Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

Background: The incidence of endometrial cancer is increasing worldwide. While delays in diagnosis reduce survival, case molecular misclassification might be associated with under- and over-treatment. The objective of this study was to evaluate genetic alterations to detect and molecularly classify...

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Autores: Pelegrina, Beatriz, Paytubi, Sonia, Marin, Fátima, Martínez, José Manuel, Carmona, Álvaro, Frias-Gómez, Jon, Peremiquel-Trillas, Paula, Dorca, Eduard, Zanca, Alba, López-Querol, Marta, Onieva, Irene, Benavente, Yolanda, Barahona, Marc, Fernández-González, Sergi, De Francisco, Javier, Caño, Victor, Vidal, August, Pijuan, Lara, Canet-Hermida, Júlia, Dueñas, Núria, Brunet, Joan, Pineda, Marta, Matias-Guiu, Xavier, Ponce, Jordi, Bosch, Francesc Xavier, De Sanjosé, Silvia, Alemany, Laia, Costas, Laura
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad Loyola Andalucía
Repositorio:Brújula
OAI Identifier:oai:repositorio.uloyola.es:20.500.12412/7039
Acceso en línea:https://hdl.handle.net/20.500.12412/7039
Access Level:acceso abierto
Palabra clave:Biomarkers
Early detection of cancer
Endometrial neoplasms
Mutation
Papanicolaou
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network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
title Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
spellingShingle Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
Pelegrina, Beatriz
Biomarkers
Early detection of cancer
Endometrial neoplasms
Mutation
Papanicolaou
title_short Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
title_full Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
title_fullStr Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
title_full_unstemmed Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
title_sort Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer
dc.creator.none.fl_str_mv Pelegrina, Beatriz
Paytubi, Sonia
Marin, Fátima
Martínez, José Manuel
Carmona, Álvaro
Frias-Gómez, Jon
Peremiquel-Trillas, Paula
Dorca, Eduard
Zanca, Alba
López-Querol, Marta
Onieva, Irene
Benavente, Yolanda
Barahona, Marc
Fernández-González, Sergi
De Francisco, Javier
Caño, Victor
Vidal, August
Pijuan, Lara
Canet-Hermida, Júlia
Dueñas, Núria
Brunet, Joan
Pineda, Marta
Matias-Guiu, Xavier
Ponce, Jordi
Bosch, Francesc Xavier
De Sanjosé, Silvia
Alemany, Laia
Costas, Laura
author Pelegrina, Beatriz
author_facet Pelegrina, Beatriz
Paytubi, Sonia
Marin, Fátima
Martínez, José Manuel
Carmona, Álvaro
Frias-Gómez, Jon
Peremiquel-Trillas, Paula
Dorca, Eduard
Zanca, Alba
López-Querol, Marta
Onieva, Irene
Benavente, Yolanda
Barahona, Marc
Fernández-González, Sergi
De Francisco, Javier
Caño, Victor
Vidal, August
Pijuan, Lara
Canet-Hermida, Júlia
Dueñas, Núria
Brunet, Joan
Pineda, Marta
Matias-Guiu, Xavier
Ponce, Jordi
Bosch, Francesc Xavier
De Sanjosé, Silvia
Alemany, Laia
Costas, Laura
author_role author
author2 Paytubi, Sonia
Marin, Fátima
Martínez, José Manuel
Carmona, Álvaro
Frias-Gómez, Jon
Peremiquel-Trillas, Paula
Dorca, Eduard
Zanca, Alba
López-Querol, Marta
Onieva, Irene
Benavente, Yolanda
Barahona, Marc
Fernández-González, Sergi
De Francisco, Javier
Caño, Victor
Vidal, August
Pijuan, Lara
Canet-Hermida, Júlia
Dueñas, Núria
Brunet, Joan
Pineda, Marta
Matias-Guiu, Xavier
Ponce, Jordi
Bosch, Francesc Xavier
De Sanjosé, Silvia
Alemany, Laia
Costas, Laura
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Biomarkers
Early detection of cancer
Endometrial neoplasms
Mutation
Papanicolaou
topic Biomarkers
Early detection of cancer
Endometrial neoplasms
Mutation
Papanicolaou
description Background: The incidence of endometrial cancer is increasing worldwide. While delays in diagnosis reduce survival, case molecular misclassification might be associated with under- and over-treatment. The objective of this study was to evaluate genetic alterations to detect and molecularly classify cases of endometrial cancer using non-invasive samples. Methods: Consecutive patients with incident endometrial cancer (N = 139) and controls (N = 107) from a recent Spanish case-control study were included in this analysis. Overall, 339 cervicovaginal samples (out of which 228 were clinician-collected and 111 were self-collected) were analysed using a test based on next-generation sequencing (NGS), which targets 47 genes. Immunohistochemical markers were evaluated in 133 tumour samples. A total of 159 samples were used to train the detection algorithm and 180 samples were used for validation. Findings: Overall, 73% (N = 94 out of 129 clinician-collected samples, and N = 66 out of 90 self-collected samples) of endometrial cancer cases had detectable mutations in clinician-collected and self-collected samples, while the specificity was 80% (79/99) for clinician-collected samples and 90% (19/21) for self-collected samples. The molecular classifications obtained using tumour samples and non-invasive gynaecologic samples in our study showed moderate-to-good agreement. The molecular classification of cases of endometrial cancer into four groups using NGS of both clinician-collected and self-collected cervicovaginal samples yielded significant differences in disease-free survival. The cases with mutations in POLE had an excellent prognosis, whereas the cases with TP53 mutations had the poorest clinical outcome, which is consistent with the data on tumour samples. Interpretation: This study classified endometrial cancer cases into four molecular groups based on the analysis of cervicovaginal samples that showed significant differences in disease-free survival. The molecular classification of endometrial cancer in non-invasive samples may improve patient care and survival by indicating the early need for aggressive surgery, as well as reducing referrals to highly specialized hospitals in cancers with good prognosis. Validation in independent sets will confirm the potential for molecular classification in non-invasive samples. Funding: This study was funded by a competitive grant from Instituto de Salud Carlos III through the projects PI19/01835, PI23/00790, and FI20/00031, CIBERESP CB06/02/0073 and CIBERONC CB16/12/00231, CB16/12/00234 (Co-funded by European Regional Development Fund. ERDF: A way to build Europe). Samples and data were provided by Biobank HUB-ICO-IDIBELL, integrated into the Spanish Biobank Network, and funded by the Instituto de Salud Carlos III (PT20/00171) and by Xarxa de Bancs de Tumors de Catalunya (XBTC) sponsored by Pla Director d'Oncologia de Catalunya. This work was supported in part by the AECC, Grupos estables (GCTRA18014MATI). It also counts with the support of the Secretariat for Universities and Research of the Department of Business and Knowledge of the Generalitat de Catalunya, and grants to support the activities of research groups 2021SGR01354 and 2021SGR1112.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.12412/7039
url https://hdl.handle.net/20.500.12412/7039
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Brújula
instname:Universidad Loyola Andalucía
instname_str Universidad Loyola Andalucía
reponame_str Brújula
collection Brújula
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869404339141869568
spelling Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancerPelegrina, BeatrizPaytubi, SoniaMarin, FátimaMartínez, José ManuelCarmona, ÁlvaroFrias-Gómez, JonPeremiquel-Trillas, PaulaDorca, EduardZanca, AlbaLópez-Querol, MartaOnieva, IreneBenavente, YolandaBarahona, MarcFernández-González, SergiDe Francisco, JavierCaño, VictorVidal, AugustPijuan, LaraCanet-Hermida, JúliaDueñas, NúriaBrunet, JoanPineda, MartaMatias-Guiu, XavierPonce, JordiBosch, Francesc XavierDe Sanjosé, SilviaAlemany, LaiaCostas, LauraBiomarkersEarly detection of cancerEndometrial neoplasmsMutationPapanicolaouBackground: The incidence of endometrial cancer is increasing worldwide. While delays in diagnosis reduce survival, case molecular misclassification might be associated with under- and over-treatment. The objective of this study was to evaluate genetic alterations to detect and molecularly classify cases of endometrial cancer using non-invasive samples. Methods: Consecutive patients with incident endometrial cancer (N = 139) and controls (N = 107) from a recent Spanish case-control study were included in this analysis. Overall, 339 cervicovaginal samples (out of which 228 were clinician-collected and 111 were self-collected) were analysed using a test based on next-generation sequencing (NGS), which targets 47 genes. Immunohistochemical markers were evaluated in 133 tumour samples. A total of 159 samples were used to train the detection algorithm and 180 samples were used for validation. Findings: Overall, 73% (N = 94 out of 129 clinician-collected samples, and N = 66 out of 90 self-collected samples) of endometrial cancer cases had detectable mutations in clinician-collected and self-collected samples, while the specificity was 80% (79/99) for clinician-collected samples and 90% (19/21) for self-collected samples. The molecular classifications obtained using tumour samples and non-invasive gynaecologic samples in our study showed moderate-to-good agreement. The molecular classification of cases of endometrial cancer into four groups using NGS of both clinician-collected and self-collected cervicovaginal samples yielded significant differences in disease-free survival. The cases with mutations in POLE had an excellent prognosis, whereas the cases with TP53 mutations had the poorest clinical outcome, which is consistent with the data on tumour samples. Interpretation: This study classified endometrial cancer cases into four molecular groups based on the analysis of cervicovaginal samples that showed significant differences in disease-free survival. The molecular classification of endometrial cancer in non-invasive samples may improve patient care and survival by indicating the early need for aggressive surgery, as well as reducing referrals to highly specialized hospitals in cancers with good prognosis. Validation in independent sets will confirm the potential for molecular classification in non-invasive samples. Funding: This study was funded by a competitive grant from Instituto de Salud Carlos III through the projects PI19/01835, PI23/00790, and FI20/00031, CIBERESP CB06/02/0073 and CIBERONC CB16/12/00231, CB16/12/00234 (Co-funded by European Regional Development Fund. ERDF: A way to build Europe). Samples and data were provided by Biobank HUB-ICO-IDIBELL, integrated into the Spanish Biobank Network, and funded by the Instituto de Salud Carlos III (PT20/00171) and by Xarxa de Bancs de Tumors de Catalunya (XBTC) sponsored by Pla Director d'Oncologia de Catalunya. This work was supported in part by the AECC, Grupos estables (GCTRA18014MATI). It also counts with the support of the Secretariat for Universities and Research of the Department of Business and Knowledge of the Generalitat de Catalunya, and grants to support the activities of research groups 2021SGR01354 and 2021SGR1112.2023info:eu-repo/semantics/articlehttps://hdl.handle.net/20.500.12412/7039reponame:Brújulainstname:Universidad Loyola AndalucíaIngléshttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uloyola.es:20.500.12412/70392026-06-24T12:48:37Z
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