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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Glutaminase inhibitor CB-839 synergizes with carfilzomib in resistant multiple myeloma cells.

Curative responses in the treatment of multiple myeloma (MM) are limited by the emergence of therapeutic resistance. To address this problem, we set out to identify druggable mechanisms that convey resistance to proteasome inhibitors (PIs; e.g., bortezomib), which are cornerstone agents in the treatment of MM. In isogenic pairs of PI sensitive and resistant cells, we observed stark differences in cellular bioenergetics between the divergent phenotypes. PI resistant cells exhibited increased mitochondrial respiration driven by glutamine as the principle fuel source. To target glutamine-induced respiration in PI resistant cells, we utilized the glutaminase-1 inhibitor, CB-839. CB-839 inhibited mitochondrial respiration and was more cytotoxic in PI resistant cells as a single agent. Furthermore, we found that CB-839 synergistically enhanced the activity of multiple PIs with the most dramatic synergy being observed with carfilzomib (Crflz), which was confirmed in a panel of genetically diverse PI sensitive and resistant MM cells. Mechanistically, CB-839 enhanced Crflz-induced ER stress and apoptosis, characterized by a robust induction of ATF4 and CHOP and the activation of caspases. Our findings suggest that the acquisition of PI resistance involves adaptations in cellular bioenergetics, supporting the combination of CB-839 with Crflz for the treatment of refractory MM.

A de novo splice site mutation in EHMT1 resulting in Kleefstra syndrome with pharmacogenomics screening and behavior therapy for regressive behaviors.

BACKGROUND: Kleefstra syndrome (KS) is a rare autosomal dominant developmental disability, caused by microdeletions or intragenic mutations within the epigenetic regulator gene EHMT1 (euchromatic histone lysine N-methyltransferase 1). In addition to common features of autism, young adult regressive behaviors have been reported. However, the genetic downstream effects of the reported deletions or mutations on KS phenotype have not yet been completely explored. While genetic backgrounds affecting drug metabolism can have a profound effect on therapeutic interventions, pharmacogenomic variations are seldom considered in directing psychotropic therapies. METHODS: In this report, we used next-generation sequencing (exome sequencing and high-throughput RNA sequencing) in a patient and his parents to identify causative genetic variants followed by pharmacogenomics-guided clinical decision-making for making positive changes toward his treatment strategies. The patient had an early autism diagnosis and showed significant regressive behaviors and physical aberrations at age 23. RESULTS: Exome sequencing identified a novel, de novo splice site variant NM_024757.4: c.2750-1G>T in EHMT1, a candidate gene for Kleefstra syndrome, in the patient that results in exon skipping and downstream frameshift and termination. Gene expression results from the patient showed, when compared to his parents, there was a significant decreased expression of several reported gene variants associated with autism risk. Further, using a pharmacogenomics genotyping panel, we discovered that the patient had the CYP2D6 nonfunctioning variant genotype *4/*4 that results in very low metabolic activity on a number of psychotropic drugs, including fluvoxamine which he was prescribed. As reported here, a change in psychotropic drugs and intense behavior therapies resulted in a significant reversal of the regressive behaviors and physical aberrations. CONCLUSION: These results demonstrate an individualized approach that integrated genetic information and behavior therapies, resulting in a dramatic improvement in regressive behaviors associated with KS.

Phenotypic and functional characterization of a bortezomib-resistant multiple myeloma cell line by flow and mass cytometry.

Multiple myeloma (MM) is an incurable malignant plasma cell neoplasm. Proteasome inhibitors including Bortezomib (Bz) are used to treat MM, and treatment failure due to drug resistance occurs. Bz-sensitive and -resistant MM cells have distinct immunophenotypic signatures that correlate with clinical outcome. These changes can be identified by fluorescence-based cytometry (FBC), however, FBC is rarely used in predicting Bz resistance. Mass cytometry (MC) is a recently developed variation of flow cytometry that detects heavy metal-ion tagged antibodies using time-of-flight mass spectrometry allowing for detection of up to 38 epitopes simultaneously in a single cell, without significant overlap, exceeding the dimensionality of FBC 3-4-fold. Here, we compared FBC and MC in the immunophenotypic characterization of Bz-sensitive and -resistant human MM cell line U266. We show that Bz-resistant cells are associated with the loss of CD56 and CD66a adhesion molecules as well as an activation signature.

Fine-Mapping of 18q21.1 Locus Identifies Single Nucleotide Polymorphisms Associated with Nonsyndromic Cleft Lip with or without Cleft Palate.

Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is one of the most common congenital birth defects. NSCL/P is a complex multifactorial disease caused by interactions between multiple environmental and genetic factors. However, the causal single nucleotide polymorphism (SNP) signature profile underlying the risk of familial NSCL/P still remains unknown. We previously reported a 5.7-Mb genomic region on chromosome 18q21.1 locus that potentially contributes to autosomal dominant, low-penetrance inheritance of NSCL/P. In the current study, we performed exome sequencing on 12 familial genomes (six affected individuals, two obligate carriers, and four seemingly unaffected individuals) of a six-generation family to identify candidate SNPs associated with NSCL/P risk. Subsequently, targeted bidirectional DNA re-sequencing of polymerase chain reaction (PCR)-amplified high-risk regions of MYO5B gene and sequenom iPLEX genotpying of 29 candidate SNPs were performed on a larger set of 33 members of this NSCL/P family (10 affected + 4 obligate carriers + 19 unaffected relatives) to find SNPs significantly associated with NSCL/P trait. SNP vs. NSCL/P association analysis showed the MYO5B SNP rs183559995 GA genotype had an odds ratio of 18.09 (95% Confidence Interval = 1.86-176.34; gender-adjusted P = 0.0019) compared to the reference GG genotype. Additionally, the following SNPs were also found significantly associated with NSCL/P risk: rs1450425 (LOXHD1), rs6507992 (SKA1), rs78950893 (SMAD7), rs8097060, rs17713847 (SCARNA17), rs6507872 (CTIF), rs8091995 (CTIF), and rs17715416 (MYO5B). We could thus identify mutations in several genes as key candidate SNPs associated with the risk of NSCL/P in this large multi-generation family.

PIAS1 Promotes Lymphomagenesis through MYC Upregulation.

The MYC proto-oncogene is a transcription factor implicated in a broad range of cancers. MYC is regulated by several post-translational modifications including SUMOylation, but the functional impact of this post-translational modification is still unclear. Here, we report that the SUMO E3 ligase PIAS1 SUMOylates MYC. We demonstrate that PIAS1 promotes, in a SUMOylation-dependent manner, MYC phosphorylation at serine 62 and dephosphorylation at threonine 58. These events reduce the MYC turnover, leading to increased transcriptional activity. Furthermore, we find that MYC is SUMOylated in primary B cell lymphomas and that PIAS1 is required for the viability of MYC-dependent B cell lymphoma cells as well as several cancer cell lines of epithelial origin. Finally, Pias1-null mice display endothelial defects reminiscent of Myc-null mice. Taken together, these results indicate that PIAS1 is a positive regulator of MYC.

Risk of multiple myeloma in a case-spouse study.

This study examined lifestyle, occupation, medical history and medication use with multiple myeloma risk in a case-spouse study (481 patients, 351 spouses). Odds ratios (ORs) and 95% confidence intervals (CI) were calculated using logistic regression. Compared to spouse controls, cases were more likely to have a family history of multiple myeloma (OR = 2.8, 95% CI = 1.2-6.4) and smoked cigarettes (OR = 1.7, 95% CI = 1.2-2.5), but less likely to have consumed alcohol (OR = 0.6, 95% CI = 0.4-0.9). Nurse/health practitioners (OR = 2.8, 95% CI = 1.3-6.2) and production workers (OR = 3.7, 95% CI = 1.0-13.7) had significantly increased risks; and some occupations linked to diesel exhaust had elevated, but non-significant, risks. History of herpes simplex (OR = 1.7, 95% CI = 1.2-2.4), shingles (OR = 1.7, 95% CI = 1.1-2.7), sexually transmitted diseases (OR = 2.0, 95% CI = 1.0-3.7) and medication allergies (OR = 1.7, 95% CI = 1.2-2.4) were associated with higher risks. Use of angiotensin-converting enzyme inhibitors, anti-convulsants, antidepressants, statins and diuretics were associated with reduced risks. The results are consistent with previous population-based studies and support the utility of patient databanks and spouse controls as a resource in epidemiologic research.

Applications and limitations in translating genomics to clinical practice.

Recent efforts to broadly apply genetics to clinical practice have been driven by the rapid advancement of genomic technologies and the discovery of genes associated with disease risk, progression, and treatment response. Yet there remain valid concerns about the complexities and limitations that confront the popular notion of clinical utility of genetics in personalized medicine. Research is still very much in the mode of discovery. The excitement of discovery and applications to diagnostics are well described in each of the articles in this issue. Yet, each article appropriately acknowledges the limitations that need to be overcome to apply new knowledge to clinical practice.