Proteomic Analysis in Multiple Myeloma Research

Proteomic Alterations in Multiple Myeloma: A Comprehensive Study Using Bone Marrow Interstitial Fluid and Serum Samples

Multiple myeloma (MM) is a plasma cell-associated cancer and exists as the second most common hematological malignancy worldwide. Although researchers have been working on MM, a comprehensive quantitative Bone Marrow Interstitial Fluid (BMIF) and serum proteomic analysis from the same patients’ samples is not yet reported. The present study involves the investigation of alterations in the BMIF and serum proteome of MM patients compared to controls using multipronged quantitative proteomic approaches viz., 2D-DIGE, iTRAQ, and SWATH-MS. A total of 279 non-redundant statistically significant differentially abundant proteins were identified by the combination of three proteomic approaches in MM BMIF, while in the case of serum 116 such differentially abundant proteins were identified. The biological context of these dysregulated proteins was deciphered using various bioinformatic tools. Verification experiments were performed in a fresh independent cohort of samples using immunoblotting and mass spectrometry based SRM assays. Thorough data evaluation led to the identification of a panel of five proteins viz., haptoglobin, kininogen 1, transferrin, and apolipoprotein A1 along with albumin that was validated using ELISA in a larger cohort of serum samples. This panel of proteins could serve as a useful tool in the diagnosis and understanding of the pathophysiology of MM in the future.

The 60-kDa heat shock protein regulates energy rearrangement and protein synthesis to promote proliferation of multiple myeloma cells

To investigate the cellular mechanisms of multiple myeloma (MM), we used liquid chromatography-tandem mass spectrometry for proteomics analysis of CD138⁺ plasma cells from patients with MM and healthy controls. We found that the 60-kDa heat shock protein (HSP60, also known as HSPD1) was significantly upregulated in myeloma cells. HSP60 is an important chaperone protein that regulates the homeostasis of mitochondrial proteins and maintains mitochondrial function. Knockdown (KD) of HSP60 in myeloma cells resulted in inhibition of proliferation and reduced the quality of the mitochondria. Mitochondrial stress tests showed that HSP60 KD inhibited glycolysis and mitochondrial activity. Metabolomics showed a decrease in glycolysis and tricarboxylic acid cycle metabolites, and inhibited the formation of creatine and phosphocreatine by the reaction of S-adenosylmethionine (SAM) with amino acids mediated by demethyladenosine transferase 1, mitochondrial (TFB1M) and reduced energy storage substances. Moreover, HSP60 silencing influenced the synthesis of ribonucleotides and nicotinamide adenine dinucleotide phosphate (NADPH) by the pentose phosphate pathway to inhibit cell proliferation. HSP60 KD inhibited 5' adenosine monophosphate-activated protein kinase (AMPK), which inhibited the key enzyme 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), effecting the metabolism of fatty acids by inhibiting malonyl-coenzyme A. Our data suggest that reduced HSP60 expression alters metabolic reprogramming in MM, inhibits tumour progression and reduces mitochondrial-dependent biosynthesis, suggesting that HSP60 is a potential therapeutic target for MM treatment.

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.

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

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

Multiple myeloma cell lines and primary tumors proteoma: protein biosynthesis and immune system as potential therapeutic targets

Despite great advance in multiple myeloma (MM) treatment since 2000s, it is still an incurable disease and novel therapies are welcome. Therefore, the purpose of this study was to explore MM plasma cells' (MM-PC) proteome, in comparison with their normal counterparts (derived from palatine tonsils of normal donors, ND-PC), in order to find potential therapeutic targets expressed on the surface of these cells. We also aimed to evaluate the proteome of MM cell lines with different genetic alterations, to confirm findings obtained with primary tumor cells. Bone marrow (BM) samples from eight new cases of MM and palatine tonsils from seven unmatched controls were submitted to PC separation and, in addition to two MM cell lines (U266, RPMI-8226), were submitted to protein extraction for mass spectrometry analyses. A total of 81 proteins were differentially expressed between MM-PC and ND-PC - 72 upregulated and nine downregulated; U266 vs. RPMI 8226 cell lines presented 61 differentially expressed proteins - 51 upregulated and 10 downregulated. On primary tumors, bioinformatics analyses highlighted upregulation of protein biosynthesis machinery, as well as downregulation of immune response components, such as MHC class I and II, and complement receptors. We also provided comprehensive information about U266 and RPMI-8226 cell lines' proteome and could confirm some patients' findings.

Proteomic analysis for finding serum pathogenic factors and potential biomarkers in multiple myeloma

BACKGROUND

Multiple myeloma (MM) is a malignant tumor, which takes the second place in malignant blood disease. The clinical symptoms are complicated that make more difficult to diagnose and therapy. Lots of researches focus on the proteins about MM in order to solve those problems. We used proteomic methods to find potential biomarkers in MM patients.

METHODS

We applied the peptide ligand library beads (PLLBs) to deplete high abundance proteins in serum for finding potential pathogenic factors and biomarkers of MM. Using 1D-Gel-liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified 789 and 849 unique serum proteins in MM patients and in healthy controls, respectively.

RESULTS

Twenty-two proteins were found differentially expressed between the two groups including serum amyloid A protein, vitamin D-binding protein isoform-1 precursor, plasma kallikrein, and apolipoprotein A-I. Changes of integrin alpha-11 and isoform-1 of multimerin-1 were validated with Western blotting. The linkage of the differentially expressed proteins and the pathogenesis pathways of MM were discussed.

CONCLUSIONS

PLLB combined with 1D-gel-LC-MS/MS analysis is an efficient method to identify differentially expressed proteins in serum from patients with MM.

Proteomics approaches for the studies of bone metabolism

Bone is an active tissue, in which bone formation by osteoblast is followed by bone resorption by osteoclasts, in a repeating cycle. Proteomics approaches may allow the detection of changes in cell signal transduction, and the regulatory mechanism of cell differentiation. LC-MS/MS-based quantitative methods can be used with labeling strategies, such as SILAC, iTRAQ, TMT and enzymatic labeling. When used in combination with specific protein enrichment strategies, quantitative proteomics methods can identify various signaling molecules and modulators, and their interacting proteins in bone metabolism, to elucidate biological functions for the newly identified proteins in the cellular context. In this article, we will briefly review recent major advances in the application of proteomics for bone biology, especially from the aspect of cellular signaling. [BMB Reports 2014; 47(3): 141-148]

The clinical value of the quantitative detection of four cancer-testis antigen genes in multiple myeloma

BACKGROUND

Cancer-testis (CT) antigen genes might promote the progression of multiple myeloma (MM). CT antigens may act as diagnostic and prognostic markers in MM, but their expression levels and clinical implications in this disease are not fully understood. This study measured the expression levels of four CT antigen genes in Chinese patients with MM and explored their clinical implications.

METHODS

Real-time quantitative polymerase chain reaction (qPCR) was used to quantify the expression of MAGE-C1/CT7, MAGE-A3, MAGE-C2/CT10 and SSX-2 mRNA in 256 bone marrow samples from 144 MM patients.

RESULTS

In the newly diagnosed patients, the positive expression rates were 88.5% for MAGE-C1/CT7, 82.1% for MAGE-C2/CT10, 76.9% for MAGE-A3 and 25.6% for SSX-2. The expression levels and the number of co-expressed CT antigens correlated significantly with several clinical indicators, including the percentage of plasma cells infiltrating the bone marrow, abnormal chromosome karyotypes and the clinical course.

CONCLUSION

MAGE-C1/CT7, MAGE-A3, MAGE-C2/CT10 and SSX-2 expression levels provide potentially effective clinical indicators for the auxiliary diagnosis and monitoring of treatment efficacy in MM.

Extracellular matrix remodeling by bone marrow fibroblast-like cells correlates with disease progression in multiple myeloma

The pathogenesis of multiple myeloma (MM) is regarded as a multistep process, in which an asymptomatic stage of monoclonal gammopathy of undetermined significance (MGUS) precedes virtually all cases of MM. Molecular events characteristic for the transition from MGUS to MM are still poorly defined. We hypothesized that fibroblast-like cells in the tumor microenvironment are critically involved in the pathogenesis of MM. Therefore, we performed a comparative proteome profiling study, analyzing primary human fibroblast-like cells isolated from the bone marrow of MM, of MGUS, as well as of non-neoplastic control patients. Thereby, a group of extracellular matrix (ECM) proteins, ECM receptors, and ECM-modulating enzymes turned out to be progressively up-regulated in MGUS and MM. These proteins include laminin α4, lysyl-hydroxylase 2, prolyl 4-hydroxylase 1, nidogen-2, integrin α5β5, c-type mannose receptor 2, PAI-1, basigin, and MMP-2, in addition to PDGF-receptor β and the growth factor periostin, which are likewise involved in ECM activities. Our results indicate that ECM remodeling by fibroblast-like cells may take place already at the level of MGUS and may become even more pronounced in MM. The identified proteins which indicate the stepwise progression from MGUS to MM may offer new tools for therapeutic strategies.

Potential biomarkers for early detection of acute graft-versus-host disease

Acute graft-versus-host disease (aGVHD) is the main complication of allogeneic hematopoietic stem cell transplantation (HCT), resulting in considerable morbidity and mortality. Currently, the diagnosis of aGVHD is largely made based on clinical parameters and invasive biopsies. For the past 20 years, researchers have been trying to find reliable biomarkers to enable early and accurate diagnosis of aGVHD. Although a number of potential aGVHD biomarkers have been published, as yet, no validated diagnostic test is available. Proteomics encompasses a broad range of rapidly developing technologies, which have shown tremendous promise for early detection of aGVHD. In this article, we review the current state of aGVHD biomarker discovery, provide a summary of the key proteins of interest and the most common analytical procedures for the clinic, as well as outlining the significant challenges faced in their use.