Multiple myeloma is an incurable and fatal cancer of immunoglobulin-secreting plasma cells. Current treatments fail because cells that can resist therapy-induced apoptosis arise in patients and cause relapse. To identify the best adjunct targets to improve killing of multiple myeloma cells, we undertook a deep profiling approach using mass cytometry (CyTOF) to simultaneously detect regulators of cell death, cell cycle, cell signaling and cancer-related pathways at the single-cell level following treatment with standard-of-care drugs, dexamethasone or bortezomib.
Time-resolved visualization algorithms combined with machine learning classification models identified a hierarchy of markers that best predict cancer cell death following treatment. We tested these predictions by combining dexamethasone with a novel inhibitor of the top survival factor hit (MCL-1) and observed synergistic killing of multiple myeloma cells lines and naïve patient cells ex vivo. Collectively, these data indicate that deep profiling of cell death responses at the single-cell level can uncover critical cancer cell vulnerabilities and predict synergies between anti-cancer agents. Furthermore, the finding that BH3 mimetics targeting MCL-1 combined with dexamethasone synergize to induce apoptotic cell death of multiple myeloma cells offers a combination that could be explored in clinical trials for the induction of deeper responses.