Interim Analysis Of The Mmrf Commpass Trial, a Longitudinal Study In Multiple Myeloma Relating Clinical Outcomes To Genomic and Immunophenotypic Profiles

Abstract

The Multiple Myeloma Research Foundation (MMRF) CoMMpass trial is the cornerstone of the MMRF Personalized Medicine Initiative. The accrual goal is 1000 patients with newly-diagnosed active multiple with sufficient tumor material for the comprehensive analysis of each tumor genome. Each eligible patient will be followed from initial diagnosis longitudinally for a minimum of 8 years. Additional tumor samples will be collected and comprehensively analyzed when possible for each patient at time of suspect CR, recurrence or progression of disease. The clinical study (NCT0145429) opened in July 2011 and now includes 56 sites in the US and Canada that have enrolled over 300 patients as of Aug. 1, 2013. The frontline treatments permitted in this study include current standard of care therapies containing a proteasome inhibitor, an IMiD or both. The comprehensive analysis of each tumor and matched normal genome involves; Long-Insert Whole Genome Sequencing (WGS) to identify somatic copy number alterations and structural changes, Whole Exome Sequencing (WES) to identify somatic single nucleotide variants and indels, and RNA sequencing (RNAseq) to define transcript expression levels and fusion transcripts. In addition, BRAF pyrosequencing and immunophenotyping analysis are being done in CAP-CLIA certified labs. An extensive, open-access, public clinical and molecular database, the CoMMpass Researcher Gateway (RG) (https://research.themmrf.org), is being developed to facilitate the rapid dissemination of the results and provides the myeloma community with a mechanism to analyze the results. The clinical endpoints and outcomes also include Quality of Life measures and health care resource utilization. An initial interim analysis on the first 178 cases has just been completed and made publicly available through the CoMMpass RG. At the molecular level, BRAF analysis on this serial sample set of newly diagnosed patients identified V600E mutations at rate of 5.7%, confirming our previous observations from a mixture of non-consecutive treated and untreated patient samples in our previous genomic efforts. The flow cytometry panel was designed to provide a comprehensive immunofingerprint of each patient that could be used for minimal residual disease monitoring and to monitor potentially therapeutic options; MS4A1/CD20, CD52, KIT/CD117, and FGFR3. These studies have identified tumors which are 100% positive for these actionable antigens at frequencies of; 16.0% for CD20, 5.7% for CD52, 49.7% for CD117, and 8.5% for FGFR3. Of the 178 cases, 34 were profiled through WGS, WES and RNAseq before this interim analysis. We identified 553 variants (median 19 per patient, range 11-55) were the variant allele detected by WES was also detected by RNAseq, suggesting the variant is potentially biologically relevant. Of these genes, 36 were seen more than once and 7 were identified in three or more patients. This includes NRAS (23.5%), KRAS (14.7%), BRAF (8.8%), DIS3 (8.8%), FAM46C (8.8%), TRAF3 (8.8%), and ZNF100 (8.8%). Interestingly, all three ZNF100 variants show preferential expression of the mutant allele. Within this cohort the only recurrent fusion gene identified is the classic IgH-MMSET fusion transcripts associate with t(4;14). The MMRF CoMMpass is providing unprecedented molecular characterization and correlating clinical datasets that will help define the determinants of response to anti-myeloma agents, reveal new, actionable targets and/or those shared with other cancers and facilitate future clinical trial designs, thus serving as a stepping stone toward personalized medicine for myeloma patients. Disclosures: Auclair: MMRC: Employment. Harrison:MMRC: Employment. Jagannath:Celgene: Honoraria; Millennium: Honoraria. Siegel:Celgene: Honoraria, Speakers Bureau; Millennium: Honoraria, Speakers Bureau; Onyx: Honoraria, Speakers Bureau. Vij:Celgene: Honoraria, Research Funding, Speakers Bureau; Millennium: Honoraria, Speakers Bureau; Onyx: Honoraria, Research Funding, Speakers Bureau. Zimmerman:Celgene: Honoraria; Millenium: Honoraria; Onyx: Honoraria. Capone:MMRC: Employment. Lonial:Millennium: Consultancy; Celgene: Consultancy; Novartis: Consultancy; BMS: Consultancy; Sanofi: Consultancy; Onyx: Consultancy.

Copy number signatures predict chromothripsis and associate with poor clinical outcomes in patients with newly diagnosed multiple myeloma

“…Somatic CN profiles for the definition of CN signatures in MM were generated from 752 NDMM patients with low-coverage long-insert WGS (median 4-8x) from the CoMMpass study. The CoMMpass study is a prospective observational clinical trial (NCT01454297) with comprehensive genomic and transcriptomic characterization of NDMM patients, funded and managed by the Multiple Myeloma Research Foundation (MMRF) 35 . The study is ongoing, with data released regularly for research use via the MMRF research gateway, https://research.themmrf.org.…”

Deep transcriptome profiling of multiple myeloma with quantitative measures using the SPECTRA approach

“…Data were generated as part of the MMRF CoMMpass Study (release IA14) 25 , all colors can be represented using 3 quantitative RGB variables. c) Standard-use, modeling on the 3 RGB variables used to identify structure across samples using hierarchical clustering.…”

“…We illustrate SPECTRA using the Multiple Myeloma Research Foundation (MMRF) CoMMpass Study data. 25 We derive the spectra equations (framework) for bulk whole transcriptome RNA sequencing (RNAseq) data from CD138+ myeloma cells. As proof-of-All rights reserved.…”

“…We illustrate SPECTRA using the Multiple Myeloma Research Foundation (MMRF) CoMMpass Study data. 26 We derive the gene transformations (framework) for bulk whole transcriptome RNA sequencing (RNAseq) data from CD138+ myeloma cells. As a proof-ofconcept, we utilize the spectra variables in various regression models to identify associations with several outcomes, including established risk scores, patient characteristics, and clinical endpoints.…”

Patient Similarity Network of Newly Diagnosed Multiple Myeloma Identifies Patient Sub-groups with Distinct Genetic Features and Clinical Implications

“…In this study, we generated MM-PSN, the first PSN of newly diagnosed MM based on multi-omics data from the MMRF CoMMpass study 20 . Clustering of MM-PSN identified 3 patient groups and 12 sub-groups, revealing novel insights into the co-occurrence of primary translocation events such as t(4;14)-MMSET and secondary adverse lesions such as gain of 1q and whole-arm deletions of 16q and 17p.…”