Editorial: Multiple Myeloma: Molecular Mechanism and Targeted Therapy.

Multiple myeloma (MM) is a plasma cell disorder representing the second most common blood cancer [...].

Multiple Myeloma Derived Extracellular Vesicle Uptake by Monocyte Cells Stimulates IL-6 and MMP-9 Secretion and Promotes Cancer Cell Migration and Proliferation.

Multiple Myeloma (MM) is an incurable haematological malignancy caused by uncontrolled growth of plasma cells. MM pathogenesis is attributed to crosstalk between plasma cells and the bone marrow microenvironment, where extracellular vesicles (EVs) play a role. In this study, EVs secreted from a panel of MM cell lines were isolated from conditioned media by ultracentrifugation and fluorescently stained EVs were co-cultured with THP-1 monocyte cells. MM EVs from three cell lines displayed a differential yet dose-dependent uptake by THP-1 cells, with H929 EVs displaying the greatest EV uptake compared to MM.1s and U266 EVs suggesting that uptake efficiency is dependent on the cell line of origin. Furthermore, MM EVs increased the secretion of MMP-9 and IL-6 from monocytes, with H929 EVs inducing the greatest effect, consistent with the greatest uptake efficiency. Moreover, monocyte-conditioned media collected following H929 EV uptake significantly increased the migration and proliferation of MM cells. Finally, EV proteome analysis revealed differential cargo enrichment that correlates with disease progression including a significant enrichment of spliceosome-related proteins in H929 EVs compared to the U266 and MM.1s EVs. Overall, this study demonstrates that MM-derived EVs modulate monocyte function to promote tumour growth and metastasis and reveals possible molecular mechanisms involved.

Using Proteomics Data to Identify Personalized Treatments in Multiple Myeloma: A Machine Learning Approach.

This paper describes a machine learning (ML) decision support system to provide a list of chemotherapeutics that individual multiple myeloma (MM) patients are sensitive/resistant to, based on their proteomic profile. The methodology used in this study involved understanding the parameter space and selecting the dominant features (proteomics data), identifying patterns of proteomic profiles and their association to the recommended treatments, and defining the decision support system of personalized treatment as a classification problem. During the data analysis, we compared several ML algorithms, such as linear regression, Random Forest, and support vector machines, to classify patients as sensitive/resistant to therapeutics. A further analysis examined data-balancing techniques that emerged due to the small cohort size. The results suggest that utilizing proteomics data is a promising approach for identifying effective treatment options for patients with MM (reaching on average an accuracy of 81%). Although this pilot study was limited by the small patient cohort (39 patients), which restricted the training and validation of the explored ML solutions to identify complex associations between proteins, it holds great promise for developing personalized anti-MM treatments using ML approaches.

Bleeding and Thrombosis in Multiple Myeloma: Platelets as Key Players during Cell Interactions and Potential Use as Drug Delivery Systems.

Multiple myeloma (MM) is a hematological malignancy originated in the bone marrow and characterized by unhindered plasma cell proliferation that results in several clinical manifestations. Although the main role of blood platelets lies in hemostasis and thrombosis, platelets also play a pivotal role in a number of other pathological conditions. Platelets are the less-explored components from the tumor microenvironment in MM. Although some studies have recently revealed that MM cells have the ability to activate platelets even in the premalignant stage, this phenomenon has not been widely investigated in MM. Moreover, thrombocytopenia, along with bleeding, is commonly observed in those patients. In this review, we discuss the hemostatic disturbances observed in MM patients and the dynamic interaction between platelets and myeloma cells, along with present and future potential avenues for the use of platelets for diagnostic and therapeutic purposes.

Proteomic and Metabolomic Analysis of Bone Marrow and Plasma from Patients with Extramedullary Multiple Myeloma Identifies Distinct Protein and Metabolite Signatures.

Multiple myeloma (MM) is an incurable haematological malignancy of plasma cells in the bone marrow. In rare cases, an aggressive form of MM called extramedullary multiple myeloma (EMM) develops, where myeloma cells enter the bloodstream and colonise distal organs or soft tissues. This variant is associated with refractoriness to conventional therapies and a short overall survival. The molecular mechanisms associated with EMM are not yet fully understood. Here, we analysed the proteome of bone marrow mononuclear cells and blood plasma from eight patients (one serial sample) with EMM and eight patients without extramedullary spread. The patients with EMM had a significantly reduced overall survival with a median survival of 19 months. Label-free mass spectrometry revealed 225 proteins with a significant differential abundance between bone marrow mononuclear cells (BMNCs) isolated from patients with MM and EMM. This plasma proteomics analysis identified 22 proteins with a significant differential abundance. Three proteins, namely vascular cell adhesion molecule 1 (VCAM1), pigment epithelium derived factor (PEDF), and hepatocyte growth factor activator (HGFA), were verified as the promising markers of EMM, with the combined protein panel showing excellent accuracy in distinguishing EMM patients from MM patients. Metabolomic analysis revealed a distinct metabolite signature in EMM patient plasma compared to MM patient plasma. The results provide much needed insight into the phenotypic profile of EMM and in identifying promising plasma-derived markers of EMM that may inform novel drug development strategies.

A Self-Assembly Method for Creating Vascularized Tumor Explants Using Biomaterials for 3D Culture.

Validation of potential therapeutic targets in cancer requires functional live assays that recapitulate the biology, anatomy, and physiology of human tumors. We present a methodology for maintaining mouse and patient tumor samples ex vivo for in vitro drug-screening as well as for the guidance of patient-specific chemotherapies. The harvested tumor biopsy, excised from mice or patients, is integrated into a support tissue that includes extended stroma and vasculature. The methodology is more representative than tissue culture assays, faster than patient-derived xenograft models, easy to implement, amenable to high-throughput assays and does not carry the ethical issues or expense associated with animal studies. Our physiologically relevant model can be successfully used for high-throughput drug screening.

Analysis of Cancer Cell Line Secretomes: A Complementary Source of Disease-Specific Protein Biomarkers.

Various types of cancer cells enrich or condition the medium that they are cultured in by secreting or shedding proteins and small molecules. These secreted or shed factors are involved in key biological processes, including cellular communication, proliferation, and migration, and are represented by protein families, including cytokines, growth factors, and enzymes. The rapid development of high-resolution mass spectrometry and shotgun strategies for proteome analysis facilitates the identification of these factors in biological models and elucidation of their potential roles in pathophysiology. Hence, the following protocol provides details on how to prepare proteins present in conditioned media for mass spectrometry analysis.

Inhibition of CXCR4 Enhances the Efficacy of Radiotherapy in Metastatic Prostate Cancer Models.

Radiotherapy (RT) is a standard treatment for patients with advanced prostate cancer (PCa). Previous preclinical studies showed that SDF1α/CXCR4 axis could mediate PCa metastasis (most often to the bones) and cancer resistance to RT. We found high levels of expression for both SDF1α and its receptor CXCR4 in primary and metastatic PCa tissue samples. In vitro analyses using PCa cells revealed an important role of CXCR4 in cell invasion but not radiotolerance. Pharmacologic inhibition of CXCR4 using AMD3100 showed no efficacy in orthotopic primary and bone metastatic PCa models. However, when combined with RT, AMD3100 potentiated the effect of local single-dose RT (12 Gy) in both models. Moreover, CXCR4 inhibition also reduced lymph node metastasis from primary PCa. Notably, CXCR4 inhibition promoted the normalization of bone metastatic PCa vasculature and reduced tissue hypoxia. In conclusion, the SDF1α/CXCR4 axis is a potential therapeutic target in metastatic PCa patients treated with RT.

Identification of Ubiquitination-Associated Proteins Using 2D-DIGE.

Ubiquitination is a post-translational modification, in which a small regulatory protein (~8.6 kDa) is tagged as a single moiety or as a chain to target proteins. Ubiquitination is the most versatile cellular regulatory mechanism, essential to the physiological and pathophysiological cellular events that regulate protein turnover, gene transcription, cell cycle progression, DNA repair, apoptosis, viral budding, and receptor-mediated endocytosis. Changes and abnormalities within the ubiquitination process can result in a plethora of diseases, including various cancers. The ubiquitination process is tightly controlled in a stepwise manner by four enzymes: E1 ubiquitin-activating enzymes, E2 ubiquitin-conjugating enzymes, E3 ubiquitin-ligating enzymes, and deubiquitinating proteases. Using fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) to detect and quantitate cellular proteins associated with the ubiquitination process will facilitate the evaluation of this post-translational modification associated with the pathophysiological phenotype.

Identification of Protein Biomarker Signatures for Acute Myeloid Leukemia (AML) Using Both Nontargeted and Targeted Approaches.

Acute myeloid leukemia (AML) is characterized by an increasing number of clonal myeloid blast cells which are incapable of differentiating into mature leukocytes. AML risk stratification is based on genetic background, which also serves as a means to identify the optimal treatment of individual patients. However, constant refinements are needed, and the inclusion of significant measurements, based on the various omics approaches that are currently available to researchers/clinicians, have the potential to increase overall accuracy with respect to patient management. Using both nontargeted (label-free mass spectrometry) and targeted (multiplex immunoassays) proteomics, a range of proteins were found to be significantly changed in AML patients with different genetic backgrounds. The inclusion of validated proteomic biomarker panels could be an important factor in the prognostic classification of AML patients. The ability to measure both cellular and secreted analytes, at diagnosis and during the course of treatment, has advantages in identifying transforming biological mechanisms in patients, assisting important clinical management decisions.

S100 Calcium Binding Protein Family Members Associate With Poor Patient Outcome and Response to Proteasome Inhibition in Multiple Myeloma.

Despite several new therapeutic options, multiple myeloma (MM) patients experience multiple relapses and inevitably become refractory to treatment. Insights into drug resistance mechanisms may lead to the development of novel treatment strategies. The S100 family is comprised of 21 calcium binding protein members with 17 S100 genes located in the 1q21 region, which is commonly amplified in MM. Dysregulated expression of S100 family members is associated with tumor initiation, progression and inflammation. However, the relationship between the S100 family and MM pathogenesis and drug response is unknown. In this study, the roles of S100 members were systematically studied at the copy number, transcriptional and protein level with patients' survival and drug response. Copy number analysis revealed a predominant pattern of gains occurring in S100 genes clustering in the 1q21 locus. In general, gains of genes encoding S100 family members associated with worse patient survival. However, S100 gene copy number and S100 gene expression did not necessarily correlate, and high expression of S100A4 associated with poor patient survival. Furthermore, integrated analysis of S100 gene expression and ex vivo drug sensitivity data showed significant negative correlation between expression of S100 family members (S100A8, S100A9, and S100A12) and sensitivity to some drugs used in current MM treatment, including proteasome inhibitors (bortezomib, carfilzomib, and ixazomib) and histone deacetylase inhibitor panobinostat. Combined proteomic and pharmacological data exhibited significant negative association of S100 members (S100A4, S100A8, and S100A9) with proteasome inhibitors and panobinostat. Clinically, the higher expression of S100A4 and S100A10 were significantly linked to shorter progression free survival in patients receiving carfilzomib-based therapy. The results indicate an association and highlight the potential functional importance of S100 members on chromosome 1q21 in the development of MM and resistance to established myeloma drugs, including proteasome inhibitors.

Clinical Proteomics of Biofluids in Haematological Malignancies.

Since the emergence of high-throughput proteomic techniques and advances in clinical technologies, there has been a steady rise in the number of cancer-associated diagnostic, prognostic, and predictive biomarkers being identified and translated into clinical use. The characterisation of biofluids has become a core objective for many proteomic researchers in order to detect disease-associated protein biomarkers in a minimally invasive manner. The proteomes of biofluids, including serum, saliva, cerebrospinal fluid, and urine, are highly dynamic with protein abundance fluctuating depending on the physiological and/or pathophysiological context. Improvements in mass-spectrometric technologies have facilitated the in-depth characterisation of biofluid proteomes which are now considered hosts of a wide array of clinically relevant biomarkers. Promising efforts are being made in the field of biomarker diagnostics for haematologic malignancies. Several serum and urine-based biomarkers such as free light chains, ß-microglobulin, and lactate dehydrogenase are quantified as part of the clinical assessment of haematological malignancies. However, novel, minimally invasive proteomic markers are required to aid diagnosis and prognosis and to monitor therapeutic response and minimal residual disease. This review focuses on biofluids as a promising source of proteomic biomarkers in haematologic malignancies and a key component of future diagnostic, prognostic, and disease-monitoring applications.

Next generation proteomics with drug sensitivity screening identifies sub-clones informing therapeutic and drug development strategies for multiple myeloma patients.

With the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.

Aminopeptidase Expression in Multiple Myeloma Associates with Disease Progression and Sensitivity to Melflufen.

Multiple myeloma (MM) is characterized by extensive immunoglobulin production leading to an excessive load on protein homeostasis in tumor cells. Aminopeptidases contribute to proteolysis by catalyzing the hydrolysis of amino acids from proteins or peptides and function downstream of the ubiquitin-proteasome pathway. Notably, aminopeptidases can be utilized in the delivery of antibody and peptide-conjugated drugs, such as melflufen, currently in clinical trials. We analyzed the expression of 39 aminopeptidase genes in MM samples from 122 patients treated at Finnish cancer centers and 892 patients from the CoMMpass database. Based on ranked abundance, LAP3, ERAP2, METAP2, TTP2, and DPP7 were highly expressed in MM. ERAP2, XPNPEP1, DPP3, RNPEP, and CTSV were differentially expressed between relapsed/refractory and newly diagnosed MM samples (p < 0.05). Sensitivity to melflufen was detected ex vivo in 11/15 MM patient samples, and high sensitivity was observed, especially in relapsed/refractory samples. Survival analysis revealed that high expression of XPNPEP1, RNPEP, DPP3, and BLMH (p < 0.05) was associated with shorter overall survival. Hydrolysis analysis demonstrated that melflufen is a substrate for aminopeptidases LAP3, LTA4H, RNPEP, and ANPEP. The sensitivity of MM cell lines to melflufen was reduced by aminopeptidase inhibitors. These results indicate critical roles of aminopeptidases in disease progression and the activity of melflufen in MM.

Current Methods of Post-Translational Modification Analysis and Their Applications in Blood Cancers.

Post-translational modifications (PTMs) add a layer of complexity to the proteome through the addition of biochemical moieties to specific residues of proteins, altering their structure, function and/or localization. Mass spectrometry (MS)-based techniques are at the forefront of PTM analysis due to their ability to detect large numbers of modified proteins with a high level of sensitivity and specificity. The low stoichiometry of modified peptides means fractionation and enrichment techniques are often performed prior to MS to improve detection yields. Immuno-based techniques remain popular, with improvements in the quality of commercially available modification-specific antibodies facilitating the detection of modified proteins with high affinity. PTM-focused studies on blood cancers have provided information on altered cellular processes, including cell signaling, apoptosis and transcriptional regulation, that contribute to the malignant phenotype. Furthermore, the mechanism of action of many blood cancer therapies, such as kinase inhibitors, involves inhibiting or modulating protein modifications. Continued optimization of protocols and techniques for PTM analysis in blood cancer will undoubtedly lead to novel insights into mechanisms of malignant transformation, proliferation, and survival, in addition to the identification of novel biomarkers and therapeutic targets. This review discusses techniques used for PTM analysis and their applications in blood cancer research.

Saliva-omics in plasma cell disorders- Proof of concept and potential as a non-invasive tool for monitoring disease burden.

Multiple Myeloma (MM), the second most common lymphoid cancer worldwide, is characterised by the uninhibited proliferation of terminally differentiated B-lymphocytes. Leading to The diagnosis typically requires the presence of a monoclonal protein (M protein) and the demonstration of CRAB features (hypercalcemia, renal impairment, anaemia and bone lesions). MM is considered incurable as, due to serial clonal evolution, the vast majority of patients succumb to treatment-refractory disease. MGUS (Monoclonal Gammopathy of Unknown Uncertain Significance) is the pre-malignant form of MM and, although 93% of MM patients exhibit M protein production associated with MGUS before diagnosis, little is known about the switch from pre-malignant to malignant disease. To explore this disease transition further, LC-MS/MS analysis was carried out to identify potential salivary biomarkers to monitor disease burden. FABP5 was detected in saliva as having a significant increase in abundance when MGUS was compared to symptomatic MM. The levels of FABP5 decreased after treatment indicating correlation with tumour burden. This finding was validated using western blot analysis and ELISA analysis. SIGNIFICANCE: The field of biomarker discovery has focused largely on serum as a biofluid. Saliva is a readily available biofluid that, as a biomarker resource, has been relatively un-explored. The identification of changes in saliva indicating disease progression underlines the utility of saliva as a non-invasive source of informative biomarkers reflecting disease burden and progression.

Multi-parametric single cell evaluation defines distinct drug responses in healthy hematologic cells that are retained in corresponding malignant cell types.

Innate drug sensitivity in healthy cells aids identification of lineage specific anti-cancer therapies and reveals off-target effects. To characterize the diversity in drug responses in the major hematopoietic cell types, we simultaneously assessed their sensitivity to 71 small molecules utilizing a multi-parametric flow cytometry assay and mapped their proteomic and basal signaling profiles. Unsupervised hierarchical clustering identified distinct drug responses in healthy cell subsets based on their cellular lineage. Compared to other cell types, CD19+/B and CD56+/NK cells were more sensitive to dexamethasone, venetoclax and midostaurin, while monocytes were more sensitive to trametinib. Venetoclax exhibited dose-dependent cell selectivity that inversely correlated to STAT3 phosphorylation. Lineage specific effect of midostaurin was similarly detected in CD19+/B cells from healthy, acute myeloid leukemia and chronic lymphocytic leukemia samples. Comparison of drug responses in healthy and neoplastic cells showed that healthy cell responses are predictive of the corresponding malignant cell response. Taken together, understanding drug sensitivity in the healthy cell-of-origin provides opportunities to obtain a new level of therapy precision and avoid off-target toxicity.

ALI multilayered co-cultures mimic biochemical mechanisms of the cancer cell-fibroblast cross-talk involved in NSCLC MultiDrug Resistance.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide. This study focuses on its most common form, Non-Small-Cell Lung Cancer (NSCLC). No cure exists for advanced NSCLC, and patient prognosis is extremely poor. Efforts are currently being made to develop effective inhaled NSCLC therapies. However, at present, reliable preclinical models to support the development of inhaled anti-cancer drugs do not exist. This is due to the oversimplified nature of currently available in vitro models, and the significant interspecies differences between animals and humans. METHODS: We have recently established 3D Multilayered Cell Cultures (MCCs) of human NSCLC (A549) cells grown at the Air-Liquid Interface (ALI) as the first in vitro tool for screening the efficacy of inhaled anti-cancer drugs. Here, we present an improved in vitro model formed by growing A549 cells and human fibroblasts (MRC-5 cell line) as an ALI multilayered co-culture. The model was characterized over 14-day growth and tested for its response to four benchmarking chemotherapeutics. RESULTS: ALI multilayered co-cultures showed an increased resistance to the four drugs tested as compared to ALI multilayered mono-cultures. The signalling pathways involved in the culture MultiDrug Resistance (MDR) were influenced by the cancer cell-fibroblast cross-talk, which was mediated through TGF-ß1 release and subsequent activation of the PI3K/AKT/mTOR pathway. As per in vivo conditions, when inhibiting mTOR phosphorylation, MDR was triggered by activation of the MEK/ERK pathway activation and up-regulation in cIAP-1/2 expression. CONCLUSIONS: Our study opens new research avenues for the development of alternatives to animal-based inhalation studies, impacting the development of anti-NSCLC drugs.