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Path to Clonal Theranostics in Luminal Breast Cancers

Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostic...

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Autores principales: Hajjaji, Nawale, Aboulouard, Soulaimane, Cardon, Tristan, Bertin, Delphine, Robin, Yves-Marie, Fournier, Isabelle, Salzet, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8793283/
https://www.ncbi.nlm.nih.gov/pubmed/35096604
http://dx.doi.org/10.3389/fonc.2021.802177
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author Hajjaji, Nawale
Aboulouard, Soulaimane
Cardon, Tristan
Bertin, Delphine
Robin, Yves-Marie
Fournier, Isabelle
Salzet, Michel
author_facet Hajjaji, Nawale
Aboulouard, Soulaimane
Cardon, Tristan
Bertin, Delphine
Robin, Yves-Marie
Fournier, Isabelle
Salzet, Michel
author_sort Hajjaji, Nawale
collection PubMed
description Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString(®)) and CDx (Foundation One(®)). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.
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spelling pubmed-87932832022-01-28 Path to Clonal Theranostics in Luminal Breast Cancers Hajjaji, Nawale Aboulouard, Soulaimane Cardon, Tristan Bertin, Delphine Robin, Yves-Marie Fournier, Isabelle Salzet, Michel Front Oncol Oncology Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString(®)) and CDx (Foundation One(®)). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs. Frontiers Media S.A. 2022-01-13 /pmc/articles/PMC8793283/ /pubmed/35096604 http://dx.doi.org/10.3389/fonc.2021.802177 Text en Copyright © 2022 Hajjaji, Aboulouard, Cardon, Bertin, Robin, Fournier and Salzet https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Hajjaji, Nawale
Aboulouard, Soulaimane
Cardon, Tristan
Bertin, Delphine
Robin, Yves-Marie
Fournier, Isabelle
Salzet, Michel
Path to Clonal Theranostics in Luminal Breast Cancers
title Path to Clonal Theranostics in Luminal Breast Cancers
title_full Path to Clonal Theranostics in Luminal Breast Cancers
title_fullStr Path to Clonal Theranostics in Luminal Breast Cancers
title_full_unstemmed Path to Clonal Theranostics in Luminal Breast Cancers
title_short Path to Clonal Theranostics in Luminal Breast Cancers
title_sort path to clonal theranostics in luminal breast cancers
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8793283/
https://www.ncbi.nlm.nih.gov/pubmed/35096604
http://dx.doi.org/10.3389/fonc.2021.802177
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