Mass Cytometry reveals unique phenotypic patterns associated with subclonal diversity and outcomes in multiple myeloma.

Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Although it is known that MM tumor cells display extensive intratumoral genetic heterogeneity, an integrated map of the tumor proteomic landscape has not been comprehensively evaluated. We evaluated 49 primary tumor samples from newly diagnosed or relapsed/refractory MM patients by mass cytometry (CyTOF) using 34 antibody targets to characterize the integrated landscape of single-cell cell surface and intracellular signaling proteins. We identified 13 phenotypic meta-clusters across all samples. The abundance of each phenotypic meta-cluster was compared to patient age, sex, treatment response, tumor genetic abnormalities and overall survival. Relative abundance of several of these phenotypic meta-clusters were associated with disease subtypes and clinical behavior. Increased abundance of phenotypic meta-cluster 1, characterized by elevated CD45 and reduced BCL-2 expression, was significantly associated with a favorable treatment response and improved overall survival independent of tumor genetic abnormalities or patient demographic variables. We validated this association using an unrelated gene expression dataset. This study represents the first, large-scale, single-cell protein atlas of primary MM tumors and demonstrates that subclonal protein profiling may be an important determinant of clinical behavior and outcome.

Return of individual research results and incidental findings in the clinical trials cooperative group setting.

The National Cancer Institute (NCI)-funded cooperative group cancer clinical trial system develops experimental therapies and often collects samples from patients for correlative research. The cooperative group bank (CGB) system maintains biobanks with a current policy not to return research results to individuals. An online survey was created, and 10 directors of CGBs completed the surveys asking about understanding and attitudes in changing policies to consider return of incidental findings (IFs) and individual research results (IRRs) of health significance. The potential impact of the 10 consensus recommendations of Wolf et al. presented in this issue are examined. Reidentification of samples is often not problematic; however, changes to the current banking and clinical trial systems would require significant effort to fulfill an obligation of recontact of subjects. Additional resources, as well as a national advisory board would be required to standardize implementation.

Mapping the inputs, analyses, and outputs of biobank research systems to identify sources of incidental findings and individual research results for potential return to participants.

Progress in the debate over returning incidental findings (IFs) and individual research results (IRRs) to research participants who provide specimens and data to biobanks in genetic and genomic research requires a new tool to allow comparison across heterogeneous biobank research systems and in-depth analysis of the sources and types of findings generated for potential return. This article presents a new visual mapping tool to allow systematic and standardized depiction of (i) the specimens initially collected, (ii) the materials and data sets then created, (iii) the analyses then performed, and finally (iv) the genetic and genomic results generated, including potential IFs and IRRs. For any individual biobank research system, this sequence of four maps can be created to anticipate the sources and types of IFs and IRRs to be generated, to plan how to handle them, and then to manage them responsibly over time. We discuss how this four-map tool was created and describe its application to four national biobank systems, thereby demonstrating that this tool can provide a common platform to visualize biobank content, anticipate how IFs and IRRs will arise in a biobank research context, and inform policy development.

Managing incidental findings and research results in genomic research involving biobanks and archived data sets.

Biobanks and archived data sets collecting samples and data have become crucial engines of genetic and genomic research. Unresolved, however, is what responsibilities biobanks should shoulder to manage incidental findings and individual research results of potential health, reproductive, or personal importance to individual contributors (using "biobank" here to refer both to collections of samples and collections of data). This article reports recommendations from a 2-year project funded by the National Institutes of Health. We analyze the responsibilities involved in managing the return of incidental findings and individual research results in a biobank research system (primary research or collection sites, the biobank itself, and secondary research sites). We suggest that biobanks shoulder significant responsibility for seeing that the biobank research system addresses the return question explicitly. When reidentification of individual contributors is possible, the biobank should work to enable the biobank research system to discharge four core responsibilities to (1) clarify the criteria for evaluating findings and the roster of returnable findings, (2) analyze a particular finding in relation to this, (3) reidentify the individual contributor, and (4) recontact the contributor to offer the finding. We suggest that findings that are analytically valid, reveal an established and substantial risk of a serious health condition, and are clinically actionable should generally be offered to consenting contributors. This article specifies 10 concrete recommendations, addressing new biobanks as well as those already in existence.

secDrug: a pipeline to discover novel drug combinations to kill drug-resistant multiple myeloma cells using a greedy set cover algorithm and single-cell multi-omics.

Multiple myeloma, the second-most common hematopoietic malignancy in the United States, still remains an incurable disease with dose-limiting toxicities and resistance to primary drugs like proteasome inhibitors (PIs) and Immunomodulatory drugs (IMiDs).We have created a computational pipeline that uses pharmacogenomics data-driven optimization-regularization/greedy algorithm to predict novel drugs ("secDrugs") against drug-resistant myeloma. Next, we used single-cell RNA sequencing (scRNAseq) as a screening tool to predict top combination candidates based on the enrichment of target genes. For in vitro validation of secDrugs, we used a panel of human myeloma cell lines representing drug-sensitive, innate/refractory, and acquired/relapsed PI- and IMiD resistance. Next, we performed single-cell proteomics (CyTOF or Cytometry time of flight) in patient-derived bone marrow cells (ex vivo), genome-wide transcriptome analysis (bulk RNA sequencing), and functional assays like CRISPR-based gene editing to explore molecular pathways underlying secDrug efficacy and drug synergy. Finally, we developed a universally applicable R-software package for predicting novel secondary therapies in chemotherapy-resistant cancers that outputs a list of the top drug combination candidates with rank and confidence scores.Thus, using 17AAG (HSP90 inhibitor) + FK866 (NAMPT inhibitor) as proof of principle secDrugs, we established a novel pipeline to introduce several new therapeutic options for the management of PI and IMiD-resistant myeloma.

Single-Cell Proteomics and Tumor RNAseq Identify Novel Pathways Associated With Clofazimine Sensitivity in PI- and IMiD- Resistant Myeloma, and Putative Stem-Like Cells.

Multiple myeloma (MM) is an incurable plasma cell malignancy with dose-limiting toxicities and inter-individual variation in response/resistance to the standard-of-care/primary drugs, proteasome inhibitors (PIs), and immunomodulatory derivatives (IMiDs). Although newer therapeutic options are potentially highly efficacious, their costs outweigh the effectiveness. Previously, we have established that clofazimine (CLF) activates peroxisome proliferator-activated receptor-γ, synergizes with primary therapies, and targets cancer stem-like cells (CSCs) in drug-resistant chronic myeloid leukemia (CML) patients. In this study, we used a panel of human myeloma cell lines as in vitro model systems representing drug-sensitive, innate/refractory, and clonally-derived acquired/relapsed PI- and cereblon (CRBN)-negative IMiD-resistant myeloma and bone marrow-derived CD138+ primary myeloma cells obtained from patients as ex vivo models to demonstrate that CLF shows significant cytotoxicity against drug-resistant myeloma as single-agent and in combination with PIs and IMiDs. Next, using genome-wide transcriptome analysis (RNA-sequencing), single-cell proteomics (CyTOF; Cytometry by time-of-flight), and ingenuity pathway analysis (IPA), we identified novel pathways associated with CLF efficacy, including induction of ER stress, autophagy, mitochondrial dysfunction, oxidative phosphorylation, enhancement of downstream cascade of p65-NFkB-IRF4-Myc downregulation, and ROS-dependent apoptotic cell death in myeloma. Further, we also showed that CLF is effective in killing rare refractory subclones like side populations that have been referred to as myeloma stem-like cells. Since CLF is an FDA-approved drug and also on WHO's list of safe and effective essential medicines, it has strong potential to be rapidly re-purposed as a safe and cost-effective anti-myeloma drug.

Understanding Drug Sensitivity and Tackling Resistance in Cancer.

Decades of research into the molecular mechanisms of cancer and the development of novel therapeutics have yielded a number of remarkable successes. However, our ability to broadly assign effective, rationally targeted therapies in a personalized manner remains elusive for many patients, and drug resistance persists as a major problem. This is in part due to the well-documented heterogeneity of cancer, including the diversity of tumor cell lineages and cell states, the spectrum of somatic mutations, the complexity of microenvironments, and immune-suppressive features and immune repertoires, which collectively require numerous different therapeutic approaches. Here, we describe a framework to understand the types and biological causes of resistance, providing translational opportunities to tackle drug resistance by rational therapeutic strategies.

Allosteric HSP70 inhibitors perturb mitochondrial proteostasis and overcome proteasome inhibitor resistance in multiple myeloma.

Proteasome inhibitor (PI) resistance remains a central challenge in multiple myeloma. To identify pathways mediating resistance, we first mapped proteasome-associated genetic co-dependencies. We identified heat shock protein 70 (HSP70) chaperones as potential targets, consistent with proposed mechanisms of myeloma cells overcoming PI-induced stress. We therefore explored allosteric HSP70 inhibitors (JG compounds) as myeloma therapeutics. JG compounds exhibited increased efficacy against acquired and intrinsic PI-resistant myeloma models, unlike HSP90 inhibition. Shotgun and pulsed SILAC mass spectrometry demonstrated that JGs unexpectedly impact myeloma proteostasis by destabilizing the 55S mitoribosome. Our data suggest JGs have the most pronounced anti-myeloma effect not through inhibiting cytosolic HSP70 proteins but instead through mitochondrial-localized HSP70, HSPA9/mortalin. Analysis of myeloma patient data further supports strong effects of global proteostasis capacity, and particularly HSPA9 expression, on PI response. Our results characterize myeloma proteostasis networks under therapeutic pressure while motivating further investigation of HSPA9 as a specific vulnerability in PI-resistant disease.

Genetic associations with thalidomide mediated venous thrombotic events in myeloma identified using targeted genotyping.

A venous thromboembolism (VTE) with the subsequent risk of pulmonary embolism is a major concern in the treatment of patients with multiple myeloma with thalidomide. The susceptibility to developing a VTE in response to thalidomide therapy is likely to be influenced by both genetic and environmental factors. To test genetic variation associated with treatment related VTE in patient peripheral blood DNA, we used a custom-built molecular inversion probe (MIP)-based single nucleotide polymorphism (SNP) chip containing 3404 SNPs. SNPs on the chip were selected in "functional regions" within 964 genes spanning 67 molecular pathways thought to be involved in the pathogenesis, treatment response, and side effects associated with myeloma therapy. Patients and controls were taken from 3 large clinical trials: Medical Research Council (MRC) Myeloma IX, Hovon-50, and Eastern Cooperative Oncology Group (ECOG) EA100, which compared conventional treatments with thalidomide in patients with myeloma. Our analysis showed that the set of SNPs associated with thalidomide-related VTE were enriched in genes and pathways important in drug transport/metabolism, DNA repair, and cytokine balance. The effects of the SNPs associated with thalidomide-related VTE may be functional at the level of the tumor cell, the tumor-related microenvironment, and the endothelium. The clinical trials described in this paper have been registered as follows: MRC Myeloma IX: ISRCTN68454111; Hovon-50: NCT00028886; and ECOG EA100: NCT00033332.

Deregulation of c-Myc Confers distinct survival requirements for memory B cells, plasma cells, and their progenitors.

Deregulation of the c-Myc oncogene is tightly associated with human and murine plasma cell (PC) neoplasms. Through the analysis of Ag-specific B cell responses in mice where Myc is targeted to the Igh Calpha locus, we show here that c-Myc dramatically impairs the primary and secondary Ab response. This impairment is differentiation stage specific, since germinal center B cell formation, affinity maturation, and class switch recombination were intact. Examination of PC viability revealed that c-Myc triggered apoptosis only upon final maturation when Ab is secreted and is resistant to the survival factor BAFF (B cell-activating factor belonging to the TNF family). In contrast, PC precursors (PC(pre)) that ultimately give rise to mature PCs survived normally and vigorously expanded with BAFF signaling. We further show that c-Myc also facilitates the apoptosis of memory B cells. Thus, Calpha-Myc controls both cellular arms of long-lived B cell immunity than previously anticipated. Only when deregulation of c-Myc was combined with enforced Bcl-x(L) expression were mature PCs able to survive in response to BAFF. These data indicate that the survival requirements for tumor-susceptible PC(pre) and PCs are distinct and that tumor progression likely develops as PC(pre) transition to functional PCs when apoptotic pathways such as members of the Bcl-2 family are disabled.

In vitro and ex vivo gene expression profiling reveals differential kinetic response of HSPs and UPR genes is associated with PI resistance in multiple myeloma.

Extensive inter-individual variation in response to chemotherapy (sensitive vs resistant tumors) is a serious cause of concern in the treatment of multiple myeloma (MM). In this study, we used human myeloma cell lines (HMCLs), and patient-derived CD138+ cells to compare kinetic changes in gene expression patterns between innate proteasome inhibitor (PI)-sensitive and PI-resistant HMCLs following test dosing with the second-generation PI Ixazomib. We found 1553 genes that changed significantly post treatment in PI-sensitive HMCLs compared with only seven in PI-resistant HMCLs (p < 0.05). Genes that were uniquely regulated in PI-resistant lines were RICTOR (activated), HNF4A, miR-16-5p (activated), MYCN (inhibited), and MYC (inhibited). Ingenuity pathway analysis (IPA) using top kinetic response genes identified the proteasome ubiquitination pathway (PUP), and nuclear factor erythroid 2-related factor 2 (NRF2)-mediated oxidative stress response as top canonical pathways in Ix-sensitive cell lines and patient-derived cells, whereas EIF2 signaling and mTOR signaling pathways were unique to PI resistance. Further, 10 genes were common between our in vitro and ex vivo post-treatment kinetic PI response profiles and Shaughnessy's GEP80-postBz gene expression signature, including the high-risk PUP gene PSMD4. Notably, we found that heat shock proteins and PUP pathway genes showed significant higher upregulation in Ix-sensitive lines compared with the fold-change in Ix-resistant myelomas.

A transgenic mouse model of plasma cell malignancy shows phenotypic, cytogenetic, and gene expression heterogeneity similar to human multiple myeloma.

Multiple myeloma is an incurable plasma cell malignancy for which existing animal models are limited. We have previously shown that the targeted expression of the transgenes c-Myc and Bcl-X(L) in murine plasma cells produces malignancy that displays features of human myeloma, such as localization of tumor cells to the bone marrow and lytic bone lesions. We have isolated and characterized in vitro cultures and adoptive transfers of tumors from Bcl-xl/Myc transgenic mice. Tumors have a plasmablastic morphology and variable expression of CD138, CD45, CD38, and CD19. Spectral karyotyping analysis of metaphase chromosomes from primary tumor cell cultures shows that the Bcl-xl/Myc tumors contain a variety of chromosomal abnormalities, including trisomies, translocations, and deletions. The most frequently aberrant chromosomes are 12 and 16. Three sites for recurring translocations were also identified on chromosomes 4D, 12F, and 16C. Gene expression profiling was used to identify differences in gene expression between tumor cells and normal plasma cells (NPC) and to cluster the tumors into two groups (tumor groups C and D), with distinct gene expression profiles. Four hundred and ninety-five genes were significantly different between both tumor groups and NPCs, whereas 124 genes were uniquely different from NPCs in tumor group C and 204 genes were uniquely different from NPCs in tumor group D. Similar to human myeloma, the cyclin D genes are differentially dysregulated in the mouse tumor groups. These data suggest the Bcl-xl/Myc tumors are similar to a subset of plasmablastic human myelomas and provide insight into the specific genes and pathways underlying the human disease.

The future of myeloma precision medicine: integrating the compendium of known drug resistance mechanisms with emerging tumor profiling technologies.

Multiple myeloma (MM) is a hematologic malignancy that is considered mostly incurable in large part due to the inability of standard of care therapies to overcome refractory disease and inevitable drug-resistant relapse. The post-genomic era has been a productive period of discovery where modern sequencing methods have been applied to large MM patient cohorts to modernize our current perception of myeloma pathobiology and establish an appreciation for the vast heterogeneity that exists between and within MM patients. Numerous pre-clinical studies conducted in the last two decades have unveiled a compendium of mechanisms by which malignant plasma cells can escape standard therapies, many of which have potentially quantifiable biomarkers. Exhaustive pre-clinical efforts have evaluated countless putative anti-MM therapeutic agents and many of these have begun to enter clinical trial evaluation. While the palette of available anti-MM therapies is continuing to expand it is also clear that malignant plasma cells still have mechanistic avenues by which they can evade even the most promising new therapies. It is therefore becoming increasingly clear that there is an outstanding need to develop and employ precision medicine strategies in MM management that harness emerging tumor profiling technologies to identify biomarkers that predict efficacy or resistance within an individual's sub-clonally heterogeneous tumor. In this review we present an updated overview of broad classes of therapeutic resistance mechanisms and describe selected examples of putative biomarkers. We also outline several emerging tumor profiling technologies that have the potential to accurately quantify biomarkers for therapeutic sensitivity and resistance at genomic, transcriptomic and proteomic levels. Finally, we comment on the future of implementation for precision medicine strategies in MM and the clear need for a paradigm shift in clinical trial design and disease management.

Identification of a de novo FOXP1 mutation and incidental discovery of inherited genetic variants contributing to a case of autism spectrum disorder and epilepsy.

BACKGROUND: Autism spectrum disorder is commonly co-diagnosed intellectual disability, language disorder, anxiety, and epilepsy, however, symptom management is difficult due to the complex genetic nature of ASD. METHODS: We present a next-generation sequencing-based case study with both de novo and inherited genetic variants and highlight the impact of structural variants on post-translational regulation of protein expression. Since management of symptoms has classically been through pharmaceutical therapies, a pharmacogenomics screen was also utilized to determine possible drug/gene interactions. RESULTS: A de novo variant was identified within the FOXP1 3' untranslated regulatory region using exome sequencing. Additionally, inherited variants that likely contribute to the current and potential future traits were identified within the COMT, SLC6A4, CYP2C19, and CYP2D6 genes. CONCLUSION: This study aims to elucidate how a collection of variant genotypes could potentially impact neural development resulting in a unique phenotype including ASD and epilepsy. Each gene's contribution to neural development is assessed, and the interplay of these genotypes is discussed. The results highlight the utility of exome sequencing in conjunction with pharmacogenomics screening when evaluating possible causes of and therapeutic treatments for ASD-related symptoms.

Molecular signatures of multiple myeloma progression through single cell RNA-Seq.

We used single cell RNA-Seq to examine molecular heterogeneity in multiple myeloma (MM) in 597 CD138 positive cells from bone marrow aspirates of 15 patients at different stages of disease progression. 790 genes were selected by coefficient of variation (CV) method and organized cells into four groups (L1-L4) using unsupervised clustering. Plasma cells from each patient clustered into at least two groups based on gene expression signature. The L1 group contained cells from all MGUS patients having the lowest expression of genes involved in the oxidative phosphorylation, Myc targets, and mTORC1 signaling pathways (p < 1.2 × 10-14). In contrast, the expression level of these pathway genes increased progressively and were the highest in L4 group containing only cells from MM patients with t(4;14) translocations. A 44 genes signature of consistently overexpressed genes among the four groups was associated with poorer overall survival in MM patients (APEX trial, p < 0.0001; HR, 1.83; 95% CI, 1.33-2.52), particularly those treated with bortezomib (p < 0.0001; HR, 2.00; 95% CI, 1.39-2.89). Our study, using single cell RNA-Seq, identified the most significantly affected molecular pathways during MM progression and provided a novel signature predictive of patient prognosis and treatment stratification.

Discovering genetic interactions bridging pathways in genome-wide association studies.

Genetic interactions have been reported to underlie phenotypes in a variety of systems, but the extent to which they contribute to complex disease in humans remains unclear. In principle, genome-wide association studies (GWAS) provide a platform for detecting genetic interactions, but existing methods for identifying them from GWAS data tend to focus on testing individual locus pairs, which undermines statistical power. Importantly, a global genetic network mapped for a model eukaryotic organism revealed that genetic interactions often connect genes between compensatory functional modules in a highly coherent manner. Taking advantage of this expected structure, we developed a computational approach called BridGE that identifies pathways connected by genetic interactions from GWAS data. Applying BridGE broadly, we discover significant interactions in Parkinson's disease, schizophrenia, hypertension, prostate cancer, breast cancer, and type 2 diabetes. Our novel approach provides a general framework for mapping complex genetic networks underlying human disease from genome-wide genotype data.

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

BACKGROUND: We have engaged in an international program designated the Bank On A Cure, 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. 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, n = 70) versus long term progression-free survivors (greater than 3 years, n = 73) in two phase III clinical trials. RESULTS: 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. CONCLUSION: 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.

Genomic research and incidental findings.

The Human Genome Project showed that there is significant genetic variation within the population. Current research is accumulating large databases that may reveal genetic variations associated with disease or health risks, even if not intended as part of the study design. These incidental findings create legal, ethical, and financial challenges for researchers. Current federal and international guidelines are not adequate. Plans for dealing with incidental findings need to be established in the study design and reviewed and approved by the Institutional Review Board.

Managing incidental findings in human subjects research: analysis and recommendations.

No consensus yet exists on how to handle incidental findings (IFs) in human subjects research. Yet empirical studies document IFs in a wide range of research studies, where IFs are findings beyond the aims of the study that are of potential health or reproductive importance to the individual research participant. This paper reports recommendations of a two-year project group funded by NIH to study how to manage IFs in genetic and genomic research, as well as imaging research. We conclude that researchers have an obligation to address the possibility of discovering IFs in their protocol and communications with the IRB, and in their consent forms and communications with research participants. Researchers should establish a pathway for handling IFs and communicate that to the IRB and research participants. We recommend a pathway and categorize IFs into those that must be disclosed to research participants, those that may be disclosed, and those that should not be disclosed.

EZH2 inhibitors sensitize myeloma cell lines to panobinostat resulting in unique combinatorial transcriptomic changes.

Multiple myeloma (MM) remains a largely incurable hematologic cancer due to an inability to broadly target inevitable drug-resistant relapse. Epigenetic abnormalities are abundantly present in multiple myeloma and have increasingly demonstrated critical roles for tumor development and relapse to standard therapies. Accumulating evidence suggests that the histone methyltransferase EZH2 is aberrantly active in MM. We tested the efficacy of EZH2 specific inhibitors in a large panel of human MM cell lines (HMCLs) and found that only a subset of HMCLs demonstrate single agent sensitivity despite ubiquitous global H3K27 demethylation. Pre-treatment with EZH2 inhibitors greatly enhanced the sensitivity of HMCLs to the pan-HDAC inhibitor panobinostat in nearly all cases regardless of single agent EZH2 inhibitor sensitivity. Transcriptomic profiling revealed large-scale transcriptomic alteration by EZH2 inhibition highly enriched for cancer-related pathways. Combination treatment greatly increased the scale of gene expression change with a large portion of differentially expressed genes being unique to the combination. Transcriptomic analysis demonstrated that combination treatment further perturbed oncogenic pathways and signaling nodes consistent with an antiproliferative/pro-apoptotic state. We conclude that combined inhibition of HDAC and EZH2 inhibitors is a promising therapeutic strategy to broadly target the epigenetic landscape of aggressive MM.