Faculty Bibliography

Incorporation of novel agents into auto-SCT for patients with multiple myeloma has led to improvement in their outcomes. However, the effects of new drugs, either single or combined, on PBSC mobilization have not been fully evaluated, particularly in phase 3 clinical studies. We analyzed the impact of two novel agent-based induction treatments in patients enrolled in the GIMEMA MMY-3006 study comparing bortezomib, thalidomide and dexamethasone (VTD) versus thalidomide and dexamethasone (TD) in preparation for double auto-SCT. Results showed that a short-term induction therapy with VTD did not adversely affect CD34(+) cell yields as compared with TD (9.75 vs 10.76 × 10(6) CD34(+) cells/kg, P=0.220). For poor mobilizers (<4 × 10(6) CD34(+) cells/kg), 5-year rates of time to progression (TTP), progression-free survival (PFS) and overall survival (OS) were significantly shorter than for successful mobilizers (TTP:17 vs 48%, P<0.0001; PFS: 16 vs 46%, P<0.0001; OS: 50 vs 80%, P<0.0001). These differences were retained across patients randomized to the TD arm; conversely, no differences in outcomes were seen in patients treated with VTD, irrespective of the number of harvested CD34(+) cells. The number of collected PBSCs predicted better outcomes after auto-SCT and VTD overcame the negative impact of a poor stem cell mobilization.

We have sequenced 463 presenting cases of myeloma entered into the UK Myeloma XI study using whole exome sequencing. Here we identify mutations induced as a consequence of misdirected AID in the partner oncogenes of IGH translocations, which are activating and associated with impaired clinical outcome. An APOBEC mutational signature is seen in 3.8% of cases and is linked to the translocation-mediated deregulation of MAF and MAFB, a known poor prognostic factor. Patients with this signature have an increased mutational load and a poor prognosis. Loss of MAF or MAFB expression results in decreased APOBEC3B and APOBEC4 expression, indicating a transcriptional control mechanism. Kataegis, a further mutational pattern associated with APOBEC deregulation, is seen at the sites of the MYC translocation. The APOBEC mutational signature seen in myeloma is, therefore, associated with poor prognosis primary and secondary translocations and the molecular mechanisms involved in generating them.

The detection of minimal residual disease (MRD) in myeloma using a 0.01% threshold (10(-4)) after treatment is an independent predictor of progression-free survival (PFS), but not always of overall survival (OS). However, MRD level is a continuous variable, and the predictive value of the depth of tumor depletion was evaluated in 397 patients treated intensively in the Medical Research Council Myeloma IX study. There was a significant improvement in OS for each log depletion in MRD level (median OS was 1 year for ≥10%, 4 years for 1% to <10%, 5.9 years for 0.1% to <1%, 6.8 years for 0.01% to <0.1%, and more than 7.5 years for <0.01% MRD). MRD level as a continuous variable determined by flow cytometry independently predicts both PFS and OS, with approximately 1 year median OS benefit per log depletion. The trial was registered at www.isrctn.com as #68454111.

In the phase III MM-003 trial, pomalidomide plus low-dose dexamethasone (POM+LoDEX) improved overall survival (OS) versus high-dose dexamethasone (HiDEX) in 455 patients with relapsed and refractory multiple myeloma (RRMM) after treatment with bortezomib and lenalidomide. Here, a two-stage Weibull method was used to adjust for the crossover of patients in the HiDEX arm to pomalidomide-based therapy. The adjusted difference in median OS between patients in the POM+LoDEX and HiDEX arms was 7·0 months (12·7 vs. 5·7 months, respectively). These findings provide important evidence for understanding the clinical efficacy of pomalidomide on OS benefits seen in RRMM patients.

Myeloma is characterized by a highly variable clinical outcome. Despite the effectiveness of high-dose therapy, 15% of patients relapse within 1 year. We show that these cases also have a significantly shorter post-relapse survival compared to the others (median 14.9 months vs. 40 months, p = 8.03 × 10(- 14)). There are no effective approaches to define this potentially distinct biological group such that treatment could be altered. In this work a series of uniformly treated patients with myeloma were used to develop a gene expression profiling (GEP)-based signature to identify this high risk clinical behavior. Gene enrichment analyses applied to the top differentially expressed genes showed a significant enrichment of epigenetic regulators as well as "stem cell" myeloma genes. A derived 17-gene signature effectively identifies patients at high risk of early relapse as well as impaired overall survival. Integrative genomic analyses showed that epigenetic mechanisms may play an important role on transcription of these genes.

BACKGROUND:Gene expression profiling (GEP) via microarray analysis is a widely used tool for assessing risk and other patient diagnostics in clinical settings. However, non-biological factors such as systematic changes in sample preparation, differences in scanners, and other potential batch effects are often unavoidable in long-term studies and meta-analysis. In order to reduce the impact of batch effects on microarray data, Johnson, Rabinovic, and Li developed ComBat for use when combining batches of gene expression microarray data. We propose a modification to ComBat that centers data to the location and scale of a pre-determined, 'gold-standard' batch. This modified ComBat (M-Combat) is designed specifically in the context of meta-analysis and batch effect adjustment for use with predictive models that are validated and fixed on historical data from a 'gold-standard' batch. RESULTS:We combined data from MIRT across two batches ('Old' and 'New' Kit sample preparation) as well as external data sets from the HOVON-65/GMMG-HD4 and MRC-IX trials into a combined set, first without transformation and then with both ComBat and M-ComBat transformations. Fixed and validated gene risk signatures developed at MIRT on the Old Kit standard (GEP5, GEP70, and GEP80 risk scores) were compared across these combined data sets. Both ComBat and M-ComBat eliminated all of the differences among probes caused by systematic batch effects (over 98% of all untransformed probes were significantly different by ANOVA with 0.01 q-value threshold reduced to zero significant probes with ComBat and M-ComBat). The agreement in mean and distribution of risk scores, as well as the proportion of high-risk subjects identified, coincided with the 'gold-standard' batch more with M-ComBat than with ComBat. The performance of risk scores improved overall using either ComBat or M-Combat; however, using M-ComBat and the original, optimal risk cutoffs allowed for greater ability in our study to identify smaller cohorts of high-risk subjects. CONCLUSION/CONCLUSIONS:M-ComBat is a practical modification to an accepted method that offers greater power to control the location and scale of batch-effect adjusted data. M-ComBat allows for historical models to function as intended on future samples despite known, often unavoidable systematic changes to gene expression data.

Risk stratification in myeloma requires an accurate assessment of the presence of a range of molecular abnormalities including the differing IGH translocations and the recurrent copy number abnormalities that can impact clinical behavior. Currently, interphase fluorescence in situ hybridization is used to detect these abnormalities. High failure rates, slow turnaround, cost, and labor intensiveness make it difficult and expensive to use in routine clinical practice. Multiplex ligation-dependent probe amplification (MLPA), a molecular approach based on a multiplex polymerase chain reaction method, offers an alternative for the assessment of copy number changes present in the myeloma genome. Here, we provide evidence showing that MLPA is a powerful tool for the efficient detection of copy number abnormalities and when combined with expression assays, MLPA can detect all of the prognostically relevant molecular events which characterize presenting myeloma. This approach opens the way for a molecular diagnostic strategy that is efficient, high throughput, and cost effective.

Autologous hematopoietic cell transplantation (AHCT) is a standard of care in multiple myeloma (MM) patients aged <65 years. To understand age-related trends in utilisation and outcome of AHCT, we analysed 53 675 MM patients who underwent a first AHCT in 31 European countries between 1991 and 2010. The number of patients undergoing AHCT increased for all age groups (<40, 40-49, 50-59, 60-64, 65-69 and ⩾70 years) throughout the observation period. The highest increase was observed for patients aged ⩾65 years, who accounted for 3% of AHCTs in 1991-1995 and for 18.8% of AHCTs in 2006-2010. Risk factors associated with survival over the entire observation period (P<0.001) were calendar period, remission status at AHCT, gender, disease duration before AHCT and age. Survival improved considerably more in older than in younger patients in recent years. In 2006-2010, median 2- and 5-year post-transplant survival ranged from 85.9 and 61.5% in patients <40 years to 80.2 and 49.7% in those ⩾70 years. All-cause day-100 mortality decreased throughout the observation period to ⩽2.4% for all age groups in 2006-2010. The results of this study demonstrate increased utilisation and safety of AHCT with improved post-transplant survival particularly in elderly MM patients in recent years in Europe.

The acquisition of the cytogenetic abnormalities hyperdiploidy or translocations into the immunoglobulin gene loci are considered as initiating events in the pathogenesis of myeloma and were often assumed to be mutually exclusive. These lesions have clinical significance; hyperdiploidy or the presence of the t(11;14) translocation is associated with a favorable outcome, whereas t(4;14), t(14;16), and t(14;20) are unfavorable. Poor outcomes are magnified when lesions occur in association with other high-risk features, del17p and +1q. Some patients have coexistence of both good and poor prognostic lesions, and there has been no consensus on their risk status. To address this, we have investigated their clinical impact using cases in the Myeloma IX study (ISRCTN68454111) and shown that the coexistence of hyperdiploidy or t(11;14) does not abrogate the poor prognosis associated with adverse molecular lesions, including translocations. We have also used single-cell analysis to study cases with coexistent translocations and hyperdiploidy to determine how these lesions cosegregate within the clonal substructure, and we have demonstrated that hyperdiploidy may precede IGH translocation in a proportion of patients. These findings have important clinical and biological implications, as we conclude patients with coexistence of adverse lesions and hyperdiploidy should be considered high risk and treated accordingly.