BSG and MCT1 Genetic Variants Influence Survival in Multiple Myeloma Patients

The interactions between monocarboxylate transporter genes MCT1, MCT2, and MCT4 and the kinetics of blood lactate production and removal after high-intensity efforts in elite males: a cross-sectional study

BACKGROUND

This cross-sectional study investigated the relationship between genetic variations in monocarboxylate transporter genes and blood lactate production and removal after high-intensity efforts in humans. The study was conducted to explore how genetic variations in the MCT1, MCT2, and MCT4 genes influenced lactate dynamics and to advance the field of sports genetics by pinpointing critical genetic markers that can enhance athletic performance and recovery.

METHODS

337 male athletes from Poland and the Czech Republic underwent two intermittent all-out Wingate tests. Before the tests, DNA samples were taken from each participant, and SNP (single nucleotide polymorphism) analysis was carried out. Two intermittent all-out tests were implemented, and lactate concentrations were assessed before and after these tests.

RESULTS

Sprinters more frequently exhibited the haplotype TAC in the MCT2 gene, which was associated with an increase in the difference between maximum lactate and final lactate concentration. Additionally, this haplotype was linked to higher maximum lactate concentration and was more frequently observed in sprinters. The genotypic interactions AG/T- and GGxT- (MCT1 rs3789592 x MCT4 rs11323780), TTxTT (MCT1 rs12028967 x MCT2 rs3763979), and MCT1 rs7556664 x MCT4 rs11323780 were all associated with an increase in the difference between maximum lactate concentration and final lactate concentration. Conversely, the AGxGG (MCT1 rs3789592 x MCT2 rs995343) interaction was linked to a decrease in this difference. The relationship between maximum lactate concentration and genotypic interactions can be observed as follows: when ATxTT (MCT2 rs3763980 x MCT4 rs11323780) or CTxCT (MCT1 rs10857983 x MCT2 rs3763979) genotypic combinations are present, it leads to a decrease in maximum lactate concentration. Similarly, the combination of CTxCT (MCT1 rs4301628 x MCT2 rs3763979), CT x TT (MCT1 rs4301628 x MCT4 rs11323780), and CTxTT (MCT1 rs4301628 x MCT2 rs3763979) results in decreased maximum lactate concentration.

CONCLUSIONS

The TAC haplotype (rs3763980, rs995343, rs3763979) in the MCT2 gene is associated with altered lactate clearance in sprinters, potentially affecting performance and recovery by elevating post-exercise lactate concentrations. While MCT4 rs11323780 is also identified as a significant variant in lactate metabolism, suggesting its role as a biomarker for sprinting performance, further investigation is necessary to clarify underlying mechanisms and consider additional factors. Based on elite male athletes from Poland and the Czech Republic, the study may not generalize to all sprinters or diverse athletic populations. Although genetic variants show promise as biomarkers for sprinting success, athletic performance is influenced by a complex interplay of genetics, environment, and training extending beyond MCT genes.

Genetic and non-genetic factors influencing the therapeutic response of valproic acid in pediatric epileptic patients

AIMS

Considerable inter-individual variability in the efficacy of valproic acid (VPA) has been reported, with approximately 20-45% of patients failing to achieve satisfactory seizure control after VPA monotherapy. The aim of this study was to investigate the influence of non-genetic and genetic factors on 12-month VPA-response in a cohort of 194 pediatric patients.

MATERIALS & METHODS

Trough concentrations were determined, and a panel of 48 variants located in pharmacokinetic and pharmacodynamic gene were genotyped.

RESULTS

Aetiology was highlighted as a significant factor for the response to VPA. Specifically, patients with idiopathic epilepsy demonstrated poorer 12-month outcomes (p < 0.001). Trough VPA concentrations did not significantly affect outcomes. Marginal association was found between VPA efficacy and the following genetic variants: GABRA1 rs10068980 (p = 0.02), SLC16A1 rs7169 (p = 0.02), ABCC2 rs1885301 (p = 0.092), ACADM rs1251079 (p = 0.061) and GABRA1 rs6883877 (p = 0.085), as indicated by Fisher's exact test. A significant cumulative effect of two genetic factors (GABRA1 rs10068980 and SLC16A1 rs7169) was observed after a multiple logistic analysis, with ORs of 2.828 (1.213, 6.594) and 4.066 (1.148,14.398), respectively.

CONCLUSION

Our study indicated that GABRA1 rs10068980 and SLC16A1 rs7169 might serve as potential biomarkers for predicting the 12-month VPA treatment outcomes in pediatric patients with epilepsy.

Metabolic Function and Therapeutic Potential of CD147 for Hematological Malignancies: An Overview

Hematological malignancies refer to a heterogeneous group of neoplastic conditions of lymphoid and hematopoietic tissues classified in leukemias, Hodgkin and non-Hodgkin lymphomas and multiple myeloma, according to their presumed cell of origin, genetic abnormalities, and clinical features. Metabolic adaptation and immune escape, which influence various cellular functions, including the proliferation and survival of hematological malignant tumor cells, are major aspects of these malignancies that lead to therapeutic drug resistance. Targeting specific metabolic pathways is emerging as a novel therapeutic strategy in hematopoietic neoplasms, particularly in acute myeloid leukemia and multiple myeloma. In this context, CD147, also known as extracellular matrix metalloproteinase inducer (EMMPRIN) or Basigin, is one target candidate involved in reprograming metabolism in different cancer cells, including hematological malignant tumor cells. CD147 overexpression significantly contributes to the metabolic transformation of these cancer cells, by mediating signaling pathway, growth, metastasis and metabolic reprogramming, through its interaction, direct or not, with various membrane proteins related to metabolic regulation, including monocarboxylate transporters, integrins, P-glycoprotein, and glucose transporter 1. This review explores the metabolic functions of CD147 and its impact on the tumor microenvironment, influencing the progression and neoplastic transformation of leukemias, myeloma, and lymphomas. Furthermore, we highlight new opportunities for the development of targeted therapies against CD147, potentially improving the treatment of hematologic malignancies.

Extracellular matrix metalloproteinases inducer gene polymorphism and reduced serum matrix metalloprotease-2 activity in preeclampsia patients

Preeclampsia increases the risk of pregnancy-related complications, nevertheless a successful spiral vessel remodeling, and trophoblast invasion reduces disorders of pregnancy. Matrix metalloproteinase-2 (MMP-2) clears the path for trophoblast invasion, and activation of MMP-2 largely depends on extracellular matrix metalloproteinases inducer (EMMPRIN) protein. This study aimed to investigate EMMPRIN gene polymorphism and MMP-2 activity in preeclampsia patients. Archival whole blood and serum samples of 74 preeclampsia and 66 normotensive pregnant women age-matched were used in this case-control study. Genomic DNA was extracted from the whole blood samples and EMMPRIN gene amplified with specific primers following fragments sequence mutation analysis. Serum MMP-2 activity was determined using enzyme-linked immunosorbent assay (ELISA) and socio-demographic data of participants retrieved from the database. Age of preeclampsia patients (32.78 ± 6.39) years and body mass index (BMI) (33.09 ± 7.27) kg/m2 compared with the normotensive counterparts (32.33 ± 5.56) years and (32.33 ± 5.56) kg/m2,respectively, were not statistically significant (P > 0.05). Serum matrix metalloprotease-2 (MMP-2) activity was significantly reduced in preeclampsia group (16.34 ± 7.07) compared with the normotensives (25.63 ± 4.56) (P < 0.001), and rs424243T/G variant (55.6%) was overrepresented among the cases compared with the normotensives (16.7%). The single-nucleotide polymorphism T/G was found to be associated with preeclampsia (odds ratio [OR] = 7.63; 95% confidence interval [CI] = 3.95-14.75; P < 0.0001). Decreased activity of MMP-2 and rs424243T/G SNP of EMMPRIN gene was reported in preeclampsia. These preliminary data warrant a further investigation into the relationship between EMMPRIN gene polymorphism and MMP-2 activity in preeclampsia.

Polymorphism of tmprss2 (rs12329760) but not ace2 (rs4240157), tmprss11a (rs353163) and cd147 (rs8259) is associated with the severity of COVID-19 in the Ukrainian population

BACKGROUND AND AIM

Angiotensin-converting enzyme 2 (ACE2), transmembrane serine 2 and serine 11A proteases (TMPRSS2, TMPRSS11A), and a cell surface cluster of differentiation 147 (CD147) might be a gene candidate that exerts the susceptibility to and mortality from coronavirus disease 19 (COVID-19). The aim of this study was to investigate the associations between ace2, tmprss2, tmprss11a, and cd147 polymorphic variants and the severity of COVID-19 in the Ukrainian population.

METHODS

The study population consisted of the Ukrainian population with COVID-19: patients without oxygen therapy (n=62), with non-invasive (n=92) and invasive (n=35) oxygen therapy, as well as control subjects (n=92). Allelic polymorphisms of ace2 rs4240157, tmprss2 rs12329760, and tmprss11a rs353163 were determined by real-time PCR, and cd147 rs8259 polymorphism was detected by PCR with subsequent restrictase analysis. We compared investigated polymorphisms distribution with other populations by meta-analysis.

RESULTS

Our study is the first to obtain data about the distribution of investigated gene polymorphisms in the Ukrainian population: tmprss2 rs12329760 - CC 60.9%, CT 35.9%, TT 3.2%; tmprss11a rs353163 - CC 46.7%, CT 40.2%, TT 13.1%; ace2 rs4240157 - CC 7.6%, C 18.5%, CT 22.8%, TT 19.6%, T 31.5%; cd147 rs8259 - TT 60.9%, AT 32.6%, AA 6.5%. This distribution was similar to the Northern, Western and Southern European populations. There was a statistically significant difference in the frequency of tmprss2 polymorphic genotypes CC 57.1%, CT 28.6%, and TT 14.3% (P<0.05) in COVID-19 patients with invasive oxygen therapy in comparison with non-invasive oxygen therapy. This tmprss2 mutation occurs in the scavenger receptor cysteine-rich (SRCR) domain and might be important for protein-protein interaction in a calcium-dependent manner.

CONCLUSIONS

Our study indicated the presence of an association between the tmprss2 rs12329760 polymorphism and the severity of COVID-19 in the Ukrainian population.

Current perspectives on interethnic variability in multiple myeloma: Single cell technology, population pharmacogenetics and molecular signal transduction

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This review discusses the emerging single cell technologies and applications in Multiple myeloma (MM), population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction.

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The role(s) of epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of MM are also discussed.

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It is understood that ethnic component acts as a driver of variable response to chemotherapy in different sub-populations globally.

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This review augments our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, myeloma microenvironment at the molecular and cellular level, and developing precision medicine strategies to combat this malignancy.

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The emerging single cell technologies hold great promise for enhancing our understanding of MM tumor heterogeneity and clonal diversity.

Multiple myeloma (MM) is an aggressive cancer characterised by malignancy of the plasma cells and a rising global incidence. The gold standard for optimum response is aggressive chemotherapy followed by autologous stem cell transplantation (ASCT). However, majority of the patients are above 60 years and this presents the clinician with complications such as ineligibility for ASCT, frailty, drug-induced toxicity and differential/partial response to treatment. The latter is partly driven by heterogenous genotypes of the disease in different subpopulations. In this review, we discuss emerging single cell technologies and applications in MM, population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction, as well as the role(s) played by epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of the disease. Taken together, our discussions further our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, augment our understanding of the myeloma microenvironment at the molecular and cellular level and provide a basis for developing precision medicine strategies to combat this malignancy.

Soluble CD147 (BSG) as a Prognostic Marker in Multiple Myeloma

CD147 (basigin, BSG) is a membrane-bound glycoprotein involved in energy metabolism that plays a role in cancer cell survival. Its soluble form is a promising marker of some diseases, but it is otherwise poorly studied. CD147 is overexpressed in multiple myeloma (MM) and is known to affect MM progression, while its genetic variants are associated with MM survival. In the present study, we aimed to assess serum soluble CD147 (sCD147) expression as a potential marker in MM. We found that sCD147 level was higher in MM patients compared to healthy individuals. It was also higher in patients with more advanced disease (ISS III) compared to both patients with less advanced MM and healthy individuals, while its level was observed to drop after positive response to treatment. Patients with high sCD147 were characterized by worse overall survival. sCD147 level did not directly correlate with bone marrow CD147 mRNA expression. In conclusion, this study suggests that serum sCD147 may be a prognostic marker in MM.

BSG (CD147) Serum Level and Genetic Variants Are Associated with Overall Survival in Acute Myeloid Leukaemia

Basigin (BSG, CD147) is a multifunctional protein involved in cancer cell survival, mostly by controlling lactate transport through its interaction with monocarboxylate transporters (MCTs) such as MCT1. Previous studies have found that single nucleotide polymorphisms (SNPs) in the gene coding for BSG and MCT1, as well as levels of the soluble form of BSG (sBSG), are potential biomarkers in various diseases. The goal of this study was to confirm BSG and MCT1 RNA overexpression in AML cell lines, as well as to analyse soluble BSG levels and selected BSG/MCT1 genetic variants as potential biomarkers in AML patients. We found that BSG and MCT1 were overexpressed in most AML cell lines. Soluble BSG was increased in AML patients compared to healthy controls, and correlated with various clinical parameters. High soluble BSG was associated with worse overall survival, higher bone marrow blast percentage, and higher white blood cell count. BSG SNPs rs4919859 and rs4682, as well as MCT1 SNP rs1049434, were also associated with overall survival of AML patients. In conclusion, this study confirms the importance of BSG/MCT1 in AML, and suggests that soluble BSG and BSG/MCT1 genetic variants may act as potential AML biomarkers.

Transport function, regulation, and biology of human monocarboxylate transporter 1 (hMCT1) and 4 (hMCT4)

Human monocarboxylate transporter 1 (hMCT1) and 4 (hMCT4) are involved in the proton-dependent transport of monocarboxylates such as L-lactate, which play an essential role in cellular metabolism and pH regulation. hMCT1 and 4 are overexpressed in a number of cancers, and polymorphisms in hMCT1 have been reported to be associated with the prognosis of some cancers. Accordingly, recent advances have focused on the inhibition of these transporters as a novel therapeutic strategy in cancers. To screen for MCT inhibitors for clinical application, it is important to study MCT function and regulation, and the effect of compounds on them, using human-derived cells. In this review, we focus on the transport function, regulation, and biology of hMCT1 and hMCT4, and the effects of genetic variation in these transporters in humans.

Genetically determined telomere length and multiple myeloma risk and outcome

Telomeres are involved in processes like cellular growth, chromosomal stability, and proper segregation to daughter cells. Telomere length measured in leukocytes (LTL) has been investigated in different cancer types, including multiple myeloma (MM). However, LTL measurement is prone to heterogeneity due to sample handling and study design (retrospective vs. prospective). LTL is genetically determined; genome-wide association studies identified 11 SNPs that, combined in a score, can be used as a genetic instrument to measure LTL and evaluate its association with MM risk. This approach has been already successfully attempted in various cancer types but never in MM. We tested the "teloscore" in 2407 MM patients and 1741 controls from the International Multiple Myeloma rESEarch (IMMeNSE) consortium. We observed an increased risk for longer genetically determined telomere length (gdTL) (OR = 1.69; 95% CI 1.36-2.11; P = 2.97 × 10^-6 for highest vs. lowest quintile of the score). Furthermore, in a subset of 1376 MM patients we tested the relationship between the teloscore and MM patients survival, observing a better prognosis for longer gdTL compared with shorter gdTL (HR = 0.93; 95% CI 0.86-0.99; P = 0.049). In conclusion, we report convincing evidence that longer gdTL is a risk marker for MM risk, and that it is potentially involved in increasing MM survival.

Overexpression of Cell-Surface Marker SLC16A1 Shortened Survival in Human High-Grade Gliomas

Solute carrier family 16 member 1 (SLC16A1) is a crucial transcription factor in modifying cancer progression and metastasis. However, its character in defining the clinical prognosis of human gliomas has not been illuminated. In our analysis from PREdiction of Clinical Outcomes from Genomic Profiles (PRECOG), The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA), we found that SLC16A1 mRNA expression level was significantly increased in high-grade gliomas in contrast to low-grade gliomas and non-tumor controls (P < 0.05). Kaplan-Meier analysis of four independent cohort studies from the Gene Expression Omnibus (GEO) profile, TCGA, and CGGA which consistently presented patients with high SLC16A1 mRNA expression displayed poor overall survival in high-grade glioma patients (P < 0.05 by log-rank test). Based on the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), the protein-protein interaction analysis of SLC16A1-regulated oncogenesis showed SLC16A1 as a potential hub protein. Immunohistochemical staining exhibited that SLC16A1 protein overexpressed in high-grade gliomas compared with low-grade clinical glioma samples. All these findings suggest that SLC16A1 expression has a positive correlation with WHO pathological grading and poor survival. SLC16A1 might be a potential biomarker of prognosis in human gliomas.

Metabolic Effects of Recurrent Genetic Aberrations in Multiple Myeloma

Oncogene activation and malignant transformation exerts energetic, biosynthetic and redox demands on cancer cells due to increased proliferation, cell growth and tumor microenvironment adaptation. As such, altered metabolism is a hallmark of cancer, which is characterized by the reprogramming of multiple metabolic pathways. Multiple myeloma (MM) is a genetically heterogeneous disease that arises from terminally differentiated B cells. MM is characterized by reciprocal chromosomal translocations that often involve the immunoglobulin loci and a restricted set of partner loci, and complex chromosomal rearrangements that are associated with disease progression. Recurrent chromosomal aberrations in MM result in the aberrant expression of MYC, cyclin D1, FGFR3/MMSET and MAF/MAFB. In recent years, the intricate mechanisms that drive cancer cell metabolism and the many metabolic functions of the aforementioned MM-associated oncogenes have been investigated. Here, we discuss the metabolic consequences of recurrent chromosomal translocations in MM and provide a framework for the identification of metabolic changes that characterize MM cells.

Discovery and validation of surface N-glycoproteins in MM cell lines and patient samples uncovers immunotherapy targets

BACKGROUND

Multiple myeloma (MM) is characterized by clonal expansion of malignant plasma cells in the bone marrow. While recent advances in treatment for MM have improved patient outcomes, the 5-year survival rate remains ~50%. A better understanding of the MM cell surface proteome could facilitate development of new directed therapies and assist in stratification and monitoring of patient outcomes.

METHODS

In this study, we first used a mass spectrometry (MS)-based discovery-driven cell surface capture (CSC) approach to map the cell surface N-glycoproteome of MM cell lines. Next, we developed targeted MS assays, and applied these to cell lines and primary patient samples to refine the list of candidate tumor markers. Candidates of interest detected by MS on MM patient samples were further validated using flow cytometry (FCM).

RESULTS

We identified 696 MM cell surface N-glycoproteins by CSC, and developed 73 targeted MS detection assays. MS-based validation using primary specimens detected 30 proteins with significantly higher abundance in patient MM cells than controls. Nine of these proteins were identified as potential immunotherapeutic targets, including five that were validated by FCM, confirming their expression on the cell surface of primary MM patient cells.

CONCLUSIONS

This MM surface N-glycoproteome will be a valuable resource in the development of biomarkers and therapeutics. Further, we anticipate that our targeted MS assays will have clinical benefit for the diagnosis, stratification, and treatment of MM patients.

Identification of Disease Risk DNA Variations is Shaping the Future of Precision Health

In recent years, the knowledge generated by decoding the human genome has allowed groundbreaking genetic research to better understand genomic architecture and heritability in healthy and disease states. The vast amount of data generated over time and yet to be generated provides the basis for translational research towards the development of preventive and therapeutic strategies for many conditions. In this special issue, we highlight the discoveries of disease-associated and protective DNA variations in common human diseases and developmental disorders.

Germline Risk Contribution to Genomic Instability in Multiple Myeloma

Genomic instability, a well-established hallmark of human cancer, is also a driving force in the natural history of multiple myeloma (MM) - a difficult to treat and in most cases fatal neoplasm of immunoglobulin producing plasma cells that reside in the hematopoietic bone marrow. Long recognized manifestations of genomic instability in myeloma at the cytogenetic level include abnormal chromosome numbers (aneuploidy) caused by trisomy of odd-numbered chromosomes; recurrent oncogene-activating chromosomal translocations that involve immunoglobulin loci; and large-scale amplifications, inversions, and insertions/deletions (indels) of genetic material. Catastrophic genetic rearrangements that either shatter and illegitimately reassemble a single chromosome (chromotripsis) or lead to disordered segmental rearrangements of multiple chromosomes (chromoplexy) also occur. Genomic instability at the nucleotide level results in base substitution mutations and small indels that affect both the coding and non-coding genome. Sometimes this generates a distinctive signature of somatic mutations that can be attributed to defects in DNA repair pathways, the DNA damage response (DDR) or aberrant activity of mutator genes including members of the APOBEC family. In addition to myeloma development and progression, genomic instability promotes acquisition of drug resistance in patients with myeloma. Here we review recent findings on the genetic predisposition to myeloma, including newly identified candidate genes suggesting linkage of germline risk and compromised genomic stability control. The role of ethnic and familial risk factors for myeloma is highlighted. We address current research gaps that concern the lack of studies on the mechanism by which germline risk alleles promote genomic instability in myeloma, including the open question whether genetic modifiers of myeloma development act in tumor cells, the tumor microenvironment (TME), or in both. We conclude with a brief proposition for future research directions, which concentrate on the biological function of myeloma risk and genetic instability alleles, the potential links between the germline genome and somatic changes in myeloma, and the need to elucidate genetic modifiers in the TME.