Immune Microenvironment Analysis of Bone Marrow By Mass Cytometry and RNA Sequencing in Multiple Myeloma Patients Treated with Daratumumab and Durvalumab
Authors: Seymour Frances , Young Mary H , Tometsko Mark , Cavenagh Jamie , Thompson Ethan G. , Whalen Elizabeth , Danziger Sam A , Fitch Alison , Fox Brian A. , Dervan Andrew , Foy Teri , Newhall Katie , Gribben John G. 
Published: October 2019

Abstract
Introduction
Relapsed and refractory multiple myeloma (RRMM) remains a challenging disease to treat due to its heterogeneity and complexity. There is an urgent need for novel combination strategies, including immunotherapy. The study of the tumour and immune microenvironment before and after treatment with combination therapy is a crucial part of understanding the underpinning of disease response.
Methods
Longitudinal samples of bone marrow aspirates and whole blood were collected from a phase II clinical trial, MEDI4736-MM-003 (NCT02807454) where daratumumab and durvalumab naïve patients were exposed simultaneously to both these drugs. A combination of mass cytometry (CyTOF), RNAseq and flow cytometry were performed on a subset of samples from these subjects. Specifically, paired bone marrow mononuclear cells (BMMC) samples from nine patients taken at screening and six weeks post-treatment were analysed by mass cytometry (CyTOF) using a 37-marker pan-immune panel that included both lineage and functional intracellular/extracellular markers. In addition, whole blood sample specimens were collected at screening and on treatment (8, 15, 30, and 45 days after treatment) and analysed by flow cytometry. Flow cytometry panels were designed to allow interrogation of the abundance and activation status of immune cell subsets. Finally, RNA from bone marrow aspirates at screening and C2D15 were analysed by RNA sequencing. Expression profiles from the aspirates were used to estimate cell proportions by computational deconvolution. Individual cell types in these microenvironments were estimated using the DCQ algorithm and a gene expression signature matrix based on the published LM22 leukocyte matrix (Newman et al., 2015) augmented with 5 bone marrow- and myeloma-specific cell types.
Results
In a heavily pre-treated population with RRMM, treatment with durvalumab and daratumumab leads to shifts in a number of key immunological populations when compared to pre-treatment. In the bone marrow, CD8 and CD4 populations rise (by CyTOF and RNAseq), while NK, DC and B cell populations fall (by CyTOF). In the bone marrow within CD8+ T lymphocyte populations, we observed a post-treatment rise in markers of degranulation (granzyme p=0.0195, perforin p=0.0078, Wilcoxon signed-rank test). This is also accompanied by a fall in PD1 expression (p=0.0078) and rise in the co-stimulatory receptor DNAM1 (p=0.0273). These changes are most marked on cells with an effector memory CD45RA+ CD8+ T cell phenotype. In the blood, similar to the bone marrow, CD8+ T cells proliferate over the course of treatment (flow cytometry).
A fall in both naïve and active NK cell populations is seen following treatment in bone marrow. NK cells express high levels of CD38 and are therefore depleted by daratumumab. Those NK cells which remain have an active phenotype with increased expression of TNFa (p=0.0039) and IFNg (p=0.0195) following treatment. Across the time points sampled in peripheral blood, NK cells were also decreased and those that remained were proliferating. Dendritic cells with a tolerogenic phenotype can be identified prior to treatment and are seen to fall in abundance following treatment with durvalumab and daratumumab.
Conclusions
The combination of durvalumab and daratumumab leads to several immune microenvironment changes that biologically portend clinical effect. We see increases in the abundance of cell populations with functional anti-tumour activity, including granzyme B+ CD8 T cells and a reduction in PD1high T cells. Despite the treatment expectedly reducing NK cell numbers, many functionally competent NK cells remain, as evidenced by the presence of anti-tumour cytokines. This combination strategy also reduces immunosuppressive tolerogenic DCs, which suppress CD4 and CD8 T cell activity. Taken together, this suggests that this chemotherapy free, doublet treatment has the potential to up-regulate anti-tumour immunological responses, which may restore immunosurveillance mechanisms critically needed in these highly refractory patients.

Disclosures
Seymour: Celgene: Research Funding. Young:Celgene Corporation: Employment, Equity Ownership. Tometsko:Celgene Corporation: Employment, Equity Ownership. Cavenagh:Celgene: Honoraria, Research Funding, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau. Thompson:Celgene Corporation: Employment, Equity Ownership. Whalen:Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Fitch:Celgene Corporation: Employment, Equity Ownership. Fox:Celgene Corporation: Employment, Equity Ownership. Dervan:Celgene Corporation: Employment, Equity Ownership. Foy:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership. Gribben:Acerta Pharma: Honoraria, Research Funding; Cancer Research UK: Research Funding; TG Therapeutics: Honoraria; Roche: Honoraria; NIH: Research Funding; Medical Research Council: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Abbvie: Honoraria; Kite: Honoraria; Pharmacyclics: Honoraria; Novartis: Honoraria; Janssen: Honoraria, Research Funding; Wellcome Trust: Research Funding; Unum: Equity Ownership.