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      Progression of Disease Within 24 Months in Follicular Lymphoma Is Associated With Reduced Intratumoral Immune Infiltration

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          Abstract

          PURPOSE

          Understanding the immunobiology of the 15% to 30% of patients with follicular lymphoma (FL) who experience progression of disease within 24 months (POD24) remains a priority. Solid tumors with low levels of intratumoral immune infiltration have inferior outcomes. It is unknown whether a similar relationship exists between POD24 in FL.

          PATIENTS AND METHODS

          Digital gene expression using a custom code set—five immune effector, six immune checkpoint, one macrophage molecules—was applied to a discovery cohort of patients with early- and advanced-stage FL (n = 132). T-cell receptor repertoire analysis, flow cytometry, multispectral immunofluorescence, and next-generation sequencing were performed. The immune infiltration profile was validated in two independent cohorts of patients with advanced-stage FL requiring systemic treatment (n = 138, rituximab plus cyclophosphamide, vincristine, prednisone; n = 45, rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone), with the latter selected to permit comparison of patients experiencing a POD24 event with those having no progression at 5 years or more.

          RESULTS

          Immune molecules showed distinct clustering, characterized by either high or low expression regardless of categorization as an immune effector, immune checkpoint, or macrophage molecule. Low programmed death-ligand 2 (PD-L2) was the most sensitive/specific marker to segregate patients with adverse outcomes; therefore, PD-L2 expression was chosen to distinguish immune infiltration HI (ie, high PD-L2) FL biopsies from immune infiltration LO (ie, low PD-L2) tumors. Immune infiltration HI tissues were highly infiltrated with macrophages and expanded populations of T-cell clones. Of note, the immune infiltration LO subset of patients with FL was enriched for POD24 events (odds ratio [OR], 4.32; c-statistic, 0.81; P = .001), validated in the independent cohorts (rituximab plus cyclophosphamide, vincristine, prednisone: OR, 2.95; c-statistic, 0.75; P = .011; and rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone: OR, 7.09; c-statistic, 0.88; P = .011). Mutations were equally proportioned across tissues, which indicated that degree of immune infiltration is capturing aspects of FL biology distinct from its mutational profile.

          CONCLUSION

          Assessment of immune-infiltration by PD-L2 expression is a promising tool with which to help identify patients who are at risk for POD24.

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          Most cited references46

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          PD-1 blockade induces responses by inhibiting adaptive immune resistance

          Therapies that target the programmed death-1 (PD-1) receptor have shown unprecedented rates of durable clinical responses in patients with various cancer types. 1–5 One mechanism by which cancer tissues limit the host immune response is via upregulation of PD-1 ligand (PD-L1) and its ligation to PD-1 on antigen-specific CD8 T-cells (termed adaptive immune resistance). 6,7 Here we show that pre-existing CD8 T-cells distinctly located at the invasive tumour margin are associated with expression of the PD-1/PD-L1 immune inhibitory axis and may predict response to therapy. We analyzed samples from 46 patients with metastatic melanoma obtained before and during anti-PD1 therapy (pembrolizumab) using quantitative immunohistochemistry, quantitative multiplex immunofluorescence, and next generation sequencing for T-cell receptors (TCR). In serially sampled tumours, responding patients showed proliferation of intratumoural CD8+ T-cells that directly correlated with radiographic reduction in tumour size. Pre-treatment samples obtained from responding patients showed higher numbers of CD8, PD1, and PD-L1 expressing cells at the invasive tumour margin and inside tumours, with close proximity between PD-1 and PD-L1, and a more clonal TCR repertoire. Using multivariate analysis, we established a predictive model based on CD8 expression at the invasive margin and validated the model in an independent cohort of 15 patients. Our findings indicate that tumour regression following therapeutic PD-1 blockade requires pre-existing CD8+ T cells that are negatively regulated by PD-1/PD-L1 mediated adaptive immune resistance.
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            Elements of cancer immunity and the cancer–immune set point

            Immunotherapy is proving to be an effective therapeutic approach in a variety of cancers. But despite the clinical success of antibodies against the immune regulators CTLA4 and PD-L1/PD-1, only a subset of people exhibit durable responses, suggesting that a broader view of cancer immunity is
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              Tumor Cell-Intrinsic Factors Underlie Heterogeneity of Immune Cell Infiltration and Response to Immunotherapy

              The biological and functional heterogeneity between tumors – both across and within cancer types – poses a challenge for immunotherapy. To understand the factors underlying tumor immune heterogeneity and immunotherapy sensitivity, we established a library of congenic tumor cell clones from an autochthonous mouse model of pancreatic adenocarcinoma. These clones generated tumors that recapitulated T-cell-inflamed and non-T-cell-inflamed tumor microenvironments upon implantation in immunocompetent mice, with distinct patterns of infiltration by immune cell subsets. Co-injecting tumor cell clones revealed the non-T-cell-inflamed phenotype is dominant and that both quantitative and qualitative features of intratumoral CD8 + T cells determine response to therapy. Transcriptomic and epigenetic analyses revealed tumor-cell-intrinsic production of the chemokine CXCL1 as a determinant of the non-T-cell-inflamed microenvironment, and ablation of CXCL1 promoted T cell infiltration and sensitivity to a combination immunotherapy regimen. Thus, tumor cell-intrinsic factors shape the tumor immune microenvironment and influence the outcome of immunotherapy.
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                Author and article information

                Journal
                J Clin Oncol
                J. Clin. Oncol
                jco
                jco
                JCO
                Journal of Clinical Oncology
                American Society of Clinical Oncology
                0732-183X
                1527-7755
                1 December 2019
                28 August 2019
                1 December 2020
                : 37
                : 34
                : 3300-3309
                Affiliations
                [ 1 ]Mater Research, University of Queensland, Brisbane, QLD, Australia
                [ 2 ]Princess Alexandra Hospital, Brisbane, QLD, Australia
                [ 3 ]Diamantina Institute, University of Queensland, Brisbane, QLD, Australia
                [ 4 ]Ochsner Health System, New Orleans, LA
                [ 5 ]Princess Margaret Cancer Centre, Toronto, Ontario, Canada
                [ 6 ]Laboratory for Experimental Leukemia and Lymphoma Research, Munich, Germany
                [ 7 ]German Cancer Consortium, Munich Germany
                [ 8 ]German Cancer Research Center, Heidelberg, Germany
                [ 9 ]University Hospital Schleswig-Holstein, Kiel, Germany
                [ 10 ]British Columbia Cancer Agency, Vancouver, British Columbia, Canada
                [ 11 ]Queensland Institute of Medical Research, Brisbane, QLD, Australia
                Author notes
                Maher K. Gandhi, MD, PhD, Level 4, Translational Research Institute, Brisbane, QLD 4102, Australia; Twitter: @MaterResearch; e-mail: maher.gandhi@ 123456mater.uq.edu.au .
                Article
                1802365
                10.1200/JCO.18.02365
                6881104
                31461379
                2a5f39f5-e468-4f9d-98ac-394b8c719330
                © 2019 by American Society of Clinical Oncology

                Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                : 23 July 2019
                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 46, Pages: 11
                Categories
                HEMA16, Hematologic Malignancies: Lymphomas: Biology & Immunology
                HEMA17, Hematologic Malignancies: Lymphomas: Translational Oncology
                ORIGINAL REPORTS
                Hematologic Malignancy
                Custom metadata
                v1

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