Adenovirus-mediated CD40L gene transfer increases Teffector/Tregulatory cell ratio and upregulates death receptors in metastatic melanoma patients

A Schiza, J Wenthe, S Mangsbo, E Eriksson, Anders Nilsson, T H Tötterman, A Loskog, G Ullenhag, A Schiza, J Wenthe, S Mangsbo, E Eriksson, Anders Nilsson, T H Tötterman, A Loskog, G Ullenhag

Abstract

Background and aims: Malignant melanoma is an aggressive tumor sensitive for immunotherapy such as checkpoint blockade antibodies. Still, most patients with late stage disease do not respond, and the side effects can be severe. Stimulation of the CD40 pathway to initiate anti-tumor immunity is a promising alternative. Herein, we demonstrate immune profiling data from melanoma patients treated with an adenovirus-based CD40 ligand gene therapy (AdCD40L).

Methods: Peripheral blood mononuclear cells and plasma were collected from malignant melanoma patients (n = 15) enrolled in a phase I/IIa study investigating intratumoral delivery of AdCD40L with or without low dose cyclophosphamide. Cells were analyzed by flow cytometry while plasma samples were analyzed by a multi-array proteomics.

Results: All patients had an increased Teffector/Tregulatory cell ratio post therapy. Simultaneously, the death receptors TNFR1 and TRAIL-R2 were significantly up-regulated post treatment. Stem cell factor (SCF), E-selectin, and CD6 correlated to enhanced overall survival while a high level of granulocytic myeloid-derived suppressor cells (gMDSCs), IL8, IL10, TGFb1, CCL4, PlGF and Fl3t ligand was highest in patients with short survival.

Conclusions: AdCD40L intratumoral injection induced desirable systemic immune effects that correlated to prolonged survival. Further studies using CD40 stimulation in malignant melanoma are warranted. Trial registration The 002:CD40L trial "Phase I/IIa AdCD40L Immunogene Therapy for Malignant Melanoma and Other Solid Tumors" (clinicalTrials.gov identifier: NCT01455259) was registered at September 2011.

Keywords: AdCD40L; Immunotherapy; Malignant melanoma; Myeloid-derived suppressor cells; Proteomics; T regulatory cells.

Figures

Fig. 1
Fig. 1
PBMCs were evaluated for the presence of T effector cells (CD3+CD4−CD127+), Tregulatory cells (CD3+CD4+FoxP3+CD127−) and NK cells (CD3−CD16+CD56+). a, b The percentage of T effector cells and NK cells before treatment (pre) and 3 weeks post treatment initiation (post) were displayed against survival. c, d The ratio of Teff/Treg and NK/Treg were calculated pre and post 3 weeks. e–h Patient plasma was analyzed by ProSeek proteomics at baseline (pre) and after 3 weeks post treatment initiation (post) and proteins connected to T cell activity are displayed. Statistical calculations were done by GraphPad Prism utilizing Wilcoxon test for paired samples
Fig. 2
Fig. 2
PBMCs were evaluated for the presence of monocytic MDSCs (CD11b+CD14+CD33+HLA-DR−) at different time points post treatment initiation (a, b) and correlated to overall survival (c Pre, d Post, e fold change) or Tregs (CD3+CD4+FoxP3+CD127−) (f) using Spearmans test for nonparametric samples. Open circles in a and b indicates responding patients, as determined by having decreased activity in tumor lesions as defined by PET/CT. g The ratio of Teff/mMDSC was calculated before and at 3 weeks post treatment initiation. Significant difference was calculated using Wilcoxon testing for paired samples. GraphPad Pris was used for statistical calculations
Fig. 3
Fig. 3
PBMCs were evaluated for the presence of granulocytic MDSCs (CD11b+CD14-CD33+HLA-DR−) at different time points post treatment initiation (a, b) and correlated to overall survival (c Pre, d Post, e fold change) or Tregs (CD3+CD4+FoxP3+CD127−) (f) using Spearmans test for nonparametric samples. Open circles in a and b indicates Responding patients, as determined by having decreased activity in tumor lesions as defined by PET/CT. g The ratio of Teff/gMDSC was calculated before and at 3 weeks post treatment initiation. Significant difference was calculated using Wilcoxon testing for paired samples. GraphPad Pris was used for statistical calculations
Fig. 4
Fig. 4
Patient plasma was analyzed by ProSeek proteomics at baseline (pre) and after 3 weeks post treatment initiation (post) and correlated to OS. Proteins connected to immunosuppression are displayed. Statistically significant correlations to OS were calculated using Spearmans test for nonparametric samples. GraphPad Prism was used for statistical calculations
Fig. 5
Fig. 5
Patient plasma was analyzed by ProSeek proteomics at baseline (pre) and after 3 weeks post treatment initiation (post) and fold changes were calculated for these time points for each analyte. The fold change of analytes were then correlated to the fold change of gMDSCs (CD11b+CD14−CD33+HLA-DR−) pre and at 3 weeks post treatment initiation using Spearmans test for nonparametric samples. GraphPad Prism was used for statistical calculations
Fig. 6
Fig. 6
Patient plasma was analyzed by ProSeek proteomics at baseline (pre) and after 3 weeks post treatment initiation (post) and proteins connected to immunity are displayed in the graphs. Analytes were correlated to OS using Spearmans test for nonparametric samples (a, c, e) and significant difference pre and at 3 weeks post treatment initiation was calculated using Wilcoxon test for paired samples (b, d, f). GraphPad Prism was used for statistical calculations

References

    1. Maio M. Melanoma as a model tumour for immuno-oncology. Ann Oncol. 2012;23(Suppl 8):10. doi: 10.1093/annonc/mds257.
    1. Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol. 2013;14(10):1014–1022. doi: 10.1038/ni.2703.
    1. Lindau D, et al. The immunosuppressive tumour network: myeloid-derived suppressor cells, regulatory T cells and natural killer T cells. Immunology. 2013;138(2):105–115. doi: 10.1111/imm.12036.
    1. Gabrilovich DI, Nagaraj S. Myeloid-derived suppressor cells as regulators of the immune system. Nat Rev Immunol. 2009;9(3):162–174. doi: 10.1038/nri2506.
    1. Mougiakakos D, et al. Regulatory T cells in cancer. Adv Cancer Res. 2010;107:57–117. doi: 10.1016/S0065-230X(10)07003-X.
    1. Mellman I, Coukos G, Dranoff G. Cancer immunotherapy comes of age. Nature. 2011;480(7378):480–489. doi: 10.1038/nature10673.
    1. Jensen IS, et al. Evaluating cost benefits of combination therapies for advanced melanoma. Drugs Context. 2016;5:212297. doi: 10.7573/dic.212297.
    1. Loskog A, Totterman TH. CD40L—a multipotent molecule for tumor therapy. Endocr Metab Immune Disord Drug Targets. 2007;7(1):23–28. doi: 10.2174/187153007780059432.
    1. Malmstrom PU, et al. AdCD40L immunogene therapy for bladder carcinoma—the first phase I/IIa trial. Clin Cancer Res. 2010;16(12):3279–3287. doi: 10.1158/1078-0432.CCR-10-0385.
    1. Loskog A, et al. Immunostimulatory AdCD40L gene therapy combined with low-dose cyclophosphamide in metastatic melanoma patients. Br J Cancer. 2016;114(8):872–880. doi: 10.1038/bjc.2016.42.
    1. Landegren U, et al. Opportunities for sensitive plasma proteome analysis. Anal Chem. 2012;84(4):1824–1830. doi: 10.1021/ac2032222.
    1. Liljenfeldt L, et al. CD40L gene therapy tilts the myeloid cell profile and promotes infiltration of activated T lymphocytes. Cancer Gene Ther. 2014;21(3):95–102. doi: 10.1038/cgt.2014.2.
    1. Beyer M, Schultze JL. Regulatory T cells in cancer. Blood. 2006;108(3):804–811. doi: 10.1182/blood-2006-02-002774.
    1. Vence L, et al. Circulating tumor antigen-specific regulatory T cells in patients with metastatic melanoma. Proc Natl Acad Sci USA. 2007;104(52):20884–20889. doi: 10.1073/pnas.0710557105.
    1. Viguier M, et al. Foxp3 expressing CD4+ CD25(high) regulatory T cells are overrepresented in human metastatic melanoma lymph nodes and inhibit the function of infiltrating T cells. J Immunol. 2004;173(2):1444–1453. doi: 10.4049/jimmunol.173.2.1444.
    1. Sakaguchi S, et al. Regulatory T cells and immune tolerance. Cell. 2008;133(5):775–787. doi: 10.1016/j.cell.2008.05.009.
    1. Jacobs JF, et al. Regulatory T cells in melanoma: the final hurdle towards effective immunotherapy? Lancet Oncol. 2012;13(1):e32–e42. doi: 10.1016/S1470-2045(11)70155-3.
    1. Bremer E. Targeting of the tumor necrosis factor receptor superfamily for cancer immunotherapy. ISRN Oncol. 2013;2013:371854.
    1. Clark J, et al. What does tumour necrosis factor excess do to the immune system long term? Ann Rheum Dis. 2005;64(Suppl 4):iv70.
    1. Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420(6917):860–867. doi: 10.1038/nature01322.
    1. Chen X, et al. Interaction of TNF with TNF receptor type 2 promotes expansion and function of mouse CD4+ CD25+ T regulatory cells. J Immunol. 2007;179(1):154–161. doi: 10.4049/jimmunol.179.1.154.
    1. Tseng HY, et al. The melanoma-associated antigen MAGE-D2 suppresses TRAIL receptor 2 and protects against TRAIL-induced apoptosis in human melanoma cells. Carcinogenesis. 2012;33(10):1871–1881. doi: 10.1093/carcin/bgs236.
    1. Ullenhag GJ, et al. The TRAIL system is over-expressed in breast cancer and FLIP a marker of good prognosis. J Cancer Res Clin Oncol. 2015;141(3):505–514. doi: 10.1007/s00432-014-1822-0.
    1. Filipazzi P, et al. Identification of a new subset of myeloid suppressor cells in peripheral blood of melanoma patients with modulation by a granulocyte-macrophage colony-stimulation factor-based antitumor vaccine. J Clin Oncol. 2007;25(18):2546–2553. doi: 10.1200/JCO.2006.08.5829.
    1. Meyer C, et al. Frequencies of circulating MDSC correlate with clinical outcome of melanoma patients treated with ipilimumab. Cancer Immunol Immunother. 2014;63(3):247–257. doi: 10.1007/s00262-013-1508-5.
    1. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–674. doi: 10.1016/j.cell.2011.02.013.
    1. Urban D, et al. CD40/CD40L interaction induces E-selectin dependent leukocyte adhesion to human endothelial cells and inhibits endothelial cell migration. Biochem Biophys Res Commun. 2011;404(1):448–452. doi: 10.1016/j.bbrc.2010.11.142.
    1. Orta-Mascaro M, et al. CD6 modulates thymocyte selection and peripheral T cell homeostasis. J Exp Med. 2016;213(8):1387–1397. doi: 10.1084/jem.20151785.
    1. Stankov K, Popovic S, Mikov M. C-KIT signaling in cancer treatment. Curr Pharm Des. 2014;20(17):2849–2880. doi: 10.2174/13816128113199990593.
    1. Natali PG, et al. Progression of human cutaneous melanoma is associated with loss of expression of c-kit proto-oncogene receptor. Int J Cancer. 1992;52(2):197–201. doi: 10.1002/ijc.2910520207.
    1. Funasaka Y, et al. c-Kit-kinase induces a cascade of protein tyrosine phosphorylation in normal human melanocytes in response to mast cell growth factor and stimulates mitogen-activated protein kinase but is down-regulated in melanomas. Mol Biol Cell. 1992;3(2):197–209. doi: 10.1091/mbc.3.2.197.
    1. Zou GM, Tam YK. Cytokines in the generation and maturation of dendritic cells: recent advances. Eur Cytokine Netw. 2002;13(2):186–199.
    1. Pagani E, et al. Placenta growth factor and neuropilin-1 collaborate in promoting melanoma aggressiveness. Int J Oncol. 2016;48(4):1581–1589.
    1. Schmidt T, et al. Loss or inhibition of stromal-derived PlGF prolongs survival of mice with imatinib-resistant Bcr-Abl1(+) leukemia. Cancer Cell. 2011;19(6):740–753. doi: 10.1016/j.ccr.2011.05.007.
    1. Gold LI. The role for transforming growth factor-beta (TGF-beta) in human cancer. Crit Rev Oncog. 1999;10(4):303–360.
    1. Moore KW, et al. Interleukin-10 and the interleukin-10 receptor. Annu Rev Immunol. 2001;19:683–765. doi: 10.1146/annurev.immunol.19.1.683.
    1. Alfaro C, et al. Tumor-produced interleukin-8 attracts human myeloid-derived suppressor cells and elicits extrusion of neutrophil extracellular traps (NETs) Clin Cancer Res. 2016;22(15):3924–3936. doi: 10.1158/1078-0432.CCR-15-2463.
    1. Waugh DJ, Wilson C. The interleukin-8 pathway in cancer. Clin Cancer Res. 2008;14(21):6735–6741. doi: 10.1158/1078-0432.CCR-07-4843.
    1. Yuan A, et al. The role of interleukin-8 in cancer cells and microenvironment interaction. Front Biosci. 2005;10:853–865. doi: 10.2741/1579.
    1. Bystry RS, et al. B cells and professional APCs recruit regulatory T cells via CCL4. Nat Immunol. 2001;2(12):1126–1132. doi: 10.1038/ni735.
    1. Adolfsson J, et al. Upregulation of Flt3 expression within the bone marrow Lin(−)Sca1(+)c-kit(+) stem cell compartment is accompanied by loss of self-renewal capacity. Immunity. 2001;15(4):659–669. doi: 10.1016/S1074-7613(01)00220-5.
    1. Kreiter S, et al. FLT3 ligand as a molecular adjuvant for naked RNA vaccines. Methods Mol Biol. 2016;1428:163–175. doi: 10.1007/978-1-4939-3625-0_11.
    1. Mosley RL, et al. Flt3 ligand augmentation of T cell mitogenesis and expansion of type 1 effector/memory T cells. Int Immunopharmacol. 2002;2(7):925–940. doi: 10.1016/S1567-5769(02)00035-8.
    1. Kikushige Y, et al. Human Flt3 is expressed at the hematopoietic stem cell and the granulocyte/macrophage progenitor stages to maintain cell survival. J Immunol. 2008;180(11):7358–7367. doi: 10.4049/jimmunol.180.11.7358.
    1. Rosborough BR, et al. Cutting edge: Flt3 ligand mediates STAT3-independent expansion but STAT3-dependent activation of myeloid-derived suppressor cells. J Immunol. 2014;192(8):3470–3473. doi: 10.4049/jimmunol.1300058.
    1. Algazi AP, et al. Clinical outcomes in metastatic uveal melanoma treated with PD-1 and PD-L1 antibodies. Cancer. 2016;122(21):3344–3353. doi: 10.1002/cncr.30258.

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