Blake T. Aftab

Targeting the AAA ATPase p97 as an Approach to Treat Cancer through Disruption of Protein Homeostasis

p97 is a AAA-ATPase with multiple cellular functions, one of which is critical regulation of protein homeostasis pathways. We describe the characterization of CB-5083, a potent, selective, and orally bioavailable inhibitor of p97. Treatment of tumor cells with CB-5083 leads to accumulation of poly-ubiquitinated proteins, retention of endoplasmic reticulum-associated degradation (ERAD) substrates, and generation of irresolvable proteotoxic stress, leading to activation of the apoptotic arm of the unfolded protein response. In xenograft models, CB-5083 causes modulation of key p97-related pathways, induces apoptosis, and has antitumor activity in a broad range of both hematological and solid tumor models. Molecular determinants of CB-5083 activity include expression of genes in the ERAD pathway, providing a potential strategy for patient selection.

Validation of the Hsp70–Bag3 Protein–Protein Interaction as a Potential Therapeutic Target in Cancer

Hsp70 is a stress-inducible molecular chaperone that is required for cancer development at several steps. Targeting the active site of Hsp70 has proven relatively challenging, driving interest in alternative approaches. Hsp70 collaborates with the Bcl2-associated athanogene 3 (Bag3) to promote cell survival through multiple pathways, including FoxM1. Therefore, inhibitors of the Hsp70–Bag3 protein–protein interaction (PPI) may provide a noncanonical way to target this chaperone. We report that JG-98, an allosteric inhibitor of this PPI, indeed has antiproliferative activity (EC50 values between 0.3 and 4 μmol/L) across cancer cell lines from multiple origins. JG-98 destabilized FoxM1 and relieved suppression of downstream effectors, including p21 and p27. On the basis of these findings, JG-98 was evaluated in mice for pharmacokinetics, tolerability, and activity in two xenograft models. The results suggested that the Hsp70–Bag3 interaction may be a promising, new target for anticancer therapy. Mol Cancer Ther; 14(3); 642–8. ©2015 AACR.

Antibody-drug conjugate targeting CD46 eliminates multiple myeloma cells

Multiple myeloma is incurable by standard approaches because of inevitable relapse and development of treatment resistance in all patients. In our prior work, we identified a panel of macropinocytosing human monoclonal antibodies against CD46, a negative regulator of the innate immune system, and constructed antibody-drug conjugates (ADCs). In this report, we show that an anti-CD46 ADC (CD46-ADC) potently inhibited proliferation in myeloma cell lines with little effect on normal cells. CD46-ADC also potently eliminated myeloma growth in orthometastatic xenograft models. In primary myeloma cells derived from bone marrow aspirates, CD46-ADC induced apoptosis and cell death, but did not affect the viability of nontumor mononuclear cells. It is of clinical interest that the CD46 gene resides on chromosome 1q, which undergoes genomic amplification in the majority of relapsed myeloma patients. We found that the cell surface expression level of CD46 was markedly higher in patient myeloma cells with 1q gain than in those with normal 1q copy number. Thus, genomic amplification of CD46 may serve as a surrogate for target amplification that could allow patient stratification for tailored CD46-targeted therapy. Overall, these findings indicate that CD46 is a promising target for antibody-based treatment of multiple myeloma, especially in patients with gain of chromosome 1q.

Genome-wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients

Here we perform the first genome-wide association study (GWAS) of multiple myeloma (MM) survival. In a meta-analysis of 306 MM patients treated at UCSF and 239 patients treated at the Mayo clinic, we find a significant association between SNPs near the gene FOPNL on chromosome 16p13 and survival (rs72773978; P=6 × 10(-10)). Patients with the minor allele are at increased risk for mortality (HR: 2.65; 95% CI: 1.94-3.58) relative to patients homozygous for the major allele. We replicate the association in the IMMEnSE cohort including 772 patients, and a University of Utah cohort including 318 patients (rs72773978 P=0.044). Using publicly available data, we find that the minor allele was associated with increased expression of FOPNL and increased expression of FOPNL was associated with higher expression of centrosomal genes and with shorter survival. Polymorphisms at the FOPNL locus are associated with survival among MM patients.

The p97 inhibitor CB-5083 is a unique disrupter of protein homeostasis in models of Multiple Myeloma.

Inhibition of the AAA ATPase, p97, was recently shown to be a novel method for targeting the ubiquitin proteasome system, and CB-5083, a first-in-class inhibitor of p97, has demonstrated broad antitumor activity in a range of both hematologic and solid tumor models. Here, we show that CB-5083 has robust activity against multiple myeloma cell lines and a number of in vivo multiple myeloma models. Treatment with CB-5083 is associated with accumulation of ubiquitinated proteins, induction of the unfolded protein response, and apoptosis. CB-5083 decreases viability in multiple myeloma cell lines and patient-derived multiple myeloma cells, including those with background proteasome inhibitor (PI) resistance. CB-5083 has a unique mechanism of action that combines well with PIs, which is likely owing to the p97-dependent retro-translocation of the transcription factor, Nrf1, which transcribes proteasome subunit genes following exposure to a PI. In vivo studies using clinically relevant multiple myeloma models demonstrate that single-agent CB-5083 inhibits tumor growth and combines well with multiple myeloma standard-of-care agents. Our preclinical data demonstrate the efficacy of CB-5083 in several multiple myeloma disease models and provide the rationale for clinical evaluation as monotherapy and in combination in multiple myeloma. Mol Cancer Ther; 16(11); 2375–86. ©2017 AACR.

Repurposing tofacitinib as an anti-myeloma therapeutic to reverse growth-promoting effects of the bone marrow microenvironment

The myeloma bone marrow microenvironment promotes proliferation of malignant plasma cells and resistance to therapy. Activation of JAK/STAT signaling is thought to be a central component of these microenvironment-induced phenotypes. In a prior drug repurposing screen, we identified tofacitinib, a pan-JAK inhibitor Food and Drug Administration (FDA) approved for rheumatoid arthritis, as an agent that may reverse the tumor-stimulating effects of bone marrow mesenchymal stromal cells. Herein, we validated in vitro, in stromal-responsive human myeloma cell lines, and in vivo, in orthotopic disseminated xenograft models of myeloma, that tofacitinib showed efficacy in myeloma models. Furthermore, tofacitinib strongly synergized with venetoclax in coculture with bone marrow stromal cells but not in monoculture. Surprisingly, we found that ruxolitinib, an FDA approved agent targeting JAK1 and JAK2, did not lead to the same anti-myeloma effects. Combination with a novel irreversible JAK3-selective inhibitor also did not enhance ruxolitinib effects. Transcriptome analysis and unbiased phosphoproteomics revealed that bone marrow stromal cells stimulate a JAK/STAT-mediated proliferative program in myeloma cells, and tofacitinib reversed the large majority of these pro-growth signals. Taken together, our results suggest that tofacitinib reverses the growth-promoting effects of the tumor microenvironment. As tofacitinib is already FDA approved, these results can be rapidly translated into potential clinical benefits for myeloma patients.

Erratum: Genome-wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients (Nature Communications (2015) 6 (7539) DOI: 10.1038/ncomms8539)

In this Article, members of the UCSF cohort who had been alive for longer than two years were inadvertently included in the data presented in Table 3. USCF/old treatments should have 109 patients with a hazard ratio of 3.35 and a P value of 0.00028 instead of the 124 patients with a hazard ratio of 3.37 and a P value of 0.00026. The USCF/new patients should have 187 patients with a hazard ratio of 3.57 and a P value of 0.0007 instead of the 208 patients with a hazard ratio of 3.62 and a P value of 0.0006. Finally, in the table legend, the first line should read ‘All models are adjusted for age, gender and principal components 1–3’. The exclusion of these individuals does not change the conclusions of the study. The correct version of Table 3 appears below.

Abstract A2-57: Identification of genetic vulnerabilities within the proteostasis network of multiple myeloma

Multiple myeloma (MM) remains an incurable disease afflicting more than 20,000 patients yearly in the US alone. Because of their secretory nature, MM cells rely on the proteostasis network and re-wire it to their advantage. We focused on two interconnected essential pathways within the proteostasis network to query genetic vulnerabilities yielding synthetic lethality. These pathways are the ubiquitin-proteasome system (UPS) and the unfolded protein response (UPR). Standard-of-care proteasome inhibitors, like bortezomib, remain non-curative in MM patients, suggesting the selection of genetic escape routes. The same rationale is applicable to the UPR, a conserved regulatory network overseeing the processing capacity of the endoplasmic reticulum (ER). Since proteasomal degradation of unfolded ER client proteins is accomplished after their dislocation and ubiquitination, we reasoned that common genetic escape routes might exist within the UPS and the UPR. Because single agents provide the driving force for acquired drug resistance and do not lead to long-term remission, we employed a systems-level shRNA screening method that systematically identified synthetic-lethal interactions that can enhance the therapeutic benefit of proteasome inhibition or modulation of the UPR. In the latter, we focused on the UPR branch overseen by the sensor kinase/nuclease IRE1 because it is thought to confer a survival advantage to MM. Applying chemical-genetics approaches using bortezomib or novel chemical inhibitors of IRE1, and an ultra-complex shRNA library we developed, we performed pooled shRNA screens in RPMI-8226 and MM1-S MM cells and identified genes whose diminished function impact the response to proteasome or IRE1 inhibition. Unlike proteasome inhibition, blocking IRE1 did not lead to considerable MM cell death, suggesting that IRE1 alone is not a fate determinant but a weakness that can be exploited through the identification of synthetic-lethal combinations. We applied the same rationale to proteasome inhibition and found synthetic-lethal pairs. Because some of these genes can be targeted pharmacologically, we explored the susceptibility of a panel of MM cells to combinations of bortezomib and drug-like molecules, including novel Hsp70 inhibitors. Retrospective analyses on publicly available gene expression datasets of MM patients treated with bortezomib indicated that several of the genes we found in our screen also predicted clinical outcomes. Together, our preliminary results indicate our approach is a powerful tool for the discovery of synthetic-lethal pairs that can be exploited in combination therapies. Citation Format: Diego Acosta-Alvear, Martin Kampmann, Min Y. Cho, Blake T. Aftab, Xiaokai Li, Jason E. Gestwicki, Marc A. Shuman, Jonathan S. Weissman, Peter Walter. Identification of genetic vulnerabilities within the proteostasis network of multiple myeloma. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-57.

Abstract 5078: Genome wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients

Background: Genome wide association studies (GWAS) have recently identified 8 loci identified with multiple myeloma (MM) susceptibility. We hypothesized that germ line genetic variants may also affect MM progression. We performed the first GWAS of MM survival, by conducting a meta-analysis of two existing studies at University of California San Francisco (UCSF) and the Mayo Clinic, and replicating findings in the International Multiple Myeloma rESEarch (IMMEnSE) consortium. Methods: The UCSF study included 353 MM patients genotyped on an Illumina Omni5 and Illumina 660 array. The Mayo clinic study included 239 MM patients genotyped on an Affymetrix 6.0 array. We imputed missing genotypes using the 1000 Genomes dataset and performed a GWAS for survival using proportional hazards models adjusting for age and gender and genetic ancestry using principal components analysis. We conducted a meta-analysis of the results from the two GWAS. We replicated the top SNPs in the IMMEnSE cohort which included 772 patients with survival data from 7 European countries and one North American site. We used the dataset from Grundberg et al (Nat Genetics 2012) to test for an association between SNPs associated with survival and gene expression in immortalized lymphocytes. We used gene expression data from Zhan et al (Blood 2006) to analyze the association between expression and survival. Results: In meta-analysis, we found a genome wide significant association between SNPs on a region at 16p13 and survival (rs72773978; p=2.9x10e-10). Patients with the minor allele were at increased risk for mortality (HR 2.73; 95% CI: 1.99 - 3.73). The top associated SNPs were all in strong linkage disequilibrium and were centered over the gene FOPNL. We replicated the association in the IMMEnSE cohort and found a significant association between the top SNP from the discovery dataset (rs72773978 p=0.037). We used previously published data to determine the association between gene expression and the top associated SNPs from the GWAS. The top SNP (rs72773978) was not in previously published eQTL databases, so we used rs7201759 which was also associated with survival in our data (p=3.8x10e-10) as a proxy. The minor allele for this SNP was associated with increased levels of expression of FOPNL (p=9x10e-5), but not with expression of any other genes within a 1 megabase region. Finally, we also observed an association between increased expression of FOPNL and shorter survival (HR: 2.62 per standard deviation.; 95% CI: 1.08 - 6.32). Conclusion: Germ line variants at 16p13 near the FOPNL gene are associated with survival among MM patients. FOPNL is thought to be involved in centrosomal function, and centrosomal activity has previously been associated with survival in MM patients. Our results support this previous observation. Furthermore, they suggest that germ line variants could also be useful in assessing prognosis for patients with MM. Citation Format: Elad Ziv, Eric Dean, Donglei Hu, Alessandro Martino, Daniel Serie, Daniele Campa, Blake Aftab, Paige Bracci, Gabriele Buda, Jennifer Caswell, Charles Dumontet, Marek Dudzinski, Laura Fejerman, Alexandra Greenberg, Scott Hunstman, Artur Jurczyszyn, Krzysztof Jamroziak, Shaji Kumar, Herlander Marques, Thomas Martin, Joaquin Martinez-Lopez, Vincent Rajkumar, Juan Sainz, Annette Juul Vangsted, Marzena Watek, Jeffrey Wolf, Susan Slager, Federico Canzian, Celine Vachon. Genome wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5078. doi:10.1158/1538-7445.AM2014-5078

Abstract PR07: Systematic genetic interaction maps reveal rewiring of the stress response network and resulting vulnerabilities in leukemia and multiple myeloma cells

Systematic, high-density mapping of genetic interactions is a powerful approach to elucidate functional pathways and reveal synthetic lethal gene pairs, and has successfully been applied in microorganisms. We have recently developed a functional genomics platform that enables the construction of high-density genetic interaction maps in mammalian cells. In a first step, we conduct pooled primary screens using an ultracomplex shRNA library that targets each protein-coding gene with 25 independent shRNAs and contains >1,000 negative control shRNAs. This strategy enables us to robustly identify hit genes and shRNAs that target them effectively, while minimizing the identification of false-positive hits, which has plagued many genome-wide RNAi screens. In a second step, we construct and screen a double-shRNA library targeting all pairwise combinations of hit genes of interest to construct a high-density genetic interaction map. Thus, our approach enables us to determine 100,000s of genetic interactions in a single experiment. Here, we present the application of our platform to identify adaptations and vulnerabilities in the stress response network of leukemia and multiple myeloma cells. Stress response pathways, including the unfolded protein response, starvation, hypoxia and oxidative stress responses, and the associated induction of autophagy, play important roles in cancer cell survival, drug resistance and tumor progression. The goal of the research presented here is to systematically characterize vulnerabilities in the stress response network of cancer cells, and in particular, to identify synthetic-lethal vulnerabilities that are potential new targets for combination drug therapy. We conducted our first experiments in two human cell lines derived from hematologic malignancies, K562 (leukemia) and RPMI-8226 (multiple myeloma), for which we determined genetic vulnerabilities and their genetic interactions in the absence and presence of stress-inducing agents. We discovered several genetic vulnerabilities that can be targeted pharmacologically. An important class of factors we detected as vulnerabilities in our screens are Hsp70 proteins, which are commonly upregulated under stress conditions and in cancer cells. We have recently synthesized a series of small-molecule Hsp70 inhibitors, which we have successfully used to selectively kill cancer cells. Using a chemical-genetics approach, we have probed the genetic factors affecting the sensitivity of cancer cells to two of these inhibitors with selectivity for Hsp70 proteins in different subcellular compartments. We externally validated several of the synthetic-lethal vulnerabilities identified in our screens by demonstrating synergistic effects of drug combinations targeting these gene pairs in panels of cancer cell lines. Comparison of drug sensitivities across our cell line panel, in conjunction with our experimentally derived set of genetic vulnerabilities, has generated testable hypotheses for the role of the genetic background in determining vulnerabilities related to the stress response network. Intriguingly, expression levels of several genes we identified as vulnerabilities in multiple myeloma cells are prognostic of patient survival in a published multiple myeloma clinical trial. This abstract is also presented as poster B25. Citation Format: Martin Kampmann, Diego Acosta-Alvear, Min Cho, Yuwen Chen, Xiaokai Li, Luke Gilbert, Blake T. Aftab, Jason Gestwicki, Peter Walter, Jonathan S. Weissman. Systematic genetic interaction maps reveal rewiring of the stress response network and resulting vulnerabilities in leukemia and multiple myeloma cells. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr PR07.