For over a decade, the mainstay of multiple myeloma therapy has been small molecules that directly attack malignant plasma cell biology. However, potent immunotherapies have recently emerged, transforming the myeloma therapeutic landscape. Here we first review new promising strategies to target plasma cells through protein homeostasis and epigenetic modulators. We then discuss emerging immunotherapy strategies that are leading to dramatic results in patients. Finally, we focus on recent preclinical data suggesting that enforcing cell-surface antigen expression through small molecules may enhance immunotherapy efficacy and avoid resistance. We argue that these emerging observations point the way toward potential convergence between drug classes. With recent rapid progress we may finally be on the verge of the 'C' word: a cure for myeloma.

Cancer cells commonly develop resistance to immunotherapy by loss of antigen expression. Combinatorial treatments that increase levels of the target antigen on the surface of cancer cells have the potential to restore efficacy to immunotherapy. Here, we use our CRISPR interference- and CRISPR activation-based functional genomics platform to systematically identify pathways controlling cell surface expression of the multiple myeloma immunotherapy antigen B-cell maturation antigen (BCMA). We discovered that pharmacologic inhibition of HDAC7 and the Sec61 complex increased cell surface BCMA, including in primary patient cells. Pharmacologic Sec61 inhibition enhanced the antimyeloma efficacy of a BCMA-targeted antibody-drug conjugate. A CRISPR interference chimeric antigen receptor T cells (CAR-T cells) coculture screen enabled us to identify both antigen-dependent and antigen-independent mechanisms controlling response of myeloma cells to BCMA-targeted CAR-T cells. Thus, our study shows the potential of CRISPR screens to uncover mechanisms controlling response of cancer cells to immunotherapy and to suggest potential combination therapies.

Enhancing the efficacy of proteasome inhibitors (PI) is a central goal in myeloma therapy. We proposed that signaling-level responses after PI may reveal new mechanisms of action that can be therapeutically exploited. Unbiased phosphoproteomics after treatment with the PI carfilzomib surprisingly demonstrates the most prominent phosphorylation changes on splicing related proteins. Spliceosome modulation is invisible to RNA or protein abundance alone. Transcriptome analysis after PI demonstrates broad-scale intron retention, suggestive of spliceosome interference, as well as specific alternative splicing of protein homeostasis machinery components. These findings lead us to evaluate direct spliceosome inhibition in myeloma, which synergizes with carfilzomib and shows potent anti-tumor activity. Functional genomics and exome sequencing further support the spliceosome as a specific vulnerability in myeloma. Our results propose splicing interference as an unrecognized modality of PI mechanism, reveal additional modes of spliceosome modulation, and suggest spliceosome targeting as a promising therapeutic strategy in myeloma.

The myeloma surface proteome (surfaceome) determines tumor interaction with the microenvironment and serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to define the myeloma surfaceome at baseline, in drug resistance, and in response to acute drug treatment. We provide a scoring system for surface antigens and identify CCR10 as a promising target in this disease expressed widely on malignant plasma cells. We engineer proof-of-principle chimeric antigen receptor (CAR) T-cells targeting CCR10 using its natural ligand CCL27. In myeloma models we identify proteins that could serve as markers of resistance to bortezomib and lenalidomide, including CD53, CD10, EVI2B, and CD33. We find that acute lenalidomide treatment increases activity of MUC1-targeting CAR-T cells through antigen upregulation. Finally, we develop a miniaturized surface proteomic protocol for profiling primary plasma cell samples with low inputs. These approaches and datasets may contribute to the biological, therapeutic, and diagnostic understanding of myeloma.