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      Profiling Immune Escape in Hodgkin’s and Diffuse large B-Cell Lymphomas Using the Transcriptome and Immunostaining

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          Abstract

          Therapeutic blockade of PD-1/PD-L1 shows promising results in Hodgkin’s lymphoma (HL) and in some diffuse large B-cell lymphoma (DLBCL) patients, but biomarkers predicting such responses are still lacking. To this end, we recently developed a transcriptional scoring of immune escape (IE) in cancer biopsies. Using this method in DLBCL, we identified four stages of IE correlated with overall survival, but whether Hodgkin’s lymphomas (HL) also display this partition was unknown. Thus, we explored the transcriptomic profiles of ~1000 HL and DLBCL using a comparative meta-analysis of their bulk microarrays. Relative to DLBCL, the HL co-clustered at the advanced stage of immune escape, displaying significant enrichment of both IE and T-cell activation genes. Analyses via transcriptome deconvolution and immunohistochemistry showed more CD3 + and CD4 + tumor-infiltrating lymphocytes (TILs) in HL than DLBCL. Both HL and non-GCB DLBCL shared a high abundance of infiltrating CD8 + T-cells, but HL had less CD68 +CD163 + macrophages. The same cellular distribution of PD-1 and TIM-3 was observed in HL and DLBCL, though HL had more PD-L1 tumor cells and LAG-3 ME cells. This study illuminates the advanced stage of immune activation and escape in HL, consistent with the response to checkpoint blockade therapies for this type of lymphoma.

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          PD-1 and CTLA-4 combination blockade expands infiltrating T cells and reduces regulatory T and myeloid cells within B16 melanoma tumors.

          Vaccination with irradiated B16 melanoma cells expressing either GM-CSF (Gvax) or Flt3-ligand (Fvax) combined with antibody blockade of the negative T-cell costimulatory receptor cytotoxic T-lymphocyte antigen-4 (CTLA-4) promotes rejection of preimplanted tumors. Despite CTLA-4 blockade, T-cell proliferation and cytokine production can be inhibited by the interaction of programmed death-1 (PD-1) with its ligands PD-L1 and PD-L2 or by the interaction of PD-L1 with B7-1. Here, we show that the combination of CTLA-4 and PD-1 blockade is more than twice as effective as either alone in promoting the rejection of B16 melanomas in conjunction with Fvax. Adding alphaPD-L1 to this regimen results in rejection of 65% of preimplanted tumors vs. 10% with CTLA-4 blockade alone. Combination PD-1 and CTLA-4 blockade increases effector T-cell (Teff) infiltration, resulting in highly advantageous Teff-to-regulatory T-cell ratios with the tumor. The fraction of tumor-infiltrating Teffs expressing CTLA-4 and PD-1 increases, reflecting the proliferation and accumulation of cells that would otherwise be anergized. Combination blockade also synergistically increases Teff-to-myeloid-derived suppressor cell ratios within B16 melanomas. IFN-gamma production increases in both the tumor and vaccine draining lymph nodes, as does the frequency of IFN-gamma/TNF-alpha double-producing CD8(+) T cells within the tumor. These results suggest that combination blockade of the PD-1/PD-L1- and CTLA-4-negative costimulatory pathways allows tumor-specific T cells that would otherwise be inactivated to continue to expand and carry out effector functions, thereby shifting the tumor microenvironment from suppressive to inflammatory.
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            Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma.

            Classical Hodgkin lymphoma (cHL) and mediastinal large B-cell lymphoma (MLBCL) are lymphoid malignancies with certain shared clinical, histologic, and molecular features. Primary cHLs and MLBCLs include variable numbers of malignant cells within an inflammatory infiltrate, suggesting that these tumors escape immune surveillance. Herein, we integrate high-resolution copy number data with transcriptional profiles and identify the immunoregulatory genes, PD-L1 and PD-L2, as key targets at the 9p24.1 amplification peak in HL and MLBCL cell lines. We extend these findings to laser-capture microdissected primary Hodgkin Reed-Sternberg cells and primary MLBCLs and find that programmed cell death-1 (PD-1) ligand/9p24.1 amplification is restricted to nodular sclerosing HL, the cHL subtype most closely related to MLBCL. Using quantitative immunohistochemical methods, we document the association between 9p24.1 copy number and PD-1 ligand expression in primary tumors. In cHL and MLBCL, the extended 9p24.1 amplification region also included the Janus kinase 2 (JAK2) locus. Of note, JAK2 amplification increased protein expression and activity, specifically induced PD-1 ligand transcription and enhanced sensitivity to JAK2 inhibition. Therefore, 9p24.1 amplification is a disease-specific structural alteration that increases both the gene dosage of PD-1 ligands and their induction by JAK2, defining the PD-1 pathway and JAK2 as complementary rational therapeutic targets.
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              Nivolumab for classical Hodgkin lymphoma after autologous stem-cell transplantation and brentuximab vedotin failure: a prospective phase 2 multi-cohort study

              Background Malignant cells of classical Hodgkin lymphoma (cHL) are characterised by genetic alterations at the 9p24·1 locus. This leads to overexpression of the programmed death 1 (PD-1) ligands and enables tumour cells to evade immune surveillance. A phase 1b study showed that nivolumab, a PD-1-blocking antibody, produced a high response rate in patients with relapsed and refractory cHL, with an acceptable safety profile. This phase 2 study assessed the clinical benefit of nivolumab monotherapy in patients with cHL after autologous stem-cell transplantation and brentuximab vedotin failure. Methods This ongoing phase 2 study (NCT02181738) assessed the efficacy and safety of nivolumab, administered intravenously over 60 minutes at 3 mg/kg every 2 weeks, in adult patients with cHL who had failed both autologous stem-cell transplantation and brentuximab vedotin. The primary endpoint was objective response rate by independent radiologic review committee (IRRC) assessment. Secondary and other endpoints included duration of response, safety, and assessment of PD-L1 and PD-L2 loci and PD-L1 and PD-L2 protein expression. Findings Among 80 treated patients, the median number of prior therapies was four (range 3–15). With a mean (SD) follow-up of 8·6 months (2·02), objective response rate per IRRC was 66·3% (53/80). The most common drug-related adverse events (≥15%) included fatigue, infusion-related reaction, and rash. The most common drug-related grade 3–4 adverse events were neutropenia and increased lipase levels (both n=4). The most common serious adverse event (any grade) was pyrexia (n=3). Interpretation Nivolumab demonstrated a high response rate and an acceptable safety profile in patients with cHL who progressed following autologous stem-cell transplantation and brentuximab vedotin. Nivolumab may therefore provide a novel treatment option for a patient population with a high unmet need. Ongoing follow-up will help to assess the durability of response. Funding Bristol-Myers Squibb.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                31 October 2018
                November 2018
                : 10
                : 11
                : 415
                Affiliations
                [1 ]Centre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, 31100 Toulouse, France; pericart.sarah@ 123456iuct-oncopole.fr (S.P.); marie.tosolini@ 123456inserm.fr (M.T.); pauline.gravelle@ 123456inserm.fr (P.G.); cedric.rossi66@ 123456gmail.com (C.R.); franchet.camille@ 123456iuct-oncopole.fr (C.F.); christine.bezombes@ 123456inserm.fr (C.B.); brousset.p@ 123456chu-toulouse.fr (P.B.); jean-jacques.fournie@ 123456inserm.fr (J.-J.F.)
                [2 ]Université Toulouse III Paul-Sabatier, 31330 Toulouse, France; amara.n@ 123456chu-toulouse.fr (N.A.); Laurent.Guy@ 123456iuct-oncopole.fr (G.L.)
                [3 ]Centre de Recherches en Cancérologie de Toulouse, ERL 5294 CNRS, 31100 Toulouse, France
                [4 ]Laboratoire d’Excellence ‘TOUCAN’, 31059 Toulouse, France
                [5 ]Programme Hospitalo-Universitaire en Cancérologie CAPTOR, 31059 Toulouse, France
                [6 ]Institut Carnot Lymphome CALYM, 69495 Pierre-Bénite, France
                [7 ]Departement de Pathologie, CHU Toulouse, Institut Universitaire du Cancer-Oncopole de Toulouse, 31059 CEDEX 09 Toulouse, France
                [8 ]Hématologie Clinique, CHU Dijon, 21000 Dijon, France
                [9 ]Hospices Civils de Lyon, Claude Bernard Lyon 1 University, INSERM 1052, 69002 Lyon, France; Alexandra.traverse-glehen@ 123456chu-lyon.fr
                [10 ]Biostatistics Unit, Institut Claudius Regaud, IUCT-O, 31059 CEDEX 09 Toulouse, France; Martin.Elodie@ 123456iuct-oncopole.fr
                [11 ]Departement d’Hematologie, CHU Toulouse, Institut Universitaire du Cancer-Oncopole de Toulouse, 31059 CEDEX 09 Toulouse, France
                Author notes
                [* ]Correspondence: laurent.c@ 123456chu-toulouse.fr ; Tel.: +33-053-115-6199
                Author information
                https://orcid.org/0000-0001-5278-5952
                Article
                cancers-10-00415
                10.3390/cancers10110415
                6266061
                30384489
                f57dbab1-7b33-43b2-ac05-f1e96ee08149
                © 2018 by the authors.

                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 ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 21 September 2018
                : 27 October 2018
                Categories
                Article

                lymphoma,immune escape,hodgkin’s lymphoma,immune checkpoints,tim-3,datamining

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