Immunomodulatory Effects of MEK Inhibition in Multiple Myeloma

Introduction

As part of the Multiple Myeloma Research Foundation (MMRF) MyDRUG umbrella clinical trial, we compared immune cell transcriptomic and proteomic signatures of multiple myeloma bone marrow samples from patients assessed by single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF). The goal of our study is to evaluate the effects of cobimetinib on the immune repertoire over the treatment course at single-cell resolution.

Methods

Bone marrow samples were collected from patients prior to therapy with cobimetinib (baseline/BL), after 2 cycles of cobimetinib therapy (EOC2), after 2 cycles of combination cobimetinib with IPd (EOC4) and at the end of treatment or at disease progression (EOT). All samples were processed into CD138+ myeloma cell and CD138- “immune cell” fractions for single-cell analysis. In this study, the CD138- “immune cell” fractions were transcriptionally profiled by single-cell RNA-sequencing (scRNA) at up to four time points.

Results

Transcriptome profiles of approximately 50,000 cells were analyzed across 22 samples from 9 patients with tumor MAPK Pathway mutations including: BRAF (p.K483Q, p.V600E, n=2); KRAS (p.Q61H, p.G12V, p.G12R, n=3); NRAS (p.Q61H, p.Q61R, p.Q61K, n=4). A subset of paired samples were subject to CyTOF with two immune related panels to supplement the single-cell transcriptomic findings. Focusing on one immune panel, 4 samples were profiled at baseline and end of cycle 2 while two samples were profiled only at baseline capturing over 600,000 cells spanning both timepoints. Our immune focused CyTOF panel contained 41 markers including T and NK cell markers (CD4,CD8A,CD3, GZMB, CD56), Myeloid lineage markers (CD14), B/Plasma markers (CD19, CD20, SLAMF7, CD38) among others. The largest populations captured by CyTOF included 260,000 neutrophils, 139,000 monocytes, 130,000 CD4/CD8 T cells, 43,000 NK cells, 40,000 dendritic cells and 22,000 B/plasmablasts/myeloma cells. Exhaustion markers, including LAG3 and TIGIT, are increased in CD8 and CD4 T cells after MEK inhibition, while PD1 is downregulated. PD-L1 is upregulated in both T cell compartments (CD4/CD8), monocytes and in residual myeloma cells profiled by both CyTOF and scRNA-seq. Both the IFNG and STAT1 pathways are concurrently upregulated post MEK inhibition in transcriptionally distinct CD8 T cell subsets profiled by scRNA-seq, suggesting a mechanism influencing PD-L1 expression.

Conclusions

These data indicate IFNG pathway activation by CD8+ T cells post MEK inhibition promotes PD-L1 expression on residual myeloma cells, suggesting the PD-L1 and IFNG signaling axes is activated in relapsed refractory myeloma patients after MEKi treatment. Here we present immunophenotypic and transcriptional profiling of longitudinal samples pre/post-MEK inhibition with multiple myeloma patients which can inform precision guided treatment options.

Cho:Genentech Roche: Research Funding; MMRF: Current Employment; BMS: Research Funding; Takeda: Research Funding. Kumar:Novartis: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; MedImmune/AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Other: Independent review committee participation; Sanofi: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.