Proteome alterations associated with transformation of multiple myeloma to secondary plasma cell leukemia

Progression of monoclonal gammopathy of undetermined significance to multiple myeloma is associated with enhanced translational quality control and overall loss of surface antigens

BACKGROUND

Despite significant advancements in treatment strategies, multiple myeloma remains incurable. Additionally, there is a distinct lack of reliable biomarkers that can guide initial treatment decisions and help determine suitable replacement or adjuvant therapies when relapse ensues due to acquired drug resistance.

METHODS

To define specific proteins and pathways involved in the progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), we have applied super-SILAC quantitative proteomic analysis to CD138 + plasma cells from 9 individuals with MGUS and 37 with MM.

RESULTS

Unsupervised hierarchical clustering defined three groups: MGUS, MM, and MM with an MGUS-like proteome profile (ML) that may represent a group that has recently transformed to MM. Statistical analysis identified 866 differentially expressed proteins between MM and MGUS, and 189 between MM and ML, 177 of which were common between MGUS and ML. Progression from MGUS to MM is accompanied by upregulated EIF2 signaling, DNA repair, and proteins involved in translational quality control, whereas integrin- and actin cytoskeletal signaling and cell surface markers are downregulated.

CONCLUSION

Compared to the premalignant plasma cells in MGUS, malignant MM cells apparently have mobilized several pathways that collectively contribute to ensure translational fidelity and to avoid proteotoxic stress, especially in the ER. The overall reduced expression of immunoglobulins and surface antigens contribute to this and may additionally mediate evasion from recognition by the immune apparatus. Our analyses identified a range of novel biomarkers with potential prognostic and therapeutic value, which will undergo further evaluation to determine their clinical significance.

Modeling cell populations metabolism and competition under maximum power constraints

Ecological interactions are fundamental at the cellular scale, addressing the possibility of a description of cellular systems that uses language and principles of ecology. In this work, we use a minimal ecological approach that encompasses growth, adaptation and survival of cell populations to model cell metabolisms and competition under energetic constraints. As a proof-of-concept, we apply this general formulation to study the dynamics of the onset of a specific blood cancer-called Multiple Myeloma. We show that a minimal model describing antagonist cell populations competing for limited resources, as regulated by microenvironmental factors and internal cellular structures, reproduces patterns of Multiple Myeloma evolution, due to the uncontrolled proliferation of cancerous plasma cells within the bone marrow. The model is characterized by a class of regime shifts to more dissipative states for selectively advantaged malignant plasma cells, reflecting a breakdown of self-regulation in the bone marrow. The transition times obtained from the simulations range from years to decades consistently with clinical observations of survival times of patients. This irreversible dynamical behavior represents a possible description of the incurable nature of myelomas based on the ecological interactions between plasma cells and the microenvironment, embedded in a larger complex system. The use of ATP equivalent energy units in defining stocks and flows is a key to constructing an ecological model which reproduces the onset of myelomas as transitions between states of a system which reflects the energetics of plasma cells. This work provides a basis to construct more complex models representing myelomas, which can be compared with model ecosystems.

Plasma cell leukemia in a 34-year-old male: rare scenario case report

Introduction

Plasma cell leukaemia is an uncommon plasma cell dyscrasia with a very poor prognosis. It is more common among males and usually presents between 55 and 65 years of age.

Case presentation

A 34-year-old male presented to Al-Assad hospital with unremitting back pain. He was given analgesics but his pain was unresponsive to treatment, and due to the COVID-19 pandemic, he refused a computed tomography scan in the hospital. Later that year, he presented again with weight loss, nausea, abdominal pain, melena, and ascites. He was pale with a moderately distended abdomen. Laboratory tests revealed anaemia, thrombocytopenia, hypercalcemia, increased total proteins, and elevated lactate dehydrogenase. Flow cytometry findings of the bone marrow aspirate showed the presence of 30% of plasma cells, positive for CD38, CD56, and kappa light chains. He was diagnosed with secondary plasma cell leukaemia and started on chemotherapy; however, he could not continue his treatment due to myeloid inhibition. He passed away 5 months later.

Clinical discussion

Multiple myeloma was not suspected in the patient due to his young age. The diagnosis was delayed even further due to the COVID-19 pandemic. His multiple myeloma progressed into secondary plasma cell leukaemia and had uncommon features like small intestinal polyps. Even though there has been groundbreaking advancements in chemotherapy, plasma cell leukaemia still possesses a fatal prognosis.

Conclusion

This report showcases a rare age presentation with unique manifestations of secondary plasma cell leukaemia. Multiple myeloma should be a differential diagnosis for cases with unexplained back pain despite an unclassical age.

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.

Serum proteomic profiling reveals MTA2 and AGO2 as potential prognostic biomarkers associated with disease activity and adverse outcomes in multiple myeloma

Multiple myeloma (MM) is an incurable plasma cell malignancy accounting for approximately 10% of hematological malignancies. Identification of reliable biomarkers for better diagnosis and prognosis remains a major challenge. This study aimed to identify potential serum prognostic biomarkers corresponding to MM disease activity and evaluate their impact on patient outcomes. Serum proteomic profiles of patients with MM and age-matched controls were performed using LC-MS/MS. In the verification and validation phases, the concentration of the candidate biomarkers was measured using an ELISA technique. In addition, the association of the proposed biomarkers with clinical outcomes was assessed. We identified 23 upregulated and 15 downregulated proteins differentially expressed in newly diagnosed and relapsed/refractory MM patients compared with MM patients who achieved at least a very good partial response to treatment (≥VGPR). The top two candidate proteins, metastasis-associated protein-2 (MTA2) and argonaute-2 (AGO2), were selected for further verification and validation studies. Both MTA2 and AGO2 showed significantly higher levels in the disease-active states than in the remission states (p < 0.001). Regardless of the patient treatment profile, high MTA2 levels were associated with shorter progression-free survival (p = 0.044; HR = 2.48; 95% CI, 1.02 to 6.02). Conversely, high AGO2 levels were associated with IgG and kappa light-chains isotypes and an occurrence of bone involvement features (p < 0.05) and were associated with prolonged time to response (p = 0.045; HR = 3.00; 95% CI, 1.03 to 8.76). Moreover, the analytic results using a publicly available NCBI GEO dataset revealed that AGO2 overexpression was associated with shorter overall survival among patients with MM (p = 0.032, HR = 1.60, 95% CI, 1.04 to 2.46). In conclusion, MTA2 and AGO2 proteins were first identified as potential biomarkers that reflect disease activity, provide prognostic values and could serve as non-invasive indicators for disease monitoring and outcome predicting among patients with MM.

Transgelin-2 in Multiple Myeloma: A New Marker of Renal Impairment?

Transgelin is a 22-kDa protein involved in cytoskeletal organization and expressed in smooth muscle tissue. According to animal studies, it is a potential mediator of kidney injury and fibrosis, and moreover, its role in tumorigenesis is emerging in a variety of cancers. The study included 126 ambulatory patients with multiple myeloma (MM). Serum transgelin-2 concentrations were measured by enzyme-linked immunoassay. We evaluated associations between baseline transgelin and kidney function (serum creatinine, estimated glomerular filtration rate—eGFR, urinary markers of tubular injury: cystatin-C, neutrophil gelatinase associated lipocalin—NGAL monomer, cell cycle arrest biomarkers IGFBP-7 and TIMP-2) and markers of MM burden. Baseline serum transgelin was also evaluated as a predictor of kidney function after a follow-up of 27 months from the start of the study. Significant correlations were detected between serum transgelin-2 and serum creatinine (R = 0.29; p = 0.001) and eGFR (R = −0.25; p = 0.007). Transgelin significantly correlated with serum free light chains lambda (R = 0.18; p = 0.047) and serum periostin (R = −0.22; p = 0.013), after exclusion of smoldering MM patients. Patients with decreasing eGFR had higher transgelin levels (median 106.6 versus 83.9 ng/mL), although the difference was marginally significant (p = 0.05). However, baseline transgelin positively correlated with serum creatinine after the follow-up period (R = 0.37; p < 0.001) and negatively correlated with eGFR after the follow-up period (R = −0.33; p < 0.001). Moreover, higher baseline serum transgelin (beta = −0.11 ± 0.05; p = 0.032) significantly predicted lower eGFR values after the follow-up period, irrespective of baseline eGFR and follow-up duration. Our study shows for the first time that elevated serum transgelin is negatively associated with glomerular filtration in MM and predicts a decline in renal function over long-term follow-up.

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.

Plasma cell leukemia: A review of the molecular classification, diagnosis, and evidenced-based treatment

Plasma cell leukemia is a rare and aggressive plasma cell dyscrasia associated with dismal outcomes. It may arise de novo, primary plasma cell leukemia, or evolve from an antecedent diagnosis of multiple myeloma, secondary plasma cell leukemia. Despite highly effective therapeutics, survival for plasma cell leukemia patients remains poor. Molecular knowledge of plasma cell leukemia has recently expanded with use of gene expression profiling and whole exome sequencing, lending new insights into prognosis and therapeutic development. In this review, we describe the molecular knowledge, clinical characteristics, evidenced-based therapeutic approaches and treatment outcomes of plasma cell leukemia.

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.

Plasma Cell Leukemia: Definition, Presentation, and Treatment

Purpose of Review

We discuss current topics on the definition of plasma cell leukemia and the distinction between plasma cell leukemia and multiple myeloma. Moreover, we review the latest literature on how to treat plasma cell leukemia.

Recent Findings

Plasma cell leukemia is clinically and genetically distinct from multiple myeloma. Plasma cell leukemia is defined by the observation in blood of more than 20% clonal plasma cells by differential count of the leucocytes or by counting more than 2 × 10⁹ per liter circulating clonal plasma cells. However, patients with lower levels of circulating plasma cells have the same adverse prognosis, which challenges the disease definition. Survival has improved after implementation of high-dose chemotherapy with stem-cell support, bortezomib, and lenalidomide in the treatment; yet, the prognosis remains poor. The results of allo-transplants have been disappointing.

Summary

The diagnostic criteria of PCL are currently discussed in the international myeloma community. Despite some improvement in survival, the prognosis remains adverse. New, more targeted treatment modalities, including immunotherapies, will hopefully improve the outcome in the near future.