Identification of Target Pathways of Acquired IMiD and Proteasome Inhibitor Resistance in Multiple Myeloma

Immunomodulatory drugs (IMiDs) such as lenalidomide and pomalidomide, and proteasome inhibitors (PIs) such bortezomib and carfilzomib are critical components of anti-multiple myeloma (MM) therapy. Despite the initial effectiveness of these therapies, MM patients all eventually develop refractory disease. Therefore, new agents and new combinations are needed to bolster the current armamentarium and to meet the individual needs of MM patients. We developed a non-biased method to identify upregulated pathways in IMiD and PI-resistant myeloma cell lines using a combination of activity-based protein profiling (ABPP) and a high-throughput protein kinase inhibitor (PKI) viability screen. Target validation was then performed using ex vivo functional PKI screens of MM patient specimens. The MM cell lines MM1.S, KAS6, 8226, and U266 along with their drug resistant counterparts MM1.S-R10R, KAS6-R10R, 8226-B25, and U266-PR, were grown in mono-culture for 24h and lysates were enriched for ATP binding proteins by affinity purification versus a chemical probe (ActiveX, Thermo). Tryptic peptides were measured using discovery proteomics (nano-UPLC and QExactive Plus mass spectrometer). Using this method, 59, 87, 85, and 35 kinases out of a total of 660, 1153, 715, and 688 proteins were preferentially enriched by 2-fold change from MM1.S-R10R, KAS6-R10R, 8226-B25, and U266-PR myeloma cells compared to parental cell lines, respectively. As proof of concept, 11 proteins dysregulated in PI-resistant lines are critical for proteasome function, including core subunit (20S) and regulatory subunit (19S) proteins. Twenty-four kinases were common among IMiD or PI-resistant cell line pairs and eight kinases were common to all four resistant cell lines, representing pathways with increased activity in acquired resistance to these two classes of therapeutic agents: CDK1, PLK1, ILK, DNAPK, Syk, MKK7, NEK2, and MARK3. These eight kinases were chosen for target validation, along with 21 others identified by pathway analysis using the Kyoto Encyclopedia of Genes and Genomes database to identify signaling networks. A label-free, high throughput assay was used to measure the viability of MM cells grown in a collagen matrix with bone marrow stroma cells in 384-well plates to simulate the tumor microenvironment by capturing brightfield images every 30 minutes for 96h using a motorized microscope equipped with an incubation chamber. Digital image analysis software measures live cell numbers by detecting membrane motion and generates viability curves as a function of drug concentration and exposure time (Silva et al . Cancer Research 2017). This functional screen confirmed known MM survival networks, validated three kinases/PKIs and highlighted novel targetable pathways. Two PKIs, dinaciclib (CDK1) and volasertib (PLK1) consistently achieved LD50s in the low-nanomolar range in all eight cell lines in accordance with the proteomic data. To provide an additional level of screening, the same PKI panel was tested by viability screening of CD138-MACS-selected cells from MM patient specimens. Several PKIs showed significant activity in primary MM specimens, with dinaciclib active in 100% (n=22), volasertib in 100% (n=5) and the PLK1i, BI2536, in 87% (n=38) of patient samples examined. Among these, dinaciclib showed the most activity in patient specimens with an average 96h LD50 of 56 nM. Future work will use molecular strategies, including RNAi and inducible expression systems, to explore dysregulated pathways in IMiD and PI resistant cell lines and refractory or relapsed patient specimens. As an additional strategy, we have processed over 220 relapsed/refractory and newly diagnosed MM patients that have RNAseq data obtained from the same biopsy through the Total Cancer Care/M2Gen/ORIEN network at Moffitt Cancer Center, over two-thirds of these were tested for sensitivity to PIs and over half were tested for sensitivity to IMiDs. Patients will be stratified into cohorts based on ex vivo drug sensitivity to mine gene expression data with the goal of discovering tumor vulnerabilities that arise during therapy. Our three-tiered pharmaco-proteomic screen identified kinases critical to MM survival in the context of acquired drug resistance and represents a unique workflow to find tumor vulnerabilities that arise during therapy.