Cargando…

Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models?

Genomics has greatly increased the understanding of the study of breast cancer (BC) and has shaped the concept of intra-tumor heterogeneity, currently recognized as a propelling force for cancer progression. In this context, knowledge and understanding of metastatic breast cancer (mBC) has somehow l...

Descripción completa

Detalles Bibliográficos
Autores principales: Cioce, Mario, Sacconi, Andrea, Donzelli, Sara, Bonomo, Claudia, Perracchio, Letizia, Carosi, Mariantonia, Telera, Stefano, Fazio, Vito Michele, Botti, Claudio, Strano, Sabrina, Blandino, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355905/
https://www.ncbi.nlm.nih.gov/pubmed/35983233
http://dx.doi.org/10.1016/j.csbj.2022.07.044
_version_ 1784763399556562944
author Cioce, Mario
Sacconi, Andrea
Donzelli, Sara
Bonomo, Claudia
Perracchio, Letizia
Carosi, Mariantonia
Telera, Stefano
Fazio, Vito Michele
Botti, Claudio
Strano, Sabrina
Blandino, Giovanni
author_facet Cioce, Mario
Sacconi, Andrea
Donzelli, Sara
Bonomo, Claudia
Perracchio, Letizia
Carosi, Mariantonia
Telera, Stefano
Fazio, Vito Michele
Botti, Claudio
Strano, Sabrina
Blandino, Giovanni
author_sort Cioce, Mario
collection PubMed
description Genomics has greatly increased the understanding of the study of breast cancer (BC) and has shaped the concept of intra-tumor heterogeneity, currently recognized as a propelling force for cancer progression. In this context, knowledge and understanding of metastatic breast cancer (mBC) has somehow lagged behind that of primary breast cancer. This may be explained by the relative scarcity of matched mBC samples, however it is possible that the mutation spectrum obtained from primary BC does not capture the full complexity of the metastatic disease. Here, we provide a few examples supporting this possibility, from public databases. We evoke the need to perform an integrated multi-OMICS characterization of mBC, to obtain a broad understanding of this complex disease, whose evolution cannot be explained solely by genomics. Pertinent to this, we suggest that rather an infrequent use of Patient-Derived –Tumor-Organoids (PDTOs) may be influenced by assuming that the metastatic conditions of PDTOs growth (mPDTOs) should be similar to those of the tissue of origin. We challenge this view by suggesting that the use of “target-organ inspired” growth conditions for mPDTOs, may better fit the emerging knowledge of metastatic disease. Thus, the integrated use of multi-OMICS and of clinically relevant mPDTOs may allow a further understanding of such disease and foster therapeutically relevant advances. We believe that our points may be valid for other solid cancers.
format Online
Article
Text
id pubmed-9355905
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Research Network of Computational and Structural Biotechnology
record_format MEDLINE/PubMed
spelling pubmed-93559052022-08-17 Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models? Cioce, Mario Sacconi, Andrea Donzelli, Sara Bonomo, Claudia Perracchio, Letizia Carosi, Mariantonia Telera, Stefano Fazio, Vito Michele Botti, Claudio Strano, Sabrina Blandino, Giovanni Comput Struct Biotechnol J Review Article Genomics has greatly increased the understanding of the study of breast cancer (BC) and has shaped the concept of intra-tumor heterogeneity, currently recognized as a propelling force for cancer progression. In this context, knowledge and understanding of metastatic breast cancer (mBC) has somehow lagged behind that of primary breast cancer. This may be explained by the relative scarcity of matched mBC samples, however it is possible that the mutation spectrum obtained from primary BC does not capture the full complexity of the metastatic disease. Here, we provide a few examples supporting this possibility, from public databases. We evoke the need to perform an integrated multi-OMICS characterization of mBC, to obtain a broad understanding of this complex disease, whose evolution cannot be explained solely by genomics. Pertinent to this, we suggest that rather an infrequent use of Patient-Derived –Tumor-Organoids (PDTOs) may be influenced by assuming that the metastatic conditions of PDTOs growth (mPDTOs) should be similar to those of the tissue of origin. We challenge this view by suggesting that the use of “target-organ inspired” growth conditions for mPDTOs, may better fit the emerging knowledge of metastatic disease. Thus, the integrated use of multi-OMICS and of clinically relevant mPDTOs may allow a further understanding of such disease and foster therapeutically relevant advances. We believe that our points may be valid for other solid cancers. Research Network of Computational and Structural Biotechnology 2022-07-28 /pmc/articles/PMC9355905/ /pubmed/35983233 http://dx.doi.org/10.1016/j.csbj.2022.07.044 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review Article
Cioce, Mario
Sacconi, Andrea
Donzelli, Sara
Bonomo, Claudia
Perracchio, Letizia
Carosi, Mariantonia
Telera, Stefano
Fazio, Vito Michele
Botti, Claudio
Strano, Sabrina
Blandino, Giovanni
Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models?
title Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models?
title_full Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models?
title_fullStr Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models?
title_full_unstemmed Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models?
title_short Breast cancer metastasis: Is it a matter of OMICS and proper ex-vivo models?
title_sort breast cancer metastasis: is it a matter of omics and proper ex-vivo models?
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355905/
https://www.ncbi.nlm.nih.gov/pubmed/35983233
http://dx.doi.org/10.1016/j.csbj.2022.07.044
work_keys_str_mv AT ciocemario breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT sacconiandrea breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT donzellisara breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT bonomoclaudia breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT perracchioletizia breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT carosimariantonia breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT telerastefano breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT faziovitomichele breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT botticlaudio breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT stranosabrina breastcancermetastasisisitamatterofomicsandproperexvivomodels
AT blandinogiovanni breastcancermetastasisisitamatterofomicsandproperexvivomodels