Faculty Bibliography

INTRODUCTION/BACKGROUND:It is understood that cancer is a clonal disease initiated by a single cell, and that metastasis, which is the spread of cancer from the primary site, is also initiated by a single cell. The seemingly natural capability of cancer to adapt dynamically in a Darwinian manner is a primary reason for therapeutic failures. Survival advantages may be induced by cancer therapies and also occur as a result of inherent cell and microenvironmental factors. The selected "more fit" clones outmatch their competition and then become dominant in the tumor via propagation of progeny. This clonal expansion leads to relapse, therapeutic resistance and eventually death. The goal of this study is to develop and demonstrate a more detailed clonality approach by utilizing integrative genomics. METHODS:Patient tumor samples were profiled by Whole Exome Sequencing (WES) and RNA-seq on an Illumina HiSeq 2500 and methylation profiling was performed on the Illumina Infinium 450K array. STAR and the Haplotype Caller were used for RNA-seq processing. Custom approaches were used for the integration of the multi-omic datasets. RESULTS:Reported are major enhancements to CloneViz, which now provides capabilities enabling a formal tumor multi-dimensional clonality analysis by integrating: i) DNA mutations, ii) RNA expressed mutations, and iii) DNA methylation data. RNA and DNA methylation integration were not previously possible, by CloneViz (previous version) or any other clonality method to date. This new approach, named iCloneViz (integrated CloneViz) employs visualization and quantitative methods, revealing an integrative genomic mutational dissection and traceability (DNA, RNA, epigenetics) thru the different layers of molecular structures. CONCLUSION/CONCLUSIONS:The iCloneViz approach can be used for analysis of clonal evolution and mutational dynamics of multi-omic data sets. Revealing tumor clonal complexity in an integrative and quantitative manner facilitates improved mutational characterization, understanding, and therapeutic assignments.

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.

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.

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.

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.

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.

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 unfolded protein response (UPR) remediates endoplasmic reticulum (ER) stress. IRE1, a component of the UPR, senses misfolded protein and cleaves XBP1 mRNA, which is ligated to code for the prosurvival transcription factor. IRE1 also cleaves other mRNAs preceding their degradation, termed regulated IRE1-dependent mRNA decay (RIDD). It has been reported that RIDD may be involved in cell viability under stress and therefore may contribute to cancer cell viability. To investigate RIDD targets that may have functional relevance in cell survival, we identified conserved RIDD targets containing stringent IRE1 RNase target sequences. Using a systematic bioinformatics approach with quantitative-PCR (qPCR) validation, we show that only BLOC1S1 is consistently a RIDD target in all systems tested. Using cancer cell lines, we show that BLOC1S1 is specifically cleaved by IRE1 at guanine 444, but only under conditions of IRE1 hyperactivation. BLOC1S1 cleavage is temporally separate from XBP1 splicing, occurring after depletion of unspliced XBP1. Expression of an uncleavable BLOC1S1 mutant or inhibition of RIDD using an IRE1 RNase inhibitor did not affect cellular recovery from acute ER stress. These data demonstrate that although hyperactivated IRE1 specifically cleaves BLOC1S1, this cleavage event and RIDD as a whole are dispensable for cell viability under acute stress.

Multiple myeloma is a B-cell malignancy stratified in part by cytogenetic abnormalities, including the high-risk copy number aberrations (CNAs) of +1q21 and 17p(-). To investigate the relationship between 1q21 CNAs and DNA hypomethylation of the 1q12 pericentromeric heterochromatin, we treated in vitro peripheral blood cultures of 5 patients with balanced constitutional rearrangements of 1q12 and 5 controls with the hypomethylating agent 5-azacytidine. Using G-banding, fluorescence in situ hybridization, and spectral karyotyping, we identified structural aberrations and copy number gains of 1q21 in the treated cells similar to those found in patients with cytogenetically defined high-risk disease. Aberrations included 1q12 triradials, amplifications of regions juxtaposed to 1q12, and jumping translocations 1q12. Strikingly, all 5 patients with constitutional 1q12 rearrangements showed amplifications on the derivative chromosomes distal to the inverted or translocated 1q12 region, including MYCN in 1 case. At the same time, no amplification of the 1q21 region was found when the 1q12 region was inverted or absent. These findings provide evidence that the hypomethylation of the 1q12 region can potentially amplify any genomic region juxtaposed to it and mimic CNAs found in the bone marrow of patients with high-risk disease.

BACKGROUND:International collaborative research is a mechanism for improving the development of disease-specific therapies and for improving health at the population level. However, limited data are available to assess the trends in research output related to orphan diseases. METHODS AND FINDINGS/RESULTS:We used bibliometric mapping and clustering methods to illustrate the level of fragmentation in myeloma research and the development of collaborative efforts. Publication data from Thomson Reuters Web of Science were retrieved for 2005-2009 and followed until 2013. We created a database of multiple myeloma publications, and we analysed impact and co-authorship density to identify scientific collaborations, developments, and international key players over time. The global annual publication volume for studies on multiple myeloma increased from 1,144 in 2005 to 1,628 in 2009, which represents a 43% increase. This increase is high compared to the 24% and 14% increases observed for lymphoma and leukaemia. The major proportion (>90% of publications) was from the US and EU over the study period. The output and impact in terms of citations, identified several successful groups with a large number of intra-cluster collaborations in the US and EU. The US-based myeloma clusters clearly stand out as the most productive and highly cited, and the European Myeloma Network members exhibited a doubling of collaborative publications from 2005 to 2009, still increasing up to 2013. CONCLUSION AND PERSPECTIVE/CONCLUSIONS:Multiple myeloma research output has increased substantially in the past decade. The fragmented European myeloma research activities based on national or regional groups are progressing, but they require a broad range of targeted research investments to improve multiple myeloma health care.