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      The role of infiltrating lymphocytes in the neo-adjuvant treatment of women with HER2-positive breast cancer

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          Abstract

          Background

          Pre-treatment tumour-associated lymphocytes (TILs) and stromal lymphocytes (SLs) are independent predictive markers of future pathological complete response (pCR) in HER2-positive breast cancer. Whilst studies have correlated baseline lymphocyte levels with subsequent pCR, few have studied the impact of neoadjuvant therapy on the immune environment.

          Methods

          We performed TIL analysis and T-cell analysis by IHC on the pretreatment and ‘On-treatment’ samples from patients recruited on the Phase-II TCHL (NCT01485926) clinical trial. Data were analysed using the Wilcoxon signed-rank test and the Spearman rank correlation.

          Results

          In our sample cohort ( n = 66), patients who achieved a pCR at surgery, post-chemotherapy, had significantly higher counts of TILs ( p = 0.05) but not SLs ( p = 0.08) in their pre-treatment tumour samples. Patients who achieved a subsequent pCR after completing neo-adjuvant chemotherapy had significantly higher SLs ( p = 9.09 × 10 –3) but not TILs ( p = 0.1) in their ‘On-treatment’ tumour biopsies. In a small cohort of samples ( n = 16), infiltrating lymphocyte counts increased after 1 cycle of neo-adjuvant chemotherapy only in those tumours of patients who did not achieve a subsequent pCR. Finally, reduced CD3 + ( p = 0.04, rho = 0.60) and CD4 + ( p = 0.01, rho = 0.72) T-cell counts in 'On-treatment' biopsies were associated with decreased residual tumour content post-1 cycle of treatment; the latter being significantly associated with increased likelihood of subsequent pCR ( p < 0.01).

          Conclusions

          The immune system may be ‘primed’ prior to neoadjuvant treatment in those patients who subsequently achieve a pCR. In those patients who achieve a pCR, their immune response may return to baseline after only 1 cycle of treatment. However, in those who did not achieve a pCR, neo-adjuvant treatment may stimulate lymphocyte influx into the tumour.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s10549-021-06244-1.

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          Most cited references30

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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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            Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression

            We introduce the Microenvironment Cell Populations-counter (MCP-counter) method, which allows the robust quantification of the absolute abundance of eight immune and two stromal cell populations in heterogeneous tissues from transcriptomic data. We present in vitro mRNA mixture and ex vivo immunohistochemical data that quantitatively support the validity of our method’s estimates. Additionally, we demonstrate that MCP-counter overcomes several limitations or weaknesses of previously proposed computational approaches. MCP-counter is applied to draw a global picture of immune infiltrates across human healthy tissues and non-hematopoietic human tumors and recapitulates microenvironment-based patient stratifications associated with overall survival in lung adenocarcinoma and colorectal and breast cancer. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1070-5) contains supplementary material, which is available to authorized users.
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              Immune checkpoint inhibitors: recent progress and potential biomarkers

              Cancer growth and progression are associated with immune suppression. Cancer cells have the ability to activate different immune checkpoint pathways that harbor immunosuppressive functions. Monoclonal antibodies that target immune checkpoints provided an immense breakthrough in cancer therapeutics. Among the immune checkpoint inhibitors, PD-1/PD-L1 and CTLA-4 inhibitors showed promising therapeutic outcomes, and some have been approved for certain cancer treatments, while others are under clinical trials. Recent reports have shown that patients with various malignancies benefit from immune checkpoint inhibitor treatment. However, mainstream initiation of immune checkpoint therapy to treat cancers is obstructed by the low response rate and immune-related adverse events in some cancer patients. This has given rise to the need for developing sets of biomarkers that predict the response to immune checkpoint blockade and immune-related adverse events. In this review, we discuss different predictive biomarkers for anti-PD-1/PD-L1 and anti-CTLA-4 inhibitors, including immune cells, PD-L1 overexpression, neoantigens, and genetic and epigenetic signatures. Potential approaches for further developing highly reliable predictive biomarkers should facilitate patient selection for and decision-making related to immune checkpoint inhibitor-based therapies.
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                Author and article information

                Contributors
                alex.eustace@dcu.ie
                Journal
                Breast Cancer Res Treat
                Breast Cancer Res Treat
                Breast Cancer Research and Treatment
                Springer US (New York )
                0167-6806
                1573-7217
                13 May 2021
                13 May 2021
                2021
                : 187
                : 3
                : 635-645
                Affiliations
                [1 ]GRID grid.15596.3e, ISNI 0000000102380260, National Institute for Cellular Biotechnology, Dublin City University, ; Dublin, Ireland
                [2 ]GRID grid.4912.e, ISNI 0000 0004 0488 7120, Data Science Centre, , Royal College of Surgeons in Ireland, ; Dublin, Ireland
                [3 ]GRID grid.4912.e, ISNI 0000 0004 0488 7120, Department of Histopathology, , Royal College of Surgeons in Ireland, ; Dublin, Ireland
                [4 ]GRID grid.4912.e, ISNI 0000 0004 0488 7120, Department of Surgery, , Royal College of Surgeons in Ireland, ; Dublin, Ireland
                [5 ]GRID grid.4912.e, ISNI 0000 0004 0488 7120, Department of Physiology, , Royal College of Surgeons in Ireland, ; Dublin, Ireland
                [6 ]GRID grid.7886.1, ISNI 0000 0001 0768 2743, Conway Institute, University College Dublin, ; Dublin, Ireland
                [7 ]GRID grid.414315.6, ISNI 0000 0004 0617 6058, Department of Medical Oncology, , Beaumont Hospital, ; Dublin, Ireland
                [8 ]GRID grid.476092.e, Cancer Trials Ireland, ; Dublin, Ireland
                [9 ]GRID grid.412751.4, ISNI 0000 0001 0315 8143, Department of Medical Oncology, , St Vincent’s University Hospital, ; Dublin, Ireland
                [10 ]GRID grid.414315.6, ISNI 0000 0004 0617 6058, Department of Radiology, , Beaumont Hospital, ; Dublin, Ireland
                [11 ]GRID grid.414315.6, ISNI 0000 0004 0617 6058, Cancer Clinical Trials and Research Unit, , Beaumont Hospital, ; Dublin, Ireland
                [12 ]GRID grid.4912.e, ISNI 0000 0004 0488 7120, Medical Oncology Group, Department of Molecular Medicine, , Royal College of Surgeons in Ireland, ; Dublin, Ireland
                Author information
                http://orcid.org/0000-0002-4092-1360
                Article
                6244
                10.1007/s10549-021-06244-1
                8197702
                33983492
                d02b1116-b02c-4e03-a80f-3a04493110fb
                © The Author(s) 2021

                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/.

                History
                : 16 May 2020
                : 22 April 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001593, Irish Cancer Society;
                Award ID: CCRC13GAL
                Funded by: NECRET
                Funded by: Dublin City University
                Categories
                Preclinical Study
                Custom metadata
                © Springer Science+Business Media, LLC, part of Springer Nature 2021

                Oncology & Radiotherapy
                her2-positive breast cancer,tumour infiltrating lymphocytes,t-cells,neo-adjuvant treatment

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