Five gene probes carry most of the discriminatory power of the 70-gene risk model in multiple myeloma

Single-Cell RNA Sequencing before and after Light Chain Escape Reveals Intrapatient Multiple Myeloma Subpopulations with Divergent Osteolytic Gene Expression

SIGNIFICANCE

scRNA-seq was used to study a patient with high-risk multiple myeloma featuring LCE. LCE was rooted in a transcriptomic subpopulation that corresponded to a genetic subclone and established novel links between LCE and LAMP5 overexpression to osteolysis and prognosis, validated in RNA-seq databases.

IRX-related homeobox gene MKX is a novel oncogene in acute myeloid leukemia

Homeobox genes encode transcription factors which organize differentiation processes in all tissue types including the hematopoietic compartment. Recently, we have reported physiological expression of TALE-class homeobox gene IRX1 in early myelopoiesis restricted to the megakaryocyte-erythroid-progenitor stage and in early B-cell development to the pro-B-cell stage. In contrast, sister homeobox genes IRX2, IRX3 and IRX5 are aberrantly activated in the corresponding malignancies acute myeloid leukemia (AML) and B-cell progenitor acute lymphoid leukemia. Here, we examined the role of IRX-related homeobox gene MKX (also termed IRXL1 or mohawk) in normal and malignant hematopoiesis. Screening of public datasets revealed silent MKX in normal myelopoiesis and B-cell differentiation, and aberrant expression in subsets of AML and multiple myeloma (MM) cell lines and patients. To investigate its dysregulation and oncogenic function we used AML cell line OCI-AML3 as model which strongly expressed MKX at both RNA and protein levels. We found that IRX5, JUNB and NFkB activated MKX in this cell line, while downregulated GATA2 and STAT5 inhibited its expression. MKX downstream analysis was conducted by siRNA-mediated knockdown and RNA-sequencing in OCI-AML3, and by comparative expression profiling analysis of a public dataset from MM patients. Analysis of these data revealed activation of CCL2 which in turn promoted proliferation. Furthermore, MKX upregulated SESN3 and downregulated BCL2L11, which may together underlie decreased etoposide-induced apoptosis. Finally, myeloid differentiation genes CEBPD and GATA2 were respectively up- and downregulated by MKX. Taken together, our study identified MKX as novel aberrantly expressed homeobox gene in AML and MM, highlighting the function of IRX1 in normal myelopoiesis and B-cell development, and of IRX-related genes in corresponding malignancies. Our data merit further investigation of MKX and its deregulated target genes to serve as novel markers and/or potential therapeutic targets in AML patient subsets.

Molecular Signatures of CB-6644 Inhibition of the RUVBL1/2 Complex in Multiple Myeloma

Multiple myeloma is the second most hematological cancer. RUVBL1 and RUVBL2 form a subcomplex of many chromatin remodeling complexes implicated in cancer progression. As an inhibitor specific to the RUVBL1/2 complex, CB-6644 exhibits remarkable anti-tumor activity in xenograft models of Burkitt's lymphoma and multiple myeloma (MM). In this work, we defined transcriptional signatures corresponding to CB-6644 treatment in MM cells and determined underlying epigenetic changes in terms of chromatin accessibility. CB-6644 upregulated biological processes related to interferon response and downregulated those linked to cell proliferation in MM cells. Transcriptional regulator inference identified E2Fs as regulators for downregulated genes and MED1 and MYC as regulators for upregulated genes. CB-6644-induced changes in chromatin accessibility occurred mostly in non-promoter regions. Footprinting analysis identified transcription factors implied in modulating chromatin accessibility in response to CB-6644 treatment, including ATF4/CEBP and IRF4. Lastly, integrative analysis of transcription responses to various chemical compounds of the molecular signature genes from public gene expression data identified CB-5083, a p97 inhibitor, as a synergistic candidate with CB-6644 in MM cells, but experimental validation refuted this hypothesis.

Fc receptor-like 5 (FCRL5)-directed CAR-T cells exhibit antitumor activity against multiple myeloma

Multiple myeloma (MM) remains a challenging hematologic malignancy despite advancements in chimeric antigen receptor T-cell (CAR-T) therapy. Current targets of CAR-T cells used in MM immunotherapy have limitations, with a subset of patients experiencing antigen loss resulting in relapse. Therefore, novel targets for enhancing CAR-T cell therapy in MM remain needed. Fc receptor-like 5 (FCRL5) is a protein marker with considerably upregulated expression in MM and has emerged as a promising target for CAR-T cell therapeutic interventions, offering an alternative treatment for MM. To further explore this option, we designed FCRL5-directed CAR-T cells and assessed their cytotoxicity in vitro using a co-culture system and in vivo using MM cell-derived xenograft models, specifically focusing on MM with gain of chromosome 1q21. Given the challenges in CAR-T therapies arising from limited T cell persistence, our approach incorporates interleukin-15 (IL-15), which enhances the functionality of central memory T (TCM) cells, into the design of FCRL5-directed CAR-T cells, to improve cytotoxicity and reduce T-cell dysfunction, thereby promoting greater CAR-T cell survival and efficacy. Both in vitro and xenograft models displayed that FCRL5 CAR-T cells incorporating IL-15 exhibited potent antitumor efficacy, effectively inhibiting the proliferation of MM cells and leading to remarkable tumor suppression. Our results highlight the capacity of FCRL5-specific CAR-T cells with the integration of IL-15 to improve the therapeutic potency, suggesting a potential novel immunotherapeutic strategy for MM treatment.

Integrating Lysosomal Genes and Immune Infiltration for Multiple Myeloma Subtyping and Prognostic Stratification

Lysosomes are crucial in the tumour immune microenvironment, which is essential for the survival and homeostasis in multiple myeloma (MM). Here, we aimed to identify lysosome-related genes for the prognosis of MM and predicted their regulatory mechanisms. Gene expression profiles of MM from the GSE2658 and GSE57317 datasets were analysed. Lysosome-related differentially expressed genes (DEGs) were identified and used for molecular subtyping of MM patients. A prognostic model was constructed using univariate Cox regression and LASSO regression analyses. The relationship between prognostic genes, immune cell types, and autophagy pathways was assessed through correlation analysis. RT-qPCR was performed to validate the expression of prognostic genes in MM cells. A total of 9,954 DEGs were identified between high and low immune score groups, with 213 intersecting with lysosomal genes. Molecular subtyping revealed two distinct MM subtypes with significant differences in immune cell types and autophagy pathway activities. Five lysosome-related DEGs (CORO1A, ELANE, PSAP, RNASE2, and SNAPIN) were identified as significant prognostic markers. The prognostic model showed moderate predictive accuracy with AUC values up to 0.723. Prognostic genes demonstrated significant correlations with various immune cell types and autophagy pathways. Additionally, CORO1A, PSAP and RNASE2 expression was up-regulated in MM cells, while ELANE and SNAPIN were down-regulated. Five lysosomal genes in MM were identified, and a new risk model for prognosis was developed using these genes. This research could lead to discovering important gene markers for the treatment and prognosis of MM.

Dependency of B-Cell Acute Lymphoblastic Leukemia and Multiple Myeloma Cell Lines on MEN1 Extends beyond MEN1-KMT2A Interaction

Menin/MEN1 is a scaffold protein that participates in proliferation, regulation of gene transcription, DNA damage repair, and signal transduction. In hematological malignancies harboring the KMT2A/MLL1 (MLLr) chromosomal rearrangements, the interaction of the oncogenic fusion protein MLLr with MEN1 has been shown to be essential. MEN1 binders inhibiting the MEN1 and KMT2A interaction have been shown to be effective against MLLr AML and B-ALL in experimental models and clinical studies. We hypothesized that in addition to the MEN1-KMT2A interaction, alternative mechanisms might be instrumental in the MEN1 dependency of leukemia. We first mined and analyzed data from publicly available gene expression databases, finding that the dependency of B-ALL cell lines on MEN1 did not correlate with the presence of MLLr. Using shRNA-mediated knockdown, we found that all tested B-ALL cell lines were sensitive to MEN1 depletion, independent of the underlying driver mutations. Most multiple myeloma cell lines that did not harbor MLLr were also sensitive to the genetic depletion of MEN1. We conclude that the oncogenic role of MEN1 is not limited to the interaction with KMT2A. Our results suggest that targeted degradation of MEN1 or the development of binders that induce global changes in the MEN1 protein structure may be more efficient than the inhibition of individual MEN1 protein interactions.

Proteomic profiling reveals CDK6 upregulation as a targetable resistance mechanism for lenalidomide in multiple myeloma

The immunomodulatory drugs (IMiDs) lenalidomide and pomalidomide are highly effective treatments for multiple myeloma. However, virtually all patients eventually relapse due to acquired drug resistance with resistance-causing genetic alterations being found only in a small subset of cases. To identify non-genetic mechanisms of drug resistance, we here perform integrated global quantitative tandem mass tag (TMT)-based proteomic and phosphoproteomic analyses and RNA sequencing in five paired pre-treatment and relapse samples from multiple myeloma patients. These analyses reveal a CDK6-governed protein resistance signature that includes myeloma high-risk factors such as TRIP13 and RRM1. Overexpression of CDK6 in multiple myeloma cell lines reduces sensitivity to IMiDs while CDK6 inhibition by palbociclib or CDK6 degradation by proteolysis targeting chimeras (PROTACs) is highly synergistic with IMiDs in vitro and in vivo. This work identifies CDK6 upregulation as a druggable target in IMiD-resistant multiple myeloma and highlights the use of proteomic studies to uncover non-genetic resistance mechanisms in cancer.

Acquired resistance to immunomodulatory drugs is common in multiple myeloma patients, but rarely attributed to genetic alterations. Here, proteomic, phosphoproteomic and RNA sequencing analysis in five paired pre-treatment and relapse samples reveals a CDK6-regulated protein resistance signature.

Bone Marrow Stroma-Induced Transcriptome and Regulome Signatures of Multiple Myeloma

Multiple myeloma (MM) is a hematological cancer with inevitable drug resistance. MM cells interacting with bone marrow stromal cells (BMSCs) undergo substantial changes in the transcriptome and develop de novo multi-drug resistance. As a critical component in transcriptional regulation, how the chromatin landscape is transformed in MM cells exposed to BMSCs and contributes to the transcriptional response to BMSCs remains elusive. We profiled the transcriptome and regulome for MM cells using a transwell coculture system with BMSCs. The transcriptome and regulome of MM cells from the upper transwell resembled MM cells that coexisted with BMSCs from the lower chamber but were distinctive to monoculture. BMSC-induced genes were enriched in the JAK2/STAT3 signaling pathway, unfolded protein stress, signatures of early plasma cells, and response to proteasome inhibitors. Genes with increasing accessibility at multiple regulatory sites were preferentially induced by BMSCs; these genes were enriched in functions linked to responses to drugs and unfavorable clinic outcomes. We proposed JUNB and ATF4::CEBPβ as candidate transcription factors (TFs) that modulate the BMSC-induced transformation of the regulome linked to the transcriptional response. Together, we characterized the BMSC-induced transcriptome and regulome signatures of MM cells to facilitate research on epigenetic mechanisms of BMSC-induced multi-drug resistance in MM.

RNA demethylase ALKBH5 promotes tumorigenesis in multiple myeloma via TRAF1-mediated activation of NF-κB and MAPK signaling pathways

N⁶-methyladenosine (m⁶A), an internal modification in mRNA, plays a critical role in regulating gene expression. Dysregulation of m⁶A modifiers promotes oncogenesis through enzymatic functions that disrupt the balance between the deposition and removal of m⁶A modification on critical transcripts. However, the roles of mRNA m⁶A in multiple myeloma (MM) are poorly understood. The present study showed that RNA demethylase ALKBH5 was overexpressed in MM and associated with a poor prognosis in MM patients. Knocking down ALKBH5 induced apoptosis and inhibited the growth of MM cells in vitro. Xenograft models and gene set enrichment analysis with patient transcriptome datasets also supported the oncogenic role of ALKBH5 in MM. Mechanistic studies showed that ALKBH5 exerted tumorigenic effects in myeloma in an m⁶A-dependent manner, and TNF receptor-associated factor 1 (TRAF1) was a critical target of ALKBH5. Specifically, ALKBH5 regulated TRAF1 expression via decreasing m⁶A abundance in the 3'-untranslated region (3'-UTR) of TRAF1 transcripts and enhancing TRAF1 mRNA stability. As a result, ALKBH5 promoted MM cell growth and survival through TRAF1-mediated activation of NF-κB and MAPK signaling pathways. Collectively, our data demonstrated that ALKBH5 played a critical role in MM tumorigenesis and suggested that ALKBH5 could be a novel therapeutic target in MM.

A Five-Gene Risk Score Model for Predicting the Prognosis of Multiple Myeloma Patients Based on Gene Expression Profiles

Multiple myeloma is a heterogeneous plasma cell malignancy that remains incurable because of the tendency of relapse for most patients. Survival outcomes may vary widely due to patient and disease variables; therefore, it is necessary to establish a more accurate prognostic model to improve prognostic precision and guide clinical therapy. Here, we developed a risk score model based on myeloma gene expression profiles from three independent datasets: GSE6477, GSE13591, and GSE24080. In this model, highly survival-associated five genes, including EPAS1, ERC2, PRC1, CSGALNACT1, and CCND1, are selected by using the least absolute shrinkage and selection operator (Lasso) regression and univariate and multivariate Cox regression analyses. At last, we analyzed three validation datasets (including GSE2658, GSE136337, and MMRF datasets) to examine the prognostic efficacy of this model by dividing patients into high-risk and low-risk groups based on the median risk score. The results indicated that the survival of patients in low-risk group was greatly prolonged compared with their counterparts in the high-risk group. Therefore, the five-gene risk score model could increase the accuracy of risk stratification and provide effective prediction for the prognosis of patients and instruction for individualized clinical treatment.

TRIP13 modulates protein deubiquitination and accelerates tumor development and progression of B cell malignancies

Multiple myeloma (MM), a terminally differentiated B cell malignancy, remains difficult to cure. Understanding the molecular mechanisms underlying the progression of MM may identify therapeutic targets and lead to a fundamental shift in treatment of the disease. Deubiquitination, like ubiquitination, is a highly regulated process, implicated in almost every cellular process. Multiple deubiquitinating enzymes (DUBs) have been identified, but their regulation is poorly defined. Here, we determined that TRIP13 increases cellular deubiquitination. Overexpression of TRIP13 in mice and cultured cells resulted in excess cellular deubiquitination by enhancing the association of the DUB USP7 with its substrates. We show that TRIP13 is an oncogenic protein because it accelerates B cell tumor development in transgenic mice. TRIP13-induced resistance to proteasome inhibition can be overcome by a USP7 inhibitor in vitro and in vivo. These findings suggest that TRIP13 expression plays a critical role in B cell lymphoma and MM by regulating deubiquitination of critical oncogenic (NEK2) and tumor suppressor (PTEN, p53) proteins. High TRIP13 identifies a high-risk patient group amenable to adjuvant anti-USP7 therapy.

Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients

Gene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype-tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10^-7 either in EBV-transformed B-lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression-free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4-rs1992292, TBRG4-rs2287535 and ENTPD1-rs2153913) showed associations with OS at P < .05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta-analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4-rs1992292 is associated with OS (hazard ratio = 1.14, 95% confidence interval 1.04-1.26, P = .007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.

Evaluation of Daratumumab for the Treatment of Multiple Myeloma in Patients With High-risk Cytogenetic Factors: A Systematic Review and Meta-analysis

Importance

The addition of daratumumab to backbone multiple myeloma (MM) regimens is associated with improved response rates and progression-free survival (PFS). Whether improved outcomes are also associated with this regimen among patients with cytogenetically defined high-risk MM (HRMM) remains unclear.

Objective

To measure PFS associated with adding daratumumab to backbone MM regimens among patients with HRMM.

Data Sources

For this systematic review and meta-analysis, MEDLINE, Embase, PubMed, Scopus, Web of Science Core Collection, Cochrane Library, clinical trials registries, and meeting libraries were searched from inception to January 2, 2020, using terms reflecting multiple myeloma and daratumumab.

Study Selection

Included studies were phase 3 randomized clinical trials that compared backbone MM regimens with the same regimen plus daratumumab in newly diagnosed or relapsed or refractory MM, such that the only difference between the intervention and control groups was use of daratumumab and reported outcomes by cytogenetic risk. High-risk MM was defined as the presence of t(4;14), t(14;16), or del(17p).

Data Extraction and Synthesis

Using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline, 2 investigators independently extracted study data, with disagreements resolved by a third investigator. Quality was assessed by the Cochrane risk-of-bias method.

Main Outcomes and Measures

Data on effectiveness were extracted using hazard ratios (HRs) for PFS. Relative log-HRs were pooled using a DerSimonian-Laird random-effects model. Heterogeneity was assessed using the Cochran Q and the I2 statistic.

Results

Of 5194 studies screened, 6 phase 3 trials were eligible, including 3 trials for newly diagnosed MM (2528 patients; 358 with HRMM) and 3 trials for relapsed or refractory MM (1533 patients; 222 with HRMM). Among patients with newly diagnosed HRMM, the addition of daratumumab to backbone regimens was associated with improved PFS (pooled HR, 0.67; 95% CI, 0.47-0.95; P = .02), with little evidence of heterogeneity (Cochran Q, P = .77; I2 = 0%). Similar results were seen among patients with relapsed or refractory HRMM (pooled HR, 0.45; 95% CI, 0.30-0.67; P < .001), again with little evidence of heterogeneity (Cochran Q, P = .63; I2 = 0%).

Conclusions and Relevance

This study suggests that incorporating daratumumab to backbone regimens may be associated with improved PFS among patients with newly diagnosed HRMM or relapsed or refractory HRMM.

Abnormal PTBP1 Expression Sustains the Disease Progression of Multiple Myeloma

Multiple myeloma (MM) is a hematopoietic malignancy characterized by heterogeneity, which corresponds to alternative splicing (AS) profiles and disadjust gene expression. Bioinformatics analysis of AS factors possibly related to MM progression identified the polypyrimidine tract binding protein (PTBP1) as candidate. The purpose of this study was to confirm the incidence and prognostic value of PTBP1 in MM patients. Several cohorts of 2971 patients presenting newly diagnosed and relapsed MM were enrolled. Correlations between PTBP1 expression and clinicopathological characteristics, proliferative activity, and response to therapy of myeloma cells were analyzed. Moreover, the effect of PTBP1 on the AS pattern of specific aerobic glycolysis-related genes was explored in MM patients. Clinically, PTBP1 expression was present at all stages; it increased with disease progression and poor prognosis, which was even stronger elevated in patients with high tumor burden and drug resistance. Mechanistically, PTBP1 modulated AS of PKM2 and aerobic glycolysis-related genes in MM patients, which play synergistic or additive effects in clinical outcome. PTBP1 may be a novel marker for prognostic prediction and a promising therapeutic target for the development of anti-MM treatments.

A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma

Purpose

Risk stratification in patients with multiple myeloma (MM) remains a challenge. As clinicopathological characteristics have been demonstrated insufficient for exactly defining MM risk, and molecular biomarkers have become the focuses of interests. Prognostic predictions based on gene expression profiles (GEPs) have been the most accurate to this day. The purpose of our study was to construct a risk score based on stemness genes to evaluate the prognosis in MM.

Materials and Methods

Bioinformatics studies by ingenuity pathway analyses in side population (SP) and non-SP (MP) cells of MM patients were performed. Firstly, co-expression network was built to confirm hub genes associated with the top five Kyoto Encyclopedia of Genes and Genomes pathways. Functional analyses of hub genes were used to confirm the biologic functions. Next, these selective genes were utilized for construction of prognostic model, and this model was validated in independent testing sets. Finally, five stemness genes (ROCK1, GSK3B, BRAF, MAPK1 and MAPK14) were used to build a MM side population 5 (MMSP5) gene model, which was demonstrated to be forcefully prognostic compared to usual clinical prognostic parameters by multivariate cox analysis. MM patients in MMSP5 low-risk group were significantly related to better prognosis than those in high-risk group in independent testing sets.

Conclusion

Our study provided proof-of-concept that MMSP5 model can be adopted to evaluate recurrence risk and clinical outcome for MM. The MMSP5 model evaluated in different databases clearly indicated novel risk stratification for personalized anti-MM treatments.

Preclinical validation of Alpha-Enolase (ENO1) as a novel immunometabolic target in multiple myeloma

Bone marrow plasmacytoid dendritic cells (pDCs) in patients with multiple myeloma (MM) promote tumor growth, survival, drug resistance, and immune suppression. Understanding the molecular signaling crosstalk among the tumor cells, pDCs and immune cells will identify novel therapeutic approaches to enhance anti-MM immunity. Using oligonucleotide arrays, we found that pDC-MM interactions induce metabolic enzyme Alpha-Enolase (ENO1) in both pDCs and MM cells. Analysis of MM patient gene expression profiling database showed that ENO1 expression inversely correlates with overall survival. Protein expression analysis showed that ENO1 is expressed in pDC and MM cells; and importantly, that pDC-MM coculture further increases ENO1 expression in both MM cells and pDCs. Using our coculture models of patient autologous pDC-T-NK-MM cells, we examined whether targeting ENO1 can enhance anti-MM immunity. Biochemical inhibition of ENO1 with ENO1 inhibitor (ENO1i) activates pDCs, as well as increases pDC-induced MM-specific CD8⁺ CTL and NK cell activity against autologous tumor cells. Combination of ENO1i and anti-PD-L1 Ab or HDAC6i ACY-241 enhances autologous MM-specific CD8⁺ CTL activity. Our preclinical data therefore provide the basis for novel immune-based therapeutic approaches targeting ENO1, alone or in combination with anti-PD-L1 Ab or ACY241, to restore anti-MM immunity, enhance MM cytotoxicity, and improve patient outcome.

Single-cell RNA sequencing reveals chemokine self-feeding of myeloma cells promotes extramedullary metastasis

In this study, we aimed to determine the mechanisms underlying the initial extramedullary translocation of myeloma cells from bone marrow into peripheral blood. We found that clonal circulating plasma cells (cPCs) are more frequently detected by flow cytometry in extramedullary plasmacytoma (EMP) patients and worsen their prognosis. It is technically much easier to collect single cPCs using FACS than it is to perform EMP biopsy. Therefore, combining EMP imaging with cPC detection may be a promising strategy for prognostic stratification. Here, using single-cell transcriptome analysis, we found that the chemokine CXCL12, a key molecule involved in CXCR4-dependent cell retention in the bone marrow, is abnormally upregulated in cPCs and might initially enable cPCs to evade bone marrow retention and translocate into the bloodstream.

PHF19 promotes multiple myeloma tumorigenicity through PRC2 activation and broad H3K27me3 domain formation

Dysregulation of polycomb repressive complex 2 (PRC2) promotes oncogenesis partly through its enzymatic function for inducing trimethylation of histone H3 lysine 27 (H3K27me3). However, it remains to be determined how PRC2 activity is regulated in normal and diseased settings. We here report a PRC2-associated cofactor, PHD finger protein 19 (PHF19; also known as polycomb-like 3), as a crucial mediator of tumorigenicity in multiple myeloma (MM). Overexpression and/or genomic amplification of PHF19 is found associated with malignant progression of MM and plasma cell leukemia, correlating to worse treatment outcomes. Using various MM models, we demonstrated a critical requirement of PHF19 for tumor growth in vitro and in vivo. Mechanistically, PHF19-mediated oncogenic effect relies on its PRC2-interacting and chromatin-binding functions. Chromatin immunoprecipitation followed by sequencing profiling showed a critical role for PHF19 in maintaining the H3K27me3 landscape. PHF19 depletion led to loss of broad H3K27me3 domains, possibly due to impaired H3K27me3 spreading from cytosine guanine dinucleotide islands, which is reminiscent to the reported effect of an "onco"-histone mutation, H3K27 to methionine (H3K27M). RNA-sequencing-based transcriptome profiling in MM lines also demonstrated a requirement of PHF19 for optimal silencing of PRC2 targets, which include cell cycle inhibitors and interferon-JAK-STAT signaling genes critically involved in tumor suppression. Correlation studies using patient sample data sets further support a clinical relevance of the PHF19-regulated pathways. Lastly, we show that MM cells are generally sensitive to PRC2 inhibitors. Collectively, this study demonstrates that PHF19 promotes MM tumorigenesis through enhancing H3K27me3 deposition and PRC2's gene-regulatory functions, lending support for PRC2 blockade as a means for MM therapeutics.

A Network Analysis of Multiple Myeloma Related Gene Signatures

Multiple myeloma (MM) is the second most prevalent hematological cancer. MM is a complex and heterogeneous disease, and thus, it is essential to leverage omics data from large MM cohorts to understand the molecular mechanisms underlying MM tumorigenesis, progression, and drug responses, which may aid in the development of better treatments. In this study, we analyzed gene expression, copy number variation, and clinical data from the Multiple Myeloma Research Consortium (MMRC) dataset and constructed a multiple myeloma molecular causal network (M3CN). The M3CN was used to unify eight prognostic gene signatures in the literature that shared very few genes between them, resulting in a prognostic subnetwork of the M3CN, consisting of 178 genes that were enriched for genes involved in cell cycle (fold enrichment = 8.4, p value = 6.1 × 10⁻²⁶). The M3CN was further used to characterize immunomodulators and proteasome inhibitors for MM, demonstrating the pleiotropic effects of these drugs, with drug-response signature genes enriched across multiple M3CN subnetworks. Network analyses indicated potential links between these drug-response subnetworks and the prognostic subnetwork. To elucidate the structure of these important MM subnetworks, we identified putative key regulators predicted to modulate the state of these subnetworks. Finally, to assess the predictive power of our network-based models, we stratified MM patients in an independent cohort, the MMRF-CoMMpass study, based on the prognostic subnetwork, and compared the performance of this subnetwork against other signatures in the literature. We show that the M3CN-derived prognostic subnetwork achieved the best separation between different risk groups in terms of log-rank test p-values and hazard ratios. In summary, this work demonstrates the power of a probabilistic causal network approach to understanding molecular mechanisms underlying the different MM signatures.

The Use of Murine Models for Studying Mechanistic Insights of Genomic Instability in Multiple Myeloma

Multiple myeloma (MM) is a B-cell malignancy characterized by the accumulation of clonal plasma cells in the bone marrow. In normal plasma cell development, cells undergo programmed DNA breaks and translocations, a process necessary for generation of a wide repertoire of antigen-specific antibodies. This process also makes them vulnerable for the acquisition of chromosomal defects. Well-known examples of these aberrations, already seen at time of MM diagnosis, are hyperdiploidy or the translocations involving the immunoglobulin heavy chain. Over the recent years, however, novel aspects concerning genomic instability and its role in tumor development, disease progression and nascence of refractory disease were identified. As such, genomic instability is becoming a very relevant research topic with the potential identification of novel disease pathways. In this review, we aim to describe recent studies involving murine MM models focusing on the deregulation of processes implicated in genomic instability and their clinical impact. More specifically, we will discuss chromosomal instability, DNA damage and repair responses, development of drug resistance, and recent insights into the study of clonal hierarchy using different murine MM models. Lastly, we will discuss the importance and the use of murine MM models in the pre-clinical evaluation of promising novel therapeutic agents.

Elevated TRIP13 drives cell proliferation and drug resistance in bladder cancer

Dysregulation of mitotic processes can induce chromosome instability, which results in aneuploidy, tumorigenesis, and chemo-resistance. Thyroid hormone receptor interactor 13 (TRIP13) is a critical mitosis regulator, and recent studies suggest that it functions as an oncogene in multiple cancers. However, the role of TRIP13 in bladder cancer (BC) is still unknown. In this study, our analysis of RNA-sequencing data from the Cancer Genome Atlas and Gene expression profiling databases showed that TRIP13 expression was upregulated in BC tissues, and overexpression of TRIP13 was significantly associated with poor prognosis of BC patients. In addition, we found a remarkable elevation of TRIP13 in BC samples compared to normal controls by immunohistochemistry. Furthermore, our in vitro functional assays showed that overexpression of TRIP13 promoted the growth/viability, colony formation ability by inducing cell cycle arrest in G2/M phase, as well as enhancing drug resistance of BC cells to cisplatin and doxorubicin. Conversely, knockdown of TRIP13 inhibited cell growth and induced apoptosis of BC cells. Furthermore, TRIP13 acted as an oncogene in BC by inhibiting spindle assembly checkpoint signaling by targeting mitotic arrest deficient 2 (MAD2) protein. TRIP13 overexpression also alleviated cisplatin- and doxorubicin-induced DNA damage and enhanced DNA repair as evidenced by the reduced expression of γH2AX and enhanced expression of RAD50 in drug-treated BC cells. In conclusion, TRIP13 may be a novel target for the treatment of BC.

Insights into a Crucial Role of TRIP13 in Human Cancer

Thyroid Hormone Receptor Interacting Protein 13 (TRIP13) plays a key role in regulating mitotic processes, including spindle assembly checkpoint and DNA repair pathways, which may account for Chromosome instability (CIN). As CIN is a predominant hallmark of cancer, TRIP13 may act as a tumor susceptibility locus. Amplification of TRIP13 has been observed in various human cancers and implicated in several aspects of malignant transformation, including cancer cell proliferation, drug resistance and tumor progression. Here, we discussed the functional significance of TRIP13 in cell progression, highlighted the recent findings on the aberrant expression in human cancers and emphasized its significance for the therapeutic potential.

Investigation of a gene signature to predict response to immunomodulatory derivatives for patients with multiple myeloma: an exploratory, retrospective study using microarray datasets from prospective clinical trials

BACKGROUND

Immunomodulatory derivatives (IMiDs), along with proteasome inhibitors, are key components of treatment regimens for multiple myeloma. Nonetheless, outcomes vary among treated individuals. Drug-specific gene-expression profile (GEP) signatures that aid the prediction of favourable and unfavourable outcomes can provide patients with the most effective therapy for their individual disease. We aimed to develop and validate a gene expression signature to suggest which patients would benefit most from IMiD-based therapies.

METHODS

For this exploratory retrospective study, we selected a cohort of patients with newly diagnosed or relapsed or refractory multiple myeloma who were treated in clinical trials with IMiD-containing regimens. Cohorts were eligible if they had publicly available GEP data from patients' bone marrow plasma cells, with long-term follow-up and clinicopathological data. In the development stage of the model, we identified 176 IMiD response genes that were differentially expressed before and after IMiD exposure using pharmacogenomic GEP data from patients who had bone marrow samples taken before and 48 h after a test dose exposure with thalidomide (n=42), lenalidomide (n=18), or pomalidomide (n=18). 14 of these genes had p values less than 0·05 for associations with progression-free survival in patients who received thalidomide in induction and maintenance therapy in the Total Therapy (TT) 2 trial (ie, the training cohort). We combined the 14 genes to create a continuous IMiD-14 score and an optimal cutoff. The subgroup with an IMiD-14 score higher than the cutoff was deemed to be IMiD-resistant. We obtained validation cohorts from four studies of IMiD combination regimens: the TT3a trial (thalidomide in induction and maintenance), the TT3b trial (thalidomide in induction and lenalidomide in maintenance), the TT6 trial (thalidomide in induction and lenalidomide in maintenance), and the vincristine, doxorubicin, and dexamethasone (VAD) group of the HOVON65/GMMG-HD4 trial (thalidomide in maintenance). The primary endpoint was to show the prognostic value of the IMiD-14 gene signature for progression-free survival.

FINDINGS

In the training cohort, progression-free survival was significantly shorter in the 83 patients with IMiD-14 high scores than in the 92 patients with IMiD-14 low scores; 3 year progression-free survival was 52% (95% CI 42-64) for the IMiD-14 high group versus 85% (78-92) for the IMiD-14 low group, with a hazard ratio (HR) of 2·51 (95% CI 1·72-3·66; p<0·0001). These findings were supported by the results in the validation cohorts, TT3a (115 patients with IMiD-14 high vs 160 patients with IMiD-14 low; 3 year progression-free survival 63% [95% CI 55-73] vs 87% [82-92]; HR 1·54 [1·11-2·15], p=0·010), TT3b (77 patients with IMiD-14 high vs 89 patients with IMiD-14 low; 62% [52-74] vs 80% [72-89]; HR 2·07 [1·28-3·34], p=0·0024), TT6 (20 patients with IMiD-14 high vs 36 patients with IMiD-14 low; 39% [22-68] vs 74% [61-90]; HR 2·40 [1·09-5·30], p=0·026), and the VAD group of HOVON65/GMMG-HD4 (65 patients with IMiD-14 high vs 77 patients with IMiD-14 low; 16% [9-28] vs 54% [44-67]; HR 2·29 [1·52-3·45], p<0·0001).

INTERPRETATION

Our results suggest that the IMiD-14 model has prognostic value in patients with multiple myeloma who are treated with IMiDs. Some genes in the model could provide novel targets for IMiD resistance and therapeutic intervention. The IMiD-14 model warrants evaluation in prospective studies.

FUNDING

Conquer Cancer Foundation ASCO Young Investigator Award and the Carolinas Myeloma Research Fund.

TRIP13 impairs mitotic checkpoint surveillance and is associated with poor prognosis in multiple myeloma

AAA-ATPase TRIP13 is one of the chromosome instability gene recently established in multiple myeloma (MM), the second most common and incurable hematological malignancy. However, the specific function of TRIP13 in MM is largely unknown. Using sequential gene expression profiling, we demonstrated that high TRIP13 expression levels were positively correlated with progression, disease relapse, and poor prognosis in MM patients. Overexpressing human TRIP13 in myeloma cells prompted cell growth and drug resistance, and overexpressing murine TRIP13, which shares 93% sequence identity with human TRIP13, led to colony formation of NIH/3T3 fibroblasts in vitro and tumor formation in vivo. Meanwhile, the knockdown of TRIP13 inhibited myeloma cell growth, induced cell apoptosis, and reduced tumor burden in xenograft MM mice. Mechanistically, we observed that the overexpression of TRIP13 abrogated the spindle checkpoint and induced proteasome-mediated degradation of MAD2 primarily through the Akt pathway. Thus, our results demonstrate that TRIP13 may serve as a biomarker for MM disease development and prognosis, making it a potential target for future therapies.

The small GTPase RhoU lays downstream of JAK/STAT signaling and mediates cell migration in multiple myeloma

Multiple myeloma is a post-germinal center B-cell neoplasm, characterized by the proliferation of malignant bone marrow plasma cells, whose survival and proliferation is sustained by growth factors and cytokines present in the bone marrow microenvironment. Among them, IL-6 triggers the signal downstream of its receptor, leading to the activation of the JAK/STAT pathway. The atypical GTPase RhoU lays downstream of STAT3 transcription factor and could be responsible for mediating its effects on cytoskeleton dynamics. Here we demonstrate that RHOU is heterogeneously expressed in primary multiple myeloma cells and significantly modulated with disease progression. At the mRNA level, RHOU expression in myeloma patients correlated with the expression of STAT3 and its targets MIR21 and SOCS3. Also, IL-6 stimulation of human myeloma cell lines up-regulated RHOU through STAT3 activation. On the other hand, RhoU silencing led to a decrease in cell migration with the accumulation of actin stress fibers, together with a decrease in cyclin D2 expression and in cell cycle progression. Furthermore, we found that even though lenalidomide positively regulated RhoU expression leading to higher cell migration rates, it actually led to cell cycle arrest probably through a p21 dependent mechanism. Lenalidomide treatment in combination with RhoU silencing determined a loss of cytoskeletal organization inhibiting cell migration, and a further increase in the percentage of cells in a resting phase. These results unravel a role for RhoU not only in regulating the migratory features of malignant plasma cells, but also in controlling cell cycle progression.

Drug response prediction in high-risk multiple myeloma

A Drug Response Prediction (DRP) score was developed based on gene expression profiling (GEP) from cell lines and tumor samples. Twenty percent of high-risk patients by GEP70 treated in Total Therapy 2 and 3A have a progression-free survival (PFS) of more than 10years. We used available GEP data from high-risk patients by GEP70 at diagnosis from Total Therapy 2 and 3A to predict the response by the DRP score of drugs used in the treatment of myeloma patients. The DRP score stratified patients further. High-risk myeloma with a predicted sensitivity to melphalan by the DRP score had a prolonged PFS, HR=2.4 (1.2-4.9, P=0.014) and those with predicted sensitivity to bortezomib had a HR 5.7 (1.2-27, P=0.027). In case of predicted sensitivity to bortezomib, a better response to treatment was found (P=0.022). This method may provide us with a tool for identifying candidates for effective personalized medicine and spare potential non-responders from suffering toxicity.

A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival

Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment.

An mRNA expression signature for prognostication in de novo acute myeloid leukemia patients with normal karyotype

Although clinical features, cytogenetics, and mutations are widely used to predict prognosis in patients with acute myeloid leukemia (AML), further refinement of risk stratification is necessary for optimal treatment, especially in cytogenetically normal (CN) patients. We sought to generate a simple gene expression signature as a predictor of clinical outcome through analyzing the mRNA arrays of 158 de novo CN AML patients. We compared the gene expression profiles of patients with poor response to induction chemotherapy with those who responded well. Forty-six genes expressed differentially between the two groups. Among them, expression of 11 genes was significantly associated with overall survival (OS) in univariate Cox regression analysis in 104 patients who received standard intensive chemotherapy. We integrated the z-transformed expression levels of these 11 genes to generate a risk scoring system. Higher risk scores were significantly associated with shorter OS (median 17.0 months vs. not reached, P < 0.001) in ours and another 3 validation cohorts. In addition, it was an independent unfavorable prognostic factor by multivariate analysis (HR 1.116, 95% CI 1.035~1.204, P = 0.004). In conclusion, we developed a simple mRNA expression signature for prognostication in CN-AML patients. This prognostic biomarker will help refine the treatment strategies for this group of patients.

The Spectrum and Clinical Impact of Epigenetic Modifier Mutations in Myeloma

PURPOSE

Epigenetic dysregulation is known to be an important contributor to myeloma pathogenesis but, unlike other B-cell malignancies, the full spectrum of somatic mutations in epigenetic modifiers has not been reported previously. We sought to address this using the results from whole-exome sequencing in the context of a large prospective clinical trial of newly diagnosed patients and targeted sequencing in a cohort of previously treated patients for comparison.

EXPERIMENTAL DESIGN

Whole-exome sequencing analysis of 463 presenting myeloma cases entered in the UK NCRI Myeloma XI study and targeted sequencing analysis of 156 previously treated cases from the University of Arkansas for Medical Sciences (Little Rock, AR). We correlated the presence of mutations with clinical outcome from diagnosis and compared the mutations found at diagnosis with later stages of disease.

RESULTS

In diagnostic myeloma patient samples, we identify significant mutations in genes encoding the histone 1 linker protein, previously identified in other B-cell malignancies. Our data suggest an adverse prognostic impact from the presence of lesions in genes encoding DNA methylation modifiers and the histone demethylase KDM6A/UTX The frequency of mutations in epigenetic modifiers appears to increase following treatment most notably in genes encoding histone methyltransferases and DNA methylation modifiers.

CONCLUSIONS

Numerous mutations identified raise the possibility of targeted treatment strategies for patients either at diagnosis or relapse supporting the use of sequencing-based diagnostics in myeloma to help guide therapy as more epigenetic targeted agents become available. Clin Cancer Res; 22(23); 5783-94. ©2016 AACR.

Impact of marital status, insurance status, income, and race/ethnicity on the survival of younger patients diagnosed with multiple myeloma in the United States

BACKGROUND

Recent advances in the treatment of multiple myeloma (MM) have been associated with improved survival, predominantly among young and white patients. The authors hypothesized that sociodemographic factors, adjusted for race/ethnicity, influence the survival of younger patients with MM.

METHODS

Overall survival (OS) data were obtained for individuals included in the Surveillance, Epidemiology, and End Results (SEER-18) program who were diagnosed with MM before the age of 65 years between 2007 and 2012. The sociodemographic variables addressed were marital status, insurance status, median household income, and educational achievement in the county of residence. Race/ethnicity was defined as a self-reported construct including Hispanic (regardless of race), non-Hispanic black, non-Hispanic white, and other.

RESULTS

There were 10,161 cases of MM included with a median follow-up of 27 months (range, 0-71 months; 22,179 person-years). Using multivariable Cox proportional hazards analysis, SEER registry; age; male sex; and 3 sociodemographic factors including marital status (other than married), insurance status (uninsured or Medicaid), and county-level income (lowest 2 quartiles), but not race/ethnicity, were found to be associated with an increased risk of death. The 4-year estimated OS rate was 71.1%, 63.2%, 53.4%, and 46.5% (P<.001), respectively, for patients with 0, 1, 2, or 3 adverse sociodemographic factors. Hispanic and non-Hispanic black individuals were found to have more adverse sociodemographic factors and worse OS. However, when the population was stratified by the cumulative number of sociodemographic factors, no consistent association between race/ethnicity and OS was observed after adjustment for confounders.

CONCLUSIONS

Sociodemographic factors that potentially affect care, but not race/ethnicity, were found to influence the survival of younger patients with MM. Cancer 2016;122:3183-90. © 2016 American Cancer Society.

How I treat high-risk myeloma

The treatment of patients with myeloma has dramatically changed over the past decade due in part to the development of new agents and myeloma-specific targets. Despite these advancements, a group for whom the long-term benefit remains less clear are patients with genetically or clinically defined high-risk myeloma. In order to successfully treat these patients, it is important to first identify these patients, treat them with aggressive combination therapy, and employ the use of aggressive long-term maintenance therapy. Future directions include the use of new immune-based treatments (antibodies or cellular-based therapies) as well as target-driven approaches. Until these treatment approaches are better defined, this review will provide a potential treatment approach for standard- and high-risk myeloma that can be followed using agents and strategies that are currently available with the goal of improving progression-free and overall survival for these patients today.

Identification and validation of potential prognostic lncRNA biomarkers for predicting survival in patients with multiple myeloma

Background

Dysregulated long non-coding RNAs (lncRNAs) have been found to have oncogenic and/or tumor suppressive roles in the development and progression of cancer, implying their potentials as novel independent biomarkers for cancer diagnosis and prognosis. However, the prognostic significance of expression profile-based lncRNA signature for outcome prediction in patients with multiple myeloma (MM) has not yet been investigated.

Methods

LncRNA expression profiles of a large cohort of patients with MM were obtained and analyzed by repurposing the publically available microarray data. An lncRNA-focus risk score model was developed from the training dataset, and then validated in the testing and another two independent external datasets. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance for survival prediction. The biological function of prognostic lncRNAs was predicted using bioinformatics analysis.

Results

Four lncRNAs were identified to be significantly associated with overall survival (OS) of patients with MM in the training dataset, and were combined to develop a four-lncRNA prognostic signature to stratify patients into high-risk and low-risk groups. Patients of training dataset in the high-risk group exhibited shorter OS than those in the low-risk group (HR = 2.718, 95 % CI = 1.937-3.815, p <0.001). The similar prognostic values of four-lncRNA signature were observed in the testing dataset, entire GSE24080 dataset and another two independent external datasets. Multivariate Cox regression and stratified analysis showed that the prognostic power of four-lncRNA signature was independent of clinical features, including serum beta 2-microglobulin (Sβ2M), serum albumin (ALB) and lactate dehydrogenase (LDH). ROC analysis also demonstrated the better performance for predicting 3-year OS. Functional enrichment analysis suggested that these four lncRNAs may be involved in known genetic and epigenetic events linked to MM.

Conclusions

Our results demonstrated potential application of lncRNAs as novel independent biomarkers for diagnosis and prognosis in MM. These lncRNA biomarkers may contribute to the understanding of underlying molecular basis of MM.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-015-0219-5) contains supplementary material, which is available to authorized users.

Removing batch effects from purified plasma cell gene expression microarrays with modified ComBat

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

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.

Systemic joint laxity and mandibular range of movement

Primary plasma cell leukemia (pPCL) is a rare and aggressive form of multiple myeloma (MM) that is characterized by the presence of ≥20% circulating plasma cells. Overall survival remains poor despite advances of anti-MM therapy. The disease biology as well as molecular mechanisms that distinguish pPCL from non-pPCL MM remain poorly understood and, given the rarity of the disease, are challenging to study. In an attempt to identify key biological mechanisms that result in the aggressive pPCL phenotype, we performed whole-exome sequencing and gene expression analysis in 23 and 41 patients with newly diagnosed pPCL, respectively. The results reveal an enrichment of complex structural changes and high-risk mutational patterns in pPCL that explain, at least in part, the aggressive nature of the disease. In particular, pPCL patients with traditional low-risk features such as translocation t(11;14) or hyperdiploidy accumulated adverse risk genetic events that could account for the poor outcome in this group. Furthermore, gene expression profiling showed upregulation of adverse risk modifiers in pPCL compared to non-pPCL MM, while adhesion molecules and extracellular matrix proteins became increasingly downregulated. In conclusion, this is one of the largest studies to dissect pPCL on a genomic and molecular level.