The Association between Metabolic Syndrome and Multiple Myeloma

Effects of methane emissions on multiple myeloma-related mortality rates: A World Health Organization perspective

In this research, it was aimed to evaluate effects of methane emissions on multiple myeloma related mortality rates. Two countries in Europe (Germany and Netherlands) and 1 country for each region (Turkey, USA, Brazil, Egypt, and Australia) were selected within The World Health Organization Database. Multiple myeloma mortality rates of countries between 2009 and 2019 were used as dependent variable of the research. Methane emission level and agriculture methane levels of countries were used as independent variables from The World Bank Database. Current health expenditure and healthy life expectancy were used as controlling variables. Multiple myeloma-related mortality rate was the highest in the USA, followed by Germany, Brazil, Turkey, Australia, Netherlands, and Egypt. Difference analysis results were significant (P < .05). Methane and agriculture methane emissions were the highest in the USA. Multiple myeloma mortality was positively correlated with methane emissions (R = 0.504; P < .01), agricultural methane emissions (R = 0.705; P < .01), and current health expenditure (R = 0.528; P < .01). According to year and country controlled correlation analysis results, multiple myeloma mortality (MMM) was positively correlated with methane emissions (R = 0.889; P < .01), agricultural methane emissions (R = 0.495; P < .01), and current health expenditure (R = 0.704; P < .01). Methane emission (B = 0.01; P < .05), Germany (B = 9010.81; P < .01), the USA (B = 26516.77; P < .01), and Brazil (B = 4886.14; P < .01) had significant effect on MMM. Nonagricultural methane production has an increasing effect on MMM. Therefore, by looking at the differences between agricultural methane emissions and general methane emissions, studies can be conducted that allow for more effective global comparisons.

Targeting myeloma metabolism: How abnormal metabolism contributes to multiple myeloma progression and resistance to proteasome inhibitors

Multiple myeloma is a hematological malignancy that has evolved from antibody-secreting B lymphocytes. Like other types of cancers, myeloma cells have acquired functional capabilities which are referred to as "Hallmarks of Cancer", and one of their most important features is the metabolic disorders. Due to the high secretory load of the MM cells, the first-line medicine proteasome inhibitors have found their pronounced effects in MM cells for blocking the degradation of misfolded proteins, leading to their accumulation in the ER and overwhelming ER stress. Moreover, proteasome inhibitors have been reported to be effective in myeloma by targeting glucose, lipid, amino acid metabolism of MM cells. In this review, we have described the abnormal metabolism of the three major nutrients, such as glucose, lipid and amino acids, which participate in the cellular functions. We have described their roles in myeloma progression, how they could be exploited for therapeutic purposes, and current therapeutic strategies targeting these metabolites, hoping to uncover potential novel therapeutic targets and promote the development of future therapeutic approaches.

Advances in research on potential inhibitors of multiple myeloma

Multiple myeloma (MM) is a common hematological malignancy. Although recent clinical applications of immunomodulatory drugs, proteasome inhibitors and CD38-targeting antibodies have significantly improved the outcome of MM patient with increased survival, the incidence of drug resistance and severe treatment-related complications is gradually on the rise. This review article summarizes the characteristics and clinical investigations of several MM drugs in clinical trials, including their structures, mechanisms of action, structure-activity relationships, and clinical study progress. Furthermore, the application potentials of the drugs that have not yet entered clinical trials are also reviewed. The review also outlines the future directions of MM drug development.

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.

Thiazolidinedione Use Is Associated with a Borderline Lower Risk of Multiple Myeloma and a Significantly Lower Risk of Death in Patients with Type 2 Diabetes Mellitus in Taiwan

BACKGROUND

Thiazolidinedione (TZD) exerts anti-proliferative effects on multiple myeloma (MM) cells. However, there has not been any human study investigating the risk of MM associated with TZD use.

METHODS

We used Taiwan's National Health Insurance database to identify 423,949 patients who had been newly diagnosed with diabetes mellitus between 1999 and 2005. After excluding ineligible patients, 86,999 pairs of patients with and without the use of TZD (rosiglitazone or pioglitazone) that had been matched based on propensity score were selected for a follow-up for MM until 31 December 2011. The hazard ratios for MM were estimated using Cox regression and weighted using a propensity score.

RESULTS

After a median follow-up of 4.6 years and 4.7 years in ever users and never users of TZD, 32 and 47 cases were diagnosed with MM, respectively. A 35% lower risk (though not statistically significant) was observed among ever users (hazard ratio 0.652, 95% confidence interval: 0.416-1.023, p = 0.0625). When ever users were divided by the median (15 months) cumulative duration of TZD therapy, the hazard ratios (95% confidence interval) for the lower and upper medians were 0.706 (0.394-1.264) and 0.603 (0.346-1.051), respectively. When treated as a continuous variable, the hazard ratio for every 1-month increment of the cumulative duration was 0.980 (95% confidence interval: 0.963-0.997, p = 0.0185). In the age subgroup analysis, a significantly lower risk could be seen in the older age subgroup of ≥65 years (hazard ratio 0.550, 95% confidence interval: 0.305-0.992, p = 0.0468). Additional analyses suggested that there were no interactions between TZD and some medications and between TZD and some clinical diagnoses, and that the use of TZD as a preventive drug for MM might not be cost-effective because a number-needed-to-treat of 5800 was too large. Survival analyses suggested that ever users had a significantly lower risk of death when all patients were analyzed (hazard ratio: 0.84, 95% confidence interval: 0.81-0.87, p < 0.0001 via a log-rank test) or when patients who developed MM were analyzed (hazard ratio: 0.40, 95% confidence interval: 0.19-0.86, p = 0.0153 via a log-rank test).

CONCLUSIONS

In Taiwanese patients with type 2 diabetes mellitus, TZD use is associated with a borderline lower risk of MM, which is more remarkable in patients aged ≥65 years. Because of the low incidence of MM, the use of TZD for the prevention of MM may not be cost-effective. Patients who have been treated with TZD may have a survival advantage. Future research is required to confirm the findings.

Action Mechanism of Metformin and Its Application in Hematological Malignancy Treatments: A Review

Hematologic malignancies (HMs) mainly include acute and chronic leukemia, lymphoma, myeloma and other heterogeneous tumors that seriously threaten human life and health. The common effective treatments are radiotherapy, chemotherapy and hematopoietic stem cell transplantation (HSCT), which have limited options and are prone to tumor recurrence and (or) drug resistance. Metformin is the first-line drug for the treatment of type 2 diabetes (T2DM). Recently, studies identified the potential anti-cancer ability of metformin in both T2DM patients and patients that are non-diabetic. The latest epidemiological and preclinical studies suggested a potential benefit of metformin in the prevention and treatment of patients with HM. The mechanism may involve the activation of the adenosine monophosphate-activated protein kinase (AMPK) signaling pathway by metformin as well as other AMPK-independent pathways to exert anti-cancer properties. In addition, combining current conventional anti-cancer drugs with metformin may improve the efficacy and reduce adverse drug reactions. Therefore, metformin can also be used as an adjuvant therapeutic agent for HM. This paper highlights the anti-hyperglycemic effects and potential anti-cancer effects of metformin, and also compiles the in vitro and clinical trials of metformin as an anti-cancer and chemosensitizing agent for the treatment of HM. The need for future research on the use of metformin in the treatment of HM is indicated.

Association between metabolic obesity phenotypes and multiple myeloma hospitalization burden: A national retrospective study

Background & purpose

Obesity and metabolic disorders were associated with increased risk of MM, a disease characterized by high risk of relapsing and require frequent hospitalizations. In this study, we conducted a retrospective cohort study to explore the association of metabolic obesity phenotypes with the readmission risk of MM.

Patients & methods

We analyzed 34,852 patients diagnosed with MM from the Nationwide Readmissions Database (NRD), a nationally representative database from US. Hospitalization diagnosis of patients were obtained using ICD-10 diagnosis codes. According to obesity and metabolic status, the population was divided into four phenotypes: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The patients with different phenotypes were observed for hospital readmission at days 30-day, 60-day, 90-day and 180-day. Multivariate cox regression model was used to estimate the relationship between obesity metabolic phenotypes and readmissions risk.

Results

There were 5,400 (15.5%), 7,255 (22.4%), 8,025 (27.0%) and 7,839 (35.6%) unplanned readmissions within 30-day, 60-day, 90-day and 180-day follow-up, respectively. For 90-day and 180-day follow-up, compared with patients with the MHNO phenotype, those with metabolic unhealthy phenotypes MUNO (90-day: P = 0.004; 180-day: P = < 0.001) and MUO (90-day: P = 0.049; 180-day: P = 0.004) showed higher risk of readmission, while patients with only obesity phenotypes MHO (90-day: P = 0.170; 180-day: P = 0.090) experienced no higher risk. However, similar associations were not observed for 30-day and 60-day. Further analysis in 90-day follow-up revealed that, readmission risk elevated with the increase of the combined factor numbers, with aHR of 1.068 (CI: 1.002-1.137, P = 0.043, with one metabolic risk factor), 1.109 (CI: 1.038-1.184, P = 0.002, with two metabolic risk factors) and 1.125 (95% CI: 1.04-1.216, P = 0.003, with three metabolic risk factors), respectively.

Conclusion

Metabolic disorders, rather than obesity, were independently associated with higher readmission risk in patients with MM, whereas the risk elevated with the increase of the number of combined metabolic factors. However, the effect of metabolic disorders on MM readmission seems to be time-dependent. For MM patient combined with metabolic disorders, more attention should be paid to advance directives to reduce readmission rate and hospitalization burden.

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.

Effects of lipemia on capillary serum protein electrophoresis in native ultra-lipemic material and intravenous lipid emulsion added sera

OBJECTIVES

This study aims to investigate the effect of natural ultralipemic material (NULM) and intravenous lipid emulsion (IVLE) on capillary serum protein electrophoresis (SPEP).

METHODS

NULM material was prepared from leftover patients' lipemic serum sample (triglyceride concentration >2,000 mg/dL) pool by a refrigerated high-speed centrifuge, and IVLE Omegaven lipid emulsion (30%) was used. Serum pools for interference study were prepared from patient samples for which serum protein electrophoresis was studied as Normal SPEP and M Peak SPEP. For both types of lipemia (DULM and IVLE), five pools with triglyceride concentrations of ∼4.52 mmol/L, ∼7.91 mmol/L, ∼14.69 mmol/L, ∼21.47 mmol/L, and ∼28.25 mmol/L were prepared. SPEP was studied in each pool with Sebia Capillarys Minicap. A repeated measure ANOVA test was used to determine the difference between the pools, and interferograms were used to evaluate the interference effect.

RESULTS

Interference was not detected in IVLE added Normal SPEP and M Peak SPEP pools, either % or concentrations of fractions. In NULM-added Normal SPEP and M Peak SPEP pools, significant positive interference in albumin % (p=0.002 and p<0.001 respectively) and significant negative interference in gamma% (p<0.001 and p=0.005 respectively) and M protein peak (p=0.002) fractions were detected. However, significant positive interference was seen only for albumin concentration fractions (p<0.001 for both pools).

CONCLUSIONS

It is vital to use NULM instead of IVLE solutions in lipemia interference studies for all laboratory tests, including CZE SPEP. The fractions concentration values calculated with the total protein concentration should be used for evaluating SPEP results.

The Risk of Multiple Myeloma Is Reduced in Metformin Initiators: A Retrospective Cohort Study in Taiwanese Patients with Type 2 Diabetes Mellitus

BACKGROUND

Whether metformin might reduce the risk of multiple myeloma (MM) has not been extensively researched in humans.

METHODS

The study subjects were enrolled from the reimbursement database of Taiwan's National Health Insurance. A total of 739,553 patients who had a new diagnosis of type 2 diabetes mellitus during 1999-2009 were identified. They were categorized as metformin initiators (metformin (+)) and non-metformin initiators (metformin (-)) based on the prescriptions of antidiabetic drugs that included metformin and did not include metformin within the initial 12 months, respectively. MM incidence was calculated after the initial 12 months of treatment group assignment until 31 December 2011. Hazard ratios based on intention-to-treat (ITT) and per-protocol (PP) approaches were estimated by Cox regression weighted by propensity scores.

RESULTS

In the ITT analyses, the respective incidence rates for 497,248 metformin (+) and 242,305 metformin (-) were 9.97 and 14.33 per 100,000 person-years. The hazard ratio that compared metformin (+) to metformin (-) in the ITT analysis was 0.710 (95% confidence interval 0.593-0.850). In the PP analysis, the respective incidence rates were 5.14 and 13.98 per 100,000 person-years, and the hazard ratio was 0.355 (95% confidence interval, 0.270-0.466). The lower risk of MM among metformin (+) was supported by subgroup and sensitivity analyses.

CONCLUSIONS

Type 2 diabetes patients who are initiated with metformin treatment have a significantly lower risk of MM, especially when they adhere to metformin treatment.

Medication Adherence Among Adults With Comorbid Chronic Conditions Initiating Oral Anticancer Agent Therapy for Multiple Myeloma

PURPOSE:

Increased use of oral anticancer agents (OAAs) has empowered adults with multiple myeloma (MM) to manage their oncolytic therapy, but such a shift may result in issues with medication use, particularly among patients being concurrently treated for pre-existing, multiple chronic conditions.

METHODS:

This retrospective cohort study used 2013-2018 commercial and Medicare claims data to assess medication use in adults with MM. To be included, adults (18 years and older) must have been diagnosed with and had 2+ claims for an OAA, had continuous enrollment for 12 months before and after OAA initiation, and have been previously diagnosed with and had prescription fills for 2+ select chronic conditions. The proportion of days covered metric assessed medication adherence and was compared for 12 months before and after the OAA initiation by Wilcoxon signed-rank tests, McNemar's tests, and difference-in-differences models.

RESULTS:

The mean OAA adherence in the first year of therapy was 58.3% (standard deviation: 24.5) and 65.1% (standard deviation: 27.01) for commercial and Medicare patients, respectively. Adherence and the proportion adherent (proportion of days covered ≥ 80%) to comorbid therapies generally declined in the first year after OAA initiation. Changes in medication use were particularly noticeable among those on antihypertensive therapy: adjusted analyses uncovered a 2.5% (Medicare) and 5.2% (commercial) difference in adherence to these medications between those initially adherent and nonadherent to OAA therapy (both P < .05).

CONCLUSION:

Initiating OAA therapy in adults with MM may complicate an already complex treatment regimen, resulting in poor overall medication adherence in patients with multiple comorbid conditions.

Association between Cholesterol Level and the Risk of Hematologic Malignancy According to Menopausal Status: A Korean Nationwide Cohort Study

Recent studies have revealed the possible association between serum cholesterol levels and hematologic malignancy (HM). However, limited information is available about how reproductive factors interact with this association. Therefore, we investigated the roles of serum cholesterol in the risk of HM according to the menopausal status. We finally identified 1,189,806 premenopausal and 1,621,604 postmenopausal women who underwent a national health screening program in 2009 using data from the Korean National Health Insurance Service database. Overall, 5449 (0.19%) developed HM. Among postmenopausal women, the inverse associations were observed between total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) levels, and the risk of overall HM. In premenopausal women, the highest quartile of HDL-C was associated with a reduced risk of HM compared with the lowest quartile of HDL-C consistent with results in postmenopausal women (adjusted hazard ratio [aHR] 0.80, 95% confidence interval [CI] [0.68–0.95]), whereas the highest quartile of triglyceride (TG) showed an increased risk of HM compared to the lowest quartile of TG, (aHR 1.22, 95% CI [1.02,1.44]) only in premenopausal women. Our finding suggests that lipid profiles are differently associated with HM risk by menopausal status.

Metformin Induces Resistance of Cancer Cells to the Proteasome Inhibitor Bortezomib

The anti-diabetic drug metformin is currently tested for the treatment of hematological and solid cancers. Proteasome inhibitors, e.g., Bortezomib, are approved for the treatment of multiple myeloma and mantle cell lymphoma but are also studied for lung cancer therapy. We here analyzed the interaction of the two drugs in two cell lines, namely the mantle cell lymphoma Jeko-1 and the non-small-cell lung cancer (NSCLC) H1299 cells, using proliferation and survival assays, native-gel analysis for proteasome activity and assembly, and expression analysis of proteasome assembly factors. Our results demonstrate that metformin treatment induces resistance of cancer cells to the proteasome inhibitor Bortezomib by impairing the activity and assembly of the 26S proteasome complexes. These effects of metformin on proteasome inhibitor sensitivity in cancer cells are of potential relevance for patients that receive proteasome inhibitor therapy.

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.

Identification of Metabolism-Related Genes Influencing Prognosis of Multiple Myeloma Patients

Multiple myeloma (MM) is the second most commonly diagnosed hematological malignancy. Understanding the basic mechanisms of the metabolism in MM may lead to new therapies that benefit patients. We collected the gene expression profile data of GSE39754 and performed differential analysis. Furthermore, identify the candidate genes that affect the prognosis of the differentially expressed genes (DEGs) related to the metabolism. Enrichment analysis is used to identify the biological effects of candidate genes. Perform coexpression analysis on the verified DEGs. In addition, the candidate genes are used to cluster MM into different subtypes through consistent clustering. Use LASSO regression analysis to identify key genes, and use Cox regression analysis to evaluate the prognostic effects of key genes. Evaluation of immune cell infiltration in MM is by CIBERSORT. We identified 2821 DEGs, of which 348 genes were metabolic-related prognostic genes and were considered candidate genes. Enrichment analysis revealed that the candidate genes are mainly related to the proteasome, purine metabolism, and cysteine and methionine metabolism signaling pathways. According to the consensus clustering method, we identified the two subtypes of group 1 and group 2 that affect the prognosis of MM patients. Using the LASSO model, we have identified 10 key genes. The prognosis of the high-risk group identified by Cox regression analysis is worse than that of the low-risk group. Among them, PKLR has a greater impact on the prognosis of MM, and the prognosis of MM patients is poor when the expression is high. In addition, the level of immune cell infiltration in the high-risk group is higher than that in the low-risk group. In the summary, metabolism-related genes significantly affect the prognosis of MM patients through the metabolic process of MM patients. PKLR may be a prognostic risk factor for MM patients.

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.

Deep Learning-Based CT Imaging in Diagnosing Myeloma and Its Prognosis Evaluation

Imaging examination plays an important role in the early diagnosis of myeloma. The study focused on the segmentation effects of deep learning-based models on CT images for myeloma, and the influence of different chemotherapy treatments on the prognosis of patients. Specifically, 186 patients with suspected myeloma were the research subjects. The U-Net model was adjusted to segment the CT images, and then, the Faster region convolutional neural network (RCNN) model was used to label the lesions. Patients were divided into bortezomib group (group 1, n = 128) and non-bortezomib group (group 2, n = 58). The biochemical indexes, blood routine indexes, and skeletal muscle of the two groups were compared before and after chemotherapy. The results showed that the improved U-Net model demonstrated good segmentation results, the Faster RCNN model can realize the labeling of the lesion area in the CT image, and the classification accuracy rate was as high as 99%. Compared with group 1, group 2 showed enlarged psoas major and erector spinae muscle after treatment and decreased bone marrow plasma cells content, blood M protein, urine 24 h light chain, pBNP, ß-2 microglobulin (β2MG), ALP, and white blood cell (WBC) levels (P < 0.05). In conclusion, deep learning is suggested in the segmentation and classification of CT images for myeloma, which can lift the detection accuracy. Two different chemotherapy regimens both improve the prognosis of patients, but the effects of non-bortezomib chemotherapy are better.