Metabolic Changes Are Associated with Melphalan Resistance in Multiple Myeloma

The proteogenomic landscape of multiple myeloma reveals insights into disease biology and therapeutic opportunities

Multiple myeloma (MM) is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, MM remains incurable, and better risk stratification as well as new therapies are therefore highly needed. The proteome of MM has not been systematically assessed before and holds the potential to uncover insight into disease biology and improved prognostication in addition to genetic and transcriptomic studies. Here we provide a comprehensive multiomics analysis including deep tandem mass tag-based quantitative global (phospho)proteomics, RNA sequencing, and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive MM, plasma cell leukemia and the premalignancy monoclonal gammopathy of undetermined significance, as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells are highly deregulated as compared with healthy plasma cells and is both defined by chromosomal alterations as well as posttranscriptional regulation. A prognostic protein signature was identified that is associated with aggressive disease independent of established risk factors in MM. Integration with functional genetics and single-cell RNA sequencing revealed general and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include potential targets for (immuno)therapies. Our study demonstrates the potential of proteogenomics in cancer and provides an easily accessible resource for investigating protein regulation and new therapeutic approaches in MM.

Metformin and chidamide synergistically suppress multiple myeloma progression and enhance lenalidomide/bortezomib sensitivity

Multiple myeloma (MM) is a common hematological malignancy, and patients with MM are recommended to take immunomodulatory drugs such as lenalidomide along with proteasome inhibitors such as bortezomib to extend survival. However, drug resistance influences the efficacy of treatment for MM. In our study, we found that metformin and chidamide both suppressed MM cell growth in a concentration- and time-dependent way (p < .001). Moreover, combined therapy with metformin and chidamide exhibited enhanced inhibition of the growth of MM cells compared with monotherapy (p < .05). Additionally, the triple-drug combination of metformin and chidamide with lenalidomide or bortezomib was used to stimulate the MM cells, and the results revealed that metformin and chidamide treatment sensitized MM cells to lenalidomide and bortezomib. As a result, the apoptosis (p < .001) together with cell cycle arrest at G0/G1 phase (p < .05) was stimulated by lenalidomide and bortezomib, and showed significant elevation in the triple-drug combination group compared with the lenalidomide or bortezomib treatment alone group (p < .05). Furthermore, the impacts of different drugs on glycolysis in MM cells were examined. We found that metformin and chidamide combined treatment significantly promoted glucose uptake and reduced energy production in MM cells treated with lenalidomide and bortezomib (p < .001), suggesting that metformin and chidamide affected glycolysis in MM cells and enhanced the sensitivity of lenalidomide and bortezomib in MM by regulating glucose metabolism. In conclusion, metformin and chidamide synergistically hindered MM cell growth and sensitized cells to lenalidomide/bortezomib. The findings of this study might provide novel clues to improve MM therapy.

Impacting T-cell fitness in multiple myeloma: potential roles for selinexor and XPO1 inhibitors

Competent T-cells with sufficient levels of fitness combat cancer formation and progression. In multiple myeloma (MM), T-cell exhaustion is caused by several factors including tumor burden, constant immune activation due to chronic disease, age, nutritional status, and certain MM treatments such as alkylating agents and proteasome inhibitors. Many currently used therapies, including bispecific T-cell engagers, anti-CD38 antibodies, proteasome inhibitors, and CART-cells, directly or indirectly depend on the anti-cancer activity of T-cells. Reduced T-cell fitness not only diminishes immune defenses, increasing patient susceptibility to opportunistic infections, but can impact effectiveness MM therapy effectiveness, bringing into focus sequencing strategies that could modulate T-cell fitness and potentially optimize overall benefit and clinical outcomes. Certain targeted agents used to treat MM, such as selective inhibitors of nuclear export (SINE) compounds, have the potential to mitigate T-cell exhaustion. Herein referred to as XPO1 inhibitors, SINE compounds inhibit the nuclear export protein exportin 1 (XPO1), which leads to nuclear retention and activation of tumor suppressor proteins and downregulation of oncoprotein expression. The XPO1 inhibitors selinexor and eltanexor reduced T-cell exhaustion in cell lines and animal models, suggesting their potential role in revitalizating these key effector cells. Additional clinical studies are needed to understand how T-cell fitness is impacted by diseases and therapeutic factors in MM, to potentially facilitate the optimal use of available treatments that depend on, and impact, T-cell function. This review summarizes the importance of T-cell fitness and the potential to optimize treatment using T-cell engaging therapies with a focus on XPO1 inhibitors.

A rapid and sensitive LC-MS/MS method for simultaneous determination of melphalan and its monohydroxy and dihydroxy metabolites in human plasma

As a hydrolysis mediated drug in vivo, the pharmacokinetics of melphalan are highly variable in patients. Few methodologies could simultaneously measure the concentrations of melphalan and its hydrolyzed metabolites in plasma. The aim of this study was to develop a simple, rapid and sensitive liquid chromatography/tandem mass spectrometry (LC-MS/MS) method for simultaneous determination of melphalan and its hydrolyzed metabolites, monohydroxy melphalan (MOH melphalan) and dihydroxy melphalan (DOH melphalan). A simple protein precipitation was employed for sample preparation and melphalan-d8 was used as internal standard. Baseline separation of target analytes was achieved using an XSelect HSS T3 column (2.1 × 50 mm, 5 µm) with a gradient elution at a flow rate of 0.5 mL/min in 5 min. The monitored transitions were m/z 305.1 → 287.7 for melphalan, m/z 287.1 → 228.0 for MOH melphalan, m/z 269.3 → 251.8 for DOH melphalan, and m/z 313.1 → 295.7 for melphalan-d8. The method was fully validated in accordance with the FDA guideline. The calibration curves were established over the range of 5.22-5220 ng/mL for melphalan, 7.94-1588 ng/mL for MOH-melphalan, and 15.0-3000 ng/mL for DOH-melphalan with the regression coefficients greater than 0.99. The intra- and inter-day coefficients of variation for the analytes were ≤11.0% and all the biases were less than 8.3%. The method has been successfully applied to the quantification of melphalan and its metabolites in clinical plasma samples obtained from hematopoietic stem cell transplantation patients who received a dose of melphalan for pre-transplant conditioning.

Proteome Coverage after Simultaneous Proteo-Metabolome Liquid-Liquid Extraction

Proteomics and metabolomics are essential in systems biology, and simultaneous proteo-metabolome liquid-liquid extraction (SPM-LLE) allows isolation of the metabolome and proteome from the same sample. Since the proteome is present as a pellet in SPM-LLE, it must be solubilized for quantitative proteomics. Solubilization and proteome extraction are critical factors in the information obtained at the proteome level. In this study, we investigated the performance of two surfactants (sodium deoxycholate (SDC), sodium dodecyl sulfate (SDS)) and urea in terms of proteome coverage and extraction efficiency of an interphase proteome pellet generated by methanol-chloroform based SPM-LLE. We also investigated how the performance differs when the proteome is extracted from the interphase pellet or by direct cell lysis. We quantified 12 lipids covering triglycerides and various phospholipid classes, and 25 polar metabolites covering central energy metabolism in chloroform and methanol extracts. Our study reveals that the proteome coverages between the two surfactants and urea for the SPM-LLE interphase pellet were similar, but the extraction efficiencies differed significantly. While SDS led to enrichment of basic proteins, which were mainly ribosomal and ribonuclear proteins, urea was the most efficient extraction agent for simultaneous proteo-metabolome analysis. The results of our study also show that the performance of surfactants for quantitative proteomics is better when the proteome is extracted through direct cell lysis rather than an interphase pellet. In contrast, the performance of urea for quantitative proteomics was significantly better when the proteome was extracted from an interphase pellet than by direct cell lysis. We demonstrated that urea is superior to surfactants for proteome extraction from SPM-LLE interphase pellets, with a particularly good performance for the extraction of proteins associated with metabolic pathways. Data are available via ProteomeXchange with identifier PXD027338.

Trends in metabolic signaling pathways of tumor drug resistance: A scientometric analysis

Background

Cancer chemotherapy resistance is one of the most critical obstacles in cancer therapy. Since Warburg O first observed alterations in cancer metabolism in the 1950s, people gradually found tumor metabolism pathways play a fundamental role in regulating the response to chemotherapeutic drugs, and the attempts of targeting tumor energetics have shown promising preclinical outcomes in recent years. This study aimed to summarize the knowledge structure and identify emerging trends and potential hotspots in metabolic signaling pathways of tumor drug resistance research.

Methods

Publications related to metabolic signaling pathways of tumor drug resistance published from 1992 to 2022 were retrieved from the Web of Science Core Collection database. The document type was set to articles or reviews with language restriction to English. Two different scientometric software including Citespace and VOS viewer were used to conduct this scientometric analysis.

Results

A total of 2,537 publications including 1,704 articles and 833 reviews were retrieved in the final analysis. The USA made the most contributions to this field. The leading institution was the University of Texas MD Anderson Cancer Center. Avan A was the most productive author, and Hanahan D was the key researcher with the most co-citations, but there is no leader in this field yet. Cancers was the most influential academic journal, and Oncology was the most popular research field. Based on keywords occurrence analysis, these selected keywords could be roughly divided into five main topics: cluster 1 (study of cancer cell apoptosis pathway); cluster 2 (study of resistance mechanisms of different cancer types); cluster 3 (study of cancer stem cells); cluster 4 (study of tumor oxidative stress and inflammation signaling pathways); and cluster 5 (study of autophagy). The keywords burst detection identified several keywords as new research hotspots, including “tumor microenvironment,” “invasion,” and “target”.

Conclusion

Tumor metabolic reprogramming of drug resistance research is advancing rapidly. This study serves as a starting point, providing a thorough overview, the development landscape, and future opportunities in this field.

Mitochondrial metabolic determinants of multiple myeloma growth, survival, and therapy efficacy

Multiple myeloma (MM) is a plasma cell dyscrasia characterized by the clonal proliferation of antibody producing plasma cells. Despite the use of next generation proteasome inhibitors (PI), immunomodulatory agents (IMiDs) and immunotherapy, the development of therapy refractory disease is common, with approximately 20% of MM patients succumbing to aggressive treatment-refractory disease within 2 years of diagnosis. A large emphasis is placed on understanding inter/intra-tumoral genetic, epigenetic and transcriptomic changes contributing to relapsed/refractory disease, however, the contribution of cellular metabolism and intrinsic/extrinsic metabolites to therapy sensitivity and resistance mechanisms is less well understood. Cancer cells depend on specific metabolites for bioenergetics, duplication of biomass and redox homeostasis for growth, proliferation, and survival. Cancer therapy, importantly, largely relies on targeting cellular growth, proliferation, and survival. Thus, understanding the metabolic changes intersecting with a drug's mechanism of action can inform us of methods to elicit deeper responses and prevent acquired resistance. Knowledge of the Warburg effect and elevated aerobic glycolysis in cancer cells, including MM, has allowed us to capitalize on this phenomenon for diagnostics and prognostics. The demonstration that mitochondria play critical roles in cancer development, progression, and therapy sensitivity despite the inherent preference of cancer cells to engage aerobic glycolysis has re-invigorated deeper inquiry into how mitochondrial metabolism regulates tumor biology and therapy efficacy. Mitochondria are the sole source for coupled respiration mediated ATP synthesis and a key source for the anabolic synthesis of amino acids and reducing equivalents. Beyond their core metabolic activities, mitochondria facilitate apoptotic cell death, impact the activation of the cytosolic integrated response to stress, and through nuclear and cytosolic retrograde crosstalk maintain cell fitness and survival. Here, we hope to shed light on key mitochondrial functions that shape MM development and therapy sensitivity.

Metabolic Vulnerabilities in Multiple Myeloma

Multiple myeloma (MM) remains an incurable malignancy with eventual emergence of refractory disease. Metabolic shifts, which ensure the availability of sufficient energy to support hyperproliferation of malignant cells, are a hallmark of cancer. Deregulated metabolic pathways have implications for the tumor microenvironment, immune cell function, prognostic significance in MM and anti-myeloma drug resistance. Herein, we summarize recent findings on metabolic abnormalities in MM and clinical implications driven by metabolism that may consequently inspire novel therapeutic interventions. We highlight some future perspectives on metabolism in MM and propose potential targets that might revolutionize the field.

Metabolic Disorders in Multiple Myeloma

Multiple myeloma (MM) is the second most common hematological malignancy and is attributed to monoclonal proliferation of plasma cells in the bone marrow. Cancer cells including myeloma cells deregulate metabolic pathways to ensure proliferation, growth, survival and avoid immune surveillance, with glycolysis and glutaminolysis being the most identified procedures involved. These disorders are considered a hallmark of cancer and the alterations performed ensure that enough energy is available for rapid cell proliferation. An association between metabolic syndrome, inflammatory cytokinesand incidence of MM has been also described, while the use of metformin and statins has been identified as a positive prognostic factor for the disease course. In this review, we aim to present the metabolic disorders that occur in multiple myeloma, the potential defects on the immune system and the potential advantage of targeting the dysregulated pathways in order to enhance antitumor therapeutics.