Transcriptome analysis reveals molecular profiles associated with evolving steps of monoclonal gammopathies

Progression of monoclonal gammopathy of undetermined significance to multiple myeloma is associated with enhanced translational quality control and overall loss of surface antigens

BACKGROUND

Despite significant advancements in treatment strategies, multiple myeloma remains incurable. Additionally, there is a distinct lack of reliable biomarkers that can guide initial treatment decisions and help determine suitable replacement or adjuvant therapies when relapse ensues due to acquired drug resistance.

METHODS

To define specific proteins and pathways involved in the progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), we have applied super-SILAC quantitative proteomic analysis to CD138 + plasma cells from 9 individuals with MGUS and 37 with MM.

RESULTS

Unsupervised hierarchical clustering defined three groups: MGUS, MM, and MM with an MGUS-like proteome profile (ML) that may represent a group that has recently transformed to MM. Statistical analysis identified 866 differentially expressed proteins between MM and MGUS, and 189 between MM and ML, 177 of which were common between MGUS and ML. Progression from MGUS to MM is accompanied by upregulated EIF2 signaling, DNA repair, and proteins involved in translational quality control, whereas integrin- and actin cytoskeletal signaling and cell surface markers are downregulated.

CONCLUSION

Compared to the premalignant plasma cells in MGUS, malignant MM cells apparently have mobilized several pathways that collectively contribute to ensure translational fidelity and to avoid proteotoxic stress, especially in the ER. The overall reduced expression of immunoglobulins and surface antigens contribute to this and may additionally mediate evasion from recognition by the immune apparatus. Our analyses identified a range of novel biomarkers with potential prognostic and therapeutic value, which will undergo further evaluation to determine their clinical significance.

Pharmacologic targeting of the p62 ZZ domain enhances both anti-tumor and bone-anabolic effects of bortezomib in multiple myeloma

Multiple myeloma (MM) is a malignancy of plasma cells whose antibody secretion creates proteotoxic stress relieved by the N-end rule pathway, a proteolytic system that degrades N-arginylated proteins in the proteasome. When the proteasome is inhibited, protein cargo is alternatively targeted for autophagic degradation by binding to the ZZ-domain of p62/ sequestosome-1. Here, we demonstrate that XRK3F2, a selective ligand for the ZZ-domain, dramatically improved two major responses to the proteasome inhibitor bortezomib (Btz) by increasing: i) killing of human MM cells by stimulating both Btz-mediated apoptosis and necroptosis, a process regulated by p62; and ii) preservation of bone mass by stimulating osteoblast differentiation and inhibiting osteoclastic bone destruction. Co-administration of Btz and XRK3F2 inhibited both branches of the bimodal N-end rule pathway exhibited synergistic anti-MM effects on MM cell lines and CD138+ cells from MM patients, and prevented stromal-mediated MM cell survival. In mice with established human MM, co-administration of Btz and XRK3F2 decreased tumor burden and prevented the progression of MM-induced osteolytic disease by inducing new bone formation more effectively than either single agent alone. The results suggest that p62-ZZ ligands enhance the anti- MM efficacy of proteasome inhibitors and can reduce MM morbidity and mortality by improving bone health.

A comparative analysis of transcriptomics of newly diagnosed multiple myeloma: exploring drug repurposing

Multiple myeloma (MM) is an incurable malignant plasma cell disorder characterized by the infiltration of clonal plasma cells in the bone marrow compartment. Gene Expression Profiling (GEP) has emerged as a powerful investigation tool in modern myeloma research enabling the dissection of the molecular background of MM and allowing the identification of gene products that could potentially serve as targets for therapeutic intervention. In this study we investigated shared transcriptomic abnormalities across newly diagnosed multiple myeloma (NDMM) patient cohorts. In total, publicly available transcriptomic data of 7 studies from CD138+ cells from 281 NDMM patients and 44 healthy individuals were integrated and analyzed. Overall, we identified 28 genes that were consistently differentially expressed (DE) between NDMM patients and healthy donors (HD) across various studies. Of those, 9 genes were over/under-expressed in more than 75% of NDMM patients. In addition, we identified 4 genes (MT1F, PURPL, LINC01239 and LINC01480) that were not previously considered to participate in MM pathogenesis. Meanwhile, by mining three drug databases (ChEMBL, IUPHAR/BPS and DrugBank) we identified 31 FDA-approved and 144 experimental drugs that target 8 of these 28 over/under-expressed MM genes. Taken together, our study offers new insights in MM pathogenesis and importantly, it reveals potential new treatment options that need to be further investigated in future studies.

Integrative analysis of an endoplasmic reticulum stress-related signature in multiple myeloma

BACKGROUND

Multiple myeloma (MM) is a malignancy in which plasma cells proliferate abnormally, and it remains incurable. The cells are characterized by high levels of endoplasmic reticulum stress (ERS) and depend on the ERS response for survival. Thus, we aim to find an ERS-related signature of MM and assess its diagnostic value.

METHODS

We downloaded three datasets of MM from the Gene Expression Omnibus database. After identifying ERS-related differentially expressed genes (ERDEGs), we analyzed them using Gene Ontology enrichment analysis. A protein-protein interaction network, a transcription factor-mRNA network, a miRNA-mRNA network and a drug-mRNA network were constructed to explore the ERDEGs. The clinical application of these genes was identified by calculating the infiltration of immune cells and using receiver operating characteistic analyses. Finally, qPCR was performed to further confirm the roles of ERDEGs.

RESULTS

We obtained nine ERDEGs of MM. Gene Ontology enrichment indicated that the ERDEGs played a role in the endoplasmic reticulum membrane. Additionally, the protein-protein interaction network showed interaction among the ERDEGs, and there were 20 proteins, 107 transcription factors, 42 drugs or molecular compounds and 51 miRNAs which were likely to interact with the nine genes. In addition, immune cell infiltration analyses showed that there was a strong correlation between the nine genes and immune cells, and these potential biomarkers exhibited good diagnostic values. Finally, the expression of ERDEGs in MM cells was different from that in healthy donor samples.

CONCLUSION

The nine ERS-related genes, CR2, DHCR7, DNAJC3, KDELR2, LPL, OSBPL3, PINK1, VCAM1 and XBP1 are potential biomarkers of MM, and this supports further clinical development of the diagnosis and treatment of MM.

Mouse models of human multiple myeloma subgroups

Multiple myeloma (MM), a tumor of germinal center (GC)-experienced plasma cells, comprises distinct genetic subgroups, such as the t(11;14)/CCND1 and the t(4;14)/MMSET subtype. We have generated genetically defined, subgroup-specific MM models by the GC B cell-specific coactivation of mouse Ccnd1 or MMSET with a constitutively active Ikk2 mutant, mimicking the secondary NF-κB activation frequently seen in human MM. Ccnd1/Ikk2ca and MMSET/Ikk2ca mice developed a pronounced, clonally restricted plasma cell outgrowth with age, accompanied by serum M spikes, bone marrow insufficiency, and bone lesions. The transgenic plasma cells could be propagated in vivo and showed distinct transcriptional profiles, resembling their human MM counterparts. Thus, we show that targeting the expression of genes involved in MM subgroup-specific chromosomal translocations into mouse GC B cells translates into distinct MM-like diseases that recapitulate key features of the human tumors, opening the way to a better understanding of the pathogenesis and therapeutic vulnerabilities of different MM subgroups.

Increased expression of CEP72 predicts poor prognosis in multiple myeloma

INTRODUCTION

Multiple myeloma (MM) is a fatal hematological malignancy and does not have adequate prognostic indicators. Previous studies indicate that CEP72 is closely related to tumorigenesis and tumor progression. However, the expression and function of CEP72 in multiple myeloma have yet to be elucidated.

METHODS

In this study, we explored the correlation between CEP72 expression and clinicopathological characteristics as well as the impacts of CEP72 expression on the survival of MM patients. In addition, PPI, GSEA and Chemotherapy drug resistance analysis identified the possible mechanism.

RESULTS

CEP72 is overexpressed in both MM patients and MM cell lines. Clinically, patients in the CEP72^high subgroup were significantly older than those in the CEP72^low subgroup (p = 0.003). Up-regulation of CEP72 was related to poor overall survival and event-free survival. PPI network showed that CEP72 was related to PCM1, KIZ, OFD1, etc. GSEA analysis showed that CEP72 was enriched in cell cycle, oocyte meiosis, protein export, lysosome and N-glycan biosynthesis pathways. Drug resistance analysis indicated that there was a positive correlation between the CEP72 expression and the IC50 values of 6-mercaptopurine, 8-chloro-adenosine, clofarabine, fludarabine and allopurinol.

CONCLUSION

High CEP72 expression was a poor prognostic factor in patients diagnosed with multiple myeloma.

Serum proteomic profiling reveals MTA2 and AGO2 as potential prognostic biomarkers associated with disease activity and adverse outcomes in multiple myeloma

Multiple myeloma (MM) is an incurable plasma cell malignancy accounting for approximately 10% of hematological malignancies. Identification of reliable biomarkers for better diagnosis and prognosis remains a major challenge. This study aimed to identify potential serum prognostic biomarkers corresponding to MM disease activity and evaluate their impact on patient outcomes. Serum proteomic profiles of patients with MM and age-matched controls were performed using LC-MS/MS. In the verification and validation phases, the concentration of the candidate biomarkers was measured using an ELISA technique. In addition, the association of the proposed biomarkers with clinical outcomes was assessed. We identified 23 upregulated and 15 downregulated proteins differentially expressed in newly diagnosed and relapsed/refractory MM patients compared with MM patients who achieved at least a very good partial response to treatment (≥VGPR). The top two candidate proteins, metastasis-associated protein-2 (MTA2) and argonaute-2 (AGO2), were selected for further verification and validation studies. Both MTA2 and AGO2 showed significantly higher levels in the disease-active states than in the remission states (p < 0.001). Regardless of the patient treatment profile, high MTA2 levels were associated with shorter progression-free survival (p = 0.044; HR = 2.48; 95% CI, 1.02 to 6.02). Conversely, high AGO2 levels were associated with IgG and kappa light-chains isotypes and an occurrence of bone involvement features (p < 0.05) and were associated with prolonged time to response (p = 0.045; HR = 3.00; 95% CI, 1.03 to 8.76). Moreover, the analytic results using a publicly available NCBI GEO dataset revealed that AGO2 overexpression was associated with shorter overall survival among patients with MM (p = 0.032, HR = 1.60, 95% CI, 1.04 to 2.46). In conclusion, MTA2 and AGO2 proteins were first identified as potential biomarkers that reflect disease activity, provide prognostic values and could serve as non-invasive indicators for disease monitoring and outcome predicting among patients with MM.

Expression levels of NONO, a nuclear protein primarily involved in paraspeckles function, are associated with several deregulated molecular pathways and poor clinical outcome in multiple myeloma

PURPOSE

The NONO protein belongs to the multifunctional family of proteins that can bind DNA, RNA and proteins. It is located in the nucleus of most mammalian cells and can affect almost every step of gene regulation. Dysregulation of NONO has been found in many types of cancer; however, data regarding its expression and relevance in Multiple Myeloma (MM) are virtually absent.

METHODS

We took advantage of a large cohort of MM patients enrolled in the Multiple Myeloma Research Foundation CoMMpass study to elucidate better the clinical and biological relevance of NONO expression in the context of the MM genomic landscape and transcriptome.

RESULTS

NONO is overexpressed in pathological samples compared to normal controls. In addition, higher NONO expression levels are significant independent prognostic markers of worse clinical outcome in MM. Our results indicate that NONO deregulation may play a pathogenetic role in MM by affecting cell cycle, DNA repair mechanisms, and influencing translation by regulating ribosome biogenesis and assembly. Furthermore, our data suggest NONO involvement in the metabolic reprogramming of glucose metabolism from respiration to aerobic glycolysis, a phenomenon known as the 'Warburg Effect' that supports rapid cancer cell growth, survival, and invasion.

CONCLUSION

These findings strongly support the need of future investigations for the understanding of the mechanisms of deregulation and the biological role and activity of NONO in MM.

Dysregulation of Small Nucleolar RNAs in B-Cell Malignancies

Small nucleolar RNAs (snoRNAs) are responsible for post-transcriptional modification of ribosomal RNAs, transfer RNAs and small nuclear RNAs, and thereby have important regulatory functions in mRNA splicing and protein translation. Several studies have shown that snoRNAs are dysregulated in human cancer and may play a role in cancer initiation and progression. In this review, we focus on the role of snoRNAs in normal and malignant B-cell development. SnoRNA activity appears to be essential for normal B-cell differentiation and dysregulated expression of sno-RNAs is determined in B-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, B-cell non-Hodgkin’s lymphoma, and plasma cell neoplasms. SnoRNA expression is associated with cytogenetic/molecular subgroups and clinical outcome in patients with B-cell malignancies. Translocations involving snoRNAs have been described as well. Here, we discuss the different aspects of snoRNAs in B-cell malignancies and report on their role in oncogenic transformation, which may be useful for the development of novel diagnostic biomarkers or therapeutic targets.

Identification of key genes and miRNA-mRNA regulatory networks associated with bone marrow immune microenvironment regulations in multiple myeloma by integrative bioinformatics analysis

The deregulation of microRNAs (miRNAs) and genes in the bone marrow microenvironment have been involved with the pathogenesis of multiple myeloma (MM). However, the exploration of miRNA-mRNA regulatory networks in MM remains lacking. We used GSE125363, GSE125361, GSE47552, GSE2658, GSE136324, GSE16558, and GSE13591 datasets for this bioinformatics study. We identified 156 downregulated and 13 upregulated differentially expressed miRNAs (DEmiRs) in MM. The DEmiRs are associated with the enrichment of pathways mainly involved with cancers, cellular signaling, and immune regulations. We identified 112 hub genes associated with five significant clusters in MM. Moreover, we identified 9 upregulated hub genes (such as IGF1, RPS28, UBA52, CDKN1A, and CDKN2A) and 52 downregulated hub genes (such as TP53, PCNA, BRCA1, CCNB1, and MSH2) in MM that is targeted by DEmiRs. The expression of DEmiRs targeted two hub genes (CDKN2A and TP53) are correlated with the survival prognosis of MM patients. Furthermore, the expression level of CDKN2A is correlated with immune signatures, including CD4+ Regulatory T cells, T cell exhaustion, MHC Class I, immune checkpoint genes, macrophages, neutrophils, and TH2 cells in the TME of MM. Finally, we revealed the consistently deregulated expression level of key gene CDKN2A and its co-regulatory DEmiRs, including hsa-mir-192, hsa-mir-10b, hsa-mir-492, and hsa-mir-24 in the independent cohorts of MM. Identifying key genes and miRNA-mRNA regulatory networks may provide new molecular insights into the tumor immune microenvironment in MM.

The effect of chromosome abnormalities on expression of SnoRNA in radioresistant and radiosensitive cell lines after irradiation

In this paper, we have studied the role of chromosomal abnormalities in the expression of small nucleolar RNAs (snoRNAs) of radioresistant (K562) and radiosensitive (HL-60) leukemia cell line. Cells were exposed to an X-ray dose of 4 Gy. SnoRNA expression was investigated using NGS sequencing. The distribution of expressed snoRNAs on chromosomes has been found to be different for two cell lines. The most significant differences in the expression of snoRNAs were found in the K562 cell line based on the analysis of the dynamics of log2fc values. The type of clustering, the number and type of snoRNAs slightly differed in the chromosomes with trisomy and monosomy and had a pronounced difference in pairs with marker chromosomes in both cell lines. In this study, we have demonstrated that chromosomal abnormalities alter the expression of snoRNA after irradiation. Trisomies and monosomies do not have such a noticeable effect on the expression of snoRNAs as the presence of marker chromosomes.

Rebalancing the unbalanced aged immune system - A special focus on zinc

Nowadays, aging is understood as a dynamic and multifaceted dysregulation process that spares almost no human organ or cell. The immune system being among the most affected, it has been shown predominantly that its integrity determines the tightrope walk between the difference of escaping or suffering from age-related diseases. Next to drug-based anti-aging strategies, micronutrient intervention may represent an emerging but less radical way to slow immune aging. While a sufficient supply of a variety of micronutrients is undeniably important, adequate intake of the trace element zinc appears to tower over others in terms of reaching old age. Inconveniently, zinc deficiency prevalence among the elderly is high, which in turn contributes to increased susceptibility to infection, decreased anti-tumor immunity as well as attenuated response to vaccination. Driven by this research, this review aims to provide a comprehensive and up-to-date overview of the various rebalancing capabilities of zinc in the unbalanced immune system of the elderly. This includes an in-depth and cell type-centered discussion on the role of zinc in immunosenescence and inflammaging. We further address upcoming translational aspects e.g. how zinc deficiency promotes the flourishing of certain pathogenic taxa of the gut microbiome and how zinc supply counteracts such alterations in a manner that may contribute to longevity. In the light of the ongoing COVID-19 pandemic, we also briefly review current knowledge on the interdependency between age, zinc status, and respiratory infections. Based on two concrete examples and considering the latest findings in the field we conclude our remarks by outlining tremendous parallels between suboptimal zinc status and accelerated aging on the one hand and an optimized zinc status and successful aging on the other hand.

Longitudinal single-cell analysis of a myeloma mouse model identifies subclonal molecular programs associated with progression

Molecular programs that underlie precursor progression in multiple myeloma are incompletely understood. Here, we report a disease spectrum-spanning, single-cell analysis of the Vκ*MYC myeloma mouse model. Using samples obtained from mice with serologically undetectable disease, we identify malignant cells as early as 30 weeks of age and show that these tumours contain subclonal copy number variations that persist throughout progression. We detect intratumoural heterogeneity driven by transcriptional variability during active disease and show that subclonal expression programs are enriched at different times throughout early disease. We then show how one subclonal program related to GCN2 stress response is progressively activated during progression in myeloma patients. Finally, we use chemical and genetic perturbation of GCN2 in vitro to support this pathway as a therapeutic target in myeloma. These findings therefore present a model of precursor progression in Vκ*MYC mice, nominate an adaptive mechanism important for myeloma survival, and highlight the need for single-cell analyses to understand the biological underpinnings of disease progression.

IDH2 contributes to tumorigenesis and poor prognosis by regulating m6A RNA methylation in multiple myeloma

Epigenetic alterations have been previously shown to contribute to multiple myeloma (MM) pathogenesis via DNA methylations and histone modifications. RNA methylation, a novel epigenetic modification, is required for cancer cell survival, and targeting this pathway has been proposed as a new therapeutic strategy. The extent to the N6-methyladenosine (m6A)-regulatory pathway functions in MM remains unknown. Here, we show that an imbalance of RNA methylation may underlies the tumorigenesis of MM. Mechanistically, isocitrate dehydrogenase 2 (IDH2) is highly expressed in CD138+ cells from MM and its levels appear a progressive increase in the progression of plasma cell dyscrasias. Downregulation of IDH2 increases global m6A RNA levels and reduces myeloma cell growth in vitro, decreases the burden of disease and prolongs overall survival in vivo. IDH2 regulates RNA methylation by activating the RNA demethylase FTO, which is an α-KG-dependent dioxygenase. Furthermore, IDH2-mediated FTO activation decreases the m6A level on WNT7B transcripts, then increases WNT7B expression and thus activated Wnt signaling pathway. Moreover, survival analysis indicates that the elevated expression of IDH2 predicts a poor prognosis. Higher expression of FTO is related to higher International Staging System (ISS) stage and higher Revised-ISS (R-ISS) stage of MM. Collectively, our studies reveal that IDH2 regulates global m6A RNA modification in MM via targeting RNA demethylases FTO. The imbalance of m6A methylation activates the Wnt signaling pathway by enhancing the WNT7B expression, and thus promoting tumorigenesis and progression of MM. IDH2 might be used as a therapeutic target and a possible prognostic factor for MM.

Natural killer cells efficiently target multiple myeloma clonogenic tumor cells

The multiple myeloma (MM) landscape has changed in the last few years, but most patients eventually relapse because current treatment modalities do not target clonogenic stem cells, which are drug-resistant and can self-renew. We hypothesized that side population (SP) cells represent myeloma clonogenic stem cells and, searching for new treatment strategies, analyzed the anti-myeloma activity of natural killer (NK) cells against clonogenic cells. Activated and expanded NK cells (NKAE) products were obtained by co-culturing NK cells from MM patients with K562-mb15-41BBL cell line and characterized by flow cytometry. Functional experiments against MM cells were performed by Eu-TDA release assays and methylcellulose clonogenic assays. Side population was detected by Dye Cycle Violet labeling and then characterized by flow cytometry and RNA-Seq. Self-renewal capacity was tested by clonogenic assays. Sorting of both kind of cells was performed for time-lapse microscopy experiments. SP cells exhibited self-renewal potential and overexpressed genes involved in stem cell metabolism. NK cells from MM patients exhibited dysregulation and had lower anti-tumor potential against clonogenic cells than healthy donors’ NK cells. Patients’ NK cells were activated and expanded. These cells recovered cytotoxic activity and could specifically destroy clonogenic myeloma cells. They also had a highly cytotoxic phenotype expressing NKG2D receptor. Blocking NKG2D receptor decreased NK cell activity against clonogenic myeloma cells, and activated NK cells were able to destroy SP cells, which expressed NKG2D ligands. SP cells could represent the stem cell compartment in MM. This is the first report describing NK cell activity against myeloma clonogenic cells.

Cancers in Agreement? Exploring the Cross-Talk of Cancer Metabolomic and Transcriptomic Landscapes Using Publicly Available Data

One of the major hallmarks of cancer is the derailment of a cell's metabolism. The multifaceted nature of cancer and different cancer types is transduced by both its transcriptomic and metabolomic landscapes. In this study, we re-purposed the publicly available transcriptomic and metabolomics data of eight cancer types (breast, lung, gastric, renal, liver, colorectal, prostate, and multiple myeloma) to find and investigate differences and commonalities on a pathway level among different cancer types. Topological analysis of inferred graphical Gaussian association networks showed that cancer was strongly defined in genetic networks, but not in metabolic networks. Using different statistical approaches to find significant differences between cancer and control cases, we highlighted the difficulties of high-level data-merging and in using statistical association networks. Cancer transcriptomics and metabolomics and landscapes were characterized by changed macro-molecule production, however, only major metabolic deregulations with highly impacted pathways were found in liver cancer. Cell cycle was enriched in breast, liver, and colorectal cancer, while breast and lung cancer were distinguished by highly enriched oncogene signaling pathways. A strong inflammatory response was observed in lung cancer and, to some extent, renal cancer. This study highlights the necessity of combining different omics levels to obtain a better description of cancer characteristics.

HLA-DPA1 gene is a potential predictor with prognostic values in multiple myeloma

Background

Multiple myeloma (MM) is an incurable hematological tumor, which is closely related to hypoxic bone marrow microenvironment. However, the underlying mechanisms are still far from fully understood. We took integrated bioinformatics analysis with expression profile GSE110113 downloaded from National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) database, and screened out major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) as a hub gene related to hypoxia in MM.

Methods

Differentially expressed genes (DEGs) were filtrated with R package “limma”. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed using “clusterProfiler” package in R. Then, protein-protein interaction (PPI) network was established. Hub genes were screened out according to Maximal Clique Centrality (MCC). PrognoScan evaluated all the significant hub genes for survival analysis. ScanGEO was used for visualization of gene expression in different clinical studies. P and Cox p value < 0.05 was considered to be statistical significance.

Results

HLA-DPA1 was finally picked out as a hub gene in MM related to hypoxia. MM patients with down-regulated expression of HLA-DPA1 has statistically significantly shorter disease specific survival (DSS) (COX p = 0.005411). Based on the clinical data of GSE47552 dataset, HLA-DPA1 expression showed significantly lower in MM patients than that in healthy donors (HDs) (p = 0.017).

Conclusion

We identified HLA-DPA1 as a hub gene in MM related to hypoxia. HLA-DPA1 down-regulated expression was associated with MM patients’ poor outcome. Further functional and mechanistic studies are need to investigate HLA-DPA1 as potential therapeutic target.

Amino acid depletion triggered by ʟ-asparaginase sensitizes MM cells to carfilzomib by inducing mitochondria ROS-mediated cell death

Metabolic reprogramming is emerging as a cancer vulnerability that could be therapeutically exploitable using different approaches, including amino acid depletion for those tumors that rely on exogenous amino acids for their maintenance. ʟ-Asparaginase (ASNase) has contributed to a significant improvement in acute lymphoblastic leukemia outcomes; however, toxicity and resistance limit its clinical use in other tumors. Here, we report that, in multiple myeloma (MM) cells, the DNA methylation status is significantly associated with reduced expression of ASNase-related gene signatures, thus suggesting ASNase sensitivity for this tumor. Therefore, we tested the effects of ASNase purified from Erwinia chrysanthemi (Erw-ASNase), combined with the next-generation proteasome inhibitor (PI) carfilzomib. We observed an impressive synergistic effect on MM cells, whereas normal peripheral blood mononuclear cells were not affected. Importantly, this effect was associated with increased reactive oxygen species (ROS) generation, compounded mitochondrial damage, and Nrf2 upregulation, regardless of the c-Myc oncogenic-specific program. Furthermore, the cotreatment resulted in genomic instability and DNA repair mechanism impairment via increased mitochondrial oxidative stress, which further enhanced its antitumor activity. Interestingly, carfilzomib-resistant cells were found to be highly dependent on amino acid starvation, as reflected by their higher sensitivity to Erw-ASNase treatment compared with isogenic cells. Overall, by affecting several cellular programs, Erw-ASNase makes MM cells more vulnerable to carfilzomib, providing proof of concept for clinical use of this combination as a novel strategy to enhance PI sensitivity in MM patients.

Imputation of Gene Expression Data in Blood Cancer and Its Significance in Inferring Biological Pathways

Purpose: Gene expression data generated from microarray technology is often analyzed for disease diagnostics and treatment. However, this data suffers with missing values that may lead to inaccurate findings. Since data capture is expensive, time consuming, and is required to be collected from subjects, it is worthwhile to recover missing values instead of re-collecting the data. In this paper, a novel but simple method, namely, DSNN (Doubly Sparse DCT domain with Nuclear Norm minimization) has been proposed for imputing missing values in microarray data. Extensive experiments including pathway enrichment have been carried out on four blood cancer dataset to validate the method as well as to establish the significance of imputation.

Methods: A new method, namely, DSNN, was proposed for missing value imputation on gene expression data. Method was validated on four dataset, CLL, AML, MM (Spanish data), and MM (Indian data). All the dataset were downloaded from GEO repository. Missing values were introduced in the original data from 10 to 90% in steps of 10% because method validation requires ground truth. Quantitative results on normalized mean square error (NMSE) between the ground truth and imputed data were computed. To further validate and establish the significance of the proposed imputation method, two experiments were carried out on the data imputed with the proposed method, data imputed with the state-of-art methods, and data with missing values. In the first experiment, classification of normal vs. cancer subjects was carried out. In the second experiment, biological significance of imputation was ascertained by identifying top candidate tumor drivers using the existing state-of-the-art SPARROW algorithm, followed by gene list enrichment analysis on top candidate drivers.

Results: Quantitative NMSE results of the DSNN method were compared with three state-of-the-art imputation methods. DSNN method was observed to perform better compared to these other methods both at high as well as low observable data. Experiment-1 demonstrated superior results on classification with imputation compared to that performed on missing data matrix as well as compared to classification on imputed data with existing methods. In experiment-2, cancer affected pathways were discovered with higher significance in the data imputed with the proposed method compared to those discovered with the missing data matrix.

Conclusion: Missing value problem in microarray data is a serious problem and can adversely influence downstream analysis. A novel method, namely, DSNN is proposed for missing value imputation. The method is validated quantitatively on the application of classification and biologically by performing pathway enrichment analysis.

Analyzing gene expression data for pediatric and adult cancer diagnosis using logic learning machine and standard supervised methods

Background

Logic Learning Machine (LLM) is an innovative method of supervised analysis capable of constructing models based on simple and intelligible rules.

In this investigation the performance of LLM in classifying patients with cancer was evaluated using a set of eight publicly available gene expression databases for cancer diagnosis.

LLM accuracy was assessed by summary ROC curve (sROC) analysis and estimated by the area under an sROC curve (sAUC). Its performance was compared in cross validation with that of standard supervised methods, namely: decision tree, artificial neural network, support vector machine (SVM) and k-nearest neighbor classifier.

Results

LLM showed an excellent accuracy (sAUC = 0.99, 95%CI: 0.98–1.0) and outperformed any other method except SVM.

Conclusions

LLM is a new powerful tool for the analysis of gene expression data for cancer diagnosis. Simple rules generated by LLM could contribute to a better understanding of cancer biology, potentially addressing therapeutic approaches.

Targeting of stromal versican by miR-144/199 inhibits multiple myeloma by downregulating FAK/STAT3 signalling

The abnormal growth of malignant plasma cells in Multiple Myeloma (MM) requires bone marrow (BM) niche consisting of proteoglycans, cytokines, etc. Versican (VCAN), a chondroitin sulphate proteoglycan promotes progression in solid tumours but there is dearth of literature in MM. Hence, we studied the involvement of VCAN in MM and its regulation by microRNAs as a therapeutic approach. Thirty MM patients and 20 controls were recruited and BM stromal cells (BMSCs) were isolated by primary culture. Molecular levels of VCAN, miR-144, miR-199 & miR-203 were determined in study subjects and cell lines. The involvement of VCAN in myeloma pathogenesis was studied using BMSCs-conditioned medium (BMSCs-CM) and VCAN-neutralizing antibody or microRNA mimics. Elevated expression of VCAN was observed in patients especially in BM stroma while microRNA expression was significantly lower and showed negative correlation with VCAN. Moreover, BMSCs-CM showed the presence of VCAN which upon supplementing to MM cells alter parameters in favour of myeloma progression, however, this effect was neutralized by VCAN antibody or miR (miR-144 and miR-199) mimics. The downstream signalling of VCAN was found to activate FAK and STAT3 which subsides by using VCAN antibody or miR mimics. The neutralization of oncogenic effect of BMSCs-CM by VCAN blockage affirms its plausible role in progression of MM. VCAN was observed as a paracrine mediator in the cross-talk of BMSCs and myeloma cells in BM microenvironment. Therefore, these findings suggest exploring VCAN as novel therapeutic target and utilization of microRNAs as a therapy to regulate VCAN for better management of MM.

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM.

A comprehensive approach to gene expression profiling in immune cells

With the advent of whole-transcriptome studies and the growing need for public repositories, it has become essential to combine multiple heterogeneous datasets for immune cells. In this chapter, we describe the implementation of a compendium of 10,833 genes for 975 samples, corresponding to 52 resting immune cell types. We begin by describing the datasets, and their selection, in particular. We then explain the methodology implemented to create a qualified compendium: the processing of each array (quality control, normalization and bias correction), integration (merging rules, global normalization and batch removal) and validation. Finally some examples of use will be detailed. The utility and limitations of the compendium are also discussed, as an introduction to the next version.

A Heuristic Algorithm for Identifying Molecular Signatures in Cancer

Molecular signatures of cancer, e.g., genes or microRNAs (miRNAs), have been recognized very important in predicting the occurrence of cancer. From gene-expression and miRNA-expression data, the challenge of identifying molecular signatures lies in the huge number of molecules compared to the small number of samples. To address this issue, in this paper, we propose a heuristic algorithm to identify molecular signatures, termed HAMS, for cancer diagnosis by modeling it as a multi-objective optimization problem. In the proposed HAMS, an elitist-guided individual update strategy is proposed to obtain a small number of molecular signatures, which are closely related with cancer and contain less redundant signatures. Experimental results demonstrate that the proposed HAMS achieves superior performance over seven state-of-the-art algorithms on both gene-expression and miRNA-expression datasets. We also validate the biological significance of the molecular signatures obtained by the proposed HAMS through biological analysis.

Utility of Circulating Cell-Free RNA Analysis for the Characterization of Global Transcriptome Profiles of Multiple Myeloma Patients

In this study, we evaluated the utility of extracellular RNA (exRNA) derived from the plasma of multiple myeloma (MM) patients for whole transcriptome characterization. exRNA from 10 healthy controls (HC), five newly diagnosed (NDMM), and 12 relapsed and refractory (RRMM) MM patients were analyzed and compared. We showed that ~45% of the exRNA genes were protein-coding genes and ~85% of the identified genes were covered >70%. Compared to HC, we identified 632 differentially expressed genes (DEGs) in MM patients, of which 26 were common to NDMM and RRMM. We further identified 54 and 191 genes specific to NDMM and RRMM, respectively, and these included potential biomarkers such as LINC00863, MIR6754, CHRNE, ITPKA, and RGS18 in NDMM, and LINC00462, PPBP, RPL5, IER3, and MIR425 in RRMM, that were subsequently validated using droplet digital PCR. Moreover, single nucleotide polymorphisms and small indels were identified in the exRNA, including mucin family genes that demonstrated different rates of mutations between NDMM and RRMM. This is the first whole transcriptome study of exRNA in hematological malignancy and has provided the basis for the utilization of exRNA to enhance our understanding of the MM biology and to identify potential biomarkers relevant to the diagnosis and prognosis of MM patients.

Identification of key candidate genes and pathways in multiple myeloma by integrated bioinformatics analysis

Multiple myeloma (MM) is a common hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. This study aimed to elucidate key candidate genes and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE6477 and GSE47552 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p < .05 and [logFC] > 1 were identified. Functional enrichment, protein–protein interaction network construction and survival analyses were then performed. First, 51 upregulated and 78 downregulated DEGs shared between the two GSE datasets were identified. Second, functional enrichment analysis showed that these DEGs are mainly involved in the B cell receptor signaling pathway, hematopoietic cell lineage, and NF‐kappa B pathway. Moreover, interrelation analysis of immune system processes showed enrichment of the downregulated DEGs mainly in B cell differentiation, positive regulation of monocyte chemotaxis and positive regulation of T cell proliferation. Finally, the correlation between DEG expression and survival in MM was evaluated using the PrognoScan database. In conclusion, we identified key candidate genes that affect the outcomes of patients with MM, and these genes might serve as potential therapeutic targets.

Gene Co-expression Network and Copy Number Variation Analyses Identify Transcription Factors Associated With Multiple Myeloma Progression

Multiple myeloma (MM) has two clinical precursor stages of disease: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). However, the mechanism of progression is not well understood. Because gene co-expression network analysis is a well-known method for discovering new gene functions and regulatory relationships, we utilized this framework to conduct differential co-expression analysis to identify interesting transcription factors (TFs) in two publicly available datasets. We then used copy number variation (CNV) data from a third public dataset to validate these TFs. First, we identified co-expressed gene modules in two publicly available datasets each containing three conditions: normal, MGUS, and SMM. These modules were assessed for condition-specific gene expression, and then enrichment analysis was conducted on condition-specific modules to identify their biological function and upstream TFs. TFs were assessed for differential gene expression between normal and MM precursors, then validated with CNV analysis to identify candidate genes. Functional enrichment analysis reaffirmed known functional categories in MM pathology, the main one relating to immune function. Enrichment analysis revealed a handful of differentially expressed TFs between normal and either MGUS or SMM in gene expression and/or CNV. Overall, we identified four genes of interest (MAX, TCF4, ZNF148, and ZNF281) that aid in our understanding of MM initiation and progression.

MALDI-TOF analysis of blood serum proteome can predict the presence of monoclonal gammopathy of undetermined significance

Monoclonal gammopathy of undetermined significance (MGUS) is a plasma cell dyscrasia that can progress to malignant multiple myeloma (MM). Specific molecular biomarkers to classify the MGUS status and discriminate the initial asymptomatic phase of MM have not been identified. We examined the serum peptidome profile of MGUS patients and healthy volunteers using MALDI-TOF mass spectrometry and developed a predictive model for classifying serum samples. The predictive model was built using a support vector machine (SVM) supervised learning method tuned by applying a 20-fold cross-validation scheme. Predicting class labels in a blinded test set containing randomly selected MGUS and healthy control serum samples validated the model. The generalization performance of the predictive model was evaluated by a double cross-validation method that showed 88% average model accuracy, 89% average sensitivity and 86% average specificity. Our model, which classifies unknown serum samples as belonging to either MGUS patients or healthy individuals, can be applied to clinical diagnosis.

Multiple Myeloma and Bone: The Fatal Interaction

Multiple myeloma (MM) is the second-most-common hematologic malignancy and the most frequent cancer to involve bone. MM bone disease (MMBD) has devastating consequences for patients, including dramatic bone loss, severe bone pain, and pathological fractures that markedly decrease the quality of life and impact survival of MM patients. MMBD results from excessive osteoclastic bone resorption and persistent suppressed osteoblastic bone formation, causing lytic lesions that do not heal, even when patients are in complete and prolonged remission. This review discusses the cellular and molecular mechanisms that regulate the uncoupling of bone remodeling in MM, the effects of MMBD on tumor growth, and potential therapeutic approaches that may prevent severe bone loss and repair damaged bone in MM patients.

Germline Lysine-Specific Demethylase 1 (LSD1/KDM1A) Mutations Confer Susceptibility to Multiple Myeloma

Given the frequent and largely incurable occurrence of multiple myeloma, identification of germline genetic mutations that predispose cells to multiple myeloma may provide insight into disease etiology and the developmental mechanisms of its cell of origin, the plasma cell (PC). Here, we identified familial and early-onset multiple myeloma kindreds with truncating mutations in lysine-specific demethylase 1 (LSD1/KDM1A), an epigenetic transcriptional repressor that primarily demethylates histone H3 on lysine 4 and regulates hematopoietic stem cell self-renewal. In addition, we found higher rates of germline truncating and predicted deleterious missense KDM1A mutations in patients with multiple myeloma unselected for family history compared with controls. Both monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma cells have significantly lower KDM1A transcript levels compared with normal PCs. Transcriptome analysis of multiple myeloma cells from KDM1A mutation carriers shows enrichment of pathways and MYC target genes previously associated with myeloma pathogenesis. In mice, antigen challenge followed by pharmacologic inhibition of KDM1A promoted PC expansion, enhanced secondary immune response, elicited appearance of serum paraprotein, and mediated upregulation of MYC transcriptional targets. These changes are consistent with the development of MGUS. Collectively, our findings show that KDM1A is the first autosomal-dominant multiple myeloma germline predisposition gene providing new insights into its mechanistic roles as a tumor suppressor during post-germinal center B-cell differentiation.Significance: KDM1A is the first germline autosomal dominant predisposition gene identified in multiple myeloma and provides new insights into multiple myeloma etiology and the mechanistic role of KDM1A as a tumor suppressor during post-germinal center B-cell differentiation. Cancer Res; 78(10); 2747-59. ©2018 AACR.

Selective inhibition of matrix metalloproteinase-2 in the multiple myeloma-bone microenvironment

Multiple myeloma is a plasma cell malignancy that homes aberrantly to bone causing extensive skeletal destruction. Despite the development of novel therapeutic agents that have significantly improved overall survival, multiple myeloma remains an incurable disease. Matrix metalloproteinase-2 (MMP-2) is associated with cancer and is significantly overexpressed in the bone marrow of myeloma patients. These data provide rationale for selectively inhibiting MMP-2 activity as a multiple myeloma treatment strategy. Given that MMP-2 is systemically expressed, we used novel “bone-seeking” bisphosphonate based MMP-2 specific inhibitors (BMMPIs) to target the skeletal tissue thereby circumventing potential off-target effects of MMP-2 inhibition outside the bone marrow-tumor microenvironment. Using in vivo models of multiple myeloma (5TGM1, U266), we examined the impact of MMP-2 inhibition on disease progression using BMMPIs. Our data demonstrate that BMMPIs can decrease multiple myeloma burden and protect against cancer-induced osteolysis. Additionally, we have shown that MMP-2 can be specifically inhibited in the multiple myeloma-bone microenvironment, underscoring the feasibility of developing targeted and tissue selective MMP inhibitors. Given the well-tolerated nature of bisphosphonates in humans, we anticipate that BMMPIs could be rapidly translated to the clinical setting for the treatment of multiple myeloma.

Targeting the MALAT1/PARP1/LIG3 complex induces DNA damage and apoptosis in multiple myeloma

Metastasis-associated lung adenocarcinoma transcript 1(MALAT1) is a highly conserved long non-coding RNA (lncRNA). Overexpression of MALAT1 has been demonstrated to related to poor prognosis of multiple myeloma(MM) patients. Here, we demonstrated that MALAT1 plays important roles in MM DNA repair and cell death. We found bone marrow plasma cells from patients with monoclonal gammopathy of undetermined significance (MGUS) and MM express elevated MALAT1 and involve in alternative-non-homozygous end joining (A-NHEJ) pathway by binding to PARP1 and LIG3, two key components of the A-NHEJ protein complex. Degradation of the MALAT1 RNA by RNase H using antisense gapmer DNA oligos in MM cells stimulated poly-ADP-ribosylation of nuclear proteins, defected the DNA repair pathway, and further provoked apoptotic pathways. Anti-MALAT1 therapy combined with PARP1 inhibitor or proteasome inhibitor in MM cells showed a synergistic effect in vitro. Furthermore, using novel single wall carbon nanotube (SWCNT) conjugated with anti-MALAT1 oligos, we successfully knocked down MALAT1 RNA in cultured MM cell lines and xenograft murine models. Most importantly, anti-MALAT1 therapy induced DNA damage and cell apoptosis in vivo, indicating that MALAT1 could serve as a potential novel therapeutic target for MM treatment.

High throughput chemical library screening identifies a novel p110-δ inhibitor that potentiates the anti-myeloma effect of bortezomib

Multiple myeloma (MM) remains an incurable plasma cell malignancy and drug resistance persists as the major cause of treatment failure leading to fatal outcomes. The phosphatidyl-inositol-3-kinase (PI3K) pathway is constitutively hyperactivated in MM to promote disease progression and drug resistance. While inhibiting PI3K induces apoptosis in MM and is predicted to increase tumor susceptibility to anticancer therapy, early-generation pan-PI3K inhibitors display poor clinical efficacy as well as intolerable side effects. Here, we found that PI3K activity is significantly upregulated in MM cell lines and patient tumor cells resistant to bortezomib and that the majority of PI3K activity in MM cells is dependent upon the p110-δ isoform. Genetic or pharmacologic inhibition of p110-δ substantially reduced myeloma viability and enhanced cellular sensitivity to bortezomib. Chemical library screens then identified a novel compound, DT97, that potently inhibited p110-δ kinase activity and induced apoptosis in MM cells. DT97 was evaluated in the NCI-60 panel of human cancer cell types and anticancer activity was greatest against MM, leukemia and lymphoma cells. Co-treatment with DT97 and bortezomib synergistically induced apoptosis in MM patient cells and overcame bortezomib-resistance. Although bone marrow stromal cells (BMSCs) promote MM growth, the pro-survival effects of BMSCs were significantly reduced by DT97 treatment. Co-treatment with bortezomib and DT97 reduced the growth of myeloma xenotransplants in murine models and prolonged host survival. Taken together, the results provide the basis for further clinical evaluation of p110-δ inhibitors, as monotherapy or in synergistic combinations, for the benefit of MM patients.

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.

In silico analysis identifies CRISP3 as a potential peripheral blood biomarker for multiple myeloma: From data modeling to validation with RT-PCR

Octamer-binding protein 2 (Oct2) binds to the ATGCAAAT octamer on the IgH enhancer and stimulates IgH expression in human multiple myeloma (MM). Cysteine-rich secreted protein 3 (CRISP3) possesses the ATGCAAAT sequence and thus is activated by Oct2 in mouse B cells, suggesting that CRISP3 may be activated in and be a potential biomarker for MM. The present study involved a meta-analysis of the gene expression profiling data of human MM peripheral blood. Significantly expressed genes were analyzed on merged super array microarray data and selected sample data with significantly expressed genes were additionally analyzed by principal component analysis and Bayesian probit regression. CRISP3, Oct2, Apha-1B-glycoprotein (A1GB) and Cyclin D2 (CCND2) were validated in clinical MM peripheral blood samples using reverse transcription quantitative polymerase chain reaction. In the gene expression profiling data, CRISP3 was significantly upregulated and had certain proportions on the discriminated principal component of significantly expressed gene sample data. RT-qPCR analysis revealed CRISP3 was significantly upregulated in MM. Therefore, CRISP3 is a potential peripheral blood biomarker for MM.

Distinct lncRNA transcriptional fingerprints characterize progressive stages of multiple myeloma

Although many efforts have recently contributed to improve our knowledge of molecular pathogenesis of multiple myeloma (MM), the role and significance of long non-coding RNAs (lncRNAs) in plasma cells (PC) malignancies remains virtually absent. To this aim, we developed a custom annotation pipeline of microarray data investigating lncRNA expression in PCs from 20 monoclonal gammopathies of undetermined significance, 33 smoldering MM, 170 MM, and 36 extra-medullary MMs/plasma cell leukemia patients, and 9 healthy donors. Our study identified 31 lncRNAs deregulated in tumor samples compared to normal controls; among these, the upregulation of MALAT1 appeared associated in MM patients with molecular pathways involving cell cycle regulation, p53-mediated DNA damage response, and mRNA maturation processes. Furthermore, we found 21 lncRNAs whose expression were progressively deregulated trough the more aggressive stages of PC dyscrasia, suggesting a possible role in the progression of the disease. Finally, in the context of molecular heterogeneity of MM, we identified a transcriptional fingerprint in hyperdiploid patients, characterized by the upregulation of lncRNAs/pseudogenes related to ribosomal protein genes, known to be upregulated in this molecular group. Overall, the data provides an important resource for future studies on the functions of lncRNAs in the pathology.

Membrane translocation of Bruton kinase in multiple myeloma cells is associated with osteoclastogenic phenotype in bone metastatic lesions

Using bone biopsy samples, we examined whether osteolytic cytokine profile is changed in situ in bone samples of metastatic multiple myeloma, and whether this creates an environment of lysis within the bone to which it has spread. This also produces the clinical features of increased circulating plasma calcium, and deleterious effects on the kidney.Using multiple myeloma biopsy and cell extracts from bone metastatic lesions, Bruton kinase, a tyrosine kinase, was demonstrated to be translocated to the membrane. Several transcription factors were upregulated included activin A, inflammatory transcription activator like such as nuclear factor kappa B, and specific bone lytic factor such as receptor activator of nuclear factor kappa-B ligand that is known to drive osteoclastogenesis as opposed to a osteogenic environment. The transcript for Bruton kinase was also elevated in its expression.Cytokines that support osteolytic activity such as a proliferation-inducing ligand, RANTES (regulated on activation, normal T cell expressed and secreted), interleukin-8, and activin A were upregulated. Tartrate resistant acid phosphatase (TRAP)-positive osteoclastic enzymatic activity was significantly elevated in the bone microenvironment in metastatic multiple myeloma. Several tyrosine kinase inhibitors, including inhibitors for Bruton kinase such as ibrutinib have been developed. The results of the present study provide evidence that multiple myeloma possess signal transduction mechanisms to support a bone lytic environment.The results provide a preliminary molecular basis to design specific inhibitors for management of bone metastasis of multiple myeloma.

The transcriptional profiling of human in vivo-generated plasma cells identifies selective imbalances in monoclonal gammopathies

Plasma cells (PC) represent the heterogeneous final stage of the B cells (BC) differentiation process. To characterize the transition of BC into PC, transcriptomes from human naïve BC were compared to those of three functionally-different subsets of human in vivo-generated PC: i) tonsil PC, mainly consisting of early PC; ii) PC released to the blood after a potent booster-immunization (mostly cycling plasmablasts); and, iii) bone marrow CD138⁺ PC that represent highly mature PC and include the long-lived PC compartment. This transcriptional transition involves subsets of genes related to key processes for PC maturation: the already known protein processing, apoptosis and homeostasis, and of new discovery including histones, macromolecule assembly, zinc-finger transcription factors and neuromodulation. This human PC signature is partially reproduced in vitro and is conserved in mouse. Moreover, the present study identifies genes that define PC subtypes (e.g., proliferation-associated genes for circulating PC and transcriptional-related genes for tonsil and bone marrow PC) and proposes some putative transcriptional regulators of the human PC signatures (e.g., OCT/POU, XBP1/CREB, E2F, among others). Finally, we also identified a restricted imbalance of the present PC transcriptional program in monoclonal gammopathies that correlated with PC malignancy.

The ubiquitin-conjugating enzyme UBE2O modulates c-Maf stability and induces myeloma cell apoptosis

Background

UBE2O is proposed as a ubiquitin-conjugating enzyme, but its function was largely unknown.

Methods

Mass spectrometry was applied to identify c-Maf ubiquitination-associated proteins. Immunoprecipitation was applied for c-Maf and UBE2O interaction. Immunoblotting was used for Maf protein stability. Luciferase assay was used for c-Maf transcriptional activity. Lentiviral infections were applied for UBE2O function in multiple myeloma (MM) cells. Flow cytometry and nude mice xenografts were applied for MM cell apoptosis and tumor growth assay, respectively.

Results

UBE2O was found to interact with c-Maf, a critical transcription factor in MM, by the affinity purification/tandem mass spectrometry assay and co-immunoprecipitation assays. Subsequent studies showed that UBE2O mediated c-Maf polyubiquitination and degradation. Moreover, UBE2O downregulated the transcriptional activity of c-Maf and the expression of cyclin D2, a typical gene modulated by c-Maf. DNA microarray revealed that UBE2O was expressed in normal bone marrow cells but downregulated in MGUS, smoldering MM and MM cells, which was confirmed by RT-PCR in primary MM cells, suggesting its potential role in myeloma pathophysiology. When UBE2O was restored, c-Maf protein in MM cells was significantly decreased and MM cells underwent apoptosis. Furthermore, the human MM xenograft in nude mice showed that re-expression of UBE2O delayed the growth of myeloma xenografts in nude mice in association with c-Maf downregulation and activation of the apoptotic pathway.

Conclusions

UBE2O mediates c-Maf polyubiquitination and degradation, induces MM cell apoptosis, and suppresses myeloma tumor growth, which provides a novel insight in understanding myelomagenesis and UBE2O biology.

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.

Gene Expression Profiles in Myeloma: Ready for the Real World?

Multiple myeloma is a plasma cell malignancy characterized by molecular and clinical heterogeneity. The outcome of the disease has been dramatically improved with the advent of new drugs in the past few years. However, even in this context of increasing therapeutic options, important challenges remain, such as accurately evaluating patients' prognosis and predicting sensitivity to specific treatments and drug combinations. Transcriptomic studies have largely contributed to help decipher multiple myeloma complexity, characterizing multiple myeloma subgroups distinguished by different outcomes. Microarrays and, more recently, RNA sequencing allow evaluation of expression of coding and noncoding genes, alternate splicing events, mutations, and novel transcriptome modifiers, providing new information regarding myeloma biology, prognostication, and therapy. In this review, we discuss the role and impact of gene expression profiling studies in myeloma. Clin Cancer Res; 22(22); 5434-42. ©2016 AACR SEE ALL ARTICLES IN THIS CCR FOCUS SECTION, "MULTIPLE MYELOMA MULTIPLYING THERAPIES".

Recurrent mutations of MAPK pathway genes in multiple myeloma but not in amyloid light-chain amyloidosis

Clinically applicable platforms revealing actionable genomic alterations may improve the treatment efficacy of myeloma patients. In this pilot study, we used a high depth targeted sequencing panel containing 83 anti-cancer drug target genes to sequence genomic DNAs extracted from bone marrow aspirates of 23 patients with myeloma and 12 patients with amyloid light-chain (AL) amyloidosis. Mutation analysis revealed NRAS as the most commonly mutated gene (30%, 7/23) in myeloma patients followed by KRAS (26%, 6/23) and BRAF (22%, 5/23). However, no significant mutations were found in the 12 patients with AL amyloidosis. Notably, 6 of the 23 myeloma patients showed multi-site and/or multi-gene mutations in NRAS, KRAS, or BRAF, indicating compound aberrations in the Mitogen activated protein kinase (MAPK) pathway. Gene panel sequencing also revealed cytogenetic abnormalities associated with prognosis in myeloma patients. In conclusion, our pilot study suggests that targeted gene sequencing may have an important prognostic value for myeloma patients for the identification of actionable genomic alterations and cytogenetic aberrations.

MGUS to myeloma: a mysterious gammopathy of underexplored significance

All cases of multiple myeloma (MM) are preceded by precursor states termed monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM). Genetic analyses of MGUS cells have provided evidence that it is a genetically advanced lesion, wherein tumor cells carry many of the genetic changes found in MM cells. Intraclonal heterogeneity is also established early during the MGUS phase. Although the genetic features of MGUS or SMM cells at baseline may predict disease risk, transition to MM involves altered growth of preexisting clones. Recent advances in mouse modeling of MGUS suggest that the clinical dormancy of the clone may be regulated in part by growth controls extrinsic to the tumor cells. Interactions of MGUS cells with immune cells, bone cells, and others in the bone marrow niche may be key regulators of malignant transformation. These interactions involve a bidirectional crosstalk leading to both growth-supporting and inhibitory signals. Because MGUS is already a genetically complex lesion, application of new tools for earlier detection should allow delineation of earlier stages, which we term as pre-MGUS Analyses of populations at increased risk of MGUS also suggest the possible existence of a polyclonal phase preceding the development of MGUS. Monoclonal gammopathy in several patients may have potential clinical significance in spite of low risk of malignancy. Understanding the entire spectrum of these disorders may have broader implications beyond prevention of clinical malignancy.

Effects of IL-8 Up-Regulation on Cell Survival and Osteoclastogenesis in Multiple Myeloma

IL-8 promotes cancer cell growth, survival, angiogenesis, and metastasis in several tumors. Herein, we investigated the sources of IL-8 production in multiple myeloma (MM) and its potential roles in MM pathogenesis. We found that bone marrow cells from patients with MM secreted higher amounts of IL-8 than healthy donors. IL-8 production was detected in cultures of CD138(+) plasma cells and CD138(-) cells isolated from bone marrows of MM patients, and in three of seven human myeloma cell lines (HMCLs) analyzed. Interactions between MM and stromal cells increased IL-8 secretion by stromal cells through cell-cell adhesion and soluble factors. Interestingly, IL8 expression also increased in HMCLs, stromal cells, and osteoclasts after treatment with the antimyeloma drugs melphalan and bortezomib. In fact, the effect of bortezomib on IL-8 production was higher than that exerted by stromal-MM cell interactions. Addition of exogenous IL-8 did not affect growth of HMCLs, although it protected cells from death induced by serum starvation through a caspase-independent mechanism. Furthermore, IL-8 induced by stromal-MM cell interactions strongly contributed to osteoclast formation in vitro, because osteoclastogenesis was markedly reduced by IL-8-specific neutralizing antibodies. In conclusion, our results implicate IL-8 in myeloma bone disease and point to the potential utility of an anti-IL-8 therapy to prevent unwanted effects of IL-8 up-regulation on survival, angiogenesis, and osteolysis in MM.

Phenotypic and genomic analysis of multiple myeloma minimal residual disease tumor cells: a new model to understand chemoresistance

We report for the first time the biological features of MRD cells in MM and unravel that clonal selection is already present at the MRD stage. MRD cells show a singular phenotypic signature that may result from persisting clones with different genetic and gene expression profiles.