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      Clinical implications of prospective genomic profiling of metastatic breast cancer patients

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          Abstract

          Background

          Metastatic breast cancer remains incurable. Next-generation sequencing (NGS) offers the ability to identify actionable genomic alterations in tumours which may then be matched with targeted therapies, but the implementation and utility of this approach is not well defined for patients with metastatic breast cancer.

          Methods

          We recruited patients with advanced breast cancer of any subtype for prospective targeted NGS of their most recent tumour samples, using a panel of 108 breast cancer-specific genes. Genes were classified as actionable or non-actionable using the European Society of Medical Oncology Scale for Clinical Actionability of Molecular Targets (ESCAT) guidelines.

          Results

          Between February 2014 and May 2019, 322 patients were enrolled onto the study, with 72% ( n = 234) of patients successfully sequenced ( n = 357 samples). The majority (74%, n = 171) of sequenced patients were found to carry a potentially actionable alteration, the most common being a PIK3CA mutation. Forty-three percent ( n = 74) of patients with actionable alterations were referred for a clinical trial or referred for confirmatory germline testing or had a change in therapy outside of clinical trials. We found alterations in AKT1, BRCA2, CHEK2, ESR1, FGFR1, KMT2C, NCOR1, PIK3CA and TSC2 to be significantly enriched in our metastatic population compared with primary breast cancers. Concordance between primary and metastatic samples for key driver genes ( TP53, ERBB2 amplification) was > 75%. Additionally, we found that patients with a higher number of mutations had a significantly worse overall survival.

          Conclusion

          Genomic profiling of patients with metastatic breast cancer can have clinical implications and should be considered in all suitable patients.

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          Most cited references14

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          Molecular and cellular heterogeneity in breast cancer: challenges for personalized medicine.

          Breast cancer is noted for disparate clinical behaviors and patient outcomes, despite common histopathological features at diagnosis. Molecular pathogenesis studies suggest that breast cancer is a collection of diseases with variable molecular underpinnings that modulate therapeutic responses, disease-free intervals, and long-term survival. Traditional therapeutic strategies for individual patients are guided by the expression status of the estrogen and progesterone receptors (ER and PR) and human epidermal growth factor receptor 2 (HER2). Although such methods for clinical classification have utility in selection of targeted therapies, short-term patient responses and long-term survival remain difficult to predict. Molecular signatures of breast cancer based on complex gene expression patterns have utility in prediction of long-term patient outcomes, but are not yet used for guiding therapy. Examination of the correspondence between these methods for breast cancer classification reveals a lack of agreement affecting a significant percentage of cases. To realize true personalized breast cancer therapy, a more complete analysis and evaluation of the molecular characteristics of the disease in the individual patient is required, together with an understanding of the contributions of specific genetic and epigenetic alterations (and their combinations) to management of the patient. Here, we discuss the molecular and cellular heterogeneity of breast cancer, the impact of this heterogeneity on practical breast cancer classification, and the challenges for personalized breast cancer treatment. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
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            Tumour-infiltrating lymphocytes in advanced HER2-positive breast cancer treated with pertuzumab or placebo in addition to trastuzumab and docetaxel: a retrospective analysis of the CLEOPATRA study.

            High quantities of tumour-infiltrating lymphocytes (TILs) in primary HER2-positive breast cancer are associated with improved prognosis and response to therapy. We aimed to investigate the prognostic role of host antitumour immunity as represented by baseline quantities of TILs in patients with advanced HER2-positive breast cancer treated with either pertuzumab or placebo in addition to trastuzumab and docetaxel.
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              CopywriteR: DNA copy number detection from off-target sequence data

              Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we present CopywriteR, which eludes these problems by exploiting ‘off-target’ sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. CopywriteR outperforms existing methods and constitutes a widely applicable alternative to available tools. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0617-1) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                sherene.loi@petermac.org
                Journal
                Breast Cancer Res
                Breast Cancer Res
                Breast Cancer Research : BCR
                BioMed Central (London )
                1465-5411
                1465-542X
                18 August 2020
                18 August 2020
                2020
                : 22
                : 91
                Affiliations
                [1 ]GRID grid.1055.1, ISNI 0000000403978434, Division of Research, , Peter MacCallum Cancer Centre, ; Melbourne, Australia
                [2 ]GRID grid.1055.1, ISNI 0000000403978434, Department of Medical Oncology, , Peter MacCallum Cancer Centre, ; Melbourne, Australia
                [3 ]Australian Centre for Disease Preparedness, Commonwealth Scientific and Industrial Research Organisation (CSIRO) Health and Biosecurity, Geelong, Australia
                [4 ]GRID grid.1055.1, ISNI 0000000403978434, Department of Pathology, , Peter MacCallum Cancer Centre, ; Melbourne, Australia
                [5 ]GRID grid.1008.9, ISNI 0000 0001 2179 088X, Sir Peter MacCallum Department of Oncology, , University of Melbourne, ; 305 Grattan St, Melbourne, VIC 3000 Australia
                Author information
                http://orcid.org/0000-0001-6137-9171
                Article
                1328
                10.1186/s13058-020-01328-0
                7436992
                32811538
                7f0def05-8b00-451b-bbd9-9a624c688658
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 11 May 2020
                : 10 August 2020
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Oncology & Radiotherapy
                breast cancer,metastasis,genomic profiling,personalised medicine
                Oncology & Radiotherapy
                breast cancer, metastasis, genomic profiling, personalised medicine

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