Anderson, Kenneth C.

Abstract Transcription factors and their cofactors are major and selective nononcogene dependencies in multiple myeloma cells. By performing a gain-of-function perturbation screen in human multiple myeloma cell lines, we identified the inhibitor of DNA binding (ID) genes as putative suppressors of multiple myeloma cell fitness. Among them, ID2 was found to be downregulated in multiple myeloma patient cells and acted as a tumor suppressor by directly binding and repressing the basic helix-loop-helix factor TCF3, also known as E2A. Lower ID2 expression in multiple myeloma cells conferred a proliferative advantage by increasing TCF3 activity, leading to a dependency on this transcription factor. In contrast, ID2 overexpression reduced TCF3 binding to DNA, which resulted in cell-cycle arrest and a halt in multiple myeloma cell proliferation. The myeloma bone marrow milieu supported this process by further decreasing the expression of ID2 and enhancing TCF3 activity, partly via IL6, revealing a mechanism by which the tumor microenvironment affects multiple myeloma cell behavior. Significance: Multiple myeloma cells exploit the oncogenic and proliferative potential of TCF3 by downregulating the transcriptional regulator ID2, a process facilitated by the bone marrow microenvironment.

Despite significant improvements in survival of patients with multiple myeloma (MM), outcomes remain heterogeneous, and a significant proportion of patients experience suboptimal outcomes. Importantly, traditional prognostic factors based on data from patients treated with older therapies no longer capture prognosis accurately in the contemporary era of novel triplet or quadruplet therapies. Therefore, risk stratification requires refinement in the context of available and investigational treatment options in routine practice and clinical trials, respectively. The current identification of high-risk MM (HRMM) in routine practice is based on the Revised International Staging System, which stratifies patients using a combination of widely available serum biomarkers and chromosomal abnormalities assessed via fluorescence in situ hybridization. In recent years, a substantial body of evidence concerning additional clinical, biological, and molecular/genomic prognostic factors has accumulated, along with new MM risk stratification tools and consensus reports. The International Myeloma Society, along with the International Myeloma Working Group, convened an Expert Panel with the primary aim of revisiting the definition of HRMM and formulating a practical and data-driven consensus definition, based on new evidence from molecular/genomic assays, updated clinical data, and contemporary risk stratification concepts. The Panel proposes the following Consensus Genomic Staging (CGS) of HRMM which relies upon the presence of at least one of these abnormalities: (1) del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation; (2) an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32); (3) monoallelic del(1p32) along with 1q+ or biallelic del(1p32); or (4) β2 microglobulin ≥5.5 mg/L with normal creatinine (<1.2 mg/dL).

7540 Background: The combination of a proteasome inhibitor (PI) with lenalidomide (R) and dex (d) has been a common initial therapy for newly diagnosed myeloma (NDMM). We designed a randomized phase 3 trial to examine if carfilzomib (K), a next generation PI, improved progression free survival (PFS) compared with bortezomib (V) when either is combined with Rd for initial treatment of NDMM. Initial analysis at a median follow up of 15.3 months (mos) showed comparable PFS for both triplets. We present the long-term results of the trial with ~70 months median follow up. Methods: Patients (Pts) with NDMM, were randomized 1:1 to receive VRd or KRd for 36 weeks followed by a 2 nd randomization (1:1) to indefinite versus 2 yrs of R maintenance. Pts without del17p, t(14;16), t(14;20), plasma cell leukemia or high-risk GEP70 profile, were enrolled. VRd arm included V 1.3 mg/m 2 on days(d) 1, 4, 8, and 11 (d1, 8 for cycles 9-12), R 25 mg d1-14, and d 20 mg d1, 2, 4, 5, 8, 9, 11, 12 of a 3-week (wk) cycle for 12 cycles, while pts in the KRd arm received K 36 mg/m 2 d1, 2, 8, 9, 15, 16 with R 25 mg daily on d1-21 and d 40 mg wkly, in 4 wk cycles for 9 cycles. Maintenance used 15 mg R d1-21 q4 wks. Results: The study accrued 1087 pts (VRd=542, KRd=545). Median age was 65y; baseline characteristics including intent to transplant were similar across the arms. Median induction duration (mos; IQR) was 7.2 (3.4-8.9) and 8.4 (5.1-9.1) for VRd and KRd, respectively; 59.8% in VRd and 45.3% in KRd did not proceed to Step 2. Median PFS (mos) was VRd=41.9 and KRd=44.6; HR = 0.89 (0.76-1.04). Toxicity data, PFS sensitivity analyses and OS probabilities are as in the table. Conclusions: In this randomized trial, with median follow up of nearly 6 years, KRd and VRd had comparable PFS and OS in an intent to treat analysis. While similar numbers proceeded to SCT in the 2 arms, more did so during induction in the VRd arm while more patients in the KRd arm went to SCT later. VRd remains a standard triplet induction regimen in standard and intermediate risk NDMM, and a suitable backbone for 4 drug combinations. Clinical trial information: NCT01863550 . N (%) VRd(n=527) KRd(n=526) SCT anytime 186 (34.3) 183 (33.6) SCT without Step 2 registration 146 112 Median Time to SCT (mos; range) 7.7 (3.5-83.9) 10.6 (3.7-70.6) Grade 3-4 Treatment-Related Toxicity 315 (59.8) 344 (65.4) Grade 5 Treatment-Related Toxicity 2 (0.4) 9 (1.7) Grade 5 All Events 11 (2.1) 20 (3.8) Survival outcomes HR Median (95% CI) Median (95% CI) PFS Primary: PD or death within 3 months of last evaluation as events 0.89(0.76-1.04) 41.9(35.7, 50.3) 44.6(38.2, 51.9) PFS Sensitivity: All deaths as events, 0.87(0.75-1.02) 39.5(34.9, 46.0) 42.8(37.4, 49.7) PFS Sensitivity: Censor at alternate Rx 0.83(0.69-0.99) 35.0(31.3, 42.6) 38.7(34.7, 49.0) PFS Sensitivity: Event at alternate Rx 0.84(0.73-0.97) 18.0(14.2, 23.0) 24.4(20.9, 27.9) Overall survival 0.92(0.75-1.12) 119(100, NE) 118(103-NE)

Abstract Multiple myeloma (MM) is a complex hematological malignancy characterized by genomic changes and transcriptomic dysregulation. Initial exome sequencing approaches have failed to identify any single, frequent (&gt;25%) mutation in the coding genome. However, using whole-genome sequencing, we found that one of the genomic regions most frequently mutated (62% of the patients with MM) was the 5′ untranslated region and/or intron 1 of the BCL7A gene. RNA-sequencing data from a large cohort suggest a loss of BCL7A expression in a large majority of patients with MM as compared with normal plasma cells. BCL7A loss of function in a panel of MM cell lines led to a highly proliferative phenotype in vitro and in vivo, whereas its ectopic expression significantly reduced cell viability, suggesting a tumor suppressor function for BCL7A in MM. We studied the cellular and molecular effects of BCL7A loss and observed that it endows myeloma cells with proliferative potential in cooperation with the plasma cell–defining transcription factor IRF4. BCL7A is involved in a direct protein-protein interaction with IRF4, limiting its DNA-binding activity. Loss of BCL7A thus enhances the expression of IRF4-associated cytokines and reduces mitochondrial metabolism and reactive oxygen species levels. Our study therefore suggests that BCL7A loss provides the necessary molecular change to allow IRF4-mediated transcriptional activity and MM cell growth and survival.

PURPOSE Newly approved drugs and combinations treating multiple myeloma (MM) have resulted in substantial improvements in patients' survival. To deliver rapid access to newer therapies, an earlier end point to expedite clinical trials is needed. Our objective was to evaluate the minimal residual disease–negative complete response (MRD-CR) as an intermediate end point for progression-free survival (PFS) and overall survival (OS) in newly diagnosed (ND) transplant-eligible (NDTE) patients, ND transplant-ineligible (NDTinE) patients, and patients with relapsed/refractory (RR) MM. PATIENTS AND METHODS Individual patient data from 20 randomized multicenter trials were collected. Eleven studies (4,773 patients) with sufficient data were analyzed to evaluate whether 9- or 12-month MRD-CR classified at a 10 –5 threshold could be reasonably likely to predict the clinical benefit of new agents regarding PFS and OS. Global odds ratio (OR) was estimated using the bivariate Plackett Copula model. Supportive evaluation included correlations of the treatment effects on MRD-CR end points and PFS/OS, evaluated by both linear regression ( R 2 weighted least squared ) and Copula ( R 2 Copula ) models. RESULTS The analysis demonstrated that both 9- and 12-month MRD-CR strongly correlated with PFS at patient level in NDTE patients, NDTinE patients, and patients with RRMM. Global ORs ranged from 3.06 to 16.24, all with 95% CIs excluding 1.0. Encouraging trial-level correlations ( R 2 , 0.61-0.70) were observed by pooling three populations and were stronger ( R 2 , 0.67-0.78) in the ND population. Similar results were observed for OS. CONCLUSION Our findings provided the support for use of MRD-CR classified at a 10 –5 threshold at either 9 or 12 months after starting of the treatment, as an intermediate end point to support accelerated approvals, in future trials in NDTE patients, NDTinE patients, and patients with RRMM.

Background: Contemporary questions about treatment and outcomes of patients (pts) living with multiple myeloma (MM) demand efficient and timely evidence generation methods, where real-world/ everyday practice data can play an important role. Relevant potential applications include understanding and addressing disparities in treatment access, mitigating toxicities of novel therapies while maintaining quality of life, appropriately sequencing treatments within long-term management strategies, and disseminating and appropriately using surrogate endpoints in practice, such as minimal residual disease. However, existing real-world data (RWD) repositories are limited by an inability to implement interventions in response to issues identified through retrospective data analysis, which is pivotal for the use of newer therapies. The ASH Research Collaborative (ASH RC) MM Data Hub Program was developed to address these gaps. Methods: We developed a multicenter network of US-based tertiary academic medical centers, engaging site clinicians, patients, biostatisticians, informaticians, and data scientists. Initial activities included constructing a shared real-world MM data model comprised of consensus core data elements. Pt data from each site, dating back to at least 2019, is currently being entered through electronic case report forms, batch uploaded utilizing existing institutional data repositories, and soon direct electronic health record import in standard data acquisition formats. Data are aggregated in the Data Hub and shared in a confidential Site Portal with each site. The Portal allows sites to track their own pts, analyze outcomes, and identify ways to improve the quality of care provided to individuals living with MM. We also developed an innovative evidence generation learning community of site clinicians who meet monthly and collaborate on the “COVID-19 OutcomeS in Myeloma and the Impact of VaCcines (COSMIC)” study, a prospective, decentralized observational study that rapidly accrued pts and collects relevant practice information. The group also shares best practices in study conduct to accelerate study enrollment and execution. Results: The MM Data Hub Program now contains twelve centers: Memorial Sloan Kettering Cancer Center, Mayo Clinic, Icahn School of Medicine at Mount Sinai, University of California San Francisco, University of California Davis, Medical College of Wisconsin, Barbara Ann Karmanos Cancer Institute, University of North Carolina Medical Center at Chapel Hill, Emory University Hospital, Washington University School of Medicine in St. Louis, Dana-Farber Cancer Institute, and Atrium Health. From this Network, six centers have contributed data from 8,824 pts (2,825 with sufficiently complete data are included in this analysis). The median age at time of MM diagnosis is 63, and of the 627 deceased pts, the median age at death is 70.6 years, with median time to death from first MM diagnosis of 6 years. The proportions of pts by decade of diagnoses are 34.9% from 2020-2024; 57.6% from 2010-2019; 7.3% from 2000-2009; and 0.9% prior to 2000. 83.1% of pts had a diagnosis of plasma cell myeloma (non-light chain), and 14.4% of pts had a diagnosis of light chain myeloma. 42.3% of pts are female, and the self-reported patient races are: 85.0% white; 9.2% black or African; and 4.3% all other races (race was not documented in 1.5% of pts). 2.8% of pts are of Hispanic ethnicity. Participant data files are currently undergoing completion and cleaning procedures; the analysis will include updated results at the meeting, and a Network-wide analytic data set will be available for initial retrospective data analyses in early 2025. The COSMIC study opened for enrollment on January 22, 2024, and completed enrollment of 200 pts on May 17, 2024. Conclusions: The ASH RC Data Hub MM Program launched in 2023 and is comprised of 12 sites that collectively have contributed participant files for 8,824 pts thus far. Utilizing the structure of the Network, we successfully implemented and established the feasibility of collecting data directly from pts electronically to monitor SARS-CoV-2 vaccines and COVID-19 related outcomes. The Program serves as a successful proof-of-concept model, providing an enduring RWD resource and a prospective evidence generation platform for the myeloma community.

Background: The COVID-19 pandemic had an outsized impact on individuals with immune compromise, such as multiple myeloma, leading to increased rates of severe COVID, hospitalization, and death in these groups. The pandemic also demonstrated the need for rapid and efficient evidence generation to address rapidly changing medical needs and accelerated the use of innovative trial designs to accomplish this goal. Methods: We designed and established a prospective, decentralized study within a site-based provider network, COVID-19 OutcomeS in Myeloma and the Impact of VaCcines (COSMIC), for patients with multiple myeloma at ASH Research Collaborative sites to monitor outcomes related to COVID-19 infection and vaccination. The direct-to-patient approach was accomplished using a study application accessed with a QR code provided to patients during usual clinical care. All study activities occurred within the patient portal at Baseline, Day 30, and Day 180, minimizing burden on site personnel and staff. Study activities included eligibility confirmation, consenting, electronic health record (EHR) data permissions, and patient-reported outcome (PRO) surveys. PRO data (EORTC QLQ-C30, EORTC QLQ MY-20) were made available to clinicians through the portal to visualize results from their patients. Patients shared if they received a COVID-19 vaccination or booster and if they had a COVID-19 infection. Patients with a history of COVID-19 infection included method of confirmation and if hospitalization was required. Patients were provided compensation for participation. Automated text and email messages were sent at three separate intervals: 24 hours, Day 8, and Day 15 for participants who initiated but did not complete study activities. A personal email reminder per participant was sent for those whose second study visit window was approaching. ASH Research Collaborative clinicians met regularly to share best practices related to enrollment and study conduct, thereby creating an innovative evidence generation learning community. We studied the feasibility of data collection in a decentralized format by focusing on the number of participants who interacted with the system, those who consented, and those who completed baseline PRO assessments. Results: The COSMIC study rapidly accrued and consented 200 patients from eight participating ASH Research Collaborative sites over four months (1/22/2024 through 5/17/2024): 69% self-reported as non-Hispanic White (NHW). Of enrolled participants, 57.5% opted to permission sharing of their EHR data, which included disease and treatment-related clinical data, laboratory results, pathology reports, and imaging reports. A total of 196 patients (98%) provided demographic and COVID-related disease and vaccine data at baseline; nearly all of these patients (n=195) provided baseline PRO data, and 150 patients provided further information at Day 30 at the time of this analysis. Those who did not provide Day 30 data were not significantly different from those who did in terms of age (median: 68 [no Day 30 data] vs. 67 [Day 30 data] years; p=0.44), sex (41% [no Day 30 data] vs. 47% [Day 30 data] Female; p=0.47), or race (65% [no Day 30 data] vs. 71% [Day 30 data] NHW; p=0.60). A higher proportion of Hispanic patients were retained at Day 30 (13/15=87%) vs. 78% of non-Hispanic patients or those who declined reporting ethnicity (2/7=29%; p=0.007). COVID-19 vaccination data were submitted by 196 patients, 186 of whom had ever received a COVID-19 vaccination. Data on number, type, brand, and dates for these vaccinations were provided. Conclusions: The COSMIC study conducted by the ASH Research Collaborative was able to rapidly accrue a diverse cohort of patients using a decentralized workflow within a site-based provider network, with high consent and compliance rates. This platform, and the innovative evidence generation learning community of ASH Research Collaborative investigators and patients, sets a precedent to address a variety of real-world questions related to disease management, infections, vaccinations, and PROs in this population of patients with multiple myeloma.

Background: Data from the ASH Research Collaborative COVID-19 Registry for Hematology demonstrated that patients with multiple myeloma and other immune compromise had elevated risk for severe complications from COVID-19 infection. To address current evidence gaps and to demonstrate proof of concept for a pandemic preparedness and response network, the ASH Research Collaborative Multiple Myeloma Program developed a prospective, decentralized study within a site-based provider network to investigate COVID-19 infections, vaccinations, and quality of life in patients with multiple myeloma. Methods: We designed and established the COVID-19 OutcomeS in Myeloma and the Impact of VacCines (COSMIC) to study COVID-19 in patients with multiple myeloma at ASH Research Collaborative network sites. A study application was accessed with a QR code and shared with patients during usual clinical care. Patients provided consent, optionally gave permission for electronic health record data collection, and completed patient-reported outcomes (EORTC QLQ-C30 and MY20) at baseline, Day 30, and Day 180 through the study portal. Clinicians at participating sites facilitated study enrollment and shared best practices monthly to accelerate study execution. Study objectives related to feasibility of data collection in a decentralized format are reported in a separate abstract. Here, we report interim results related to SARS-CoV-2 vaccination history, COVID-19 infection, and how these relate to patient reported outcomes and clinical outcomes in enrolled participants. Results: The COSMIC study rapidly accrued and consented 200 patients from eight participating ASH Research Collaborative sites over four months (1/22/2024 through 5/17/2024). Consented participants' ages ranged from 29 to 93 years, with median of 67 years; 46% were female, 69% were non-Hispanic White (NHW), 17% were non-Hispanic Black (NHB), and 8% were Hispanic/Latino. Of the 196 patients who reported COVID-19 data, 111 (57%) reported at baseline that they had a history of COVID-19 infection, with 12 having required hospitalization for this (12/111=11%). Overall, 95% (186/196) reported a history of COVID-19 vaccination, where the median number of vaccinations was 4 (range: 1 to 6); 44 patients (23%) expressed willingness to discuss getting a yearly booster vaccine with their provider. At 1-month follow-up, there were 3 additional patients who reported a COVID-19 infection and 18 patients who received an additional COVID-19 vaccination. The baseline EORTC QLQ-C30 median Global Health Status/QOL score was 66.7 (mean=64.4, range: 8.3 - 100, n=196). This overall global QOL score was not significantly different between those who did vs. did not have a history of COVID-19 infection (mean [SD]: 63.7 [19.3] vs. 65.8 [17.6]; p=0.57). In analyses adjusted for age, biological sex, and race/ethnicity group, history of COVID-19 infection was not associated with HRQOL (odds ratio=0.93, 95% CI: 0.78 - 1.10; p=0.38). Data collection is ongoing and final study results will be reported at a later date. Conclusion: COSMIC is a prospective, decentralized study within a site-based provider network conducted by the ASH Research Collaborative Multiple Myeloma Program that demonstrates the feasibility of using an innovative evidence generation strategy to drive rapid accrual of patients to address a rapidly evolving area of need. The COSMIC study also provides proof of concept that a real-world evidence generation network can play an important role in national pandemic preparedness and response. The COSMIC experience reinforces the ability to accrue diverse patient populations representing the demographic of myeloma patients in the US.

AbstractSmoldering multiple myeloma (SMM) is a precursor stage that precedes multiple myeloma (MM). SMM is heterogenous with nearly 40% of patients progressing to MM in the first 5 years. The high rate of progression of SMM patients highlights the need for early intervention, which underscores the importance of identifying SMM patients with the highest risk of progression. Several risk stratification models showed utility in identifying high‐risk SMM patients; however, these systems showed limited sensitivity. To date, identifying high‐risk SMM patients remains an important clinical need. In this study, we present the 3‐dimensional telomere profiling as a structural biomarker capable of stratifying SMM patients as a function of genomic instability. Quantifying telomere dysfunction using the TeloView technology showed utility in risk stratification of cancer patients, particularly hematological malignancies. In this study, we analyzed 168 SMM patients. We report an AUC in ROC analysis of 0.8 using a subset of the patients as a training dataset. We then conducted a blind validation on a different cohort and demonstrated a positive predictive value of 85% and negative predictive value of 73%, with sensitivity and specificity of 83% and 76%, respectively. We examined the correlation between the TeloView prediction and the 20‐2‐20 scoring system, and cytogenetic abnormalities. We report a correlation of 53% with the 20‐2‐20 scores and over 60% correlation with cytogenetic abnormalities. The result of this study presents the telomere profiling as an effective biomarker able to stratify SMM patients to their respective risk groups with high sensitivity and specificity.