Proteomic profiling of naïve multiple myeloma patient plasma cells identifies pathways associated with favourable response to bortezomib-based treatment regimens

Circulating serum microRNAs as biomarkers of drug resistance in multiple myeloma patients treated with bortezomib-based regimens - pilot study

Despite advances in multiple myeloma (MM) treatment, drug resistance remains a clinical challenge. We aimed to develop a prognostic model for bortezomib resistance based on miRNA expression profiling. The study included 40 previously untreated MM patients receiving bortezomib-based regimens (20 treatment-sensitive, 20 resistant). Pretreatment venous blood samples were analyzed for miRNA expression. Differential expression analysis revealed upregulated miR-27b-3p (FC 1.45, p = 0.017) and let-7b-5p (FC 1.44, p = 0.025) in the resistant group. Univariate analysis identified let-7b-5p (OR 3.17, 95%CI: 1.19-11.4, p = 0.04) and miR-27b-3p (OR 4.73, 95%CI: 1.4-26.6, p = 0.036) as risk factors for resistance. The final multivariate model included miR-27b-3p (OR 23.1, 95% CI: 2.8-452, p = 0.015), let-7b-5p (OR 4.38, 95% CI: 1.28-22.2, p = 0.038), and miR-103a-3p (OR 15.3, 95% CI: 1.33-351, p = 0.049). These miRNAs may serve as biomarkers of treatment response in MM. However, external validation is necessary to confirm the clinical utility of our model.

Proteomic Alteration in the Progression of Multiple Myeloma: A Comprehensive Review

Multiple myeloma (MM) is an incurable hematologic malignancy. Most MM patients are diagnosed at a late stage because the early symptoms of the disease can be uncertain and nonspecific, often resembling other, more common conditions. Additionally, MM patients are commonly associated with rapid relapse and an inevitable refractory phase. MM is characterized by the abnormal proliferation of monoclonal plasma cells in the bone marrow. During the progression of MM, massive genomic alterations occur that target multiple signaling pathways and are accompanied by a multistep process involving differentiation, proliferation, and invasion. Moreover, the transformation of healthy plasma cell biology into genetically heterogeneous MM clones is driven by a variety of post-translational protein modifications (PTMs), which has complicated the discovery of effective treatments. PTMs have been identified as the most promising candidates for biomarker detection, and further research has been recommended to develop promising surrogate markers. Proteomics research has begun in MM, and a comprehensive literature review is available. However, proteomics applications in MM have yet to make significant progress. Exploration of proteomic alterations in MM is worthwhile to improve understanding of the pathophysiology of MM and to search for new treatment targets. Proteomics studies using mass spectrometry (MS) in conjunction with robust bioinformatics tools are an excellent way to learn more about protein changes and modifications during disease progression MM. This article addresses in depth the proteomic changes associated with MM disease transformation.

Simultaneously Targeting Two Coupled Signalling Molecules in the Mesenchymal Stem Cell Support Efficiently Sensitises the Multiple Myeloma Cell Line H929 to Bortezomib

Several studies have shown that diverse components of the bone marrow (BM) microenvironment play a central role in the progression, pathophysiology, and drug resistance in multiple myeloma (MM). In particular, the dynamic interaction between BM mesenchymal stem cells (BM-MSC) and MM cells has shown great relevance. Here we showed that inhibiting both PKC and NF-κB signalling pathways in BM-MSC reduced cell survival in the MM cell line H929 and increased its susceptibility to the proteasome inhibitor bortezomib. PKC-mediated cell survival inhibition and bortezomib susceptibility induction were better performed by the chimeric peptide HKPS than by the classical enzastaurin inhibitor, probably due to its greatest ability to inhibit cell adhesion and its increased capability to counteract the NF-κB-related signalling molecules increased by the co-cultivation of BM-MSC with H929 cells. Thus, inhibiting two coupled signalling molecules in BM-MSC was more effective in blocking the supportive cues emerging from the mesenchymal stroma. Considering that H929 cells were also directly susceptible to PKC and NF-κB inhibition, we showed that treatment of co-cultures with the HKPS peptide and BAY11-7082, followed by bortezomib, increased H929 cell death. Therefore, targeting simultaneously connected signalling elements of BM-MSC responsible for MM cells support with compounds that also have anti-MM activity can be an improved treatment strategy.

Prognostic Value of Resistance Proteins in Plasma Cells from Multiple Myeloma Patients Treated with Bortezomib-Based Regimens

While multiple myeloma (MM) treatment with proteasome inhibitors and other agents yields encouraging results, primary and secondary resistance remains an emerging problem. An important factor in such treatment resistance is the overexpression of several proteins. The present study comprehensively evaluates the expression of POMP, PSMB5, NRF2, XBP1, cMAF and MAFb proteins in plasma cells isolated from the bone marrow of 39 MM patients treated with bortezomib-based regimens using an enzyme-linked immunosorbent assay (ELISA). The proteins were selected on the basis of previous laboratory and clinical studies in bortezomib-treated MM patients. It was found that the expression of the investigated proteins did not significantly differ between bortezomib-sensitive and bortezomib-refractory patients. However, the expression of some proteins correlated with overall survival (OS); this was significantly shorter in patients with higher POMP expression (HR 2.8, 95% CI: 1.1–7.0, p = 0.0277) and longer in those with higher MAFB expression (HR 0.32, 95% CI: 0.13–0.80, p = 0.0147). Our results indicate that a high expression of POMP and MAFB in MM plasma cells may serve as predictors of OS in MM patients treated with bortezomib-based regimens. However, further studies are needed to determine the role of these factors in effective strategies for improving anti-myeloma therapy.

Prognostic and predictive biomarker developments in multiple myeloma

New approaches to stratify multiple myeloma patients based on prognosis and therapeutic decision-making, or prediction, are needed since patients are currently managed in a similar manner regardless of individual risk factors or disease characteristics. However, despite new and improved biomarkers for determining the prognosis of patients, there is currently insufficient information to utilise biomarkers to intensify, reduce or altogether change treatment, nor to target patient-specific biology in a so-called predictive manner. The ever-increasing number and complexity of drug classes to treat multiple myeloma have improved response rates and so clinically useful biomarkers will need to be relevant in the era of such novel therapies. Therefore, the field of multiple myeloma biomarker development is rapidly progressing, spurred on by new technologies and therapeutic approaches, and underpinned by a deeper understanding of tumour biology with individualised patient management the goal. In this review, we describe the main biomarker categories in multiple myeloma and relate these to diagnostic, prognostic and predictive applications.

Real-Life Experience With First-Line Therapy Bortezomib Plus Melphalan and Prednisone in Elderly Patients With Newly Diagnosed Multiple Myeloma Ineligible for High Dose Chemotherapy With Autologous Stem-Cell Transplantation

Introduction: Currently, the regimen with bortezomib plus melphalan and prednisone (VMP) is a standard treatment for multiple myeloma and it is recommended as the first-line therapy for patients with multiple myeloma (MM) ineligible for high-dose chemotherapy with autologous stem-cell transplantation.

Objectives: Participants of the clinical trial are highly selected populations; therefore, the aim of this study was to present observations from real practice that can provide important information for practitioners and to investigate clinical outcomes of VMP regimen in elderly patients with newly diagnosed MM.

Patients and Methods: We retrospectively analyzed the data on the efficacy and survival parameters, such as overall survival (OS) and event-free survival (EFS), with attention to the effect of gender, age and International Staging System (ISS) stage, of VMP regimen in 164 patients with newly diagnosed MM not eligible for high-dose chemotherapy with autologous stem-cell transplantation (median age, 75 years; range, 60–86 years).

Results: Patients aged 75 years or older constituted 50.6% of the study cohort. Frail patients were 10.36%, according to the clinical frailty scale of geriatric assessment (GA). A total of 1203 courses of VMP regimen (mainly VMP 1–29, 99.16 %) were administered. The median cumulative delivered dose of bortezomib was 46.8 mg/m2. The overall response rate (ORR), including all patients with a partial response or better, was 81.7% and the complete response rate (CRR) was 10.36 %. After a median 38.51 months of follow-up, the median overall survival (OS) was 34.33 months; the median event-free survival (EFS) after VMP and second-line therapy (mainly Rd, 56.31%) were 18.51 and 10.75 months, respectively. In the subgroup of patients with 75 years or older the median OS was 29.76 months; the median EFS after first and second-line therapy were 17.76 and 8.93 months, respectively. The hazard ratio for OS was 2.276 (p-value 0.046) and for EFS was 1.507 (p-value 0.055) for the ISS stage II and III group. Age and gender were not negative predictors of survival.

Conclusions: VMP treatment is highly effective in the first-line therapy of elderly patients with multiple myeloma ineligible for HDT with auto-SCT.

Tumor Microenvironment Proteomics: Lessons From Multiple Myeloma

Although the "seed and soil" hypothesis was proposed by Stephen Paget at the end of the 19th century, where he postulated that tumor cells (seeds) need a propitious medium (soil) to be able to establish metastases, only recently the tumor microenvironment started to be more studied in the field of Oncology. Multiple myeloma (MM), a malignancy of plasma cells, can be considered one of the types of cancers where there is more evidence in the literature of the central role that the bone marrow (BM) microenvironment plays, contributing to proliferation, survival, migration, and drug resistance of tumor cells. Despite all advances in the therapeutic arsenal for MM treatment in the last years, the disease remains incurable. Thus, studies aiming a better understanding of the pathophysiology of the disease, as well as searching for new therapeutic targets are necessary and welcome. Therefore, the present study aimed to evaluate the protein expression profiling of mononuclear cells derived from BM of MM patients in comparison with these same cell types derived from healthy individuals, in order to fill this gap in MM treatment. Proteomic analysis was performed using the mass spectrometry technique and further analyses were done using bioinformatics tools, to identify dysregulated biological pathways and/or processes in the BM microenvironment of patients with MM as a result of the disease. Among the pathways identified in this study, we can highlight an upregulation of proteins related to protein biosynthesis, especially chaperone proteins, in patients with MM. Additionally, we also found an upregulation of several proteins involved in energy metabolism, which is one of the cancer hallmarks. Finally, with regard to the downregulated proteins, we can highlight mainly those involved in different pathways of the immune response, corroborating the data that has demonstrated that the immune system of MM is impaired and, therefore, the immunotherapies that have been studied recently for the treatment of the disease are extremely necessary in the search for a control and a cure for these patients who live with the disease.

Proteomics-Based Approach Reveals the Involvement of SERPINB9 in Recurrent and Relapsed Multiple Myeloma

Multiple myeloma (MM) is a common hematological malignancy with poorly understood recurrence and relapse mechanisms. Notably, bortezomib resistance leading to relapse makes MM treatment significantly challenging. To clarify the drug resistance mechanism, we employed a quantitative proteomics approach to identify differentially expressed protein candidates implicated in bortezomib-resistant recurrent and relapsed MM (RRMM). Bone marrow aspirates from five patients newly diagnosed with MM (NDMM) were compared with those from five patients diagnosed with bortezomib-resistant RRMM using tandem mass tag-mass spectrometry (TMT-MS). Subcellular localization and functional classification of the differentially expressed proteins were determined by gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and hierarchical clustering analyses. The top candidates identified were validated with parallel reaction monitoring (PRM) analysis using tissue samples from 11 NDMM and 8 RRMM patients, followed by comparison with the NCBI Gene Expression Omnibus (GEO) dataset of 10 MM patients and 10 healthy controls (accession no.: GSE80608). Thirty-four differentially expressed proteins in RRMM, including proteinase inhibitor 9 (SERPINB9), were identified by TMT-MS. Subsequent functional enrichment analyses of the identified protein candidates indicated their involvement in regulating cellular metabolism, apoptosis, programmed cell death, lymphocyte-mediated immunity, and defense response pathways in RRMM. The top protein candidate SERPINB9 was confirmed by PRM analysis and western blotting as well as by comparison with an NCBI GEO dataset. We elucidated the proteome landscape of bortezomib-resistant RRMM and identified SERPINB9 as a promising novel therapeutic target. Our results provide a resource for future studies on the mechanism of RRMM.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Multi-omics tumor profiling technologies to develop precision medicine in multiple myeloma

Multiple myeloma (MM), the second most common hematologic cancer, is caused by accumulation of aberrant plasma cells in the bone marrow. Its molecular causes are not fully understood and its great heterogeneity among patients complicates therapeutic decision-making. In the past decades, development of new therapies and drugs have significantly improved survival of MM patients. However, resistance to drugs and relapse remain the most common causes of mortality and are the major challenges to overcome. The advent of high throughput omics technologies capable of analyzing big amount of clinical and biological data has changed the way to diagnose and treat MM. Integration of omics data (gene mutations, gene expression, epigenetic information, and protein and metabolite levels) with clinical histories of thousands of patients allows to build scores to stratify the risk at diagnosis and predict the response to treatment, helping clinicians to make better educated decisions for each particular case. There is no doubt that the future of MM treatment relies on personalized therapies based on predictive models built from omics studies. This review summarizes the current treatments and the use of omics technologies in MM, and their importance in the implementation of personalized medicine.

Discovery and validation of surface N-glycoproteins in MM cell lines and patient samples uncovers immunotherapy targets

BACKGROUND

Multiple myeloma (MM) is characterized by clonal expansion of malignant plasma cells in the bone marrow. While recent advances in treatment for MM have improved patient outcomes, the 5-year survival rate remains ~50%. A better understanding of the MM cell surface proteome could facilitate development of new directed therapies and assist in stratification and monitoring of patient outcomes.

METHODS

In this study, we first used a mass spectrometry (MS)-based discovery-driven cell surface capture (CSC) approach to map the cell surface N-glycoproteome of MM cell lines. Next, we developed targeted MS assays, and applied these to cell lines and primary patient samples to refine the list of candidate tumor markers. Candidates of interest detected by MS on MM patient samples were further validated using flow cytometry (FCM).

RESULTS

We identified 696 MM cell surface N-glycoproteins by CSC, and developed 73 targeted MS detection assays. MS-based validation using primary specimens detected 30 proteins with significantly higher abundance in patient MM cells than controls. Nine of these proteins were identified as potential immunotherapeutic targets, including five that were validated by FCM, confirming their expression on the cell surface of primary MM patient cells.

CONCLUSIONS

This MM surface N-glycoproteome will be a valuable resource in the development of biomarkers and therapeutics. Further, we anticipate that our targeted MS assays will have clinical benefit for the diagnosis, stratification, and treatment of MM patients.

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

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

The power of proteasome inhibition in multiple myeloma

INTRODUCTION

Proteasome inhibitors (PIs) are therapeutic backbones of multiple myeloma treatment, with PI-based therapies being standards of care throughout the treatment algorithm. Proteasome inhibition affects multiple critical signaling pathways in myeloma cells and interacts synergistically with mechanisms of action of other conventional and novel agents, resulting in substantial anti-myeloma activity and at least additive effects. Areas covered: This review summarizes the biologic effects of proteasome inhibition in myeloma and provides an overview of the importance of proteasome inhibition to the current treatment algorithm. It reviews key clinical data on three PIs, specifically bortezomib, carfilzomib, and ixazomib; assesses ongoing phase 3 trials with these agents; and looks ahead to the increasingly broad role of both approved PIs and PIs under investigation in the frontline and relapsed settings. Expert commentary: Progress to date with PIs in multiple myeloma has been impressive, but there remain unmet needs and challenges, as well as increasing opportunities to optimize the use of these agents. Understanding discrepancies between PIs in terms of efficacy and safety profile is a key goal of ongoing research, along with proteomics-based efforts to identify potential biomarkers of sensitivity and resistance, thereby enabling increasingly personalized treatment approaches in the future.

Comparative proteomic profiling of refractory/relapsed multiple myeloma reveals biomarkers involved in resistance to bortezomib-based therapy

Identifying biomarkers of the resistance in multiple myeloma (MM) is a key research challenge. We aimed to identify proteins that differentiate plasma cells in patients with refractory/relapsed MM (RRMM) who achieved at least very good partial response (VGPR) and in those with reduced response to PAD chemotherapy (bortezomib, doxorubicin and dexamethasone). Comparative proteomic analysis was conducted on pretreatment plasma cells from 77 proteasome inhibitor naïve patients treated subsequently with PAD due to RRMM. To increase data confidence we used two independent proteomic platforms: isobaric Tags for Relative and Absolute Quantitation (iTRAQ) and label free (LF). Proteins were considered as differentially expressed when their accumulation between groups differed by at least 50% in iTRAQ and LF. The proteomic signature revealed 118 proteins (35 up-regulated and 83 down-regulated in ≥ VGPR group). Proteins were classified into four classes: (1) involved in proteasome function; (2) involved in the response to oxidative stress; (3) related to defense response; and (4) regulating the apoptotic process. We confirmed the differential expression of proteasome activator complex subunit 1 (PSME1) by enzyme-linked immunosorbent assay. Increased expression of proteasomes and proteins involved in protection from oxidative stress (eg., TXN, TXNDC5) plays a major role in bortezomib resistance.

RPL5 on 1p22.1 is recurrently deleted in multiple myeloma and its expression is linked to bortezomib response

Chromosomal region 1p22 is deleted in ≥20% of multiple myeloma (MM) patients, suggesting the presence of an unidentified tumor suppressor. Using high-resolution genomic profiling, we delimit a 58 kb minimal deleted region (MDR) on 1p22.1 encompassing two genes: ectopic viral integration site 5 (EVI5) and ribosomal protein L5 (RPL5). Low mRNA expression of EVI5 and RPL5 was associated with worse survival in diagnostic cases. Patients with 1p22 deletion had lower mRNA expression of EVI5 and RPL5, however, 1p22 deletion status is a bad predictor of RPL5 expression in some cases, suggesting that other mechanisms downregulate RPL5 expression. Interestingly, RPL5 but not EVI5 mRNA levels were significantly lower in relapsed patients responding to bortezomib and; both in newly diagnosed and relapsed patients, bortezomib treatment could overcome their bad prognosis by raising their progression-free survival to equal that of patients with high RPL5 expression. In conclusion, our genetic data restrict the MDR on 1p22 to EVI5 and RPL5 and although the role of these genes in promoting MM progression remains to be determined, we identify RPL5 mRNA expression as a biomarker for initial response to bortezomib in relapsed patients and subsequent survival benefit after long-term treatment in newly diagnosed and relapsed patients.

Towards Stratified Medicine in Plasma Cell Myeloma

Plasma cell myeloma is a clinically heterogeneous malignancy accounting for approximately one to 2% of newly diagnosed cases of cancer worldwide. Treatment options, in addition to long-established cytotoxic drugs, include autologous stem cell transplant, immune modulators, proteasome inhibitors and monoclonal antibodies, plus further targeted therapies currently in clinical trials. Whilst treatment decisions are mostly based on a patient’s age, fitness, including the presence of co-morbidities, and tumour burden, significant scope exists for better risk stratification, sub-classification of disease, and predictors of response to specific therapies. Clinical staging, recurring acquired cytogenetic aberrations, and serum biomarkers such as β-2 microglobulin, and free light chains are in widespread use but often fail to predict the disease progression or inform treatment decision making. Recent scientific advances have provided considerable insight into the biology of myeloma. For example, gene expression profiling is already making a contribution to enhanced understanding of the biology of the disease whilst Next Generation Sequencing has revealed great genomic complexity and heterogeneity. Pathways involved in the oncogenesis, proliferation of the tumour and its resistance to apoptosis are being unravelled. Furthermore, knowledge of the tumour cell surface and its interactions with bystander cells and the bone marrow stroma enhance this understanding and provide novel targets for cell and antibody-based therapies. This review will discuss the development in understanding of the biology of the tumour cell and its environment in the bone marrow, the implementation of new therapeutic options contributing to significantly improved outcomes, and the progression towards more personalised medicine in this disorder.