Faculty Bibliography

BACKGROUND:Multiple Myeloma (MM) is a hematological malignancy with genomic heterogeneity and poor survival outcome. Apart from the central role of genetic lesions, epigenetic anomalies have been identified as drivers in the development of the disease. METHODS:Alterations in the DNA methylome were mapped in 52 newly diagnosed MM (NDMM) patients of six molecular subgroups and matched with loci-specific chromatin marks to define their impact on gene expression. Differential DNA methylation analysis was performed using DMAP with a ≥10% increase (hypermethylation) or decrease (hypomethylation) in NDMM subgroups, compared to control samples, considered significant for all the subsequent analyses with p<0.05 after adjusting for a false discovery rate. RESULTS:We identified differentially methylated regions (DMRs) within the etiological cytogenetic subgroups of myeloma, compared to control plasma cells. Using gene expression data we identified genes that are dysregulated and correlate with DNA methylation levels, indicating a role for DNA methylation in their transcriptional control. We demonstrated that 70% of DMRs in the MM epigenome were hypomethylated and overlapped with repressive H3K27me3. In contrast, differentially expressed genes containing hypermethylated DMRs within the gene body or hypomethylated DMRs at the promoters overlapped with H3K4me1, H3K4me3, or H3K36me3 marks. Additionally, enrichment of BRD4 or MED1 at the H3K27ac enriched DMRs functioned as super-enhancers (SE), controlling the overexpression of genes or gene-cassettes. CONCLUSIONS:Therefore, this study presents the underlying epigenetic regulatory networks of gene expression dysregulation in NDMM patients and identifies potential targets for future therapies.

Multiple myeloma (MM) progression is characterized by the seeding of cancer cells in different anatomic sites. To characterize this evolutionary process, we interrogated, by whole genome sequencing, 25 samples collected at autopsy from 4 patients with relapsed MM and an additional set of 125 whole exomes collected from 51 patients. Mutational signatures analysis showed how cytotoxic agents introduce hundreds of unique mutations in each surviving cancer cell, detectable by bulk sequencing only in cases of clonal expansion of a single cancer cell bearing the mutational signature. Thus, a unique, single-cell genomic barcode can link chemotherapy exposure to a discrete time window in a patient's life. We leveraged this concept to show that MM systemic seeding is accelerated at relapse and appears to be driven by the survival and subsequent expansion of a single myeloma cell following treatment with high-dose melphalan therapy and autologous stem cell transplant.

IMPORTANCE/OBJECTIVE:New York City is a global epicenter for the SARS-CoV-2 outbreak with a significant number of individuals infected by the virus. Patients with multiple myeloma have a compromised immune system, due to both the disease and anti-myeloma therapies, and may therefore be particularly susceptible to coronavirus disease 2019 (COVID-19); however, there is limited information to guide clinical management. OBJECTIVE:To assess risk factors and outcomes of COVID-19 in patients with multiple myeloma. DESIGN/METHODS:Case-series. SETTING/METHODS:Five large academic centers in New York City. PARTICIPANTS/METHODS:Patients with multiple myeloma and related plasma cell disorders who were diagnosed with COVID-19 between March 10th, 2020 and April 30th, 2020. Exposures: Clinical features and risk factors were analyzed in relation to severity of COVID-19. Main Outcomes and Measures: Descriptive statistics as well as logistic regression were used to estimate disease severity reflected in hospital admissions, intensive care unit (ICU) admission, need for mechanical ventilation, or death. RESULTS:Of 100 multiple myeloma patients (male 58%; median age 68, range 41-91) diagnosed with COVID-19, 74 (74%) were admitted; of these 13 (18%) patients were placed on mechanical ventilation, and 18 patients (24%) expired. None of the studied risk factors were significantly associated (P>0.05) with adverse outcomes (ICU-admission, mechanical ventilation, or death): hypertension (N=56) odds ratio (OR) 2.3 (95% confidence interval [CI] 0.9-5.9); diabetes (N=18) OR 1.1 (95% CI 0.3-3.2); age >65 years (N=63) OR 2.0 (95% CI 0.8-5.3); high dose melphalan with autologous stem cell transplant <12 months (N=7) OR 1.2 (95% CI 0.2-7.4), IgG<650 mg/dL (N=42) OR=1.2 (95% CI 0.4-3.1). In the entire series of 127 patients with plasma cell disorders, hypertension was significantly associated with the combined end-point (OR 3.4, 95% CI 1.5-8.1). CONCLUSIONS AND RELEVANCE/CONCLUSIONS:Although multiple myeloma patients have a compromised immune system due to both the disease and therapy; in this largest disease specific cohort to date of patients with multiple myeloma and COVID-19, compared to the general population, we found risk factors for adverse outcome to be shared and mortality rates to be within the higher range of officially reported mortality rates.

The etiology of multiple myeloma (MM) is poorly understood. Summary data from genome-wide association studies (GWASs) of multiple phenotypes can be exploited in a Mendelian randomization (MR) phenome-wide association study (PheWAS) to search for factors influencing MM risk. We performed an MR-PheWAS analyzing 249 phenotypes, proxied by 10 225 genetic variants, and summary genetic data from a GWAS of 7717 MM cases and 29 304 controls. Odds ratios (ORs) per 1 standard deviation increase in each phenotype were estimated under an inverse variance weighted random effects model. A Bonferroni-corrected threshold of P = 2 × 10-4 was considered significant, whereas P < .05 was considered suggestive of an association. Although no significant associations with MM risk were observed among the 249 phenotypes, 28 phenotypes showed evidence suggestive of association, including increased levels of serum vitamin B6 and blood carnitine (P = 1.1 × 10-3) with greater MM risk and ω-3 fatty acids (P = 5.4 × 10-4) with reduced MM risk. A suggestive association between increased telomere length and reduced MM risk was also noted; however, this association was primarily driven by the previously identified risk variant rs10936599 at 3q26 (TERC). Although not statistically significant, increased body mass index was associated with increased risk (OR, 1.10; 95% confidence interval, 0.99-1.22), supporting findings from a previous meta-analysis of prospective observational studies. Our study did not provide evidence supporting any modifiable factors examined as having a major influence on MM risk; however, it provides insight into factors for which the evidence has previously been mixed.

Newly diagnosed multiple myeloma (NDMM) patients treated with immunomodulatory drugs (IMiDs) are at high venous thrombosis (VTE) risk, but data are lacking from large prospective cohorts. We present thrombosis outcome data from Myeloma IX (n=1936) and Myeloma XI (n=4358), phase III randomized controlled trials for NDMM, treating transplant-eligible and ineligible patients before and after publication of thrombosis prevention guidelines. In Myeloma IX, compared to CTD (cyclophosphamide, thalidomide and dexamethasone), transplant-eligible patients randomized to CVAD induction (cyclophosphamide, vincristine, doxorubicin and dexamethasone) had higher VTE risk (22.5%(n=121/538) vs 16.1%(n=89/554), aHR:1.46,95%CI:1.11-1.93). For transplant-ineligible patients, compared to MP (melphalan and prednisolone), patients randomized to CTDa (attenuated CTD) induction had higher VTE risk (16.0%(n=68/425) vs 4.1%(n=17/419), aHR:4.25,95%CI:2.50-7.20). In Myeloma XI, there was no difference in VTE or arterial thrombosis risk between transplant-eligible pathways, CRD (cyclophosphamide, lenalidomide and dexamethasone) and CTD (VTE:12.2%(n=124/1014) vs 13.2%(n=133/1008), aHR:0.92,95%CI:0.72-1.18; arterial events:1.2%(n=12/1014) vs 1.5%(n=15/1008), aHR:0.80,95%CI:0.37-1.70). For transplant-ineligible patients, there was no difference in VTEs between CRDa (attenuated CRD) and CTDa (10.4%(n=95/916) vs 10.7%(n=97/910), aHR:0.97, 95%CI:0.73-1.29). However, arterial risk was higher with CRDa than CTDa (3.1%(n=28/916) vs 1.6%(n=15/910), aHR:1.91,95%CI:1.02-3.57). Thrombotic events occurred almost entirely within 6m of treatment initiation. Thrombosis was not associated with inferior progression-free or overall survival (OS), apart from inferior OS for patients with arterial events (aHR:1.53, 95%CI:1.12-2.08) in Myeloma XI. The Myeloma XI trial protocol incorporated IMWG thrombosis prevention recommendations and compared to Myeloma IX, more patients were on thromboprophylaxis (80.5% vs 22.3%) with lower VTE rates for identical regimens (CTD:13.2% vs 16.1%, CTDa:10.7% vs 16.0%). However, thrombosis remained frequent in spite of IMWG-guided thromboprophylaxis, suggesting new approaches are needed.

Multiple myeloma is the second most common lymphoproliferative disorder, characterized by aberrant expansion of monoclonal plasma cells. In the last years, thanks to novel next generation sequencing technologies, multiple myeloma has emerged as one of the most complex hematological cancers, shaped over time by the activity of multiple mutational processes and by the acquisition of key driver events. In this review, we describe how whole genome sequencing is emerging as a key technology to decipher this complexity at every stage of myeloma development: precursors, diagnosis and relapsed/refractory. Defining the time windows when driver events are acquired improves our understanding of cancer etiology and paves the way for early diagnosis and ultimately prevention.

Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10-6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10-12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.