Cargando…

Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer

BACKGROUND: While the efficacy of neoadjuvant chemotherapy (NACT) in treating triple-negative breast cancer (TNBC) is generally accepted, not all patients derive benefit from this preoperative treatment. Presently, there are no validated biomarkers to predict the NACT response, and previous attempts...

Descripción completa

Detalles Bibliográficos
Autores principales: Omar, Mohamed, Nuzzo, Pier Vitale, Ravera, Francesco, Bleve, Sara, Fanelli, Giuseppe Nicolò, Zanettini, Claudio, Valencia, Itzel, Marchionni, Luigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647131/
https://www.ncbi.nlm.nih.gov/pubmed/37964363
http://dx.doi.org/10.1186/s12967-023-04713-3
_version_ 1785147507957825536
author Omar, Mohamed
Nuzzo, Pier Vitale
Ravera, Francesco
Bleve, Sara
Fanelli, Giuseppe Nicolò
Zanettini, Claudio
Valencia, Itzel
Marchionni, Luigi
author_facet Omar, Mohamed
Nuzzo, Pier Vitale
Ravera, Francesco
Bleve, Sara
Fanelli, Giuseppe Nicolò
Zanettini, Claudio
Valencia, Itzel
Marchionni, Luigi
author_sort Omar, Mohamed
collection PubMed
description BACKGROUND: While the efficacy of neoadjuvant chemotherapy (NACT) in treating triple-negative breast cancer (TNBC) is generally accepted, not all patients derive benefit from this preoperative treatment. Presently, there are no validated biomarkers to predict the NACT response, and previous attempts to develop predictive classifiers based on gene expression data have not demonstrated clinical utility. However, predictive models incorporating biological constraints have shown increased robustness and improved performance compared to agnostic classifiers. METHODS: We used the preoperative transcriptomic profiles from 298 patients with TNBC to train and test a rank-based classifier, k-top scoring pairs, to predict whether the patient will have pathological complete response (pCR) or residual disease (RD) following NACT. To reduce overfitting and enhance the signature’s interpretability, we constrained the training process to genes involved in the Notch signaling pathway. Subsequently, we evaluated the signature performance on two independent cohorts with 75 and 71 patients. Finally, we assessed the prognostic value of the signature by examining its association with relapse-free survival (RFS) using Kaplan‒Meier (KM) survival estimates and a multivariate Cox proportional hazards model. RESULTS: The final signature consists of five gene pairs, whose relative ordering can be predictive of the NACT response. The signature has a robust performance at predicting pCR in TNBC patients with an area under the ROC curve (AUC) of 0.76 and 0.85 in the first and second testing cohorts, respectively, outperforming other gene signatures developed for the same purpose. Additionally, the signature was significantly associated with RFS in an independent TNBC patient cohort even after adjusting for T stage, patient age at the time of diagnosis, type of breast surgery, and menopausal status. CONCLUSION: We introduce a robust gene signature to predict pathological complete response (pCR) in patients with TNBC. This signature applies easily interpretable, rank-based decision rules to genes regulated by the Notch signaling pathway, a known determinant in breast cancer chemoresistance. The robust predictive and prognostic performance of the signature make it a strong candidate for clinical implementation, aiding in the stratification of TNBC patients undergoing NACT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04713-3.
format Online
Article
Text
id pubmed-10647131
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-106471312023-11-15 Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer Omar, Mohamed Nuzzo, Pier Vitale Ravera, Francesco Bleve, Sara Fanelli, Giuseppe Nicolò Zanettini, Claudio Valencia, Itzel Marchionni, Luigi J Transl Med Research BACKGROUND: While the efficacy of neoadjuvant chemotherapy (NACT) in treating triple-negative breast cancer (TNBC) is generally accepted, not all patients derive benefit from this preoperative treatment. Presently, there are no validated biomarkers to predict the NACT response, and previous attempts to develop predictive classifiers based on gene expression data have not demonstrated clinical utility. However, predictive models incorporating biological constraints have shown increased robustness and improved performance compared to agnostic classifiers. METHODS: We used the preoperative transcriptomic profiles from 298 patients with TNBC to train and test a rank-based classifier, k-top scoring pairs, to predict whether the patient will have pathological complete response (pCR) or residual disease (RD) following NACT. To reduce overfitting and enhance the signature’s interpretability, we constrained the training process to genes involved in the Notch signaling pathway. Subsequently, we evaluated the signature performance on two independent cohorts with 75 and 71 patients. Finally, we assessed the prognostic value of the signature by examining its association with relapse-free survival (RFS) using Kaplan‒Meier (KM) survival estimates and a multivariate Cox proportional hazards model. RESULTS: The final signature consists of five gene pairs, whose relative ordering can be predictive of the NACT response. The signature has a robust performance at predicting pCR in TNBC patients with an area under the ROC curve (AUC) of 0.76 and 0.85 in the first and second testing cohorts, respectively, outperforming other gene signatures developed for the same purpose. Additionally, the signature was significantly associated with RFS in an independent TNBC patient cohort even after adjusting for T stage, patient age at the time of diagnosis, type of breast surgery, and menopausal status. CONCLUSION: We introduce a robust gene signature to predict pathological complete response (pCR) in patients with TNBC. This signature applies easily interpretable, rank-based decision rules to genes regulated by the Notch signaling pathway, a known determinant in breast cancer chemoresistance. The robust predictive and prognostic performance of the signature make it a strong candidate for clinical implementation, aiding in the stratification of TNBC patients undergoing NACT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04713-3. BioMed Central 2023-11-15 /pmc/articles/PMC10647131/ /pubmed/37964363 http://dx.doi.org/10.1186/s12967-023-04713-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Omar, Mohamed
Nuzzo, Pier Vitale
Ravera, Francesco
Bleve, Sara
Fanelli, Giuseppe Nicolò
Zanettini, Claudio
Valencia, Itzel
Marchionni, Luigi
Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer
title Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer
title_full Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer
title_fullStr Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer
title_full_unstemmed Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer
title_short Notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer
title_sort notch-based gene signature for predicting the response to neoadjuvant chemotherapy in triple-negative breast cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10647131/
https://www.ncbi.nlm.nih.gov/pubmed/37964363
http://dx.doi.org/10.1186/s12967-023-04713-3
work_keys_str_mv AT omarmohamed notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer
AT nuzzopiervitale notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer
AT raverafrancesco notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer
AT blevesara notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer
AT fanelligiuseppenicolo notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer
AT zanettiniclaudio notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer
AT valenciaitzel notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer
AT marchionniluigi notchbasedgenesignatureforpredictingtheresponsetoneoadjuvantchemotherapyintriplenegativebreastcancer