Targeting lipid metabolism in multiple myeloma cells: rational development of a synergistic strategy with proteasome inhibitors

Synthesis and functional screening of novel inhibitors targeting the HDAC6 zinc finger ubiquitin-binding domain

Histone deacetylase 6 (HDAC6) is a promising target for treating neurodegenerative disorders, several cancer types and viral infections. Unique among HDACs, the HDAC6 isoform possesses a zinc finger ubiquitin-binding domain (UBD) crucial for managing misfolded protein aggregates and facilitating viral infection. HDAC6 binds aggregated polyubiquitinated proteins through its UBD, mediating their transport to the aggresome and subsequent removal via autophagy. Despite the importance of the UBD in proteostasis and viral infection, its pharmacological inhibition has been minimally explored thus far, with research largely focused on the deacetylase domain. We synthesized a diverse library of new compounds designed to target the HDAC6-UBD, termed HZUBi, with varied core structures including quinazolinone, oxindole and tetrahydrothiopyrano[4,3-b]indole, aimed at enhancing UBD interaction and extending into the side pocket. New structure-activity relationships were established, computational docking and molecular dynamics studies were performed and the functional impact of selected inhibitors was assessed in the context of multiple myeloma and viral infection. Several new HZUBi could displace a ubiquitin peptide from HDAC6-UBD in a differential manner, although to a lower extent than the literature reference compound HZUBi-3e. Despite exhibiting in vitro target engagement, neither HZUBi-3e nor its ester prodrug HZUBi-1e enhanced proteasome inhibitor-mediated multiple myeloma cell killing. Finally, none of the screened HZUBi triggered anti-viral activity.

Lipid levels and multiple myeloma risk: insights from Meta-analysis and mendelian randomization

BACKGROUND

Lipid levels have been suggset to be correlated with multiple myeloma (MM) risk, though causality remains unconfirmed. To explore this further, a detailed study combining meta-analysis and Mendelian randomization (MR) was conducted.

METHODS

Literature searches were performed on PubMed and Embase; summary data for plasma lipid traits were extracted from the IEU and MM data from the FinnGen database. Meta-analysis and MR were utilized to analyze the link of lipids with MM risk, including mediator MR to identify potential mediators. The study was conducted in accordance with PRISMA and STROBE-MR guidelines.

RESULTS

Observational studies analyzed through meta-analysis showed that elevated levels of LDL, HDL, total cholesterol (TC), and triglycerides correlate with a lower risk of MM, with HRs of 0.73, 0.59, 0.60, and 0.84, respectively. MR analysis confirmed a potential causal link of triglyceride with a reduced MM risk (OR: 0.67, 95% CI: 0.46-0.98), independent of BMI. Mediation analysis pointed to X-11,423-O-sulfo-L-tyrosine and neuropilin-2 as potential mediators.

CONCLUSIONS

The findings suggest that higher lipid levels (LDL, HDL, TC, and triglycerides) are linked with a reduced MM risk, and higher triglyceride levels are causally associated with a reduced MM risk. This suggests new avenues for therapeutic interventions targeting MM.

Identification of lipid metabolism-related gene signature in the bone marrow microenvironment of multiple myelomas through deep analysis of transcriptomic data

Dysregulated lipid metabolism in the bone marrow microenvironment (BMM) plays a vital role in multiple myeloma (MM) development, progression, and drug resistance. However, the exact mechanism by which lipid metabolism impacts the BMM, promotes tumorigenesis, and triggers drug resistance remains to be fully elucidated.By analyzing the bulk sequencing and single-cell sequencing data of MM patients, we identified lipid metabolism-related genes differential expression significantly associated with MM prognosis, referred to as LMRPgenes. Using a cohort of ten machine learning algorithms and 117 combinations, LMRPgenes predictive models were constructed. Further exploration of the effects of the model risk score (RS) on the survival status, immune status of patients with BMM, and response to immunotherapy was conducted. The study also facilitated the identification of personalized therapeutic strategies targeting specified risk categories within patient cohorts.Analysis of the scRNA-seq data revealed increased lipid metabolism-related gene enrichment scores (LMESs) in erythroblasts and progenitor, malignant, and Tprolif cells but decreased LMESs in lymphocytes. LMESs were also strongly correlated with most of the 50 hallmark pathways within these cell populations. An elevated malignant cell ratio and reduced lymphocytes were observed in the high LMES group. Moreover, the LMRPgenes predictive model, consisting of 14 genes, showed great predictive power. The risk score emerged as an independent indicator of poor outcomes. Inverse relationships between the RS and immune status were noted, and a high RS was associated with impaired immunotherapy responses. Drug sensitivity assays indicated the effectiveness of bortezomib, buparlisib, dinaciclib, staurosporine, rapamycin, and MST-312 in the high-RS group, suggesting their potential for treating patients with high-RS values and poor response to immunotherapy. Ultimately, upon verification via qRT-PCR, we observed a significant upregulation of ACBD6 in NDMM group compared to the control group.Our research enhances the knowledge base regarding the association between lipid metabolism-related genes (LMRGs) and the BMM in MM patients, offering substantive insights into the mechanistic effects of the BMM mediated by LMRGs.

High-density lipoprotein cholesterol and multiple myeloma: A systematic review and meta-analysis

Background and aims

To systematically investigate all relevant evidence on the association between high-density lipoprotein cholesterol (HDL-C) and multiple myeloma (MM).

Methods

We searched PubMed and Cochrane library databases (up to 20 September 2022) for studies with evidence on HDL-C in patients with MM. A qualitative synthesis of published prospective and retrospective studies for the role of HDL-C and other lipid profile parameters in MM was performed. Additionally, a meta-analysis on HDL-C mean differences (MD) between MM cases and controls was performed.

Results

Fourteen studies (3 prospective, 11 retrospective) including 895 MM patients were eligible for this systematic review. Ten studies compared HDL-C levels in MM patients with healthy controls. In these 10 studies (n = 17,213), pooled analyses showed that MM patients had significantly lower HDL-C levels compared to healthy controls (MD: -13.07 mg/dl, 95% CI: -17.83, -8.32, p < 0.00001). Regarding secondary endpoints, total cholesterol (TC) (MD: -22.19 mg/dl, 95% CI: -39.08, -5.30) and apolipoprotein A-I (apoA-I) (-40.20 mg/dl, 95% CI: -55.00, -25.39) demonstrated significant decreases, while differences in low-density lipoprotein cholesterol (LDL-C) (MD: -11.33 mg/dl, 95% CI: -36.95, 14.30) and triglycerides (MD: 9.93 mg/dl, 95% CI: -3.40, 23.26) were not shown to be significant.

Conclusions

HDL-C, as well as TC and apoA-I, levels are significantly decreased in MM. Hence, lipid profile parameters should be taken into account when assessing such patients.

Lipid metabolic vulnerabilities of multiple myeloma

Multiple myeloma (MM) is the second most common hematological malignancy worldwide, characterized by abnormal proliferation of malignant plasma cells within a tumor-permissive bone marrow microenvironment. Metabolic dysfunctions are emerging as key determinants in the pathobiology of MM. In this review, we highlight the metabolic features of MM, showing how alterations in various lipid pathways, mainly involving fatty acids, cholesterol and sphingolipids, affect the growth, survival and drug responsiveness of MM cells, as well as their cross-talk with other cellular components of the tumor microenvironment. These findings will provide a new path to understanding the mechanisms underlying how lipid vulnerabilities may arise and affect the phenotype of malignant plasma cells, highlighting novel druggable pathways with a significant impact on the management of MM.

Metabolic changes underlying drug resistance in the multiple myeloma tumor microenvironment

Multiple myeloma (MM) is characterized by the clonal expansion of malignant plasma cells in the bone marrow (BM). MM remains an incurable disease, with the majority of patients experiencing multiple relapses from different drugs. The MM tumor microenvironment (TME) and in particular bone-marrow stromal cells (BMSCs) play a crucial role in the development of drug resistance. Metabolic reprogramming is emerging as a hallmark of cancer that can potentially be exploited for cancer treatment. Recent studies show that metabolism is further adjusted in MM cells during the development of drug resistance. However, little is known about the role of BMSCs in inducing metabolic changes that are associated with drug resistance. In this Perspective, we summarize current knowledge concerning the metabolic reprogramming of MM, with a focus on those changes associated with drug resistance to the proteasome inhibitor Bortezomib (BTZ). In addition, we present proof-of-concept fluxomics (glucose isotope-tracing) and Seahorse data to show that co-culture of MM cells with BMSCs skews the metabolic phenotype of MM cells towards a drug-resistant phenotype, with increased oxidative phosphorylation (OXPHOS), serine synthesis pathway (SSP), TCA cycle and glutathione (GSH) synthesis. Given the crucial role of BMSCs in conveying drug resistance, insights into the metabolic interaction between MM and BMSCs may ultimately aid in the identification of novel metabolic targets that can be exploited for therapy.

Metabolic Alterations in Multiple Myeloma: From Oncogenesis to Proteasome Inhibitor Resistance

Despite significant improvements in treatment strategies over the past couple of decades, multiple myeloma (MM) remains an incurable disease due to the development of drug resistance. Metabolic reprogramming is a key feature of cancer cells, including MM, and acts to fuel increased proliferation, create a permissive tumour microenvironment, and promote drug resistance. This review presents an overview of the key metabolic adaptations that occur in MM pathogenesis and in the development of resistance to proteasome inhibitors, the backbone of current MM therapy, and considers the potential for therapeutic targeting of key metabolic pathways to improve outcomes.

Obesity and myeloma: Clinical and mechanistic contributions to disease progression

Obesity and obesogenic behaviors are positively associated with both monoclonal gammopathy of unknown significance (MGUS) and multiple myeloma (MM). As the only known modifiable risk factor, this association has emerged as a new potential target for MM prevention, but little is known about the mechanistic relationship of body weight with MM progression. Here we summarize epidemiological correlations between weight, body composition, and the various stages of myeloma disease progression and treatments, as well as the current understanding of the molecular contributions of obesity-induced changes in myeloma cell phenotype and signaling. Finally, we outline groundwork for the future characterization of the relationship between body weight patterns, the bone marrow microenvironment, and MM pathogenesis in animal models, which have the potential to impact our understanding of disease pathogenesis and inform MM prevention messages.

Vitamin D deficiency linked to abnormal bone and lipid metabolism predicts high-risk multiple myeloma with poorer prognosis

Purpose

Vitamin D deficiency is frequent in patients with multiple myeloma (MM), however, its prognostic relevance in MM was rather inconclusive. We first investigated the association of vitamin D deficiency with abnormal bone and lipid metabolism in newly diagnosed multiple myeloma (NDMM), and next assessed the impact of serum ratio of vitamin D to carboxy-terminal telopeptide of type I collagen (β-CTX) on progression-free survival (PFS) and overall free survival (OS) in patients with NDMM.

Methods

The data of 431 consecutive patients with NDMM at Beijing Jishuitan Hospital from September 2013 to December 2022 were collected and retrospectively reviewed through our electronic medical record system. The measurement of 25-hydroxyvitamin D in the blood is an indicator of an individual's overall vitamin D status.

Results

The serum levels of vitamin D were negatively correlated with β-CTX in NDMM patients. Of note, positive correlation between vitamin D and cholesterol levels in the serum was found in this study. The cohort (n = 431) was divided into two groups based on the serum ratio of vitamin D to β-CTX. Compared to the group with a higher vitamin D to β-CTX ratio, the group with a lower vitamin D to β-CTX ratio (n = 257, 60%) exhibited hypocholesterolemia, inferior PFS and OS, along with increased cases of ISS stage-III and R-ISS stage-III, a higher number of plasma cells in the bone marrow, and elevated serum calcium levels. Consistent with this, multivariate analysis confirmed that the vitamin D to β-CTX ratio was an independent unfavorable indicator for survival in NDMM patients.

Conclusion

Our data demonstrated the ratio of vitamin D to β-CTX in the serum is a unique biomarker for NDMM patients to identify the high-risk cases with poor prognosis, which is superior to vitamin D itself for predicting PFS and OS in NDMM. Also, it is worth mentioning that our data on the connection between vitamin D deficiency and hypocholesterolemia might help clarify novel mechanistic aspects of myeloma development.

MSC Senescence-Related Genes Are Associated with Myeloma Prognosis and Lipid Metabolism-Mediated Resistance to Proteasome Inhibitors

BACKGROUND

Complex carcinogenic mechanisms and the existence of tumour heterogeneity in multiple myeloma (MM) prevent the most commonly used staging system from effectively interpreting the prognosis of patients. Since the microenvironment plays an important role in driving tumour development and MM occurs most often in middle-aged and elderly patients, we hypothesize that ageing of bone marrow mesenchymal stem cells (BM-MSCs) may be associated with the progression of MM.

METHODS

In this study, we collected the transcriptome data on MM from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Differentially expressed genes in both senescent MSCs and MM tumour cells were considered relevant damaged genes. GO and KEGG analyses were applied for functional evaluation. A PPI network was constructed to identify hub genes. Subsequently, we studied the damaged genes that affected the prognosis of MM. Least absolute shrinkage and selection operator (lasso) regression was used to identify the most important features, and a risk model was created. The reliability of the risk model was evaluated with the other 3 GEO validation cohorts. In addition, ROC analysis was used to evaluate the novel risk model. An analysis of immune checkpoint-related genes, tumour immune dysfunction and exclusion (TIDE), and immunophenotypic scoring (IPS) were performed to assess the immune status of risk groups. pRRophetic was utilized to predict the sensitivity to administration of chemotherapeutic agents.

RESULTS

We identified that MAPK, PI3K, and p53 signalling pathways were activated in both senescent MSCs and tumour cells, and we also located hub genes. In addition, we constructed a 14-gene prognostic risk model, which was analysed with the ROC and validated in different datasets. Further analysis revealed significant differences in predicted risk values across the International Staging System (ISS) stage, sex, and 1q21 copy number. A high-risk group with higher immunogenicity was predicted to have low proteasome inhibitor sensitivity and respond poorly to immunotherapy. Lipid metabolism pathways were found to be significantly different between high-risk and low-risk groups. A nomogram was created by combining clinical data, and the optimization model was further improved. Finally, real-time qPCR was used to validate two bortezomib-resistant myeloma cell lines, and the test confirmed that 10 genes were detected to be expressed in resistant cell lines with the same trend as in the high-risk cohort compared to nonresistant cells.

CONCLUSION

Fourteen genes related to ageing in BM-MSCs were associated with the prognosis of MM, and by combining this genotypic information with clinical factors, a promising clinical prognostic model was established.

Looking into Endoplasmic Reticulum Stress: The Key to Drug-Resistance of Multiple Myeloma?

Multiple myeloma (MM) is the second most common hematologic malignancy, resulting from the clonal proliferation of malignant plasma cells within the bone marrow. Despite significant advances that have been made with novel drugs over the past two decades, MM patients often develop therapy resistance, especially to bortezomib, the first-in-class proteasome inhibitor that was approved for treatment of MM. As highly secretory monoclonal protein-producing cells, MM cells are characterized by uploaded endoplasmic reticulum stress (ERS), and rely heavily on the ERS response for survival. Great efforts have been made to illustrate how MM cells adapt to therapeutic stresses through modulating the ERS response. In this review, we summarize current knowledge on the mechanisms by which ERS response pathways influence MM cell fate and response to treatment. Moreover, based on promising results obtained in preclinical studies, we discuss the prospect of applying ERS modulators to overcome drug resistance in MM.

Mechanistic Studies and a Retrospective Cohort Study: The Interaction between PPAR Agonists and Immunomodulatory Agents in Multiple Myeloma

Our previous study demonstrated that peroxisome proliferator-activated receptor (PPAR) agonists downregulated cereblon (CRBN) expression and reduced the anti-myeloma activity of lenalidomide in vitro and in vivo. We aimed to determine whether DNA methylation and protein degradation contribute to the effects of PPAR agonists. CRBN promoter methylation status was detected using methylation-specific polymerase chain reaction. The CRBN protein degradation rate was measured using a cycloheximide chase assay. Metabolomic analysis was performed in multiple myeloma (MM) cells treated with PPAR agonists and/or lenalidomide. Our retrospective study determined the effect of co-administration of PPAR agonists with immunomodulatory drugs on the outcomes of patients with MM. CpG islands of the CRBN promoter region became highly methylated upon treatment with PPAR agonists, whereas treatment with PPAR antagonists resulted in unmethylation. The CRBN protein was rapidly degraded after treatment with PPAR agonists. Lenalidomide and fenofibrate showed opposite effects on acylcarnitines and amino acids. Co-administration of immunomodulatory drugs and PPAR agonists was associated with inferior treatment responses and poor survival. Our study provides the first evidence that PPAR agonists reduce CRBN expression through various mechanisms including inducing methylation of CRBN promoter CpG island, enhancing CRBN protein degradation, and affecting metabolomics of MM cells.

Novel lipometabolism biomarker for chemotherapy and immunotherapy response in breast cancer

Emerging proof shows that abnormal lipometabolism affects invasion, metastasis, stemness and tumor microenvironment in carcinoma cells. However, molecular markers related to lipometabolism have not been further established in breast cancer. In addition, numerous studies have been conducted to screen for prognostic features of breast cancer only with RNA sequencing profiles. Currently, there is no comprehensive analysis of multiomics data to extract better biomarkers. Therefore, we have downloaded the transcriptome, single nucleotide mutation and copy number variation dataset for breast cancer from the TCGA database, and constructed a riskScore of twelve genes by LASSO regression analysis. Patients with breast cancer were categorized into high and low risk groups based on the median riskScore. The high-risk group had a worse prognosis than the low-risk group. Next, we have observed the mutated frequencies and the copy number variation frequencies of twelve lipid metabolism related genes LMRGs and analyzed the association of copy number variation and riskScore with OS. Meanwhile, the ESTIMATE and CIBERSORT algorithms assessed tumor immune fraction and degree of immune cell infiltration. In immunotherapy, it is found that high-risk patients have better efficacy in TCIA analysis and the TIDE algorithm. Furthermore, the effectiveness of six common chemotherapy drugs was estimated. At last, high-risk patients were estimated to be sensitive to six chemotherapeutic agents and six small molecule drug candidates. Together, LMRGs could be utilized as a de novo tumor biomarker to anticipate better the prognosis of breast cancer patients and the therapeutic efficacy of immunotherapy and chemotherapy.

Metabolic cross-talk within the bone marrow milieu: focus on multiple myeloma

Cancer cells are well-known for their capacity to adapt their metabolism to their increasing energy demands which is necessary for tumor progression. This is no different for Multiple Myeloma (MM), a hematological cancer which develops in the bone marrow (BM), whereby the malignant plasma cells accumulate and impair normal BM functions. It has become clear that the hypoxic BM environment contributes to metabolic rewiring of the MM cells, including changes in metabolite levels, increased/decreased activity of metabolic enzymes and metabolic shifts. These adaptations will lead to a pro-tumoral environment stimulating MM growth and drug resistance In this review, we discuss the identified metabolic changes in MM and the BM microenvironment and summarize how these identified changes have been targeted (by inhibitors, genetic approaches or deprivation studies) in order to block MM progression and survival.

Bone Marrow Stroma-Induced Transcriptome and Regulome Signatures of Multiple Myeloma

Multiple myeloma (MM) is a hematological cancer with inevitable drug resistance. MM cells interacting with bone marrow stromal cells (BMSCs) undergo substantial changes in the transcriptome and develop de novo multi-drug resistance. As a critical component in transcriptional regulation, how the chromatin landscape is transformed in MM cells exposed to BMSCs and contributes to the transcriptional response to BMSCs remains elusive. We profiled the transcriptome and regulome for MM cells using a transwell coculture system with BMSCs. The transcriptome and regulome of MM cells from the upper transwell resembled MM cells that coexisted with BMSCs from the lower chamber but were distinctive to monoculture. BMSC-induced genes were enriched in the JAK2/STAT3 signaling pathway, unfolded protein stress, signatures of early plasma cells, and response to proteasome inhibitors. Genes with increasing accessibility at multiple regulatory sites were preferentially induced by BMSCs; these genes were enriched in functions linked to responses to drugs and unfavorable clinic outcomes. We proposed JUNB and ATF4::CEBPβ as candidate transcription factors (TFs) that modulate the BMSC-induced transformation of the regulome linked to the transcriptional response. Together, we characterized the BMSC-induced transcriptome and regulome signatures of MM cells to facilitate research on epigenetic mechanisms of BMSC-induced multi-drug resistance in MM.

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.