Logic programming reveals alteration of key transcription factors in multiple myeloma

c-FOS is an integral component of the IKZF1 transactivator complex and mediates lenalidomide resistance in multiple myeloma

BACKGROUND

The immunomodulatory drug lenalidomide, which is now widely used for the treatment of multiple myeloma (MM), exerts pharmacological action through the ubiquitin-dependent degradation of IKZF1 and subsequent down-regulation of interferon regulatory factor 4 (IRF4), a critical factor for the survival of MM cells. IKZF1 acts principally as a tumour suppressor via transcriptional repression of oncogenes in normal lymphoid lineages. In contrast, IKZF1 activates IRF4 and other oncogenes in MM cells, suggesting the involvement of unknown co-factors in switching the IKZF1 complex from a transcriptional repressor to an activator. The transactivating components of the IKZF1 complex might promote lenalidomide resistance by residing on regulatory regions of the IRF4 gene to maintain its transcription after IKZF1 degradation.

METHODS

To identify unknown components of the IKZF1 complex, we analyzed the genome-wide binding of IKZF1 in MM cells using chromatin immunoprecipitation-sequencing (ChIP-seq) and screened for the co-occupancy of IKZF1 with other DNA-binding factors on the myeloma genome using the ChIP-Atlas platform.

RESULTS

We found that c-FOS, a member of the activator protein-1 (AP-1) family, is an integral component of the IKZF1 complex and is primarily responsible for the activator function of the complex in MM cells. The genome-wide screening revealed the co-occupancy of c-FOS with IKZF1 on the regulatory regions of IKZF1-target genes, including IRF4 and SLAMF7, in MM cells but not normal bone marrow progenitors, pre-B cells or mature T-lymphocytes. c-FOS and IKZF1 bound to the same consensus sequence as the IKZF1 complex through direct protein-protein interactions. The complex also includes c-JUN and IKZF3 but not IRF4. Treatment of MM cells with short-hairpin RNA against FOS or a selective AP-1 inhibitor significantly enhanced the anti-MM activity of lenalidomide in vitro and in two murine MM models. Furthermore, an AP-1 inhibitor mitigated the lenalidomide resistance of MM cells.

CONCLUSIONS

C-FOS determines lenalidomide sensitivity and mediates drug resistance in MM cells as a co-factor of IKZF1 and thus, could be a novel therapeutic target for further improvement of the prognosis of MM patients.

Integrative Analysis of Proteomics and Transcriptomics Reveals Endothelin Receptor B as Novel Single Target and Identifies New Combinatorial Targets for Multiple Myeloma

Despite the recent introduction of next-generation immunotherapeutic agents, multiple myeloma (MM) remains incurable. New strategies targeting MM-specific antigens may result in a more effective therapy by preventing antigen escape, clonal evolution, and tumor resistance. In this work, we adapted an algorithm that integrates proteomic and transcriptomic results of myeloma cells to identify new antigens and possible antigen combinations. We performed cell surface proteomics on 6 myeloma cell lines based and combined these results with gene expression studies. Our algorithm identified 209 overexpressed surface proteins from which 23 proteins could be selected for combinatorial pairing. Flow cytometry analysis of 20 primary samples confirmed the expression of FCRL5, BCMA, and ICAM2 in all samples and IL6R, endothelin receptor B (ET_B), and SLCO5A1 in >60% of myeloma cases. Analyzing possible combinations, we found 6 combinatorial pairs that can target myeloma cells and avoid toxicity on other organs. In addition, our studies identified ET_B as a tumor-associated antigen that is overexpressed on myeloma cells. This antigen can be targeted with a new monoclonal antibody RB49 that recognizes an epitope located in a region that becomes highly accessible after activation of ET_B by its ligand. In conclusion, our algorithm identified several candidate antigens that can be used for either single-antigen targeting approaches or for combinatorial targeting in new immunotherapeutic approaches in MM.

Current perspectives on interethnic variability in multiple myeloma: Single cell technology, population pharmacogenetics and molecular signal transduction

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This review discusses the emerging single cell technologies and applications in Multiple myeloma (MM), population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction.

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The role(s) of epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of MM are also discussed.

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It is understood that ethnic component acts as a driver of variable response to chemotherapy in different sub-populations globally.

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This review augments our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, myeloma microenvironment at the molecular and cellular level, and developing precision medicine strategies to combat this malignancy.

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The emerging single cell technologies hold great promise for enhancing our understanding of MM tumor heterogeneity and clonal diversity.

Multiple myeloma (MM) is an aggressive cancer characterised by malignancy of the plasma cells and a rising global incidence. The gold standard for optimum response is aggressive chemotherapy followed by autologous stem cell transplantation (ASCT). However, majority of the patients are above 60 years and this presents the clinician with complications such as ineligibility for ASCT, frailty, drug-induced toxicity and differential/partial response to treatment. The latter is partly driven by heterogenous genotypes of the disease in different subpopulations. In this review, we discuss emerging single cell technologies and applications in MM, population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction, as well as the role(s) played by epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of the disease. Taken together, our discussions further our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, augment our understanding of the myeloma microenvironment at the molecular and cellular level and provide a basis for developing precision medicine strategies to combat this malignancy.

The Role of AP-1 Transcription Factors in Plasma Cell Biology and Multiple Myeloma Pathophysiology

Multiple myeloma (MM) is an incurable hematologic malignancy characterized by the clonal expansion of malignant plasma cells within the bone marrow. Activator Protein-1 (AP-1) transcription factors (TFs), comprised of the JUN, FOS, ATF and MAF multigene families, are implicated in a plethora of physiologic processes and tumorigenesis including plasma cell differentiation and MM pathogenesis. Depending on the genetic background, the tumor stage, and cues of the tumor microenvironment, specific dimeric AP-1 complexes are formed. For example, AP-1 complexes containing Fra-1, Fra-2 and B-ATF play central roles in the transcriptional control of B cell development and plasma cell differentiation, while dysregulation of AP-1 family members c-Maf, c-Jun, and JunB is associated with MM cell proliferation, survival, drug resistance, bone marrow angiogenesis, and bone disease. The present review article summarizes our up-to-date knowledge on the role of AP-1 family members in plasma cell differentiation and MM pathophysiology. Moreover, it discusses novel, rationally derived approaches to therapeutically target AP-1 TFs, including protein-protein and protein-DNA binding inhibitors, epigenetic modifiers and natural products.

Preclinical Studies of PROTACs in Hematological Malignancies

Incorrectly expressed or mutated proteins associated with hematologic malignancies have been generally targeted by chemotherapy using small-molecule inhibitors or monoclonal antibodies. But the majority of these intracellular proteins are without active sites and antigens. PROTACs, proteolysis targeting chimeras, are bifunctional molecules designed to polyubiquitinate and degrade specific pathological proteins of interest (POIs) by hijacking the activity of E3-ubiquitin ligases for POI polyubiquitination and subsequent degradation by the proteasome. This strategy utilizes the ubiquitin-proteasome system for the degradation of specific proteins in the cell. In many cases, including hematologic malignancies, inducing protein degradation as a therapeutic strategy offers therapeutic benefits over classical enzyme inhibition connected with resistance to inhibitors. Limitations of small-molecule inhibitors are shown. PROTACs can polyubiquitinate and mark for degradation of "undruggable"proteins, e.g. transcription factor STAT3 and scaffold proteins. Today, this technology is used in preclinical studies in various hematologic malignancies, mainly for targeting drug-resistant bromodomain and extraterminal proteins and Bruton tyrosine kinase. Several mechanisms limiting selectivity and safety of PROTAC molecules function are also discussed.

Latest perspectives on glucocorticoid-induced apoptosis and resistance in lymphoid malignancies

Glucocorticoids are essential drugs in the treatment protocols of lymphoid malignancies. These steroidal hormones trigger apoptosis of the malignant cells by binding to the glucocorticoid receptor (GR), which is a member of the nuclear receptor superfamily. Long term glucocorticoid treatment is limited by two major problems: the development of glucocorticoid-related side effects, which hampers patient quality of life, and the emergence of glucocorticoid resistance, which is a gradual process that is inevitable in many patients. This emphasizes the need to reevaluate and optimize the widespread use of glucocorticoids in lymphoid malignancies. To achieve this goal, a deep understanding of the mechanisms governing glucocorticoid responsiveness is required, yet, a recent comprehensive overview is currently lacking. In this review, we examine how glucocorticoids mediate apoptosis by detailing GR's genomic and non-genomic action mechanisms in lymphoid malignancies. We continue with a discussion of the glucocorticoid-related problems and how these are intertwined with one another. We further zoom in on glucocorticoid resistance by critically analyzing the plethora of proposed mechanisms and highlighting therapeutic opportunities that emerge from these studies. In conclusion, early detection of glucocorticoid resistance in patients remains an important challenge as this would result in a timelier treatment reorientation and reduced glucocorticoid-instigated side effects.

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.

Clinical prognostic implications of EPB41L4A expression in multiple myeloma

Background: Multiple myeloma (MM) is one of the most common incurable malignancies in malignant plasma cell disease. EPB41L4A is a target gene for the Wnt/β-catenin pathway, which is closely related to the survival of multiple myeloma cells. However, there is currently no research report on the prognostic significance of the EPB41L4A gene in MM. Methods: We studied the biological significance and prognostic significance of EPB41L4A expression in MM by integrating 1956 MM samples from 7 datasets, and explored the relationship between EPB41L4A expression and MM ISS stage, molecular type, therapeutic response and survival. Results: We found that the expression level of EPB41L4A is inversely proportional to the copy number of 1q21 (P = 3.4e-13). EPB41L4A was low expressed in MAF, MMSET and proliferating molecular typing patients (P <= 0.001). High expression of EPB41L4A can predict good survival in MM (EFS: P < 0.0001; OS: P < 0.0001). We found that patients with relapsed MM had lower expression levels of EPB41L4A than those without recurrence (P = 0.0039). We also found that EPB41L4A can predict the prognosis of MM patients may be related to DNA replication. These results indicate that the initial expression level of EPB41L4A can predict the prognosis of MM patients. Conclusions: We found that the high expression of EPB41L4A predicts good survival level in MM.

High expression of CHML predicts poor prognosis of multiple myeloma

Multiple myeloma is a hematological tumor with a malignant proliferation of myeloma cells. Although the survival time after treatment has improved, the recurrence rate of MM is still high. Choroideremia-like (CHML) protein is essential for the prenylation modification of various Rab proteins and it exerts biological effects on vesicle trafficking and signal transduction. However, little is identified about the relationship between CHML gene and MM. We integrated gene expression profiles of 1907 MM patients (1959 MM samples) from the 7 datasets. The relationship between CHML gene expression level and event-free survival (EFS), overall survival (OS), ISS stage, molecular subtype, relapse, therapy was analyzed. The differential gene exression profile of CHML-high MM group and CHML-low MM group and possible pathway related to CHML were conducted. Our data showed that EFS (P < 0.0001) and OS (P < 0.0001) in MM patients with high expression of CHML were lower than those with low CHML expression. The gene expression level of CHML was increased in subtypes of MM with poor prognosis, especially in proliferation subtype (P < 0.001). Cell division pathway (P < 0.01) was high enriched of the differential expressed genes of CHML-high group vs CHML-low group. CHML gene can be considered as an independent factor to evaluate the prognosis of MM. High expression of CHML is associated with poor survival, which is related to cell proliferation and cell division of myeloma cells.

Alterations in the Transcriptional Programs of Myeloma Cells and the Microenvironment during Extramedullary Progression Affect Proliferation and Immune Evasion

PURPOSE

In multiple myeloma, extramedullary progression is associated with treatment resistance and a high mortality rate. To understand the molecular mechanisms controlling the devastating progression of myeloma, we applied single-cell RNA-sequencing (RNA-seq) to myeloma in the bone marrow and myelomatous pleural effusions or ascites.

EXPERIMENTAL DESIGN

Bone marrow or extramedullary myeloma samples were collected from 15 patients and subjected to single-cell RNA-seq. The single-cell transcriptome data of malignant plasma cells and the surrounding immune microenvironment were analyzed.

RESULTS

Comparisons of single-cell transcriptomes revealed the systematic activation of proliferation, antigen presentation, proteasomes, glycolysis, and oxidative phosphorylation pathways in extramedullary myeloma cells. The myeloma cells expressed multiple combinations of growth factors and receptors, suggesting autonomous and pleiotropic growth potential at the single-cell level. Comparisons of the tumor microenvironment revealed the presence of cytotoxic T lymphocytes and natural killer (NK) cells in both the bone marrow and extramedullary ascites, demonstrating a gene-expression phenotype indicative of functional compromise. In parallel, isolated myeloma cells persistently expressed class I MHC molecules and upregulated inhibitory molecules for cytotoxic T and NK cells.

CONCLUSIONS

These data suggest that myeloma cells are equipped with specialized immune evasion mechanisms in cytotoxic microenvironments. Taken together, single-cell transcriptome analysis revealed transcriptional programs associated with aggressive myeloma progression that support autonomous cell proliferation and immune evasion.

Prognosis value of RBBP8 expression in plasma cell myeloma

Plasma cell myeloma (PCM) secretes monoclonal immunoglobulin (Ig) by clonal plasma cells of abnormal proliferation in the bone marrow. As PCM is incurable, it is necessary to find new biomarkers to predict the prognosis and recurrence of PCM. The relationship between cancer and RBBP8 has not been fully studied. The role of RBBP8 in tumorigenesis remains inconsistent. We described the expression of RBBP8 in the gene expression profile of 1930 PCM samples (1878 PCM patients) from seven independent data sets. We analyzed the relationship between RBBP8 and survival prognosis, recurrence, and treatment response in patients with PCM, and the biological significance of RBBP8 in PCM. The gene expression level of RBBP8 was significantly related to the International staging system (ISS) grade of PCM (P = 0.0012). RBBP8 expression in different molecular subtypes was different (P < 2.2e-16). High RBBP8 expression is associated with poor survival in PCM (P < 0.0001). High expression of RBBP8 indicates that PCM patients are more likely to relapse (P = 0.0078). The biological significance of RBBP8 in PCM is related to the cell cycle (P < 0.05). High RBBP8 expression predicts poorer survival and more likely relapse in PCM. RBBP8 plays an important role in the cell cycle of PCM. RBBP8 can be considered an independent prognostic factor for PCM. RBBP8 can be used as a potential biomarker for assessing the prognosis of PCM patients.

High expression of UBE2T predicts poor prognosis and survival in multiple myeloma

Multiple myeloma (MM) is one of hematological malignancies, characterized by malignant proliferation of plasma cells. Biomarkers play an important role in evaluating the development and prognosis of MM. Ubiquitin-conjugating enzyme E2T (UBE2T) is served to connect with particular E3 ubiquitin ligase to degraded-related substrates, contributing to DNA repair in the Fanconi anemia pathway. Also, numerous evidences reported that UBE2T is closely related to cell proliferation and carcinogenesis. However, the relationship between MM and UBE2T has not been studied. Here, we integrated eight datasets and analyzed the relationship of expression of UBE2T and ISS, 1q21, relapse and survival in MM 2684 patients (totally 2893 samples). We found that the expression of UBE2T increased with the deterioration of MM (P = 1.4e-07), especially in the early stage. UBE2T is closely related to IgG serotype MM (P = 6.9e-05). High expression of UBE2T is associated with poor survival and prognosis (EFS: P = 1.43e-03, OS: P = 5.47e-05). UBE2T is likely to play a part in the cell division pathway, affecting the survival and prognosis of MM. Therefore, UBE2T could be considered as an early alternative biomarker for the prognosis of MM.

Prediction and prognostic significance of BCAR3 expression in patients with multiple myeloma

Background

Multiple myeloma (MM) is the plasma cell tumor, which is characterized by clonal proliferation of tumor cells, with high risk of progression to renal impairment, bone damage and amyloidosis. Although the survival rate of patients with MM has improved in the past decade, most people inevitably relapse. The treatment and prognosis of MM are still urgent problems. Breast Cancer Antiestrogen Resistance 3 (BCAR3) is a protein-coding gene that is associated with many tumors. However, there have been few studies on the relationship of BCAR3 and MM.

Methods

We analyzed 1878 MM patients (1930 samples) from 7 independent datasets. First, we compared the BCAR3 expression level of MM patients in different stages and MM patients with different amplification of 1q21. Second, we analyzed BCAR3 expression levels in MM patients with different molecular subtypes. Finally, we explored the event-free survival rate (EFS) and overall survival rate (OS) of MM patients with high or low BCAR3 expression, including patients before and after relapse, and their therapeutic responses to bortezomib and dexamethasone.

Results

The expression of BCAR3 showed a decreasing trend in stages I, II and III (P = 0.00068). With the increase of 1q21 amplification level, the expression of BCAR3 decreased (P = 0.022). Patients with high BCAR3 expression had higher EFS and OS (EFS: P < 0.0001, OS: P < 0.0001). The expression of BCAR3 gene before relapse was higher than that after relapse (P = 0.0045). BCAR3 is an independent factor affecting prognosis (EFS: P = 5.17E−03; OS: P = 3.33E−04).

Conclusion

We found that high expression level of BCAR3 predicted better prognosis of MM patients. Low expression of BCAR3 at diagnosis can predict early relapse. BCAR3 is an independent prognostic factor for MM. BCAR3 can be used as a potential biomarker.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1728-8) contains supplementary material, which is available to authorized users.

Upregulation of FOXM1 leads to diminished drug sensitivity in myeloma

BACKGROUND

Following up on previous work demonstrating the involvement of the transcription factor forkhead box M1 (FOXM1) in the biology and outcome of a high-risk subset of newly diagnosed multiple myeloma (nMM), this study evaluated whether FOXM1 gene expression may be further upregulated upon tumor recurrence in patients with relapsed multiple myeloma (rMM). Also assessed was the hypothesis that increased levels of FOXM1 diminish the sensitivity of myeloma cells to commonly used myeloma drugs, such as the proteasome inhibitor bortezomib (Bz) and the DNA intercalator doxorubicin (Dox).

METHODS

FOXM1 message was evaluated in 88 paired myeloma samples from patients with nMM and rMM, using gene expression microarrays as measurement tool. Sources of differential gene expression were identified and outlier analyses were performed using statistical methods. Two independent human myeloma cell lines (HMCLs) containing normal levels of FOXM1 (FOXM1N) or elevated levels of lentivirus-encoded FOXM1 (FOXM1Hi) were employed to determine FOXM1-dependent changes in cell proliferation, survival, efflux-pump activity, and drug sensitivity. Levels of retinoblastoma (Rb) protein were determined with the assistance of Western blotting.

RESULTS

Upregulation of FOXM1 occurred in 61 of 88 (69%) patients with rMM, including 4 patients that exhibited > 20-fold elevated expression peaks. Increased FOXM1 levels in FOXM1Hi myeloma cells caused partial resistance to Bz (1.9-5.6 fold) and Dox (1.5-2.9 fold) in vitro, using FOXM1N myeloma as control. Reduced sensitivity of FOXM1Hi cells to Bz was confirmed in vivo using myeloma-in-mouse xenografts. FOXM1-dependent regulation of total and phosphorylated Rb agreed with a working model of myeloma suggesting that FOXM1 governs both chromosomal instability (CIN) and E2F-dependent proliferation, using a mechanism that involves interaction with NIMA related kinase 2 (NEK2) and cyclin dependent kinase 6 (CDK6), respectively.

CONCLUSIONS

These findings enhanced our understanding of the emerging FOXM1 genetic network in myeloma and provided preclinical support for the therapeutic targeting of the FOXM1-NEK2 and CDK4/6-Rb-E2F pathways using small-drug CDK and NEK2 inhibitors. Clinical research is warranted to assess whether this approach may overcome drug resistance in FOXM1Hi myeloma and, thereby, improve the outcome of patients in which the transcription factor is expressed at high levels.

Proteomics Versus Clinical Data and Stochastic Local Search Based Feature Selection for Acute Myeloid Leukemia Patients' Classification

The use of data issued from high throughput technologies in drug target problems is widely widespread during the last decades. This study proposes a meta-heuristic framework using stochastic local search (SLS) combined with random forest (RF) where the aim is to specify the most important genes and proteins leading to the best classification of Acute Myeloid Leukemia (AML) patients. First we use a stochastic local search meta-heuristic as a feature selection technique to select the most significant proteins to be used in the classification task step. Then we apply RF to classify new patients into their corresponding classes. The evaluation technique is to run the RF classifier on the training data to get a model. Then, we apply this model on the test data to find the appropriate class. We use as metrics the balanced accuracy (BAC) and the area under the receiver operating characteristic curve (AUROC) to measure the performance of our model. The proposed method is evaluated on the dataset issued from DREAM 9 challenge. The comparison is done with a pure random forest (without feature selection), and with the two best ranked results of the DREAM 9 challenge. We used three types of data: only clinical data, only proteomics data, and finally clinical and proteomics data combined. The numerical results show that the highest scores are obtained when using clinical data alone, and the lowest is obtained when using proteomics data alone. Further, our method succeeds in finding promising results compared to the methods presented in the DREAM challenge.

Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data

Background

The integration of gene expression profiles (GEPs) and large-scale biological networks derived from pathways databases is a subject which is being widely explored. Existing methods are based on network distance measures among significantly measured species. Only a small number of them include the directionality and underlying logic existing in biological networks. In this study we approach the GEP-networks integration problem by considering the network logic, however our approach does not require a prior species selection according to their gene expression level.

Results

We start by modeling the biological network representing its underlying logic using Logic Programming. This model points to reachable network discrete states that maximize a notion of harmony between the molecular species active or inactive possible states and the directionality of the pathways reactions according to their activator or inhibitor control role. Only then, we confront these network states with the GEP. From this confrontation independent graph components are derived, each of them related to a fixed and optimal assignment of active or inactive states. These components allow us to decompose a large-scale network into subgraphs and their molecular species state assignments have different degrees of similarity when compared to the same GEP.

We apply our method to study the set of possible states derived from a subgraph from the NCI-PID Pathway Interaction Database. This graph links Multiple Myeloma (MM) genes to known receptors for this blood cancer.

Conclusion

We discover that the NCI-PID MM graph had 15 independent components, and when confronted to 611 MM GEPs, we find 1 component as being more specific to represent the difference between cancer and healthy profiles.