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Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer
BACKGROUND: Despite treatment advances, there remains a significant risk of recurrence in ovarian cancer, at which stage it is usually incurable. Consequently, there is a clear need for improved patient stratification. However, at present clinical prognosticators remain largely unchanged due to the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838425/ https://www.ncbi.nlm.nih.gov/pubmed/31648981 http://dx.doi.org/10.1016/j.ebiom.2019.10.001 |
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author | Nawaz, Sidra Trahearn, Nicholas A. Heindl, Andreas Banerjee, Susana Maley, Carlo C. Sottoriva, Andrea Yuan, Yinyin |
author_facet | Nawaz, Sidra Trahearn, Nicholas A. Heindl, Andreas Banerjee, Susana Maley, Carlo C. Sottoriva, Andrea Yuan, Yinyin |
author_sort | Nawaz, Sidra |
collection | PubMed |
description | BACKGROUND: Despite treatment advances, there remains a significant risk of recurrence in ovarian cancer, at which stage it is usually incurable. Consequently, there is a clear need for improved patient stratification. However, at present clinical prognosticators remain largely unchanged due to the lack of reproducible methods to identify high-risk patients. METHODS: In high-grade serous ovarian cancer patients with advanced disease, we spatially define a tumour ecological balance of stromal resource and immune hazard using high-throughput image and spatial analysis of routine histology slides. On this basis an EcoScore is developed to classify tumours by a shift in this balance towards cancer-favouring or inhibiting conditions. FINDINGS: The EcoScore provides prognostic value stronger than, and independent of, known risk factors. Crucially, the clinical relevance of mutational burden and genomic instability differ under different stromal resource conditions, suggesting that the selective advantage of these cancer hallmarks is dependent on the context of stromal spatial structure. Under a high resource condition defined by a high level of geographical intermixing of cancer and stromal cells, selection appears to be driven by point mutations; whereas, in low resource tumours featured with high hypoxia and low cancer-immune co-localization, selection is fuelled by aneuploidy. INTERPRETATION: Our study offers empirical evidence that cancer fitness depends on tumour spatial constraints, and presents a biological basis for developing better assessments of tumour adaptive strategies in overcoming ecological constraints including immune surveillance and hypoxia. |
format | Online Article Text |
id | pubmed-6838425 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68384252019-11-12 Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer Nawaz, Sidra Trahearn, Nicholas A. Heindl, Andreas Banerjee, Susana Maley, Carlo C. Sottoriva, Andrea Yuan, Yinyin EBioMedicine Research paper BACKGROUND: Despite treatment advances, there remains a significant risk of recurrence in ovarian cancer, at which stage it is usually incurable. Consequently, there is a clear need for improved patient stratification. However, at present clinical prognosticators remain largely unchanged due to the lack of reproducible methods to identify high-risk patients. METHODS: In high-grade serous ovarian cancer patients with advanced disease, we spatially define a tumour ecological balance of stromal resource and immune hazard using high-throughput image and spatial analysis of routine histology slides. On this basis an EcoScore is developed to classify tumours by a shift in this balance towards cancer-favouring or inhibiting conditions. FINDINGS: The EcoScore provides prognostic value stronger than, and independent of, known risk factors. Crucially, the clinical relevance of mutational burden and genomic instability differ under different stromal resource conditions, suggesting that the selective advantage of these cancer hallmarks is dependent on the context of stromal spatial structure. Under a high resource condition defined by a high level of geographical intermixing of cancer and stromal cells, selection appears to be driven by point mutations; whereas, in low resource tumours featured with high hypoxia and low cancer-immune co-localization, selection is fuelled by aneuploidy. INTERPRETATION: Our study offers empirical evidence that cancer fitness depends on tumour spatial constraints, and presents a biological basis for developing better assessments of tumour adaptive strategies in overcoming ecological constraints including immune surveillance and hypoxia. Elsevier 2019-10-21 /pmc/articles/PMC6838425/ /pubmed/31648981 http://dx.doi.org/10.1016/j.ebiom.2019.10.001 Text en © 2019 The Authors http://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 | Research paper Nawaz, Sidra Trahearn, Nicholas A. Heindl, Andreas Banerjee, Susana Maley, Carlo C. Sottoriva, Andrea Yuan, Yinyin Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer |
title | Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer |
title_full | Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer |
title_fullStr | Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer |
title_full_unstemmed | Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer |
title_short | Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer |
title_sort | analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer |
topic | Research paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838425/ https://www.ncbi.nlm.nih.gov/pubmed/31648981 http://dx.doi.org/10.1016/j.ebiom.2019.10.001 |
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