1\%), 234 with MMRd (35.6\%), 95 with p53abn (14.4\%) and 282 with NSMP (42.8\%) tumors. Advanced stage after primary surgery (III-IV FIGO 2009) was diagnosed in 11.7\% of patients, p53abn tumors showed increased extrauterine spread (34.1\%) and nodal involvement (30.1\%) (p < .001). In multivariate analysis, only p53abn subgroup (aOR = 16.0, CI95\% = 1.5–165.1) and radiological suspicion of extrauterine disease (aOR = 24.2, CI95\% = 12.2–48.2) independently predicted the finding of extrauterine disease after primary surgery. In patients with preoperative uterine-confined disease, deep myometrial and cervical involvement in radiological assessment and p53abn molecular subtype were the best variables to identify patients at-risk of occult extrauterine disease after the staging surgery. Conclusion: EC molecular classification is more accurate than histotype or grade in preoperative biopsy to predict advanced disease, and together with imaging tests are the most reliable preoperative information. This work provides an initial framework for using molecular information preoperatively to tailor surgical treatment.",

keywords = "Endometrial cancer, Extrauterine disease, Molecular classification, Preoperative assessment, Surgery",

author = "Silvia Cabrera and Vicente Bebia and Carlos L{\'o}pez-Gil and Ana Luzarraga-Aznar and Melek Denizli and Lourdes Salazar-Huayna and Nihed Abdessayed and Josep Castellv{\'i} and Eva Colas and Antonio Gil-Moreno",

note = "Publisher Copyright: {\textcopyright} 2024 Elsevier Inc.",

year = "2024",

month = oct,

doi = "10.1016/j.ygyno.2024.07.003",

language = "English",

volume = "189",

pages = "56--63",

journal = "Gynecologic Oncology",

issn = "0090-8258",

publisher = "Academic Press Inc.",

}

TY - JOUR

T1 - Molecular classification improves preoperative risk assessment of endometrial cancer

AU - Cabrera, Silvia

AU - Bebia, Vicente

AU - López-Gil, Carlos

AU - Luzarraga-Aznar, Ana

AU - Denizli, Melek

AU - Salazar-Huayna, Lourdes

AU - Abdessayed, Nihed

AU - Castellví, Josep

AU - Colas, Eva

AU - Gil-Moreno, Antonio

PY - 2024/10

Y1 - 2024/10

N2 - Objective: We aimed to evaluate the performance of endometrial cancer (EC) molecular classification in predicting extrauterine disease after primary surgery alone and in combination with other clinical data available in preoperative setting. Methods: Retrospective single-center observational study including patients with endometrial adenocarcinoma treated with primary surgery between December 1994 and May 2022. Molecular profiling was performed using immunohistochemistry of p53, MLH1, PMS2, MSH2 and MSH6; and KASP genotyping of the 6 most common mutations of POLE gene. Clinical, pathological and imaging information was reviewed. Logistic regression, regression trees and random forest classification techniques (CART) were performed. Results: We enrolled 658 patients, 47 with POLEmut (7.1%), 234 with MMRd (35.6%), 95 with p53abn (14.4%) and 282 with NSMP (42.8%) tumors. Advanced stage after primary surgery (III-IV FIGO 2009) was diagnosed in 11.7% of patients, p53abn tumors showed increased extrauterine spread (34.1%) and nodal involvement (30.1%) (p < .001). In multivariate analysis, only p53abn subgroup (aOR = 16.0, CI95% = 1.5–165.1) and radiological suspicion of extrauterine disease (aOR = 24.2, CI95% = 12.2–48.2) independently predicted the finding of extrauterine disease after primary surgery. In patients with preoperative uterine-confined disease, deep myometrial and cervical involvement in radiological assessment and p53abn molecular subtype were the best variables to identify patients at-risk of occult extrauterine disease after the staging surgery. Conclusion: EC molecular classification is more accurate than histotype or grade in preoperative biopsy to predict advanced disease, and together with imaging tests are the most reliable preoperative information. This work provides an initial framework for using molecular information preoperatively to tailor surgical treatment.

AB - Objective: We aimed to evaluate the performance of endometrial cancer (EC) molecular classification in predicting extrauterine disease after primary surgery alone and in combination with other clinical data available in preoperative setting. Methods: Retrospective single-center observational study including patients with endometrial adenocarcinoma treated with primary surgery between December 1994 and May 2022. Molecular profiling was performed using immunohistochemistry of p53, MLH1, PMS2, MSH2 and MSH6; and KASP genotyping of the 6 most common mutations of POLE gene. Clinical, pathological and imaging information was reviewed. Logistic regression, regression trees and random forest classification techniques (CART) were performed. Results: We enrolled 658 patients, 47 with POLEmut (7.1%), 234 with MMRd (35.6%), 95 with p53abn (14.4%) and 282 with NSMP (42.8%) tumors. Advanced stage after primary surgery (III-IV FIGO 2009) was diagnosed in 11.7% of patients, p53abn tumors showed increased extrauterine spread (34.1%) and nodal involvement (30.1%) (p < .001). In multivariate analysis, only p53abn subgroup (aOR = 16.0, CI95% = 1.5–165.1) and radiological suspicion of extrauterine disease (aOR = 24.2, CI95% = 12.2–48.2) independently predicted the finding of extrauterine disease after primary surgery. In patients with preoperative uterine-confined disease, deep myometrial and cervical involvement in radiological assessment and p53abn molecular subtype were the best variables to identify patients at-risk of occult extrauterine disease after the staging surgery. Conclusion: EC molecular classification is more accurate than histotype or grade in preoperative biopsy to predict advanced disease, and together with imaging tests are the most reliable preoperative information. This work provides an initial framework for using molecular information preoperatively to tailor surgical treatment.

KW - Endometrial cancer

KW - Extrauterine disease

KW - Molecular classification

KW - Preoperative assessment

KW - Surgery

UR - https://www.scopus.com/pages/publications/85198524901

U2 - 10.1016/j.ygyno.2024.07.003

DO - 10.1016/j.ygyno.2024.07.003

M3 - Article

C2 - 39018900

AN - SCOPUS:85198524901

SN - 0090-8258

VL - 189

SP - 56

EP - 63

JO - Gynecologic Oncology

JF - Gynecologic Oncology

ER -

Molecular classification improves preoperative risk assessment of endometrial cancer

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