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Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts

Cancer cells grow in highly complex stromal microenvironments, which through metabolic remodelling, catabolism, autophagy and inflammation nurture them and are able to facilitate metastasis and resistance to therapy. However, these changes in the metabolic profile of stromal cancer-associated fibrob...

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Autores principales: Peiris-Pagès, Maria, Smith, Duncan L., Győrffy, Balázs, Sotgia, Federica, Lisanti, Michael P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4637208/
https://www.ncbi.nlm.nih.gov/pubmed/26539730
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author Peiris-Pagès, Maria
Smith, Duncan L.
Győrffy, Balázs
Sotgia, Federica
Lisanti, Michael P.
author_facet Peiris-Pagès, Maria
Smith, Duncan L.
Győrffy, Balázs
Sotgia, Federica
Lisanti, Michael P.
author_sort Peiris-Pagès, Maria
collection PubMed
description Cancer cells grow in highly complex stromal microenvironments, which through metabolic remodelling, catabolism, autophagy and inflammation nurture them and are able to facilitate metastasis and resistance to therapy. However, these changes in the metabolic profile of stromal cancer-associated fibroblasts and their impact on cancer initiation, progression and metastasis are not well-known. This is the first study to provide a comprehensive proteomic portrait of the azathioprine and taxol-induced catabolic state on human stromal fibroblasts, which comprises changes in the expression of metabolic enzymes, myofibroblastic differentiation markers, antioxidants, proteins involved in autophagy, senescence, vesicle trafficking and protein degradation, and inducers of inflammation. Interestingly, many of these features are major contributors to the aging process. A catabolic stroma signature, generated with proteins found differentially up-regulated in taxol-treated fibroblasts, strikingly correlates with recurrence, metastasis and poor patient survival in several solid malignancies. We therefore suggest the inhibition of the catabolic state in healthy cells as a novel approach to improve current chemotherapy efficacies and possibly avoid future carcinogenic processes.
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spelling pubmed-46372082015-12-11 Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts Peiris-Pagès, Maria Smith, Duncan L. Győrffy, Balázs Sotgia, Federica Lisanti, Michael P. Aging (Albany NY) Research Paper Cancer cells grow in highly complex stromal microenvironments, which through metabolic remodelling, catabolism, autophagy and inflammation nurture them and are able to facilitate metastasis and resistance to therapy. However, these changes in the metabolic profile of stromal cancer-associated fibroblasts and their impact on cancer initiation, progression and metastasis are not well-known. This is the first study to provide a comprehensive proteomic portrait of the azathioprine and taxol-induced catabolic state on human stromal fibroblasts, which comprises changes in the expression of metabolic enzymes, myofibroblastic differentiation markers, antioxidants, proteins involved in autophagy, senescence, vesicle trafficking and protein degradation, and inducers of inflammation. Interestingly, many of these features are major contributors to the aging process. A catabolic stroma signature, generated with proteins found differentially up-regulated in taxol-treated fibroblasts, strikingly correlates with recurrence, metastasis and poor patient survival in several solid malignancies. We therefore suggest the inhibition of the catabolic state in healthy cells as a novel approach to improve current chemotherapy efficacies and possibly avoid future carcinogenic processes. Impact Journals LLC 2015-10-23 /pmc/articles/PMC4637208/ /pubmed/26539730 Text en Copyright: © 2015 Peiris-Pagès etal. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Peiris-Pagès, Maria
Smith, Duncan L.
Győrffy, Balázs
Sotgia, Federica
Lisanti, Michael P.
Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts
title Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts
title_full Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts
title_fullStr Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts
title_full_unstemmed Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts
title_short Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts
title_sort proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4637208/
https://www.ncbi.nlm.nih.gov/pubmed/26539730
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