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The Genomic Landscape of Lobular Breast Cancer

SIMPLE SUMMARY: We present a meta-analysis of invasive lobular carcinoma (ILC) sequencing data to provide a unified resource for ILC research. A large amount of data has been generated, but remains siloed due to the application of different sequencing approaches and limitations around cohort size an...

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Autores principales: McCart Reed, Amy E., Foong, Samuel, Kutasovic, Jamie R., Nones, Katia, Waddell, Nicola, Lakhani, Sunil R., Simpson, Peter T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8073944/
https://www.ncbi.nlm.nih.gov/pubmed/33919581
http://dx.doi.org/10.3390/cancers13081950
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author McCart Reed, Amy E.
Foong, Samuel
Kutasovic, Jamie R.
Nones, Katia
Waddell, Nicola
Lakhani, Sunil R.
Simpson, Peter T.
author_facet McCart Reed, Amy E.
Foong, Samuel
Kutasovic, Jamie R.
Nones, Katia
Waddell, Nicola
Lakhani, Sunil R.
Simpson, Peter T.
author_sort McCart Reed, Amy E.
collection PubMed
description SIMPLE SUMMARY: We present a meta-analysis of invasive lobular carcinoma (ILC) sequencing data to provide a unified resource for ILC research. A large amount of data has been generated, but remains siloed due to the application of different sequencing approaches and limitations around cohort size and clinical annotation. To enact the goals of precision oncology in the field of lobular breast cancer, a substantive reference point is required, which we present herein. Furthermore, with combined datasets, we were able to define the prognostic significance of relevant clinico-pathology features. ABSTRACT: Invasive lobular carcinoma (ILC) is the second most common breast cancer histologic subtype, accounting for approximately 15% of all breast cancers. It is only recently that its unique biology has been assessed in high resolution. Here, we present a meta-analysis of ILC sequencing datasets, to provide a long-awaited ILC-specific resource, and to confirm the prognostic value and strength of association between a number of clinico-pathology features and genomics in this special tumour type. We consider panel (n = 684), whole exome (n = 215) and whole genome sequencing data (n = 48), and review histology of The Cancer Genome Atlas cases to assign grades and determine whether the ILC is of classic type or a variant, such as pleomorphic, prior to performing statistical analyses. We demonstrate evidence of considerable genomic heterogeneity underlying a broadly homogeneous tumour type (typically grade 2, estrogen receptor (ER)-positive); with genomes exhibiting few somatic mutations or structural alterations, genomes with a hypermutator phenotype, and tumours with highly rearranged genomes. We show that while CDH1 (E-cadherin) and PIK3CA mutations do not significantly impact survival, overall survival is significantly poorer for patients with a higher tumour mutation burden; this is also true for grade 3 tumours, and those carrying a somatic TP53 mutation (and these cases were more likely to be ER-negative). Taken together, we have compiled a meta-dataset of ILC with molecular profiling, and our analyses show that the genomic landscape significantly impacts the tumour’s variable natural history and overall survival of ILC patients.
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spelling pubmed-80739442021-04-27 The Genomic Landscape of Lobular Breast Cancer McCart Reed, Amy E. Foong, Samuel Kutasovic, Jamie R. Nones, Katia Waddell, Nicola Lakhani, Sunil R. Simpson, Peter T. Cancers (Basel) Article SIMPLE SUMMARY: We present a meta-analysis of invasive lobular carcinoma (ILC) sequencing data to provide a unified resource for ILC research. A large amount of data has been generated, but remains siloed due to the application of different sequencing approaches and limitations around cohort size and clinical annotation. To enact the goals of precision oncology in the field of lobular breast cancer, a substantive reference point is required, which we present herein. Furthermore, with combined datasets, we were able to define the prognostic significance of relevant clinico-pathology features. ABSTRACT: Invasive lobular carcinoma (ILC) is the second most common breast cancer histologic subtype, accounting for approximately 15% of all breast cancers. It is only recently that its unique biology has been assessed in high resolution. Here, we present a meta-analysis of ILC sequencing datasets, to provide a long-awaited ILC-specific resource, and to confirm the prognostic value and strength of association between a number of clinico-pathology features and genomics in this special tumour type. We consider panel (n = 684), whole exome (n = 215) and whole genome sequencing data (n = 48), and review histology of The Cancer Genome Atlas cases to assign grades and determine whether the ILC is of classic type or a variant, such as pleomorphic, prior to performing statistical analyses. We demonstrate evidence of considerable genomic heterogeneity underlying a broadly homogeneous tumour type (typically grade 2, estrogen receptor (ER)-positive); with genomes exhibiting few somatic mutations or structural alterations, genomes with a hypermutator phenotype, and tumours with highly rearranged genomes. We show that while CDH1 (E-cadherin) and PIK3CA mutations do not significantly impact survival, overall survival is significantly poorer for patients with a higher tumour mutation burden; this is also true for grade 3 tumours, and those carrying a somatic TP53 mutation (and these cases were more likely to be ER-negative). Taken together, we have compiled a meta-dataset of ILC with molecular profiling, and our analyses show that the genomic landscape significantly impacts the tumour’s variable natural history and overall survival of ILC patients. MDPI 2021-04-18 /pmc/articles/PMC8073944/ /pubmed/33919581 http://dx.doi.org/10.3390/cancers13081950 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
McCart Reed, Amy E.
Foong, Samuel
Kutasovic, Jamie R.
Nones, Katia
Waddell, Nicola
Lakhani, Sunil R.
Simpson, Peter T.
The Genomic Landscape of Lobular Breast Cancer
title The Genomic Landscape of Lobular Breast Cancer
title_full The Genomic Landscape of Lobular Breast Cancer
title_fullStr The Genomic Landscape of Lobular Breast Cancer
title_full_unstemmed The Genomic Landscape of Lobular Breast Cancer
title_short The Genomic Landscape of Lobular Breast Cancer
title_sort genomic landscape of lobular breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8073944/
https://www.ncbi.nlm.nih.gov/pubmed/33919581
http://dx.doi.org/10.3390/cancers13081950
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