Long-term Survival and Clinical Beneï¬پt from Adoptive T ... Research Article Long-term Survival...

download Long-term Survival and Clinical Beneï¬پt from Adoptive T ... Research Article Long-term Survival and

If you can't read please download the document

  • date post

    26-Jul-2020
  • Category

    Documents

  • view

    1
  • download

    0

Embed Size (px)

Transcript of Long-term Survival and Clinical Beneï¬پt from Adoptive T ... Research Article Long-term Survival...

  • Research Article

    Long-term Survival and Clinical Benefit from Adoptive T-cell Transfer in Stage IV Melanoma Patients Is Determined by a Four-Parameter Tumor Immune Signature Sara M. Melief1,Valeria V.Visconti1, Marten Visser1, Merel van Diepen2, Ellen H.W. Kapiteijn1, Joost H. van den Berg3, John B.A.G. Haanen3, Vincent T.H.B.M. Smit4, Jan Oosting5, Sjoerd H. van der Burg1, and Els M.E. Verdegaal1

    Abstract

    The presence of tumor-infiltrating immune cells is associated with longer survival and a better response to immunotherapy in early-stage melanoma, but a comprehensive study of the in situ immune microenvironment in stage IV melanoma has not been performed. We investigated the combined influence of a series of immune factors on survival and response to adoptive cell transfer (ACT) in stage IV melanoma patients. Metastases of 73 stage IV melanoma patients, 17 of which were treated with ACT, were studied with respect to the number and functional phenotype of lymphocytes and myeloid cells as well as for expression of galectins-1, -3, and -9. Single factors associatedwithbetter survival were identified using Kaplan–Meier curves and multivariate Cox

    regression analyses, and those factors were used for interac- tion analyses. The results were validated using The Cancer Genome Atlas database. We identified four parameters that were associated with a better survival: CD8þ T cells, galectin- 9þ dendritic cells (DC)/DC-like macrophages, a high M1/M2 macrophage ratio, and the expression of galectin-3 by tumor cells. The presence of at least three of these parameters formed an independent positive prognostic factor for long-term sur- vival. Patients displaying this four-parameter signature were found exclusively among patients responding to ACT and were the ones with sustained clinical benefit. Cancer Immunol Res; 5(2); 170–9. �2017 AACR.

    Introduction Melanoma is the most aggressive form of skin cancer and has

    long been recognized as a highly immunogenic tumor and a good target for immunotherapy (1). In different types of cancer, includ- ing melanoma, the presence of type I cytokine–oriented tumor- infiltrating lymphocytes (TIL) has been associated with improved survival (2). Indeed, a strong ongoing immune response was linked to spontaneous regression in about half of the primary melanomas (3) and longer survival of patients with stage I–III primary and regionally metastasized melanoma (4–6). More recently, a large study inpatientswith stage IV (distantmetastases) melanoma revealed that even at this stage, intratumoral T-cell

    content was associated with improved survival (7). However, the predictive value for survival was not so strong, indicating that other immune-related factors previously studied in primary mel- anoma may also play a role (8–12); this involvement of other immune parameters was also suggested by studies at the gene expression level (13, 14). In parallel, studies showing that a strong intratumoral T-cell infiltrate fosters a better response to PD-1 checkpoint therapy (15) and autologous tumor cell vaccination (11), but also that intratumoralmacrophages can hamper CTLA-4 checkpoint therapy (16), suggest that the tumor's immune con- texture may also influence the response to immunotherapy.

    In this study, we have expanded on earlier studies (4, 7) by assessing the influence of a series of immune factors in the metastatic tumor microenvironment in a large group of stage IV melanoma patients with up to 10 years of follow-up since metas- tasis. We identified four parameters, each of which was associated with better survival. These parameters comprised CD8 T cells, the presence of galectin-9þ dendritic cells (DC)/DC-like macro- phages, a higher M1/M2macrophage ratio, and galectin-3 expres- sion by tumor cells. The presence of at least three parameters was an independent prognostic factor for survival, which was validat- ed by analysis of these parameters in stage IV melanoma patients in TheCancer GenomeAtlas (TCGA) database. Furthermore, with the introduction of targeted therapies and checkpoint inhibitors, adoptive cell transfer (ACT) has mostly become a salvage therapy (17) for treatment of stage IV melanoma patients. Analysis of the predictive value of this signature for the response to ACT revealed that the pretreatment tumors of patients without clinical benefit

    1Department of Clinical Oncology, Leiden University Medical Center, Leiden, the Netherlands. 2Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands. 3Division of Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands. 4Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands. 5Bioinformatics Center of Expertise, Leiden University Medical Center, Leiden, the Netherlands.

    Note: Supplementary data for this article are available at Cancer Immunology Research Online (http://cancerimmunolres.aacrjournals.org/).

    Corresponding Author: Els M.E. Verdegaal, Department of Clinical Oncology, Leiden University Medical Center, P.O. Box 9600, Leiden 2300 RC, the Nether- lands. Phone: 317-1526-3464; Fax: 317-1526-6760; E-mail: e.verdegaal@lumc.nl

    doi: 10.1158/2326-6066.CIR-16-0288

    �2017 American Association for Cancer Research.

    Cancer Immunology Research

    Cancer Immunol Res; 5(2) February 2017170

    on September 30, 2020. © 2017 American Association for Cancer Research. cancerimmunolres.aacrjournals.org Downloaded from

    Published OnlineFirst January 10, 2017; DOI: 10.1158/2326-6066.CIR-16-0288

    http://cancerimmunolres.aacrjournals.org/

  • (CB) predominantly display two or fewer of the beneficial immune parameters, whereas the presence of three or four of these parameterswasmost frequent in patients showing sustained CB after ACT.

    Materials and Methods Patient material

    Formalin-fixed, paraffin-embedded tissue blocks from 73 stage IV metastatic melanoma patients undergoing surgery were col- lected at Leiden University Medical Center (LUMC, Leiden, the Netherlands) and at the Netherlands Cancer Institute (NCI, Amsterdam, the Netherlands). The patients were included in clinical studies that were approved by a local ethical committee (LUMC study P04.085, NCI study EudraCT 2010-021885-31), and all patients gave written informed consent. All specimens were frommetastases, and biopsies were taken before any immu- notherapeutic treatment. Classification ofmetastaseswas done by tumor–node–metastasis (TNM) staging criteria (18), and infor- mation on the concentration of lactate dehydrogenase (LDH) at the moment of sampling was collected. Included in the cohort of 73patientswere 17patients thatwere treatedwithACT inongoing clinical studies in the LUMC and NCI. Of these patients, 7 were classified as patientswithoutCB [progressive disease (PD)] and10 patients with CB (stable disease (SD), partial response (PR), and complete response (CR)] according to RECIST1.1 criteria.

    Immunofluorescence and IHC The presence of T-cell and macrophage infiltrate in the tumor

    area and the expression of galectin-1, galectin-3, and galectin-9 by the tumor was analyzed using previously determined optimal antibody concentrations and immunofluorescence staining pro- tocols as described before (19, 20). Briefly, T-cell infiltrates were stained with antibodies to CD3, CD8, and FoxP3. Macrophages were identified using antibodies to CD14 and CD163. To exam- ine which cells expressed galectin-9, a small part of the cohort received triple immunofluorescence staining with antibodies to galectin-9, CD68, and CD11c. All secondary antibodies were isotype-specific antibodies labeled with the fluorochromes Alexa Fluor 488, 546, or 647. The expression of Tbet was analyzed by IHC as described before (19) with the exception that after incubation with the primary Tbet antibody and incubation with BrightVision poly-HRP anti-mouse/rabbit/rat IgG, the antigen- antibody reactions were visualized using the NovaRED Substrate Kit for peroxidase (Vector Laboratories). For all antibody label- ing, negative controls and controls omitting the primary or secondary antibody were performed. Positive control tissue slides were included for all antibody labeling, using tonsil for T cells, colon for galectin, and placenta for macrophage controls. Images were captured using a confocal microscope (LSM15, Zeiss) for the immunofluorescence labeling and a spectralmicro- scope (Leica DM4000 B, Leica Microsystems) for the immuno- histochemical stains. Random images (five per slide) were taken for analysis. Analysis of the images was done using ImageJ. Intratumoral T cells, macrophages, galectin-9þ cells, and Tbetþ

    cells were manually counted using the "cell counter" plugin of ImageJ and presented as number of cells/mm2 (average of five images). Galectin-1 and galectin-3 expression by tumor cells were analyzed using an immunoreactive score (IRS; ref. 21), taking into account the percentage of positive cells and the intensity of the staining (Supplementary Table S1A).

    TCGA analysis For validation of our results of the IHC and immunofluores-

    cence experiments, we analyzed data from the publicly available TCGA database (5). To reconstruct our parameters, we used gene expression profiles of the subset of patients with stage IV mela- noma. CD8þ T cells were identified by taking the average of CD8A and CD8B expression, galectin-9þ DC-like macrophages by GALS9 expression,M1/M2macrophage ratio by the ratio of CD86 and CD163 expression, and expression of galectin-3 by tumor cells by LGALS3 expression. This approach assumes that the genes we used are expressed preferably by the target cells for the parameter, and not in the other cell types in the sample. We used the z-scores as available in the TCGA data. This