Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Pelegrina, Beatriz, Paytubi, Sonia, Marin, Fátima, Martínez, José Manuel, Carmona, Álvaro, Frias-Gomez, Jon, Peremiquel-Trillas, Paula, Dorca, Eduard, Zanca, Alba, López-Querol, Marta, Onieva, Irene, Benavente, Yolanda, Barahona, Marc, Fernandez-Gonzalez, Sergi, De Francisco, Javier, Caño, Víctor, 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393602/
https://www.ncbi.nlm.nih.gov/pubmed/37480623
http://dx.doi.org/10.1016/j.ebiom.2023.104716
_version_ 1785083196106342400
author Pelegrina, Beatriz
Paytubi, Sonia
Marin, Fátima
Martínez, José Manuel
Carmona, Álvaro
Frias-Gomez, Jon
Peremiquel-Trillas, Paula
Dorca, Eduard
Zanca, Alba
López-Querol, Marta
Onieva, Irene
Benavente, Yolanda
Barahona, Marc
Fernandez-Gonzalez, Sergi
De Francisco, Javier
Caño, Víctor
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_facet Pelegrina, Beatriz
Paytubi, Sonia
Marin, Fátima
Martínez, José Manuel
Carmona, Álvaro
Frias-Gomez, Jon
Peremiquel-Trillas, Paula
Dorca, Eduard
Zanca, Alba
López-Querol, Marta
Onieva, Irene
Benavente, Yolanda
Barahona, Marc
Fernandez-Gonzalez, Sergi
De Francisco, Javier
Caño, Víctor
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_sort Pelegrina, Beatriz
collection PubMed
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 10.13039/501100004587Instituto 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 10.13039/501100008530European 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 10.13039/501100004587Instituto de Salud Carlos III (PT20/00171) and by 10.13039/501100014540Xarxa 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 10.13039/501100002809Generalitat de Catalunya, and grants to support the activities of research groups 2021SGR01354 and 2021SGR1112.
format Online
Article
Text
id pubmed-10393602
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-103936022023-08-03 Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer Pelegrina, Beatriz Paytubi, Sonia Marin, Fátima Martínez, José Manuel Carmona, Álvaro Frias-Gomez, Jon Peremiquel-Trillas, Paula Dorca, Eduard Zanca, Alba López-Querol, Marta Onieva, Irene Benavente, Yolanda Barahona, Marc Fernandez-Gonzalez, Sergi De Francisco, Javier Caño, Víctor 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 eBioMedicine Articles 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 10.13039/501100004587Instituto 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 10.13039/501100008530European 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 10.13039/501100004587Instituto de Salud Carlos III (PT20/00171) and by 10.13039/501100014540Xarxa 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 10.13039/501100002809Generalitat de Catalunya, and grants to support the activities of research groups 2021SGR01354 and 2021SGR1112. Elsevier 2023-07-20 /pmc/articles/PMC10393602/ /pubmed/37480623 http://dx.doi.org/10.1016/j.ebiom.2023.104716 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles
Pelegrina, Beatriz
Paytubi, Sonia
Marin, Fátima
Martínez, José Manuel
Carmona, Álvaro
Frias-Gomez, Jon
Peremiquel-Trillas, Paula
Dorca, Eduard
Zanca, Alba
López-Querol, Marta
Onieva, Irene
Benavente, Yolanda
Barahona, Marc
Fernandez-Gonzalez, Sergi
De Francisco, Javier
Caño, Víctor
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
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
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_short 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
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393602/
https://www.ncbi.nlm.nih.gov/pubmed/37480623
http://dx.doi.org/10.1016/j.ebiom.2023.104716
work_keys_str_mv AT pelegrinabeatriz evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT paytubisonia evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT marinfatima evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT martinezjosemanuel evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT carmonaalvaro evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT friasgomezjon evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT peremiqueltrillaspaula evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT dorcaeduard evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT zancaalba evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT lopezquerolmarta evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT onievairene evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT benaventeyolanda evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT barahonamarc evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT fernandezgonzalezsergi evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT defranciscojavier evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT canovictor evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT vidalaugust evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT pijuanlara evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT canethermidajulia evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT duenasnuria evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT brunetjoan evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT pinedamarta evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT matiasguiuxavier evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT poncejordi evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT boschfrancescxavier evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT desanjosesilvia evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT alemanylaia evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer
AT costaslaura evaluationofsomaticmutationsincervicovaginalsamplesasanoninvasivemethodforthedetectionandmolecularclassificationofendometrialcancer