Faculty Bibliography

Multiple myeloma is a plasma cell malignancy that is characterized by refractory and relapsing course of disease. Despite the introduction of high-dose chemotherapy in combination with autologous stem cell transplantation and innovative agents such as proteasome inhibitors and immunomodulatory drugs, achieving cure in multiple myeloma is a challenging endeavor. In the last couple of years, enormous advances were made in implementing monoclonal antibody therapy in multiple myeloma. A large number of preclinical and clinical studies have been introduced successfully, demonstrating a safe and efficient administration of monoclonal antibodies in multiple myeloma. In particular, the application of monoclonal antibodies in combination with immunomodulatory drugs, proteasome inhibitors, corticosteroids or conventional chemotherapy seem to be promising and will expand the treatment arsenal for patients with multiple myeloma.

This study examined lifestyle, occupation, medical history and medication use with multiple myeloma risk in a case-spouse study (481 patients, 351 spouses). Odds ratios (ORs) and 95% confidence intervals (CI) were calculated using logistic regression. Compared to spouse controls, cases were more likely to have a family history of multiple myeloma (OR = 2.8, 95% CI = 1.2-6.4) and smoked cigarettes (OR = 1.7, 95% CI = 1.2-2.5), but less likely to have consumed alcohol (OR = 0.6, 95% CI = 0.4-0.9). Nurse/health practitioners (OR = 2.8, 95% CI = 1.3-6.2) and production workers (OR = 3.7, 95% CI = 1.0-13.7) had significantly increased risks; and some occupations linked to diesel exhaust had elevated, but non-significant, risks. History of herpes simplex (OR = 1.7, 95% CI = 1.2-2.4), shingles (OR = 1.7, 95% CI = 1.1-2.7), sexually transmitted diseases (OR = 2.0, 95% CI = 1.0-3.7) and medication allergies (OR = 1.7, 95% CI = 1.2-2.4) were associated with higher risks. Use of angiotensin-converting enzyme inhibitors, anti-convulsants, antidepressants, statins and diuretics were associated with reduced risks. The results are consistent with previous population-based studies and support the utility of patient databanks and spouse controls as a resource in epidemiologic research.

BACKGROUND:Gene expression profiling (GEP) has significantly contributed to the elucidation of the molecular heterogeneity of multiple myeloma plasma cells (MMPC) and only recently it has been recommended for risk stratification. Prior to GEP MMPC need to be enriched resulting in an inability to immediately freeze bone marrow aspirates or use RNA stabilization reagents. As a result in multi-center MM trials sample processing delay due to shipping may be an important confounder of molecular analyses and risk stratification based on GEP data. RESULTS:We compared GEP data of 145 in-house and 246 shipped samples and detected 3301 down-regulated and 3501 up-regulated genes in shipped samples. For 3994 genes we confirmed differential expression in an independent set of 85 in-house and 97 shipped samples. Differentially expressed genes were enriched in processes like ribosome biogenesis, cell cycle, and apoptosis. Among GEP based risk predictors the IFM-15 seemed to underestimate high risk in shipped samples, whereas the GEP70 and the EMC-92 gene signatures were more robust. In order to provide a tool to assess the "shipping effect" in public repositories, we generated a 17-gene predictor for shipped samples with a 10-fold cross validation error rate of 0.06 for the training set and an error rate of 0.15 for the validation set. CONCLUSION/CONCLUSIONS:Sample processing delay significantly influences GEP of MMPC, implying it should be avoided if samples were used for risk stratification.

PURPOSE/OBJECTIVE:At the molecular level, myeloma is characterized by copy number abnormalities and recurrent translocations into the immunoglobulin heavy chain locus. Novel methods, such as massively parallel sequencing, have begun to describe the pattern of tumor-acquired mutations, but their clinical relevance has yet to be established. METHODS:We performed whole-exome sequencing for 463 patients who presented with myeloma and were enrolled onto the National Cancer Research Institute Myeloma XI trial, for whom complete molecular cytogenetic and clinical outcome data were available. RESULTS:We identified 15 significantly mutated genes: IRF4, KRAS, NRAS, MAX, HIST1H1E, RB1, EGR1, TP53, TRAF3, FAM46C, DIS3, BRAF, LTB, CYLD, and FGFR3. The mutational spectrum is dominated by mutations in the RAS (43%) and nuclear factor-κB (17%) pathways, but although they are prognostically neutral, they could be targeted therapeutically. Mutations in CCND1 and DNA repair pathway alterations (TP53, ATM, ATR, and ZNFHX4 mutations) are associated with a negative impact on survival. In contrast, those in IRF4 and EGR1 are associated with a favorable overall survival. We combined these novel mutation risk factors with the recurrent molecular adverse features and international staging system to generate an international staging system mutation score that can identify a high-risk population of patients who experience relapse and die prematurely. CONCLUSION/CONCLUSIONS:We have refined our understanding of genetic events in myeloma and identified clinically relevant mutations that may be used to better stratify patients at presentation.

Patients with multiple myeloma have variable survival and require reliable prognostic and predictive scoring systems. Currently, clinical and biological risk markers are used independently. Here, International Staging System (ISS), fluorescence in situ hybridization (FISH) markers, and gene expression (GEP) classifiers were combined to identify novel risk classifications in a discovery/validation setting. We used the datasets of the Dutch-Belgium Hemato-Oncology Group and German-speaking Myeloma Multicenter Group (HO65/GMMG-HD4), University of Arkansas for Medical Sciences-TT2 (UAMS-TT2), UAMS-TT3, Medical Research Council-IX, Assessment of Proteasome Inhibition for Extending Remissions, and Intergroupe Francophone du Myelome (IFM-G) (total number of patients: 4750). Twenty risk markers were evaluated, including t(4;14) and deletion of 17p (FISH), EMC92, and UAMS70 (GEP classifiers), and ISS. The novel risk classifications demonstrated that ISS is a valuable partner to GEP classifiers and FISH. Ranking all novel and existing risk classifications showed that the EMC92-ISS combination is the strongest predictor for overall survival, resulting in a 4-group risk classification. The median survival was 24 months for the highest risk group, 47 and 61 months for the intermediate risk groups, and the median was not reached after 96 months for the lowest risk group. The EMC92-ISS classification is a novel prognostic tool, based on biological and clinical parameters, which is superior to current markers and offers a robust, clinically relevant 4-group model.

PURPOSE/OBJECTIVE:The clinical outcome of multiple myeloma (MM) is heterogeneous. A simple and reliable tool is needed to stratify patients with MM. We combined the International Staging System (ISS) with chromosomal abnormalities (CA) detected by interphase fluorescent in situ hybridization after CD138 plasma cell purification and serum lactate dehydrogenase (LDH) to evaluate their prognostic value in newly diagnosed MM (NDMM). PATIENTS AND METHODS/METHODS:Clinical and laboratory data from 4,445 patients with NDMM enrolled onto 11 international trials were pooled together. The K-adaptive partitioning algorithm was used to define the most appropriate subgroups with homogeneous survival. RESULTS:ISS, CA, and LDH data were simultaneously available in 3,060 of 4,445 patients. We defined the following three groups: revised ISS (R-ISS) I (n = 871), including ISS stage I (serum β2-microglobulin level < 3.5 mg/L and serum albumin level ≥ 3.5 g/dL), no high-risk CA [del(17p) and/or t(4;14) and/or t(14;16)], and normal LDH level (less than the upper limit of normal range); R-ISS III (n = 295), including ISS stage III (serum β2-microglobulin level > 5.5 mg/L) and high-risk CA or high LDH level; and R-ISS II (n = 1,894), including all the other possible combinations. At a median follow-up of 46 months, the 5-year OS rate was 82% in the R-ISS I, 62% in the R-ISS II, and 40% in the R-ISS III groups; the 5-year PFS rates were 55%, 36%, and 24%, respectively. CONCLUSION/CONCLUSIONS:The R-ISS is a simple and powerful prognostic staging system, and we recommend its use in future clinical studies to stratify patients with NDMM effectively with respect to the relative risk to their survival.

Multiple myeloma is preceded by an asymptomatic phase, comprising monoclonal gammopathy of uncertain significance and smoldering myeloma. Compared to the former, smoldering myeloma has a higher and non-uniform rate of progression to clinical myeloma, reflecting a subset of patients with higher risk. We evaluated the gene expression profile of smoldering myeloma plasma cells among 105 patients enrolled in a prospective observational trial at our institution, with a view to identifying a high-risk signature. Baseline clinical, bone marrow, cytogenetic and radiologic data were evaluated for their potential to predict time to therapy for symptomatic myeloma. A gene signature derived from four genes, at an optimal binary cut-point of 9.28, identified 14 patients (13%) with a 2-year therapy risk of 85.7%. Conversely, a low four-gene score (< 9.28) combined with baseline monoclonal protein < 3 g/dL and albumin ≥ 3.5 g/dL identified 61 patients with low-risk smoldering myeloma with a 5.0% chance of progression at 2 years. The top 40 probe sets showed concordance with indices of chromosome instability. These data demonstrate high discriminatory power of a gene-based assay and suggest a role for dysregulation of mitotic checkpoints in the context of genomic instability as a hallmark of high-risk smoldering myeloma.

Multiple Myeloma (MM) is a malignancy characterized by the hyperdiploid (HD-MM) and the non-hyperdiploid (nHD-MM) subtypes. To shed light within the molecular architecture of these subtypes, we used a novel integromics approach. By annotated MM patient mRNA/microRNA (miRNA) datasets, we investigated mRNAs and miRNAs profiles with relation to changes in transcriptional regulators expression. We found that HD-MM displays specific gene and miRNA expression profiles, involving the Signal Transducer and Activator of Transcription (STAT)3 pathway as well as the Transforming Growth Factor-beta (TGFβ) and the transcription regulator Nuclear Protein-1 (NUPR1). Our data define specific molecular features of HD-MM that may translate in the identification of novel relevant druggable targets.

As part of Total Therapy (TT) 3b, baseline marrow aspirates were subjected to two-color flow cytometry of nuclear DNA content and cytoplasmic immunoglobulin (DNA/CIG) as well as plasma cell gene expression profiling (GEP). DNA/CIG-derived parameters, GEP and standard clinical variables were examined for their effects on overall survival (OS) and progression-free survival (PFS). Among DNA/CIG parameters, the percentage of the light chain-restricted (LCR) cells and their cytoplasmic immunoglobulin index (CIg) were linked to poor outcome. In the absence of GEP data, low CIg <2.8, albumin <3.5 g/dl and age ⩾65 years were significantly associated with inferior OS and PFS. When GEP information was included, low CIg survived the model along with GEP70-defined high risk and low albumin. Low CIg was linked to beta-2-microglobulin >5.5 mg/l, a percentage of LCR cells exceeding 50%, C-reactive protein ⩾8 mg/l and GEP-derived high centrosome index. Further analysis revealed an association of low CIg with 12 gene probes implicated in cell cycle regulation, differentiation and drug transportation from which a risk score was developed in TT3b that held prognostic significance also in TT3a, TT2 and HOVON trials, thus validating its general applicability. Low CIg is a powerful new prognostic variable and has identified potentially drug-able targets.