PD-1 inhibition in advanced myeloproliferative neoplasms

Gabriela Hobbs, Cansu Cimen Bozkus, Erin Moshier, Mikaela Dougherty, Michal Bar-Natan, Lonette Sandy, Kathryn Johnson, Julia Elise Foster, Tina Som, Molly Macrae, Hetal Marble, Mohamed Salama, Siraj M El Jamal, Nicole Zubizarreta, Martha Wadleigh, Richard Stone, Nina Bhardwaj, Camelia Iancu-Rubin, John Mascarenhas, Gabriela Hobbs, Cansu Cimen Bozkus, Erin Moshier, Mikaela Dougherty, Michal Bar-Natan, Lonette Sandy, Kathryn Johnson, Julia Elise Foster, Tina Som, Molly Macrae, Hetal Marble, Mohamed Salama, Siraj M El Jamal, Nicole Zubizarreta, Martha Wadleigh, Richard Stone, Nina Bhardwaj, Camelia Iancu-Rubin, John Mascarenhas

Abstract

Myelofibrosis (MF) is a clonal stem cell neoplasm characterized by abnormal JAK-STAT signaling, chronic inflammation, cytopenias, and risk of transformation to acute leukemia. Despite improvements in the therapeutic options for patients with MF, allogeneic hematopoietic stem cell transplantation remains the only curative treatment. We previously demonstrated multiple immunosuppressive mechanisms in patients with MF, including increased expression of programmed cell death protein 1 (PD-1) on T cells compared with healthy controls. Therefore, we conducted a multicenter, open-label, phase 2, single-arm study of pembrolizumab in patients with Dynamic International Prognostic Scoring System category of intermediate-2 or greater primary, post-essential thrombocythemia or post-polycythemia vera myelofibrosis that were ineligible for or were previously treated with ruxolitinib. The study followed a Simon 2-stage design and enrolled a total of 10 patients, 5 of whom had JAK2V617mutation, 2 had CALR mutation, and 6 had additional mutations. Most patients were previously treated with ruxolitinib. Pembrolizumab treatment was well tolerated, but there were no objective clinical responses, so the study closed after the first stage was completed. However, immune profiling by flow cytometry, T-cell receptor sequencing, and plasma proteomics demonstrated changes in the immune milieu of patients, which suggested improved T-cell responses that can potentially favor antitumor immunity. The fact that these changes were not reflected in a clinical response strongly suggests that combination immunotherapeutic approaches rather than monotherapy may be necessary to reverse the multifactorial mechanisms of immune suppression in myeloproliferative neoplasms. This trial was registered at www.clinicaltrials.gov as #NCT03065400.

© 2021 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.

Figures

Graphical abstract
Graphical abstract
Figure 1.
Figure 1.
Study schema. Patients with primary or secondary MF enrolled in the Simon two-stage design; if <1 of 9 responded, the study would not proceed to stage 2. In addition, there was an exploratory cohort for accelerated and blast phase disease. Pembrolizumab 200 mg was administered intravenously (IV) once every 3 weeks.
Figure 2.
Figure 2.
Changes in T-cell frequencies in blood after administration of pembrolizumab. Frequencies of cell populations among PBMCs collected before pembrolizumab administration (baseline), on C3D1 or C7D1 were evaluated. (A) Frequency of PD-1+ cells at baseline, gated under the T-cell populations indicated on the x-axis. Color key shows patients by ID number. (B) Frequency of PD-L1+ cells among live cells. Frequency of T cells as analyzed by flow cytometry (C) (CD3+) or TCR sequencing (D) (TCRseq) (number of cells expressing TCR/number of total nucleated cells). (E) Changes in T-cell subset ratios (% CD3+CD4+/% CD3+CD8+). Statistical significance was evaluated by Wilcoxon matched-pairs signed-rank test. P < .05 was considered significant. *P = .0391.
Figure 3.
Figure 3.
Pembrolizumab-induced alterations in T-cell repertoire. TCR Vβ chains of peripheral blood T cells collected before administration of pembrolizumab (baseline) and on C3D1 or C7D1 were sequenced. (A) Clonality of T cells was calculated using the Simpson index (scores range from 0 to 1); a score of 1 indicates a monoclonal population. Statistical significance was evaluated by Wilcoxon matched-pairs signed-rank test. (B) Top 500 clones with the highest total productive frequencies (the sum of frequencies found in each sample) were evaluated to identify shared clones. The plot displays the number of patients (n = 9, y-axis) or samples sequenced (n = 22, x-axis), in which individual clones were found. The size of the bubbles indicates the total frequency of clones. (C) Number of clones for each patient that were significantly expanded at C3D1 and C7D1 compared to baseline. (D) Changes in the abundance of unique TCR Vβ sequences after 2 cycles of pembrolizumab treatment were analyzed (C3D1 vs baseline). Only clones with a minimum cumulative abundance of 10 were included in the analysis. Significantly expanded or contracted clones are denoted in orange and blue, respectively. The clones analyzed at C3D1 were evaluated for their presence at C7D1, where available (titled in red), and those that were also found at C7D1 were marked by a black circle. Significance was evaluated by the binomial method (two-sided), and false discovery rates were controlled by using the Benjamini-Hochberg method. Differential abundance of clones was considered significant if P ≤ .01. NA, not applicable.
Figure 4.
Figure 4.
Changes in the profiles of the plasma proteins after administration of pembrolizumab. Plasma samples collected before administration of pembrolizumab (screen), on C3D1 or C7D1 were analyzed using an OLINK Immuno-Oncology panel. Normalized protein expression values (NPX) are displayed. (A) Heatmap comparing the normalized expression of 80 proteins (y-axis) in the plasma of patients before and after receiving pembrolizumab (x-axis). Color intensity indicates NPX value. Analytes with a significant increase on C3D1 compared with screening are denoted with asterisks. Plasma protein profiles throughout the treatment were plotted for PD-1 (screen vs C3D1, P < .0001; screen vs C7D1, P = .0076) (B), CXCL9 (screen vs C3D1, P = .0033; screen vs C7D1, P = .0035) (C), and CXCL10 (screen vs C3D1, P = .0978; screen vs C7D1, P = .0427) (D). Statistical significance was evaluated by paired Student t test. P < .05 was considered significant. *P < .05; **P < .01; ****P < .0001. Ns, not significant; Ref, healthy donor control reference.

References

    1. Mascarenhas J, Mughal TI, Verstovsek S. Biology and clinical management of myeloproliferative neoplasms and development of the JAK inhibitor ruxolitinib. Curr Med Chem. 2012;19(26):4399-4413.
    1. Vannucchi AM, Lasho TL, Guglielmelli P, et al. . Mutations and prognosis in primary myelofibrosis. Leukemia. 2013;27(9):1861-1869.
    1. Rumi E, Pietra D, Pascutto C, et al. ; Associazione Italiana per la Ricerca sul Cancro Gruppo Italiano Malattie Mieloproliferative Investigators . Clinical effect of driver mutations of JAK2, CALR, or MPL in primary myelofibrosis. Blood. 2014;124(7):1062-1069.
    1. Mondet J, Hussein K, Mossuz P. Circulating cytokine levels as markers of inflammation in Philadelphia negative myeloproliferative neoplasms: diagnostic and prognostic interest. Mediators Inflamm. 2015;2015:670580.
    1. Barcellini W, Iurlo A, Radice T, et al. . Increased prevalence of autoimmune phenomena in myelofibrosis: relationship with clinical and morphological characteristics, and with immunoregulatory cytokine patterns. Leuk Res. 2013;37(11):1509-1515.
    1. Gangat N, Caramazza D, Vaidya R, et al. . DIPSS plus: a refined Dynamic International Prognostic Scoring System for primary myelofibrosis that incorporates prognostic information from karyotype, platelet count, and transfusion status. J Clin Oncol. 2011;29(4):392-397.
    1. Gowin K, Ballen K, Ahn KW, et al. . Survival following allogeneic transplant in patients with myelofibrosis. Blood Adv. 2020;4(9):1965-1973.
    1. Kvasnicka HM, Thiele J, Bueso-Ramos CE, et al. . Long-term effects of ruxolitinib versus best available therapy on bone marrow fibrosis in patients with myelofibrosis. J Hematol Oncol. 2018;11(1):42.
    1. Mascarenhas J, Hoffman R. A comprehensive review and analysis of the effect of ruxolitinib therapy on the survival of patients with myelofibrosis. Blood. 2013;121(24):4832-4837.
    1. Wang M, Fayad L, Wagner-Bartak N, et al. . Lenalidomide in combination with rituximab for patients with relapsed or refractory mantle-cell lymphoma: a phase 1/2 clinical trial. Lancet Oncol. 2012;13(7):716-723.
    1. Kuykendall AT, Shah S, Talati C, et al. . Between a rux and a hard place: evaluating salvage treatment and outcomes in myelofibrosis after ruxolitinib discontinuation. Ann Hematol. 2018;97(3):435-441.
    1. Garon EB, Rizvi NA, Hui R, et al. ; KEYNOTE-001 Investigators . Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med. 2015;372(21):2018-2028.
    1. Gandhi L, Rodríguez-Abreu D, Gadgeel S, et al. ; KEYNOTE-189 Investigators . Pembrolizumab plus chemotherapy in metastatic non-small-cell lung cancer. N Engl J Med. 2018;378(22):2078-2092.
    1. Hamid O, Robert C, Daud A, et al. . Five-year survival outcomes for patients with advanced melanoma treated with pembrolizumab in KEYNOTE-001. Ann Oncol. 2019;30(4):582-588.
    1. Al Hadidi SA, Lee HJ. Pembrolizumab for the treatment of Hodgkin lymphoma. Expert Opin Biol Ther. 2020;20(11):1275-1282.
    1. Wang JC, Chen C, Kundra A, et al. . Programmed cell death receptor (PD-1) ligand (PD-L1) expression in Philadelphia chromosome-negative myeloproliferative neoplasms. Leuk Res. 2019;79:52-59.
    1. Cimen Bozkus C, Roudko V, Finnigan JP, et al. . Immune checkpoint blockade enhances shared neoantigen-induced T-cell immunity directed against mutated calreticulin in myeloproliferative neoplasms. Cancer Discov. 2019;9(9):1192-1207.
    1. Tefferi A, Cervantes F, Mesa R, et al. . Revised response criteria for myelofibrosis: International Working Group-Myeloproliferative Neoplasms Research and Treatment (IWG-MRT) and European LeukemiaNet (ELN) consensus report. Blood. 2013;122(8):1395-1398.
    1. Thiele J, Kvasnicka HM, Facchetti F, Franco V, van der Walt J, Orazi A. European consensus on grading bone marrow fibrosis and assessment of cellularity. Haematologica. 2005;90(8):1128-1132.
    1. Kamphorst AO, Pillai RN, Yang S, et al. . Proliferation of PD-1+ CD8 T cells in peripheral blood after PD-1-targeted therapy in lung cancer patients. Proc Natl Acad Sci USA. 2017;114(19):4993-4998.
    1. Huang AC, Postow MA, Orlowski RJ, et al. . T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature. 2017;545(7652):60-65.
    1. Kumar V, Patel S, Tcyganov E, Gabrilovich DI. The nature of myeloid-derived suppressor cells in the tumor microenvironment. Trends Immunol. 2016;37(3):208-220.
    1. Cristescu R, Mogg R, Ayers M, et al. . Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science. 2018; 362(6411):eaar3593.
    1. Balachandran VP, Łuksza M, Zhao JN, et al. ; ARC-Net Centre for Applied Research on Cancer . Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer. Nature. 2017;551(7681):512-516.
    1. Shin DS, Zaretsky JM, Escuin-Ordinas H, et al. . Primary resistance to PD-1 blockade mediated by JAK1/2 mutations. Cancer Discov. 2017;7(2):188-201.
    1. Prestipino A, Emhardt AJ, Aumann K, et al. . Oncogenic JAK2V617F causes PD-L1 expression, mediating immune escape in myeloproliferative neoplasms. Sci Transl Med. 2018;10(429):eaam7729.
    1. Carbognin L, Pilotto S, Milella M, et al. . Differential activity of nivolumab, pembrolizumab and MPDL3280A according to the tumor expression of programmed death-ligand-1 (PD-L1): sensitivity analysis of trials in melanoma, lung and genitourinary cancers. PLoS One. 2015;10(6):e0130142.
    1. Vannucchi AM, Guglielmelli P, Rotunno G, et al. . Mutation-enhanced International Prognostic Scoring System (MIPSS) for primary myelofibrosis: an AGIMM & IWG-MRT Project [abstract]. Blood. 2014;124(21). Abstract 405.
    1. Wherry EJ. T cell exhaustion. Nat Immunol. 2011;12(6):492-499.
    1. Holmström MO, Riley CH, Svane IM, Hasselbalch HC, Andersen MH. The CALR exon 9 mutations are shared neoantigens in patients with CALR mutant chronic myeloproliferative neoplasms. Leukemia. 2016;30(12):2413-2416.
    1. Handlos Grauslund J, Holmström MO, Jørgensen NG, et al. . Therapeutic cancer vaccination with a peptide derived from the calreticulin exon 9 mutations induces strong cellular immune responses in patients with CALR-mutant chronic myeloproliferative neoplasms. Front Oncol. 2021;11:637420.
    1. Kim KH, Kim CG, Shin EC. Peripheral blood immune cell-based biomarkers in anti-PD-1/PD-L1 therapy. Immune Netw. 2020;20(1):e8.
    1. Khan M, Zhao Z, Arooj S, Fu Y, Liao G. Soluble PD-1: Predictive, prognostic, and therapeutic value for cancer immunotherapy. Front Immunol. 2020;11:587460.
    1. Nielsen C, Ohm-Laursen L, Barington T, Husby S, Lillevang ST. Alternative splice variants of the human PD-1 gene. Cell Immunol. 2005;235(2):109-116.
    1. Huang J, Jochems C, Anderson AM, et al. . Soluble CD27-pool in humans may contribute to T cell activation and tumor immunity. J Immunol. 2013;190(12):6250-6258.
    1. Metzemaekers M, Vanheule V, Janssens R, Struyf S, Proost P. Overview of the mechanisms that may contribute to the non-redundant activities of interferon-inducible CXC chemokine receptor 3 ligands. Front Immunol. 2018;8:1970.
    1. Qian L, Yu S, Yin C, et al. . Plasma IFN-γ-inducible chemokines CXCL9 and CXCL10 correlate with survival and chemotherapeutic efficacy in advanced pancreatic ductal adenocarcinoma. Pancreatology. 2019;19(2):340-345.
    1. House IG, Savas P, Lai J, et al. . Macrophage-derived CXCL9 and CXCL10 are required for antitumor immune responses following immune checkpoint blockade. Clin Cancer Res. 2020;26(2):487-504.
    1. Vilgelm AE, Richmond A. Chemokines modulate immune surveillance in tumorigenesis, metastasis, and response to immunotherapy. Front Immunol. 2019;10:333.
    1. Wang JC, Kundra A, Andrei M, et al. . Myeloid-derived suppressor cells in patients with myeloproliferative neoplasm. Leuk Res. 2016;43:39-43.
    1. Haverkamp JM, Crist SA, Elzey BD, Cimen C, Ratliff TL. In vivo suppressive function of myeloid-derived suppressor cells is limited to the inflammatory site. Eur J Immunol. 2011;41(3):749-759.
    1. Cimen Bozkus C, Elzey BD, Crist SA, Ellies LG, Ratliff TL. Expression of cationic amino acid transporter 2 is required for myeloid-derived suppressor cell-mediated control of T cell immunity. J Immunol. 2015;195(11):5237-5250.
    1. Kleppe M, Koche R, Zou L, et al. . Dual targeting of oncogenic activation and inflammatory signaling increases therapeutic efficacy in myeloproliferative neoplasms. Cancer Cell. 2018;33(1):29-43.e7.
    1. Bai X, Yi M, Jiao Y, Chu Q, Wu K. Blocking TGF-β signaling to enhance the efficacy of immune checkpoint inhibitor. OncoTargets Ther. 2019;12:9527-9538.

Source: PubMed

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