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      Multiplexed immunofluorescence identifies high stromal CD68 +PD-L1 + macrophages as a predictor of improved survival in triple negative breast cancer

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          Abstract

          Triple negative breast cancer (TNBC) comprises 10–15% of all breast cancers and has a poor prognosis with a high risk of recurrence within 5 years. PD-L1 is an important biomarker for patient selection for immunotherapy but its cellular expression and co-localization within the tumour immune microenvironment and associated prognostic value is not well defined. We aimed to characterise the phenotypes of immune cells expressing PD-L1 and determine their association with overall survival (OS) and breast cancer-specific survival (BCSS). Using tissue microarrays from a retrospective cohort of TNBC patients from St George Hospital, Sydney (n = 244), multiplexed immunofluorescence (mIF) was used to assess staining for CD3, CD8, CD20, CD68, PD-1, PD-L1, FOXP3 and pan-cytokeratin on the Vectra Polaris™ platform and analysed using QuPath. Cox multivariate analyses showed high CD68 +PD-L1 + stromal cell counts were associated with improved prognosis for OS (HR 0.56, 95% CI 0.33–0.95, p = 0.030) and BCSS (HR 0.47, 95% CI 0.25–0.88, p = 0.018) in the whole cohort and in patients receiving chemotherapy, improving incrementally upon the predictive value of PD-L1 + alone for BCSS. These data suggest that CD68 +PD-L1 + status can provide clinically useful prognostic information to identify sub-groups of patients with good or poor prognosis and guide treatment decisions in TNBC.

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          QuPath: Open source software for digital pathology image analysis

          QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath’s flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.
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            Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer

            Unresectable locally advanced or metastatic triple-negative (hormone-receptor-negative and human epidermal growth factor receptor 2 [HER2]-negative) breast cancer is an aggressive disease with poor outcomes. Nanoparticle albumin-bound (nab)-paclitaxel may enhance the anticancer activity of atezolizumab.
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              Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies.

              Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem-like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted "driver" signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
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                Author and article information

                Contributors
                ewan.millar@health.nsw.gov.au
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                3 November 2021
                3 November 2021
                2021
                : 11
                : 21608
                Affiliations
                [1 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, St George and Sutherland Clinical School, , University of New South Wales Sydney, ; Kensington, Australia
                [2 ]GRID grid.416398.1, ISNI 0000 0004 0417 5393, Cancer Care Centre, , St George Hospital, ; Kogarah, Australia
                [3 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, Biomedical Imaging Facility, Mark Wainwright Analytical Centre, , University of New South Wales Sydney, ; Kensington, Australia
                [4 ]GRID grid.10784.3a, ISNI 0000 0004 1937 0482, Department of Clinical Oncology, Prince of Wales Hospital, , Chinese University of Hong Kong, ; Shatin, Hong Kong
                [5 ]GRID grid.416398.1, ISNI 0000 0004 0417 5393, Department of Anatomical Pathology, New South Wales Health Pathology, , St George Hospital, ; Kogarah, Australia
                [6 ]GRID grid.1029.a, ISNI 0000 0000 9939 5719, Faculty of Medicine and Health Sciences, , Western Sydney University, ; Campbelltown, Australia
                [7 ]GRID grid.117476.2, ISNI 0000 0004 1936 7611, University of Technology, ; Sydney, Australia
                Article
                1116
                10.1038/s41598-021-01116-6
                8566595
                34732817
                6fbe05cf-b79d-4768-976e-c140e2ca19f6
                © The Author(s) 2021

                Open Access This 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/.

                History
                : 9 August 2021
                : 15 October 2021
                Categories
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                Custom metadata
                © The Author(s) 2021

                Uncategorized
                cancer,immunology,biomarkers,medical research,oncology
                Uncategorized
                cancer, immunology, biomarkers, medical research, oncology

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