Faculty Bibliography

PURPOSE/OBJECTIVE:Molibresib is a selective, small molecule inhibitor of the BET protein family. This was an open-label, two-part, Phase I/II study investigating molibresib monotherapy for the treatment of hematological malignancies (NCT01943851). EXPERIMENTAL DESIGN/METHODS:Part 1 (dose escalation) determined the recommended Phase 2 dose (RP2D) of molibresib in patients with acute myeloid leukemia (AML), non-Hodgkin's lymphoma (NHL), or multiple myeloma. Part 2 (dose expansion) investigated the safety and efficacy of molibresib at the RP2D in patients with relapsed/refractory myelodysplastic syndrome (MDS; as well as AML evolved from antecedent MDS) or cutaneous T cell lymphoma (CTCL). The primary endpoint in Part 1 was safety and the primary endpoint in Part 2 was objective response rate (ORR). RESULTS:There were 111 patients enrolled (87 in Part 1, 24 in Part 2). Molibresib RP2Ds of 75 mg QD (for MDS) and 60 mg QD (for CTCL) were selected. Most common Grade 3+ AEs included thrombocytopenia (37%), anemia (15%) and febrile neutropenia (15%). Six patients achieved complete responses (three in Part 1 [two AML, one NHL], three in Part 2 [MDS]), and seven patients achieved partial responses (six in Part 1 [four AML, two NHL], one in Part 2 [MDS]). The ORRs for Part 1, Part 2, and the total study population were 10% (95% CI: 4.8-18.7), 25% (95% CI: 7.3-52.4), and 13% (95% CI: 6.9-20.6), respectively. CONCLUSIONS:While anti-tumor activity was observed with molibresib, use was limited by gastrointestinal and thrombocytopenia toxicities. Investigations of molibresib as part of combination regimens may be warranted.

Large-scale analyses of genomic data from newly-diagnosed multiple myeloma patients (ndMM) have been undertaken, however, large-scale analysis of relapsed/refractory multiple myeloma (rrMM) has not been performed. We hypothesize that somatic variants chronicle the therapeutic exposures and clonal structure of myeloma from ndMM to rrMM stages. We generated whole genome sequencing (WGS) data from 418 tumors (386 patients) derived from six rrMM clinical trials and compared them with WGS from 198 unrelated ndMM patients in a population-based case-control fashion. We identified significantly enriched events at the rrMM stage, including drivers (DUOX2, EZH2, TP53), biallelic inactivation (TP53), non-coding mutations in bona fide drivers (TP53BP1, BLM), copy number aberrations (CNA; 1qGain, 17pLOH) and double-hit events (Amp1q-ISS3, 1qGain-17pLOH). Mutational signature analysis identified a subclonal defective mismatch repair signature enriched in rrMM and highly active in high mutation burden tumors, a likely feature of therapy-associated expanding subclones. Further analysis focused on the association of genomic aberrations enriched at different stages of resistance to immunomodulatory agent (IMiDsÃ’)-based therapy. This analysis revealed that TP53, DUOX2, 1qGain and 17pLOH increased in prevalence from ndMM to lenalidomide (LEN)- to pomalidomide (POM)-resistant stages while enrichment of MAML3 along with IGL and MYC translocations distinguished POM from the LEN subgroup. Genomic drivers associated with rrMM are those that confer clonal selective advantage under therapeutic pressure. Their role in therapy evasion should be evaluated further in longitudinal patient samples, to confirm these associations with the evolution of clinical resistance and to identify molecular subsets of rrMM for the development of targeted therapies.

Aminopeptidases, which catalyze the cleavage of amino acids from the amino terminus of proteins, are widely distributed in the natural world and play a crucial role in cellular processes and functions, including metabolism, signaling, angiogenesis, and immunology. They are also involved in the homeostasis of amino acids and proteins that are required for cellular proliferation. Tumor cells are highly dependent on the exogenous supply of amino acids for their survival, and overexpression of aminopeptidase facilitates rapid tumor cell proliferation. In addition, clinical studies have demonstrated that patients with cancers with high aminopeptidase expression often have poorer outcomes. Emerging evidence supports the rationale of inhibiting aminopeptidase activity as a targeted approach for novel treatment options, as limiting the availability of amino acids can be selectively lethal to tumor cells. While there are agents that directly target aminopeptidases that demonstrate potential as cancer therapies, such as bestatin and tosedostat, more selective and more targeted therapeutic approaches are needed. This article specifically looks at the biological role of aminopeptidases in both normal and cancer processes, and their potential as a biological target for future therapeutic strategies. When examining previous publications, most do not cover aminopeptidases and their role in cancer processes. Aminopeptidases play a vital role in cell processes and functions; however, their overexpression may lead to a rapid proliferation of tumor cells. Emerging evidence supports the rationale of leveraging aminopeptidase activity as a targeted approach for new oncological treatments. This article specifically looks at the biological role of aminopeptidases in both normal and cancer processes, and their potential as a biological target for future therapeutic strategies.

Early alterations within the bone marrow microenvironment that contribute to the progression of multiple myeloma (MM) from its precursor stages could hold the key to identifying novel therapeutic approaches, yet the intrinsic variability in cellular populations between patients together with differences in sample processing and analysis methods have made it difficult to identify consistent changes between datasets. Here, we used single-cell RNA sequencing of BM cells from precursor stages, monoclonal gammopathy of unknown significance (MGUS), smoldering MM (SMM) and newly diagnosed MM and analyzed our data in combination with a previously published dataset that used a similar patient population and sample processing. Despite vast interpatient heterogeneity, some alterations were seen consistently in both datasets. We identified changes in immune cell populations as disease progressed that were characterized by a substantial decrease in memory and naïve CD4 T cells and an increase in CD8+ effector T cells and T-regulatory cells. These alterations were further accompanied by an enrichment of non-clonal memory B cells and an increase of CD14 and CD16 monocytes in MM compared to its precursor stages. These results provide crucial information of the immune changes associated with the progression to clinical MM and can help to develop immune based strategies for patient stratification and early therapeutic intervention.

Deciphering Multiple Myeloma evolution in the whole bone marrow is key to inform curative strategies. Here, we perform spatial-longitudinal whole-exome sequencing, including 140 samples collected from 24 Multiple Myeloma patients during up to 14 years. Applying imaging-guided sampling we observe three evolutionary patterns, including relapse driven by a single-cell expansion, competing/co-existing sub-clones, and unique sub-clones at distinct locations. While we do not find the unique relapse sub-clone in the baseline focal lesion(s), we show a close phylogenetic relationship between baseline focal lesions and relapse disease, highlighting focal lesions as hotspots of tumor evolution. In patients with ≥3 focal lesions on positron-emission-tomography at diagnosis, relapse is driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion is typically seen (p < 0.01). Notably, we observe resistant sub-clones that can be hidden over years, suggesting that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy.

The multiple myeloma treatment landscape has changed dramatically. This change, paralleled by an increase in scientific knowledge, has resulted in significant improvement in survival. However, heterogeneity remains in clinical outcomes, with a proportion of patients not benefiting from current approaches and continuing to have a poor prognosis. A significant proportion of the variability in outcome can be predicted on the basis of clinical and biochemical parameters and tumor-acquired genetic variants, allowing for risk stratification and a more personalized approach to therapy. This article discusses the principles that can enable the rational and effective development of therapeutic approaches for high-risk multiple myeloma.

IgD myeloma is a subtype often considered to have adverse features and inferior survival but there is a paucity of data from large clinical studies. We compare the clinical characteristics and outcomes of IgD myeloma patients from UK Phase III myeloma trials analysed in two groups; old (1980-2002) and recent (2002-2016) clinical trials, based on the time of adoption of novel myeloma therapies. IgD myeloma patients comprised 44/2789 (1.6%) and 70/5773 (1.2%) of the old and recent trials respectively. Overall, IgD myeloma was associated with male predominance, low-level paraproteinemia (<10g/l) and lambda light chain preference. The frequency of ultra-high risk cytogenetics was similar in IgD myeloma compared with other subtypes (4.3% vs 5.3%, p>0.99). Despite the old trial series being a younger group (median age: 59 years vs 63 years, p=0.015), there was a higher frequency of bone lesions, advanced stage at diagnosis, worse performance status and severe renal impairment compared with the recent trials. Furthermore, the early mortality rate was significantly higher for the old trial series (20% vs 4%, p=0.01). The overall response rate following induction therapy was significantly higher in the recent trials (89% vs 43%, p<0.0001) and this was consistent with improved median overall survival (48 months; 95% CI 35-67 months vs 22 months, 95% CI 16-29 months). Survival outcomes for IgD myeloma have significantly improved and are now comparable to other myeloma types due to earlier diagnosis, novel therapies and improved supportive care. (Myeloma IX International Standard Randomised Controlled Trial Number: 68454111, Myeloma XI International Standard Randomised Controlled Trial Number: 49407852).

Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrate 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identify six distinct genetic subtypes. These subtypes are differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three genetic subtypes are associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification models.

Deciphering genomic architecture is key to identifying novel disease drivers and understanding the mechanisms underlying myeloma initiation and progression. In this work, using the CoMMpass dataset, we show that structural variants (SV) occur in a nonrandom fashion throughout the genome with an increased frequency in the t(4;14), RB1, or TP53 mutated cases and reduced frequency in t(11;14) cases. By mapping sites of chromosomal rearrangements to topologically associated domains and identifying significantly upregulated genes by RNAseq we identify both predicted and novel putative driver genes. These data highlight the heterogeneity of transcriptional dysregulation occurring as a consequence of both the canonical and novel structural variants. Further, it shows that the complex rearrangements chromoplexy, chromothripsis and templated insertions are common in MM with each variant having its own distinct frequency and impact on clinical outcome. Chromothripsis is associated with a significant independent negative impact on clinical outcome in newly diagnosed cases consistent with its use alongside other clinical and genetic risk factors to identify prognosis.