The genomic landscape of Vk*MYC myeloma highlights shared pathways of transformation between mice and humans.

Multiple myeloma (MM) is a heterogeneous disease characterized by frequent MYC translocations. Sporadic MYC activation in the germinal center of genetically engineered Vk*MYC mice is sufficient to induce plasma cell tumors in which a variety of secondary mutations are spontaneously acquired and selected over time. Analysis of 119 Vk*MYC myeloma reveals recurrent copy number alterations, structural variations, chromothripsis, driver mutations, apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC) mutational activity, and a progressive decrease in immunoglobulin transcription that inversely correlates with proliferation. Moreover, we identify frequent insertional mutagenesis by endogenous retro-elements as a murine specific mechanism to activate NF-kB and IL6 signaling pathways shared with human MM. Despite the increased genomic complexity associated with progression, advanced tumors remain dependent on MYC. In summary, here we credential the Vk*MYC mouse as a unique resource to explore MM genomic evolution and describe a fully annotated collection of diverse and immortalized murine MM tumors.

Transcriptional Heterogeneity Overcomes Super-Enhancer Disrupting Drug Combinations in Multiple Myeloma.

Multiple myeloma (MM) is a malignancy that is often driven by MYC and that is sustained by IRF4, which are upregulated by super-enhancers. IKZF1 and IKZF3 bind to super-enhancers and can be degraded using immunomodulatory imide drugs (IMiD). Successful IMiD responses downregulate MYC and IRF4; however, this fails in IMiD-resistant cells. MYC and IRF4 downregulation can also be achieved in IMiD-resistant tumors using inhibitors of BET and EP300 transcriptional coactivator proteins; however, in vivo these drugs have a narrow therapeutic window. By combining IMiDs with EP300 inhibition, we demonstrate greater downregulation of MYC and IRF4, synergistic killing of myeloma in vitro and in vivo, and an increased therapeutic window. Interestingly, this potent combination failed where MYC and IRF4 expression was maintained by high levels of the AP-1 factor BATF. Our results identify an effective drug combination and a previously unrecognized mechanism of IMiD resistance. SIGNIFICANCE: These results highlight the dependence of MM on IKZF1-bound super-enhancers, which can be effectively targeted by a potent therapeutic combination pairing IMiD-mediated degradation of IKZF1 and IKZF3 with EP300 inhibition. They also identify AP-1 factors as an unrecognized mechanism of IMiD resistance in MM. See related article by Neri, Barwick, et al., p. 56. See related commentary by Yun and Cleveland, p. 5. This article is featured in Selected Articles from This Issue, p. 4.

ETV4-Dependent Transcriptional Plasticity Maintains MYC Expression and Results in IMiD Resistance in Multiple Myeloma.

Immunomodulatory drugs (IMiD) are a backbone therapy for multiple myeloma (MM). Despite their efficacy, most patients develop resistance, and the mechanisms are not fully defined. Here, we show that IMiD responses are directed by IMiD-dependent degradation of IKZF1 and IKZF3 that bind to enhancers necessary to sustain the expression of MYC and other myeloma oncogenes. IMiD treatment universally depleted chromatin-bound IKZF1, but eviction of P300 and BRD4 coactivators only occurred in IMiD-sensitive cells. IKZF1-bound enhancers overlapped other transcription factor binding motifs, including ETV4. Chromatin immunoprecipitation sequencing showed that ETV4 bound to the same enhancers as IKZF1, and ETV4 CRISPR/Cas9-mediated ablation resulted in sensitization of IMiD-resistant MM. ETV4 expression is associated with IMiD resistance in cell lines, poor prognosis in patients, and is upregulated at relapse. These data indicate that ETV4 alleviates IKZF1 and IKZF3 dependency in MM by maintaining oncogenic enhancer activity and identify transcriptional plasticity as a previously unrecognized mechanism of IMiD resistance. SIGNIFICANCE: We show that IKZF1-bound enhancers are critical for IMiD efficacy and that the factor ETV4 can bind the same enhancers and substitute for IKZF1 and mediate IMiD resistance by maintaining MYC and other oncogenes. These data implicate transcription factor redundancy as a previously unrecognized mode of IMiD resistance in MM. See related article by Welsh, Barwick, et al., p. 34. See related commentary by Yun and Cleveland, p. 5. This article is featured in Selected Articles from This Issue, p. 4.

The Vk*MYC Mouse Model recapitulates human multiple myeloma evolution and genomic diversity.

Despite advancements in profiling multiple myeloma (MM) and its precursor conditions, there is limited information on mechanisms underlying disease progression. Clincal efforts designed to deconvolute such mechanisms are challenged by the long lead time between monoclonal gammopathy and its transformation to MM. MM mouse models represent an opportunity to overcome this temporal limitation. Here, we profile the genomic landscape of 118 genetically engineered Vk*MYC MM and reveal that it recapitulates the genomic heterogenenity and life history of human MM. We observed recurrent copy number alterations, structural variations, chromothripsis, driver mutations, APOBEC mutational activity, and a progressive decrease in immunoglobulin transcription that inversely correlates with proliferation. Moreover, we identified frequent insertional mutagenesis by endogenous retro-elements as a murine specific mechanism to activate NF-kB and IL6 signaling pathways shared with human MM. Despite the increased genomic complexity associated with progression, advanced tumors remain dependent on MYC expression, that drives the progression of monoclonal gammopathy to MM.

Tumor burden limits bispecific antibody efficacy through T cell exhaustion averted by concurrent cytotoxic therapy.

BCMA-CD3-targeting bispecific antibodies (BsAb) are a recently developed immunotherapy class which shows potent tumor killing activity in multiple myeloma (MM). Here, we investigated a murine BCMA-CD3-targeting BsAb in the immunocompetent Vk*MYC and its IMiD-sensitive derivative Vk*MYChCRBN models of MM. The BCMA-CD3 BsAb was safe and efficacious in a subset of mice, but failed in those with high-tumor burden, consistent with clinical reports of BsAb in leukemia. The combination of BCMA-CD3 BsAb with pomalidomide expanded lytic T cells and improved activity even in IMiD resistant high-tumor burden cases. Yet, survival was only marginally extended due to acute toxicity and T cell exhaustion, which impaired T cell persistence. In contrast, the combination with cyclophosphamide was safe and allowed for a tempered pro-inflammatory response associated with long-lasting complete remission. Concurrent cytotoxic therapy with BsAb actually improved T cell persistence and function, offering a promising approach to patients with a large tumor burden.

Monosomic loss of MIR15A/MIR16-1 is a driver of multiple myeloma proliferation and disease progression.

The most common genetic abnormality in multiple myeloma (MM) is the deletion of chromosome 13, seen in almost half of newly diagnosed patients. Unlike chronic lymphocytic leukemia, where a recurrent minimally deleted region including MIR15A/MIR16-1 has been mapped, the deletions in MM predominantly involve the entire chromosome and no specific driver gene has been identified. Additional candidate loci include RB1 and DIS3, but while biallelic deletion of RB1 is associated with disease progression, DIS3 is a common essential gene and complete inactivation is not observed. The Vk*MYC transgenic mouse model of MM spontaneously acquires del(14), syntenic to human chromosome 13, and Rb1 complete inactivation, but not Dis3 mutations. Taking advantage of this model, we explored the role in MM initiation and progression of two candidate loci on chromosome 13: RB1 and MIR15A/MIR16-1. Monoallelic deletion of Mir15a/Mir16-1 but not Rb1 was sufficient to accelerate the development of monoclonal gammopathy in wildtype mice, and the progression of MM in Vk*MYC mice, resulting in increased expression of Mir15a/Mir16-1 target genes and plasma cell proliferation, which was similarly observed in patients with MM.

Identification of PIKfyve kinase as a target in multiple myeloma.

The cellular cytotoxicity of APY0201, a PIKfyve inhibitor, against multiple myeloma was initially identified in an unbiased in vitro chemical library screen. The activity of APY0201 was confirmed in all 25 cell lines tested and in 40% of 100 ex vivo patient-derived primary samples, with increased activity in primary samples harboring trisomies and lacking t(11;14). The broad anti-multiple myeloma activity of PIKfyve inhibitors was further demonstrated in confirmatory screens and showed the superior potency of APY0201 when compared to the PIKfyve inhibitors YM201636 and apilimod, with a mid-point half maximal effective concentration (EC50) at nanomolar concentrations in, respectively, 65%, 40%, and 5% of the tested cell lines. Upregulation of genes in the lysosomal pathway and increased cellular vacuolization were observed in vitro following APY0201 treatment, although these cellular effects did not correlate well with responsiveness. We confirm that PIKfyve inhibition is associated with activation of the transcription factor EB, a master regulator of lysosomal biogenesis and autophagy. Furthermore, we established an assay measuring autophagy as a predictive marker of APY0201 sensitivity. Overall, these findings indicate promising activity of PIKfyve inhibitors secondary to disruption of autophagy in multiple myeloma and suggest a strategy to enrich for likely responders.

The varied distribution and impact of RAS codon and other key DNA alterations across the translocation cyclin D subgroups in multiple myeloma.

We examined a set of 805 cases that underwent DNA sequencing using the FoundationOne Heme (F1H) targeted sequencing panel and gene expression profiling. Known and likely variant calls from the mutational data were analyzed for significant associations with gene expression defined translocation cyclin D (TC) molecular subgroups. The spectrum of KRAS, NRAS, and BRAF codon mutations varied across subgroups with NRAS mutations at Q61 codon being common in hyperdiploid (HRD) and t(11;14) myeloma while being rare in MMSET and MAF. In addition, the presence of RAS-RAF mutations was inversely associated with NFκB pathway activation in all subgroups excluding MAF. In the MMSET subgroup, cases with low FGFR3 expression frequently had RAS-RAF mutations. Conditional inference tree analysis determined that mutation and homozygous deletion of TP53, CDKN2C, and RB1 were key prognostic factors associated with adverse outcome in a non-relapse clinical setting. In conclusion, this study highlights the heterogeneity in the distribution and clinical outcomes of RAS codon and other mutations in multiple myeloma dependent upon primary molecular subgroup.

Removing batch effects from purified plasma cell gene expression microarrays with modified ComBat.

BACKGROUND: Gene expression profiling (GEP) via microarray analysis is a widely used tool for assessing risk and other patient diagnostics in clinical settings. However, non-biological factors such as systematic changes in sample preparation, differences in scanners, and other potential batch effects are often unavoidable in long-term studies and meta-analysis. In order to reduce the impact of batch effects on microarray data, Johnson, Rabinovic, and Li developed ComBat for use when combining batches of gene expression microarray data. We propose a modification to ComBat that centers data to the location and scale of a pre-determined, 'gold-standard' batch. This modified ComBat (M-Combat) is designed specifically in the context of meta-analysis and batch effect adjustment for use with predictive models that are validated and fixed on historical data from a 'gold-standard' batch. RESULTS: We combined data from MIRT across two batches ('Old' and 'New' Kit sample preparation) as well as external data sets from the HOVON-65/GMMG-HD4 and MRC-IX trials into a combined set, first without transformation and then with both ComBat and M-ComBat transformations. Fixed and validated gene risk signatures developed at MIRT on the Old Kit standard (GEP5, GEP70, and GEP80 risk scores) were compared across these combined data sets. Both ComBat and M-ComBat eliminated all of the differences among probes caused by systematic batch effects (over 98% of all untransformed probes were significantly different by ANOVA with 0.01 q-value threshold reduced to zero significant probes with ComBat and M-ComBat). The agreement in mean and distribution of risk scores, as well as the proportion of high-risk subjects identified, coincided with the 'gold-standard' batch more with M-ComBat than with ComBat. The performance of risk scores improved overall using either ComBat or M-Combat; however, using M-ComBat and the original, optimal risk cutoffs allowed for greater ability in our study to identify smaller cohorts of high-risk subjects. CONCLUSION: M-ComBat is a practical modification to an accepted method that offers greater power to control the location and scale of batch-effect adjusted data. M-ComBat allows for historical models to function as intended on future samples despite known, often unavoidable systematic changes to gene expression data.