Identification of proteins found to be significantly altered when comparing the serum proteome from Multiple Myeloma patients with varying degrees of bone disease

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.

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.

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.

An atlas of the bone marrow bone proteome in patients with dysproteinemias

Multiple myeloma (MM) bone disease is a significant cause of morbidity but there is a paucity of data on the impact of malignant plasma cells on adjacent trabecular bone within the BM. Here, we characterize the proteome of trabecular bone tissue from BM biopsies of 56 patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering (SMM), newly diagnosed (NDMM), relapsed MM (RMM), and normal controls. Proteins involved in extracellular matrix (ECM) formation and immunity pathways were decreased in SMM and active MM. Among the proteins most decreased were immunoglobulins, type IV collagen, and TIMP3, suggesting increased immunoparesis and decreased ECM remodelling within trabecular bone. Proteins most increased in SMM/MM were APP (enhances osteoclast activity), ENPP1 (enhances bone mineralization), and MZB1 (required for normal plasmablast differentiation). Pathway analyses showed that proteins involved in gamma -carboxylation, a pathway implicated in osteocalcin function, osteoblast differentiation, and normal hematopoiesis, were also overexpressed in SMM/MM. This study is the first comprehensive proteomic atlas of the BM bone proteome in dysproteinemias. We identify new key proteins and pathways for MM bone disease and potentially impaired hematopoiesis, and show for the first time that gamma -carboxylation pathways are increased in the bone tissue of SMM/MM.

An atlas of the bone marrow bone proteome in patients with dysproteinemias

Multiple myeloma (MM) bone disease is a significant cause of morbidity but there is a paucity of data on the impact of malignant plasma cells on adjacent trabecular bone within the BM. Here, we characterize the proteome of trabecular bone tissue from BM biopsies of 56 patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering (SMM), newly diagnosed (NDMM), relapsed MM (RMM), and normal controls. Proteins involved in extracellular matrix (ECM) formation and immunity pathways were decreased in SMM and active MM. Among the proteins most decreased were immunoglobulins, type IV collagen, and TIMP3, suggesting increased immunoparesis and decreased ECM remodelling within trabecular bone. Proteins most increased in SMM/MM were APP (enhances osteoclast activity), ENPP1 (enhances bone mineralization), and MZB1 (required for normal plasmablast differentiation). Pathway analyses showed that proteins involved in gamma -carboxylation, a pathway implicated in osteocalcin function, osteoblast differentiation, and normal hematopoiesis, were also overexpressed in SMM/MM. This study is the first comprehensive proteomic atlas of the BM bone proteome in dysproteinemias. We identify new key proteins and pathways for MM bone disease and potentially impaired hematopoiesis, and show for the first time that gamma -carboxylation pathways are increased in the bone tissue of SMM/MM.

Protein Digestion for 2D-DIGE Analysis

In-gel digestion of protein spots derived from two-dimensional gels and their subsequent identification by mass spectrometry is involved in a multitude of mass spectrometry-driven proteomic experiments, including fluorescence two-dimensional difference gel electrophoresis (2D-DIGE). This type of proteomic methodology has been involved in the establishment of comparative proteome maps and in the identification of differentially expressed proteins and their isoforms in health and disease. Most in-gel digestion protocols follow a number of common steps including excision of the protein spots of interest, destaining, reduction and alkylation (for silver-stained gels), and dehydration and overnight digestion with the proteolytic enzyme of choice. While trypsin has been a mainstay of peptide digestion for many years, it does have its shortcomings, particularly related to incomplete peptide digestion, and this has led to a rise in popularity for other proteolytic enzymes either used alone or in combination. This chapter discusses the alternative enzymes available and describes the process of in-gel digestion using the enzyme trypsin.

Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems

Liquid chromatography/mass spectrometry (LC/MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization, and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin-based depletion column followed by either protein In-Gel enzymatic digestion or protein In-Solution enzymatic digestion using a simple kit-based approach (i.e., using the PreOmics iST sample preparation kit), followed by analysis using one-dimensional reverse-phase chromatography (RPC) or high pH reversed-phase peptide fractionation.

Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma

BACKGROUND

The aim of this study was to construct a model based on the prognostic features associated with epithelial-mesenchymal transition (EMT) to explore the various mechanisms and therapeutic strategies available for the treatment of metastasis and invasion by hepatocellular carcinoma (HCC) cells.

METHODS

EMT-associated genes were identified, and their molecular subtypes were determined by consistent clustering analysis. The differentially expressed genes (DEGs) among the molecular subtypes were ascertained using the limma package and they were subjected to functional enrichment analysis. The immune cell scores of the molecular subtypes were evaluated using ESTIMATE, MCPcounter, and GSCA packages of R. A multi-gene prognostic model was constructed using lasso regression, and the immunotherapeutic effects of the model were analyzed using the Imvigor210 cohort. In addition, immunohistochemical analysis was performed on a cohort of HCC tissue to validate gene expression.

RESULTS

Based on the 59 EMT-associated genes identified, the 365-liver hepatocellular carcinoma (LIHC) samples were divided into two subtypes, C1 and C2. The C1 subtype mostly showed poor prognosis, had higher immune scores compared to the C2 subtype, and showed greater correlation with pathways of tumor progression. A four-gene signature construct was fabricated based on the 1130 DEGs among the subtypes. The construct was highly robust and showed stable predictive efficacy when validated using datasets from different platforms (HCCDB18 and GSE14520). Additionally, compared to currently existing models, our model demonstrated better performance. The results of the immunotherapy cohort showed that patients in the low-risk group have a better immune response, leading to a better patient's prognosis. Immunohistochemical analysis revealed that the expression levels of the FTCD, PON1, and TMEM45A were significantly over-expressed in 41 normal samples compared to HCC samples, while that of the G6PD was significantly over-expressed in cancerous tissues.

CONCLUSIONS

The four-gene signature construct fabricated based on the EMT-associated genes provides valuable information to further study the pathogenesis and clinical management of HCC.

Liquid biopsy: an evolving paradigm for the biological characterisation of plasma cell disorders

Liquid biopsies-a source of circulating cell-free nucleic acids, proteins and extracellular vesicles-are currently being explored for the quantitative and qualitative characterisation of the tumour genome and as a mode of non-invasive therapeutic monitoring in cancer. Emerging data suggest that liquid biopsies might offer a potentially simple, non-invasive, repeatable strategy for diagnosis, prognostication and therapeutic decision making in a genetically heterogeneous disease like multiple myeloma (MM), with particular applicability in subsets of patients where conventional markers of disease burden may be less informative. In this review, we describe the emerging utility of the evaluation of circulating tumour DNA, extracellular RNA, cell-free proteins and metabolites and extracellular vesicles in MM.

Complement C3a activates osteoclasts by regulating the PI3K/PDK1/SGK3 pathway in patients with multiple myeloma

OBJECTIVE

Myeloma bone disease (MBD) is the most common complication of multiple myeloma (MM). Our previous study showed that the serum levels of C3/C4 in MM patients were significantly positively correlated with the severity of bone disease. However, the mechanism of C3a/C4a in osteoclasts MM patients remains unclear.

METHODS

The formation and function of osteoclasts were analyzed after adding C3a/C4a in vitro. RNA-seq analysis was used to screen the potential pathways affecting osteoclasts, and the results were verified by Western blot, qRT-PCR, and pathway inhibitors.

RESULTS

The osteoclast area per view induced by 1 μg/mL (mean ± SD: 50.828 ± 12.984%) and 10 μg/mL (53.663 ± 12.685%) of C3a was significantly increased compared to the control group (0 μg/mL) (34.635 ± 8.916%) (P < 0.001 and P < 0.001, respectively). The relative mRNA expressions of genes, OSCAR/TRAP/RANKL/cathepsin K, induced by 1 μg/mL (median: 5.041, 3.726, 1.638, and 4.752, respectively) and 10 μg/mL (median: 5.140, 3.702, 2.250, and 5.172, respectively) of C3a was significantly increased compared to the control group (median: 3.137, 2.004, 0.573, and 2.257, respectively) (1 μg/mL P = 0.001, P = 0.003, P < 0.001, and P = 0.008, respectively; 10 μg/mL: P < 0.001, P = 0.019, P < 0.001, and P = 0.002, respectively). The absorption areas of the osteoclast resorption pits per view induced by 1 μg/mL (mean ± SD: 51.464 ± 11.983%) and 10 μg/mL (50.219 ± 12.067%) of C3a was also significantly increased (33.845 ± 8.331%) (P < 0.001 and P < 0.001, respectively) compared to the control. There was no difference between the C4a and control groups. RNA-seq analysis showed that C3a promoted the proliferation of osteoclasts using the phosphoinositide 3-kinase (PI3K) signaling pathway. The relative expressions of PIK3CA/phosphoinositide dependent kinase-1 (PDK1)/serum and glucocorticoid inducible protein kinases (SGK3) genes and PI3K/PDK1/p-SGK3 protein in the C3a group were significantly higher than in the control group. The activation role of C3a in osteoclasts of MM patients was reduced by the SGK inhibitor (EMD638683).

CONCLUSIONS

C3a activated osteoclasts by regulating the PI3K/PDK1/SGK3 pathways in MM patients, which was reduced using a SGK inhibitor. Overall, our results identified potential therapeutic targets and strategies for MBD patients.

Protective Effects of Vitamin K Compounds on the Proteomic Profile of Osteoblasts under Oxidative Stress Conditions

Oxidative stress, which accompanies the pathogenesis of many bone diseases, contributes to the reduction of osteoblast activity, resulting in the inhibition of differentiation. This study aimed to assess the effect of vitamins K1 and K2 (MK4 and MK7) on the proteomic profile of human osteoblasts cell line under oxidative conditions induced by hydrogen peroxide (H₂O₂). The analysis was performed using QExactiveHF mass spectrometer with a nanoelectrospray ionization source. The osteoblast protein exposed to oxidative stress and vitamin K was compared with the proteome of cells exposed only to oxidative stress. Our proteomic analysis identified 1234 proteins changed after 5 days, 967 after 15 days, and 1214 after 20 days of culture. We observed the most frequent changes in the expression of proteins with catalytic activity or protein/DNA binding properties (45% and 40%, respectively). Significant changes were also observed in proteins with transcription/translation regulator activity (2–6%), regulators of molecular functions (5–6%), signal transducers (1–4%), transporters (4–6%), and structural molecules (3–5%). Our results clearly show that vitamins K protect cells from H₂O₂-induced changes in protein expression, primarily through their effects on transcriptional regulators and transporter proteins. As a result, vitamins K can support the formation, remodeling, and mineralization of bone tissue.

Proteomics-inspired precision medicine for treating and understanding multiple myeloma

Introduction

Remarkable progress in molecular characterization methods has led to significant improvements in how we manage multiple myeloma (MM). The introduction of novel therapies has led to significant improvements in overall survival over the past 10 years. However, MM remains incurable and treatment choice is largely based on outdated risk-adaptive strategies that do not factor in improved treatment outcomes in the context of modern therapies.

Areas covered

This review discusses current risk-adaptive strategies in MM and the clinical application of proteomics in the monitoring of treatment response, disease progression, and minimal residual disease (MRD). We also discuss promising biomarkers of disease progression, treatment response, and chemoresistance. Finally, we will discuss an immunomics-based approach to monoclonal antibody (mAb), vaccine, and CAR-T cell development.

Expert opinion

It is an exciting era in oncology with basic scientific knowledge translating in novel therapeutic approaches to improve patient outcomes. With the advent of effective immunotherapies and targeted therapies, it has become crucial to identify biomarkers to aid in the stratification of patients based on anticipated sensitivity to chemotherapy. As a paradigm of diseases highly dependent on protein homeostasis, multiple myeloma provides the perfect opportunity to investigate the use of proteomics to aid in precision medicine.

Current and future biomarkers for risk-stratification and treatment personalisation in multiple myeloma

Multiple myeloma, an incurable malignancy of the plasma cells in the bone marrow, has a complex pathogenesis due to clonal heterogeneity. Over the years, many clinical trials and researches have led to the development of effective myeloma treatments, resulting in survival prolongation. Molecular prognostic markers for risk-stratification to predict survival, and predictive markers for treatment response are being extensively explored. This review discusses the current risk-adaptive strategies based on genetic and molecular risk signatures that are in practice to predict survival and describes the future prognostic and predictive biomarkers across the fields of genomics, proteomics, and glycomics in myeloma. Gene expression profiling and next generation sequencing are coming to the forefront of risk-stratification and therapeutic-response prediction. Similarly, proteomic and glycomic-based platforms are gaining momentum in biomarker discovery to predict drug resistance and disease progression.

Rapid discrimination of multiple myeloma patients by artificial neural networks coupled with mass spectrometry of peripheral blood plasma

Multiple myeloma (MM) is a highly heterogeneous disease of malignant plasma cells. Diagnosis and monitoring of MM patients is based on bone marrow biopsies and detection of abnormal immunoglobulin in serum and/or urine. However, biopsies have a single-site bias; thus, new diagnostic tests and early detection strategies are needed. Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectrometry (MALDI-TOF MS) is a powerful method that found its applications in clinical diagnostics. Artificial intelligence approaches, such as Artificial Neural Networks (ANNs), can handle non-linear data and provide prediction and classification of variables in multidimensional datasets. In this study, we used MALDI-TOF MS to acquire low mass profiles of peripheral blood plasma obtained from MM patients and healthy donors. Informative patterns in mass spectra served as inputs for ANN that specifically predicted MM samples with high sensitivity (100%), specificity (95%) and accuracy (98%). Thus, mass spectrometry coupled with ANN can provide a minimally invasive approach for MM diagnostics.

Variability of serum novel serum peptide biomarkers correlates with the disease states of multiple myeloma

Background

The bone marrow microenvironment provides an optimal substrate for multiple myeloma (MM) initiation and progression. The soluble component of MM niche is dynamic with the disease states of MM. We formerly employed proteomic profiling to construct a MM model. Four peptides constituting the model were selected by supervised neural network algorithm (SNN).

Methods

62 Newly diagnosed (ND) MM and 64 healthy controls (HCs) were picked up for validating the distinguishing capability of the SNN model. Nano-liquid chromatography-electrospray ionization-tandem mass spectrometry was used for peptide identification. MM in different disease states and HCs were choosed for peptides relative intensities comparison. Western blot and ELISA were employed to validate the variability.

Results

The sensitivity and specificity of the independent testing data set for blind validation were 93.55% and 92.19%. The relative intensities of three out of the four peptides were increased in ND and refractory and relapse patients but decreased to that level of HCs in complete remission and very good partial remission patients. Relative intensity of the remaining peptide was negatively associated with MM remission. The peptides sequencing results showed that they were derived from dihydropyrimidinase-like 2, fibrinogen alpha chain, platelet factor 4 and alpha-fetoprotein.

Conclusions

The potential value of the four peptides in monitoring MM treatment response was arised from their close correlation with MM disease states.

Differential expression of serum proteins in multiple myeloma

The exact cause instigating multiple myeloma (MM) has not been fully elucidated, and the disease has a median survival of 6 months without any treatment. To identify potential biomarkers of MM, serum proteins reflecting alteration in their proteomes were analyzed in 6 patients with MM compared with 6 healthy controls using two-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time-of flight mass spectrometry. The most notable differentially expressed proteins were validated by immunoblotting and changes in mRNA expression were evaluated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 11 differentially expressed protein spots were found. The expression levels of 7 proteins [Immunoglobulin heavy constant µ; proto-oncogene diffuse B-cell lymphoma (DBL2); 26S protease regulatory subunit 4 (P26s4); serum albumin; haptoglobin; and two unknown proteins with isoelectronic point (pI) of 6.41 and molecular weight of 35.4 kDa, and pI of 8.05 and molecular weight of 27.4 kDa, respectively] were downregulated in MM compared with healthy controls. Expression of gel actin-related protein 2/3 complex subunit 1A (ARPC1A); immunoglobulin heavy constant γ 1; fibrinogen α chain (FGA) fragment D; and zinc finger protein 70 were increased in serum of MM patients. Protein expressions of ARPC1A, FGA, P26s4 and DBL2 were measured by immunoblotting in an independent cohort of 12 MM patients and 10 healthy controls. RT-qPCR analysis demonstrated that ARPC1A expression only mimicked protein expression, whereas FGA, PSMC1 (encoding P26s4) and MCF2 (encoding DBL2) did not exhibit significant changes in mRNA expression between control and MM samples. These proteins represent putative serological biomarkers for patients with MM.

Development and characterisation of a panel of phosphatidylinositide 3-kinase - mammalian target of rapamycin inhibitor resistant lung cancer cell lines

The PI3K-mTOR pathway is involved in regulating all hallmarks of cancer, and is often dysregulated in NSCLC, making it an attractive therapeutic target in this setting. Acquired resistance to PI3K-mTOR inhibition is a major hurdle to overcome in the success of PI3K-mTOR targeted agents. H460, A549, and H1975 resistant cells were generated by prolonged treatment in culture with Apitolisib (GDC-0980), a dual PI3K-mTOR inhibitor over a period of several months, from age-matched parent cells. Resistance was deemed to have developed when a log fold difference in IC50 had been achieved. Resistant cell lines also exhibited resistance to another widely investigated PI3K-mTOR dual inhibitor; Dactolisib (BEZ235). Cell lines were characterised at the level of mRNA (expression array profiling expression of >150 genes), miRNA (expression array profiling of 2100 miRNAs), protein (bottoms-up label-free mass spectrometry) and phosphoprotein (expression array profiling of 84 phospho/total proteins). Key alterations were validated by qPCR and Western blot. H1975 cells were initially most sensitive to Apitolisib (GDC-0980), but developed resistance more quickly than the other cell lines, perhaps due to increased selective pressure from the impressive initial effect. In-depth molecular profiling suggested epithelial-mesenchymal transition (EMT) may play a role in resistance to PI3K-mTOR dual inhibition in NSCLC.

Protein Digestion for DIGE Analysis

In-gel digestion of protein spots derived from two-dimensional gels and their subsequent identification by mass spectrometry is involved in a multitude of mass spectrometry-driven proteomic experiments, including fluorescence difference gel electrophoresis (DIGE). This type of proteomic methodology has been involved in the establishment of comparative proteome maps and in the identification of differentially expressed proteins and protein isoforms in health and disease. Most in-gel digestion protocols follow a number of common steps including excision of the protein spots of interest, de-staining, reduction and alkylation (for silver-stained gels), dehydration and overnight digestion with the proteolytic enzyme of choice. While trypsin has been a mainstay of peptide digestion for many years, it does have its shortcomings, particularly related to incomplete peptide digestion, and this has led to a rise in popularity for other proteolytic enzymes either used alone or in combination. This chapter discusses the alternative enzymes available and describes the process of in-gel digestion using the enzyme trypsin.

The role of paraoxonase in cancer

The paraoxonase (PON) gene family includes three proteins, PON1, PON2 and PON3. PON1 and PON3 are both associated with high-density lipoprotein (HDL) particles and exert anti-oxidant and anti-inflammatory properties. PON2 and PON3 are intracellular enzymes which modulate mitochondrial superoxide anion production and endoplasmic reticulum (ER) stress-induced apoptosis. The pleiotropic roles exerted by PONs have been mainly investigated in cardiovascular and neurodegenerative diseases. In recent years, overexpression of PON2 and PON3 has been observed in cancer cells and it has been proposed that both enzymes could be involved in tumor survival and stress resistance. Moreover, a lower activity of serum PON1 has been reported in cancer patients. This review summarizes literature data on the role of PONs in human cancers and their potential role as a target for antitumor drugs.

Novel panel of protein biomarkers to predict response to bortezomib-containing induction regimens in multiple myeloma patients

BACKGROUND

Multiple myeloma (MM) is a complex heterogeneous disease. Various risk stratification models have been recommended including cytogenetic and FISH analysis to identify high-risk patients who may benefit from novel treatments, but such facilities are not widely available. The International Scoring System (ISS) using beta-2-microglobulin and albumin remains a widely used prognostic scoring system in many clinical practices; however it is not useful in predicting response to treatment in MM. The aim of this study is to identify clinically useful biomarkers to predict response to treatment containing bortezomib.

METHODS

17 MM patient serum samples (9 responders/8 non-responders) were used for the discovery phase (label-free mass spectrometry) and an additional 20 MM patient serum samples were used for the ELISA-based validation phase (14 responders/6 non-responders).

RESULTS

CLU and ANG mean levels were higher in the responders group, while Complement C1q had lower concentrations. The combination of all standard biomarkers (albumin, beta-2-microglobulin (ß2M), paraprotein and kappa/lambda (K/L) ratio) had an AUC value of 0.71 with 65% correct classification, while an overall combination of new candidate protein biomarkers with standard biomarkers had an AUC value of 0.89 with 85.3% correct classification.

CONCLUSIONS

A combination of new and standard biomarkers consisting of CLU, ANG, C1Q, albumin, ß2M, paraprotein and K/L ratio may have potential as a novel panel of biomarkers to predict MM response to treatment containing bortezomib.

GENERAL SIGNIFICANCE

Use of this biomarker panel could facilitate a more personalized therapy approach and to minimize unnecessary side effects from ineffective drugs.

Molecular mechanisms, current management and next generation therapy in myeloma bone disease

Multiple myeloma (MM) bone disease is a major cause of morbidity and mortality in MM patients and persists even in patients in remission. This bone disease is caused by an uncoupling of bone remodeling, with increased osteoclast and decreased osteoblast activity and formation, culminating in lytic bone destruction. Bisphosphonates are the current standard of care but new therapies are needed. As the molecular mechanisms controlling MM bone disease are increasingly well understood, new therapeutic targets are extensively explored in the preclinical setting and initial clinical trials with novel compounds now show promising results. In this review, we will provide a comprehensive overview of the biology of MM bone disease, summarize its current clinical management and discuss preclinical and clinical data on next generation therapies.

Proteomic profiling of mdx-4cv serum reveals highly elevated levels of the inflammation-induced plasma marker haptoglobin in muscular dystrophy

X-linked muscular dystrophy is caused by primary abnormalities in the Dmd gene and is characterized by the almost complete loss of the membrane cytoskeletal protein dystrophin, which triggers sarcolemmal instability, abnormal calcium homeostasis, increased proteolysis and impaired excitation-contraction coupling. In addition to progressive necrosis, crucial secondary pathologies are represented by myofibrosis and the invasion of immune cells in damaged muscle fibres. In order to determine whether these substantial changes within the skeletal musculature are reflected by an altered rate of protein release into the circulatory system or other plasma fluctuations, we used label-free mass spectrometry to characterize serum from the mdx-4cv model of Duchenne muscular dystrophy. Comparative proteomics revealed a large number of increased vs. decreased protein species in mdx-4cv serum. A serum component with greatly elevated levels was identified as the inflammation-inducible plasma marker haptoglobin. This acute phase response protein is usually secreted in relation to tissue damage and sterile inflammation. Both immunoblot analyses and enzyme-linked immunosorbent assays confirmed the increased concentration of haptoglobin in crude mdx-4cv serum. This suggests that haptoglobin, in conjunction with other altered serum proteins, represents a novel diagnostic, prognostic and/or therapy-monitoring biomarker candidate to evaluate the inflammatory response in the mdx-4cv animal model of dystrophinopathy.

Proteomic analysis of bronchoalveolar lavage fluid (BALF) from lung cancer patients using label-free mass spectrometry

BACKGROUND

Lung cancer is the leading cause of cancer-related mortality in both men and women throughout the world. The need to detect lung cancer at an early, potentially curable stage, is essential and may reduce mortality by 20%. The aim of this study was to identify distinct proteomic profiles in bronchoalveolar fluid (BALF) and plasma that are able to discriminate individuals with benign disease from those with non-small cell lung cancer (NSCLC).

METHODS

Using label-free mass spectrometry analysis of BALF during discovery-phase analysis, a significant number of proteins were found to have different abundance levels when comparing control to adenocarcinoma (AD) or squamous cell lung carcinoma (SqCC). Validation of candidate biomarkers identified in BALF was performed in a larger cohort of plasma samples by detection with enzyme-linked immunoassay.

RESULTS

Four proteins (Cystatin-C, TIMP-1, Lipocalin-2 and HSP70/HSPA1A) were selected as a representative group from discovery phase mass spectrometry BALF analysis. Plasma levels of TIMP-1, Lipocalin-2 and Cystatin-C were found to be significantly elevated in AD and SqCC compared to control.

CONCLUSION

The results presented in this study indicate that BALF is an important proximal biofluid for the discovery and identification of candidate lung cancer biomarkers.

GENERAL SIGNIFICANCE

There is good correlation between the trend of protein abundance levels in BALF and that of plasma which validates this approach to develop a blood biomarker to aid lung cancer diagnosis, particularly in the era of lung cancer screening. The protein signatures identified also provide insight into the molecular mechanisms associated with lung malignancy.

Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems

Liquid chromatography-mass spectrometry (LC-MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin based depletion column followed by either protein In-gel enzymatic digestion or protein in-solution enzymatic digestion and then analysis by one-dimensional reverse-phase chromatography or two-dimensional strong cation exchange (SCX)-reverse-phase chromatography (RPC).

Proteome analysis of human serum proteins adsorbed onto different titanium surfaces used in dental implants

Titanium dental implants are commonly used due to their biocompatibility and biochemical properties; blasted acid-etched Ti is used more frequently than smooth Ti surfaces. In this study, physico-chemical characterisation revealed important differences in roughness, chemical composition and hydrophilicity, but no differences were found in cellular in vitro studies (proliferation and mineralization). However, the deposition of proteins onto the implant surface might affect in vivo osseointegration. To test that hypothesis, protein layers formed on discs of both surface type after incubation with human serum were analysed. Using mass spectrometry (LC/MS/MS), 218 proteins were identified, 30 of which were associated with bone metabolism. Interestingly, Apo E, antithrombin and protein C adsorbed mostly onto blasted and acid-etched Ti, whereas the proteins of the complement system (C3) were found predominantly on smooth Ti surfaces. These results suggest that physico-chemical characteristics could be responsible for the differences observed in the adsorbed protein layer.

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.

Multiple myeloma: is it time for biomarker-driven therapy?

Remarkable strides have been made in understanding the molecular mechanisms by which multiple myeloma develops, leading to more sophisticated classification that incorporates not only the traditional diagnostic criteria, but also immunophenotype, genetic, and molecular features. However, even with this added information, considerable heterogeneity in clinical outcomes exists within the identified subtypes. The present paradigm for myeloma treatment is built on the basic step of defining transplant eligibility versus noneligibility, as determined by age, performance status, and cumulative burden of comorbidities. An incredibly complex heterogeneous disease is, therefore, treated in a generalized way with the result that large interpatient variability exists in the outcome. As antimyeloma therapeutics continue to expand it is becoming even more crucial to personalize treatment approaches that provide the most value to a specific patient. Development of biomarkers, either individually or as larger sets or patterns and ranging from analysis of blood or bone marrow to biomedical imaging, is a major focus in the field. Biomarkers such as involved serum free light chain ratio and MRI focal lesions have been implemented in the new definition of multiple myeloma and guide clinicians to initiate treatment in otherwise asymptomatic individuals. Currently, however, there is not enough evidence to support intensifying the treatment for high-risk disease or reducing the treatment for low-risk disease. Minimal residual disease-negative status is an important biomarker that holds promise for monitoring the effectiveness of response-adapted strategies. This article sheds light on the forward landscape and rear-mirror view of biomarkers in myeloma.

Human paraoxonase-1 (PON1): Gene structure and expression, promiscuous activities and multiple physiological roles

Human PON1 is a HDL-associated lipolactonase capable of preventing LDL and cell membrane oxidation and is therefore considered to be atheroprotective. PON1 contributes to the antioxidative function of HDL and reductions in HDL-PON1 activity, prevalent in a wide variety of diseases with an inflammatory component, are believed to lead to dysfunctional HDL which can promote inflammation and atherosclerosis. However, PON1 is multifunctional and may contribute to other HDL functions such as in innate immunity, preventing infection by quorum sensing gram negative bacteria by destroying acyl lactone mediators of quorum sensing, and putative new roles in cancer development and the promotion of healthy ageing. In this review we explore the physiological roles of PON1 in disease development, as well as PON1 gene and protein structure, promiscuous activities and the roles of SNPs and ethnicity in determining PON1 activity.