Cargando…

Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture

To improve the success rate of current preclinical drug trials, there is a growing need for more complex and relevant models that can help predict clinical resistance to anticancer agents. Here, we present a three‐dimensional (3D) technology, based on biomimetic collagen scaffolds, that enables the...

Descripción completa

Detalles Bibliográficos
Autores principales: Liverani, Chiara, De Vita, Alessandro, Spadazzi, Chiara, Miserocchi, Giacomo, Cocchi, Claudia, Bongiovanni, Alberto, De Lucia, Anna, La Manna, Federico, Fabbri, Francesco, Tebaldi, Michela, Amadori, Dino, Tasciotti, Ennio, Martinelli, Giovanni, Mercatali, Laura, Ibrahim, Toni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847989/
https://www.ncbi.nlm.nih.gov/pubmed/34109737
http://dx.doi.org/10.1002/1878-0261.13037
_version_ 1784652158127308800
author Liverani, Chiara
De Vita, Alessandro
Spadazzi, Chiara
Miserocchi, Giacomo
Cocchi, Claudia
Bongiovanni, Alberto
De Lucia, Anna
La Manna, Federico
Fabbri, Francesco
Tebaldi, Michela
Amadori, Dino
Tasciotti, Ennio
Martinelli, Giovanni
Mercatali, Laura
Ibrahim, Toni
author_facet Liverani, Chiara
De Vita, Alessandro
Spadazzi, Chiara
Miserocchi, Giacomo
Cocchi, Claudia
Bongiovanni, Alberto
De Lucia, Anna
La Manna, Federico
Fabbri, Francesco
Tebaldi, Michela
Amadori, Dino
Tasciotti, Ennio
Martinelli, Giovanni
Mercatali, Laura
Ibrahim, Toni
author_sort Liverani, Chiara
collection PubMed
description To improve the success rate of current preclinical drug trials, there is a growing need for more complex and relevant models that can help predict clinical resistance to anticancer agents. Here, we present a three‐dimensional (3D) technology, based on biomimetic collagen scaffolds, that enables the modeling of the tumor hypoxic state and the prediction of in vivo chemotherapy responses in terms of efficacy, molecular alterations, and emergence of resistance mechanisms. The human breast cancer cell lines MDA‐MB‐231 (triple negative) and MCF‐7 (luminal A) were treated with scaling doses of doxorubicin in monolayer cultures, 3D collagen scaffolds, or orthotopically transplanted murine models. Lineage‐specific resistance mechanisms were revealed by the 3D tumor model. Reduced drug uptake, increased drug efflux, and drug lysosomal confinement were observed in triple‐negative MDA‐MB‐231 cells. In luminal A MCF‐7 cells, the selection of a drug‐resistant subline from parental cells with deregulation of p53 pathways occurred. These cells were demonstrated to be insensitive to DNA damage. Transcriptome analysis was carried out to identify differentially expressed genes (DEGs) in treated cells. DEG evaluation in breast cancer patients demonstrated their potential role as predictive biomarkers. High expression of the transporter associated with antigen processing 1 (TAP1) and the tumor protein p53‐inducible protein 3 (TP53I3) was associated with shorter relapse in patients affected by ER(+) breast tumor. Likewise, the same clinical outcome was associated with high expression of the lysosomal‐associated membrane protein 1 LAMP1 in triple‐negative breast cancer. Hypoxia inhibition by resveratrol treatment was found to partially re‐sensitize cells to doxorubicin treatment. Our model might improve preclinical in vitro analysis for the translation of anticancer compounds as it provides: (a) more accurate data on drug efficacy and (b) enhanced understanding of resistance mechanisms and molecular drivers.
format Online
Article
Text
id pubmed-8847989
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-88479892022-02-25 Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture Liverani, Chiara De Vita, Alessandro Spadazzi, Chiara Miserocchi, Giacomo Cocchi, Claudia Bongiovanni, Alberto De Lucia, Anna La Manna, Federico Fabbri, Francesco Tebaldi, Michela Amadori, Dino Tasciotti, Ennio Martinelli, Giovanni Mercatali, Laura Ibrahim, Toni Mol Oncol Research Articles To improve the success rate of current preclinical drug trials, there is a growing need for more complex and relevant models that can help predict clinical resistance to anticancer agents. Here, we present a three‐dimensional (3D) technology, based on biomimetic collagen scaffolds, that enables the modeling of the tumor hypoxic state and the prediction of in vivo chemotherapy responses in terms of efficacy, molecular alterations, and emergence of resistance mechanisms. The human breast cancer cell lines MDA‐MB‐231 (triple negative) and MCF‐7 (luminal A) were treated with scaling doses of doxorubicin in monolayer cultures, 3D collagen scaffolds, or orthotopically transplanted murine models. Lineage‐specific resistance mechanisms were revealed by the 3D tumor model. Reduced drug uptake, increased drug efflux, and drug lysosomal confinement were observed in triple‐negative MDA‐MB‐231 cells. In luminal A MCF‐7 cells, the selection of a drug‐resistant subline from parental cells with deregulation of p53 pathways occurred. These cells were demonstrated to be insensitive to DNA damage. Transcriptome analysis was carried out to identify differentially expressed genes (DEGs) in treated cells. DEG evaluation in breast cancer patients demonstrated their potential role as predictive biomarkers. High expression of the transporter associated with antigen processing 1 (TAP1) and the tumor protein p53‐inducible protein 3 (TP53I3) was associated with shorter relapse in patients affected by ER(+) breast tumor. Likewise, the same clinical outcome was associated with high expression of the lysosomal‐associated membrane protein 1 LAMP1 in triple‐negative breast cancer. Hypoxia inhibition by resveratrol treatment was found to partially re‐sensitize cells to doxorubicin treatment. Our model might improve preclinical in vitro analysis for the translation of anticancer compounds as it provides: (a) more accurate data on drug efficacy and (b) enhanced understanding of resistance mechanisms and molecular drivers. John Wiley and Sons Inc. 2021-07-10 2022-02 /pmc/articles/PMC8847989/ /pubmed/34109737 http://dx.doi.org/10.1002/1878-0261.13037 Text en © 2021 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Liverani, Chiara
De Vita, Alessandro
Spadazzi, Chiara
Miserocchi, Giacomo
Cocchi, Claudia
Bongiovanni, Alberto
De Lucia, Anna
La Manna, Federico
Fabbri, Francesco
Tebaldi, Michela
Amadori, Dino
Tasciotti, Ennio
Martinelli, Giovanni
Mercatali, Laura
Ibrahim, Toni
Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture
title Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture
title_full Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture
title_fullStr Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture
title_full_unstemmed Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture
title_short Lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3D biomimetic culture
title_sort lineage‐specific mechanisms and drivers of breast cancer chemoresistance revealed by 3d biomimetic culture
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847989/
https://www.ncbi.nlm.nih.gov/pubmed/34109737
http://dx.doi.org/10.1002/1878-0261.13037
work_keys_str_mv AT liveranichiara lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT devitaalessandro lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT spadazzichiara lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT miserocchigiacomo lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT cocchiclaudia lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT bongiovannialberto lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT deluciaanna lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT lamannafederico lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT fabbrifrancesco lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT tebaldimichela lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT amadoridino lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT tasciottiennio lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT martinelligiovanni lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT mercatalilaura lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture
AT ibrahimtoni lineagespecificmechanismsanddriversofbreastcancerchemoresistancerevealedby3dbiomimeticculture