Using Genomics to Identify High-Risk Myeloma after Autologous Stem Cell Transplantation

AbstractMultiple myeloma is a malignancy of antibody-secreting plasma cells that expand in the bone marrow. Although high-dose therapy/autologous stem cell transplantation has become the standard of care for patients with multiple myeloma, survival is highly variable and can range from a few years to >10 years after diagnosis. Application of high-throughput genomics on a large uniformly untreated cohort of patients has revealed that activation of 1 of the 3 cyclin D genes is a universal initiating event in this disease and that acquisition of abnormalities of chromosome 1 leads to activation of CKS1B, a regulator of p27Kip1 degradation. Synergy between cyclin D2 and CKS1B, but not cyclin D1 and CKS1B, may lead to early treatment failure

Evaluation of Multiple Models to Distinguish Closely Related Forms of Disease Using DNA Microarray Data: an Application to Multiple Myeloma

Motivation: Standard laboratory classification of the plasma cell dyscrasia monoclonal gammopathy of undetermined significance (MGUS) and the overt plasma cell neoplasm multiple myeloma (MM) is quite accurate, yet, for the most part, biologically uninformative. Most, if not all, cancers are caused by inherited or acquired genetic mutations that manifest themselves in altered gene expression patterns in the clonally related cancer cells. Microarray technology allows for qualitative and quantitative measurements of the expression levels of thousands of genes simultaneously, and it has now been used both to classify cancers that are morphologically indistinguishable and to predict response to therapy. It is anticipated that this information can also be used to develop molecular diagnostic models and to provide insight into mechanisms of disease progression, e.g., transition from healthy to benign hyperplasia or conversion of a benign hyperplasia to overt malignancy. However, standard data analysis techniques are not trivial to employ on these large data sets. Methodology designed to handle large data sets (or modified to do so) is needed to access the vital information contained in the genetic samples, which in turn can be used to develop more robust and accurate methods of clinical diagnostics and prognostics.Results: Here we report on the application of a panel of statistical and data mining methodologies to classify groups of samples based on expression of 12,000 genes derived from a high density oligonucleotide microarray analysis of highly purified plasma cells from newly diagnosed MM, MGUS, and normal healthy donors. The three groups of samples are each tested against each other. The methods are found to be similar in their ability to predict group membership; all do quite well at predicting MM vs. normal and MGUS vs. normal. However, no method appears to be able to distinguish explicitly the genetic mechanisms between MM and MGUS. We believe this might be due to the lack of genetic differences between these two conditions, and may not be due to the failure of the models. We report the prediction errors for each of the models and each of the methods. Additionally, we report ROC curves for the results on group prediction.Availability: Logistic regression: standard software, available, for example in SAS. Decision trees and boosted trees: C5.0 from www.rulequest.com. SVM: SVM-light is publicly available from svmlight.joachims.org. Naïve Bayes and ensemble of voters are publicly available from www.biostat.wisc.edu/~mwaddell/eov.html. Nearest Shrunken Centroids is publicly available from http://www-stat.stanford.edu/~tibs/PAM

Paradoxical expression of INK4c in proliferative multiple myeloma tumors: bi-allelic deletion vs increased expression

BACKGROUND: A high proliferative capacity of tumor cells usually is associated with shortened patient survival. Disruption of the RB pathway, which is critically involved in regulating the G1 to S cell cycle transition, is a frequent target of oncogenic events that are thought to contribute to increased proliferation during tumor progression. Previously, we determined that p18INK4c, an essential gene for normal plasma cell differentiation, was bi-allelically deleted in five of sixteen multiple myeloma (MM) cell lines. The present study was undertaken to investigate a possible role of p18INK4c in increased proliferation of myeloma tumors as they progress. RESULTS: Thirteen of 40 (33%) human myeloma cell lines do not express normal p18INK4c, with bi-allelic deletion of p18 in twelve, and expression of a mutated p18 fragment in one. Bi-allelic deletion of p18, which appears to be a late progression event, has a prevalence of about 2% in 261 multiple myeloma (MM) tumors, but the prevalence is 6 to10% in the 50 tumors with a high expression-based proliferation index. Paradoxically, 24 of 40 (60%) MM cell lines, and 30 of 50 (60%) MM tumors with a high proliferation index express an increased level of p18 RNA compared to normal bone marrow plasma cells, whereas this occurs in only five of the 151 (3%) MM tumors with a low proliferation index. Tumor progression is often accompanied by increased p18 expression and an increased proliferation index. Retroviral-mediated expression of exogenous p18 results in marked growth inhibition in three MM cell lines that express little or no endogenous p18, but has no effect in another MM cell line that already expresses a high level of p18. CONCLUSION: Paradoxically, although loss of p18 appears to contribute to increased proliferation of nearly 10% of MM tumors, most MM cell lines and proliferative MM tumors have increased expression of p18. Apart from a small fraction of cell lines and tumors that have inactivated the RB1 protein, it is not yet clear how other MM cell lines and tumors have become insensitive to the anti-proliferative effects of increased p18 expression

Frequent and specific immunity to the embryonal stem cell–associated antigen SOX2 in patients with monoclonal gammopathy

Specific targets of cellular immunity in human premalignancy are largely unknown. Monoclonal gammopathy of undetermined significance (MGUS) represents a precursor lesion to myeloma (MM). We show that antigenic targets of spontaneous immunity in MGUS differ from MM. MGUS patients frequently mount a humoral and cellular immune response against SOX2, a gene critical for self-renewal in embryonal stem cells. Intranuclear expression of SOX2 marks the clonogenic CD138− compartment in MGUS. SOX2 expression is also detected in a proportion of CD138+ cells in MM patients. However, these patients lack anti-SOX2 immunity. Cellular immunity to SOX2 inhibits the clonogenic growth of MGUS cells in vitro. Detection of anti-SOX2 T cells predicts favorable clinical outcome in patients with asymptomatic plasmaproliferative disorders. Harnessing immunity to antigens expressed by tumor progenitor cells may be critical for prevention and therapy of human cancer

A Phase 2 Study of Bortezomib in Relapsed, Refractory Myeloma

BACKGROUND Bortezomib, a boronic acid dipeptide, is a novel proteasome inhibitor that has been shown in preclinical and phase 1 studies to have antimyeloma activity. METHODS In this multicenter, open-label, nonrandomized, phase 2 trial, we enrolled 202 patients with relapsed myeloma that was refractory to the therapy they had received most recently. Patients received 1.3 mg of bortezomib per square meter of body-surface area twice weekly for 2 weeks, followed by 1 week without treatment, for up to eight cycles (24 weeks). In patients with a suboptimal response, oral dexamethasone (20 mg daily, on the day of and the day after bortezomib administration) was added to the regimen. The response was evaluated according to the criteria ofthe European Group for Blood and Marrow Transplantation and confirmed by an independent review committee. RESULTS Of 193 patients who could be evaluated, 92 percent had been treated with three or more ofthe major classes of agents for myeloma, and in 91 percent, the myeloma was refractory to the therapy received most recently. The rate of response to bortezomib was 35 percent, and those with a response included 7 patients in whom myeloma protein became undetectable and 12 in whom myeloma protein was detectable only by immuno-fixation. The median overall survival was 16 months, with a median duration of response of 12 months. Grade 3 adverse events included thrombocytopenia (in 28 percent of patients), fatigue (in 12 percent), peripheral neuropathy (in 12 percent), and neutropenia (in 11 percent). Grade 4 events occurred in 14 percent of patients. CONCLUSIONS Bortezomib, a member of a new class of anticancer drugs, is active in patients with relapsed multiple myeloma that is refractory to conventional chemotherapy

Clinical predictors of long-term survival in newly diagnosed transplant eligible multiple myeloma - an IMWG Research Project

Purpose: multiple myeloma is considered an incurable hematologic cancer but a subset of patients can achieve long-term remissions and survival. The present study examines the clinical features of long-term survival as it correlates to depth of disease response. Patients & Methods: this was a multi-institutional, international, retrospective analysis of high-dose melphalan-autologous stem cell transplant (HDM-ASCT) eligible MM patients included in clinical trials. Clinical variable and survival data were collected from 7291 MM patients from Czech Republic, France, Germany, Italy, Korea, Spain, the Nordic Myeloma Study Group and the United States. Kaplan–Meier curves were used to assess progression-free survival (PFS) and overall survival (OS). Relative survival (RS) and statistical cure fractions (CF) were computed for all patients with available data. Results: achieving CR at 1 year was associated with superior PFS (median PFS 3.3 years vs. 2.6 years, p < 0.0001) as well as OS (median OS 8.5 years vs. 6.3 years, p < 0.0001). Clinical variables at diagnosis associated with 5-year survival and 10-year survival were compared with those associated with 2-year death. In multivariate analysis, age over 65 years (OR 1.87, p = 0.002), IgA Isotype (OR 1.53, p = 0.004), low albumin < 3.5 g/dL (OR = 1.36, p = 0.023), elevated beta 2 microglobulin ≥ 3.5 mg/dL (OR 1.86, p < 0.001), serum creatinine levels ≥ 2 mg/dL (OR 1.77, p = 0.005), hemoglobin levels < 10 g/dL (OR 1.55, p = 0.003), and platelet count < 150k/μL (OR 2.26, p < 0.001) appeared to be negatively associated with 10-year survival. The relative survival for the cohort was ~0.9, and the statistical cure fraction was 14.3%. Conclusions: these data identify CR as an important predictor of long-term survival for HDM-ASCT eligible MM patients. They also identify clinical variables reflective of higher disease burden as poor prognostic markers for long-term survival

The spectrum and clinical impact of epigenetic modifier mutations in myeloma

Epigenetic dysregulation is known to be an important contributor to myeloma pathogenesis but, unlike in other B cell malignancies, the full spectrum of somatic mutations in epigenetic modifiers has not been previously reported. We sought to address this using results from whole-exome sequencing in the context of a large prospective clinical trial of newly diagnosed patients and targeted sequencing in a cohort of previously treated patients for comparison.Whole-exome sequencing analysis of 463 presenting myeloma cases entered in the UK NCRI Myeloma XI study and targeted sequencing analysis of 156 previously treated cases from the University of Arkansas for Medical Sciences. We correlated the presence of mutations with clinical outcome from diagnosis and compared the mutations found at diagnosis with later stages of disease.In diagnostic myeloma patient samples we identify significant mutations in genes encoding the histone 1 linker protein, previously identified in other B-cell malignancies. Our data suggest an adverse prognostic impact from the presence of lesions in genes encoding DNA methylation modifiers and the histone demethylase KDM6A/UTX. The frequency of mutations in epigenetic modifiers appears to increase following treatment most notably in genes encoding histone methyltransferases and DNA methylation modifiers.Numerous mutations identified raise the possibility of targeted treatment strategies for patients either at diagnosis or relapse supporting the use of sequencing-based diagnostics in myeloma to help guide therapy as more epigenetic targeted agents become available

Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival

<p>Abstract</p> <p>Background</p> <p>We have engaged in an international program designated the <it>Bank On A Cure</it>, which has established DNA banks from multiple cooperative and institutional clinical trials, and a platform for examining the association of genetic variations with disease risk and outcomes in multiple myeloma.</p> <p>We describe the development and content of a novel custom SNP panel that contains 3404 SNPs in 983 genes, representing cellular functions and pathways that may influence disease severity at diagnosis, toxicity, progression or other treatment outcomes. A systematic search of national databases was used to identify non-synonymous coding SNPs and SNPs within transcriptional regulatory regions. To explore SNP associations with PFS we compared SNP profiles of short term (less than 1 year, <it>n </it>= 70) versus long term progression-free survivors (greater than 3 years, <it>n </it>= 73) in two phase III clinical trials.</p> <p>Results</p> <p>Quality controls were established, demonstrating an accurate and robust screening panel for genetic variations, and some initial racial comparisons of allelic variation were done. A variety of analytical approaches, including machine learning tools for data mining and recursive partitioning analyses, demonstrated predictive value of the SNP panel in survival. While the entire SNP panel showed genotype predictive association with PFS, some SNP subsets were identified within drug response, cellular signaling and cell cycle genes.</p> <p>Conclusion</p> <p>A targeted gene approach was undertaken to develop an SNP panel that can test for associations with clinical outcomes in myeloma. The initial analysis provided some predictive power, demonstrating that genetic variations in the myeloma patient population may influence PFS.</p

Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups

Sequencing studies have shed some light on the pathogenesis of progression from smouldering multiple myeloma (SMM) and symptomatic multiple myeloma (MM). Given the scarcity of smouldering samples, little data are available to determine which translational programmes are dysregulated and whether the mechanisms of progression are uniform across the main molecular subgroups. In this work, we investigated 223 SMM and 1348 MM samples from the University of Arkansas for Medical Sciences (UAMS) for which we had gene expression profiling (GEP). Patients were analysed by TC-7 subgroup for gene expression changes between SMM and MM. Among the commonly dysregulated genes in each subgroup, PHF19 and EZH2 highlight the importance of the PRC2.1 complex. We show that subgroup specific differences exist even at the SMM stage of disease with different biological features driving progression within each TC molecular subgroup. These data suggest that MMSET SMM has already transformed, but that the other precursor diseases are distinct clinical entities from their symptomatic counterpart