Validation Study for Non-Invasive Prediction of IDH Mutation Status in Patients with Glioma Using In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning.

The isocitrate dehydrogenase (IDH) mutation status is an indispensable prerequisite for diagnosis of glioma (astrocytoma and oligodendroglioma) according to the WHO classification of brain tumors 2021 and is a potential therapeutic target. Usually, immunohistochemistry followed by sequencing of tumor tissue is performed for this purpose. In clinical routine, however, non-invasive determination of IDH mutation status is desirable in cases where tumor biopsy is not possible and for monitoring neuro-oncological therapies. In a previous publication, we presented reliable prediction of IDH mutation status employing proton magnetic resonance spectroscopy (1H-MRS) on a 3.0 Tesla (T) scanner and machine learning in a prospective cohort of 34 glioma patients. Here, we validated this approach in an independent cohort of 67 patients, for which 1H-MR spectra were acquired at 1.5 T between 2002 and 2007, using the same data analysis approach. Despite different technical conditions, a sensitivity of 82.6% (95% CI, 61.2-95.1%) and a specificity of 72.7% (95% CI, 57.2-85.0%) could be achieved. We concluded that our 1H-MRS based approach can be established in a routine clinical setting with affordable effort and time, independent of technical conditions employed. Therefore, the method provides a non-invasive tool for determining IDH status that is well-applicable in an everyday clinical setting.

A Predictive Model for Progression of CKD to Kidney Failure Based on Routine Laboratory Tests.

RATIONALE & OBJECTIVE: Stratification of chronic kidney disease (CKD) patients at risk for progressing to kidney failure requiring kidney replacement therapy (KFRT) is important for clinical decision-making and trial enrollment. STUDY DESIGN: Four independent prospective observational cohort studies. SETTING & PARTICIPANTS: The development cohort comprised 4,915 CKD patients, and 3 independent validation cohorts comprised a total of 3,063. Patients were observed for approximately 5 years. EXPOSURE: 22 demographic, anthropometric, and laboratory variables commonly assessed in CKD patients. OUTCOME: Progression to KFRT. ANALYTICAL APPROACH: A least absolute shrinkage and selection operator (LASSO) Cox proportional hazards model was fit to select laboratory variables that best identified patients at high risk for KFRT. Model discrimination and calibration were assessed and compared against the 4-variable Tangri (T4) risk equation both in a resampling approach within the development cohort and in the validation cohorts using cause-specific concordance (C) statistics, net reclassification improvement, and calibration graphs. RESULTS: The newly derived 6-variable risk score (Z6) included serum creatinine, albumin, cystatin C, and urea, as well as hemoglobin and the urinary albumin-creatinine ratio. In the the resampling approach, Z6 achieved a median C statistic of 0.909 (95% CI, 0.868-0.937) at 2 years after the baseline visit, whereas the T4 achieved a median C statistic of 0.855 (95% CI, 0.799-0.915). In the 3 independent validation cohorts, the Z6C statistics were 0.894, 0.921, and 0.891, whereas the T4C statistics were 0.882, 0.913, and 0.862. LIMITATIONS: The Z6 was both derived and tested only in White European cohorts. CONCLUSIONS: A new risk equation based on 6 routinely available laboratory tests facilitates identification of patients with CKD who are at high risk of progressing to KFRT.

Cold Atmospheric Plasma Changes the Amino Acid Composition of Solutions and Influences the Anti-Tumor Effect on Melanoma Cells.

Cold Atmospheric Plasma (CAP) is an ionized gas near room temperature. Its anti-tumor effect can be transmitted either by direct treatment or mediated by a plasma-treated solution (PTS), such as treated standard cell culture medium, which contains different amino acids, inorganic salts, vitamins and other substances. Despite extensive research, the active components in PTS and its molecular or cellular mechanisms are not yet fully understood. The purpose of this study was the measurement of the reactive species in PTS and their effect on tumor cells using different plasma modes and treatment durations. The PTS analysis yielded mode- and dose-dependent differences in the production of reactive oxygen and nitrogen species (RONS), and in the decomposition and modification of the amino acids Tyrosine (Tyr) and Tryptophan (Trp). The Trp metabolites Formylkynurenine (FKyn) and Kynurenine (Kyn) were produced in PTS with the 4 kHz (oxygen) mode, inducing apoptosis in Mel Im melanoma cells. Nitrated derivatives of Trp and Tyr were formed in the 8 kHz (nitrogen) mode, elevating the p16 mRNA expression and senescence-associated ß-Galactosidase staining. In conclusion, the plasma mode has a strong impact on the composition of the active components in PTS and affects its anti-tumor mechanism. These findings are of decisive importance for the development of plasma devices and the effectiveness of tumor treatment.

Lactonization of the Oncometabolite D-2-Hydroxyglutarate Produces a Novel Endogenous Metabolite.

In recent years, onco-metabolites like D-2-hydroxyglutarate, which is produced in isocitrate dehydrogenase-mutated tumors, have gained increasing interest. Here, we report a metabolite in human specimens that is closely related to 2-hydroxyglutarate: the intramolecular ester of 2-hydroxyglutarate, 2-hydroxyglutarate-γ-lactone. Using 13C5-L-glutamine tracer analysis, we showed that 2-hydroxyglutarate is the endogenous precursor of 2-hydroxyglutarate-lactone and that there is a high exchange between these two metabolites. Lactone formation does not depend on mutated isocitrate dehydrogenase, but its formation is most probably linked to transport processes across the cell membrane and favored at low environmental pH. Furthermore, human macrophages showed not only striking differences in uptake of 2-hydroxyglutarate and its lactone but also in the enantiospecific hydrolysis of the latter. Consequently, 2-hydroxyglutarate-lactone may play a critical role in the modulation of the tumor microenvironment.

Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning.

Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard 1H-magnetic resonance spectroscopy (1H-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) for optimized voxel placement in 1H-MRS. Routine 1H-magnetic resonance (1H-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the 1H-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2-99.9%) and a specificity of 75.0% (95% CI, 42.9-94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo 1H-nuclear magnetic resonance (1H-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting.

High CD206 levels in Hodgkin lymphoma-educated macrophages are linked to matrix-remodeling and lymphoma dissemination.

Macrophages (Mφ) are abundantly present in the tumor microenvironment and may predict outcome in solid tumors and defined lymphoma subtypes. Mφ heterogeneity, the mechanisms of their recruitment, and their differentiation into lymphoma-promoting, alternatively activated M2-like phenotypes are still not fully understood. Therefore, further functional studies are required to understand biological mechanisms associated with human tumor-associated Mφ (TAM). Here, we show that the global mRNA expression and protein abundance of human Mφ differentiated in Hodgkin lymphoma (HL)-conditioned medium (CM) differ from those of Mφ educated by conditioned media from diffuse large B-cell lymphoma (DLBCL) cells or, classically, by macrophage colony-stimulating factor (M-CSF). Conditioned media from HL cells support TAM differentiation through upregulation of surface antigens such as CD40, CD163, CD206, and PD-L1. In particular, RNA and cell surface protein expression of mannose receptor 1 (MRC1)/CD206 significantly exceed the levels induced by classical M-CSF stimulation in M2-like Mφ; this is regulated by interleukin 13 to a large extent. Functionally, high CD206 enhances mannose-dependent endocytosis and uptake of type I collagen. Together with high matrix metalloprotease9 secretion, HL-TAMs appear to be active modulators of the tumor matrix. Preclinical in ovo models show that co-cultures of HL cells with monocytes or Mφ support dissemination of lymphoma cells via lymphatic vessels, while tumor size and vessel destruction are decreased in comparison with lymphoma-only tumors. Immunohistology of human HL tissues reveals a fraction of cases feature large numbers of CD206-positive cells, with high MRC1 expression being characteristic of HL-stage IV. In summary, the lymphoma-TAM interaction contributes to matrix-remodeling and lymphoma cell dissemination.

Identification of ADGRE5 as discriminating MYC target between Burkitt lymphoma and diffuse large B-cell lymphoma.

BACKGROUND: MYC is a heterogeneously expressed transcription factor that plays a multifunctional role in many biological processes such as cell proliferation and differentiation. It is also associated with many types of cancer including the malignant lymphomas. There are two types of aggressive B-cell lymphoma, namely Burkitt lymphoma (BL) and a subgroup of diffuse large cell lymphoma (DLBCL), which both carry MYC translocations and overexpress MYC but both differ significantly in their clinical outcome. In DLBCL, MYC translocations are associated with an aggressive behavior and poor outcome, whereas MYC-positive BL show a superior outcome. METHODS: To shed light on this phenomenon, we investigated the different modes of actions of MYC in aggressive B-cell lymphoma cell lines subdivided into three groups: (i) MYC-positive BL, (ii) DLBCL with MYC translocation (DLBCLpos) and (iii) DLBCL without MYC translocation (DLBCLneg) for control. In order to identify genome-wide MYC-DNA binding sites a chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) was performed. In addition, ChIP-Seq for H3K4me3 was used for determination of genomic regions accessible for transcriptional activity. These data were supplemented with gene expression data derived from RNA-Seq. RESULTS: Bioinformatics integration of all data sets revealed different MYC-binding patterns and transcriptional profiles in MYC-positive BL and DLBCL cell lines indicating different functional roles of MYC for gene regulation in aggressive B-cell lymphomas. Based on this multi-omics analysis we identified ADGRE5 (alias CD97) - a member of the EGF-TM7 subfamily of adhesion G protein-coupled receptors - as a MYC target gene, which is specifically expressed in BL but not in DLBCL regardless of MYC translocation. CONCLUSION: Our study describes a diverse genome-wide MYC-DNA binding pattern in BL and DLBCL cell lines with and without MYC translocations. Furthermore, we identified ADREG5 as a MYC target gene able to discriminate between BL and DLBCL irrespectively of the presence of MYC breaks in DLBCL. Since ADGRE5 plays an important role in tumor cell formation, metastasis and invasion, it might also be instrumental to better understand the different pathobiology of BL and DLBCL and help to explain discrepant clinical characteristics of BL and DLBCL.

Cooperative STAT/NF-κB signaling regulates lymphoma metabolic reprogramming and aberrant GOT2 expression.

Knowledge of stromal factors that have a role in the transcriptional regulation of metabolic pathways aside from c-Myc is fundamental to improvements in lymphoma therapy. Using a MYC-inducible human B-cell line, we observed the cooperative activation of STAT3 and NF-κB by IL10 and CpG stimulation. We show that IL10 + CpG-mediated cell proliferation of MYClow cells depends on glutaminolysis. By 13C- and 15N-tracing of glutamine metabolism and metabolite rescue experiments, we demonstrate that GOT2 provides aspartate and nucleotides to cells with activated or aberrant Jak/STAT and NF-κB signaling. A model of GOT2 transcriptional regulation is proposed, in which the cooperative phosphorylation of STAT3 and direct joint binding of STAT3 and p65/NF-κB to the proximal GOT2 promoter are important. Furthermore, high aberrant GOT2 expression is prognostic in diffuse large B-cell lymphoma underscoring the current findings and importance of stromal factors in lymphoma biology.

Visceral adipose tissue but not subcutaneous adipose tissue is associated with urine and serum metabolites.

Obesity is a complex multifactorial phenotype that influences several metabolic pathways. Yet, few studies have examined the relations of different body fat compartments to urinary and serum metabolites. Anthropometric phenotypes (visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), the ratio between VAT and SAT (VSR), body mass index (BMI), waist circumference (WC)) and urinary and serum metabolite concentrations measured by nuclear magnetic resonance spectroscopy were measured in a population-based sample of 228 healthy adults. Multivariable linear and logistic regression models, corrected for multiple testing using the false discovery rate, were used to associate anthropometric phenotypes with metabolites. We adjusted for potential confounding variables: age, sex, smoking, physical activity, menopausal status, estimated glomerular filtration rate (eGFR), urinary glucose, and fasting status. In a fully adjusted logistic regression model dichotomized for the absence or presence of quantifiable metabolite amounts, VAT, BMI and WC were inversely related to urinary choline (ß = -0.18, p = 2.73*10-3), glycolic acid (ß = -0.20, 0.02), and guanidinoacetic acid (ß = -0.12, p = 0.04), and positively related to ethanolamine (ß = 0.18, p = 0.02) and dimethylamine (ß = 0.32, p = 0.02). BMI and WC were additionally inversely related to urinary glutamine and lactic acid. Moreover, WC was inversely associated with the detection of serine. VAT, but none of the other anthropometric parameters, was related to serum essential amino acids, such as valine, isoleucine, and phenylalanine among men. Compared to other adiposity measures, VAT demonstrated the strongest and most significant relations to urinary and serum metabolites. The distinct relations of VAT, SAT, VSR, BMI, and WC to metabolites emphasize the importance of accurately differentiating between body fat compartments when evaluating the potential role of metabolic regulation in the development of obesity-related diseases, such as insulin resistance, type 2 diabetes, and cardiovascular disease.

Comprehensive Metaboproteomics of Burkitt's and Diffuse Large B-Cell Lymphoma Cell Lines and Primary Tumor Tissues Reveals Distinct Differences in Pyruvate Content and Metabolism.

Burkitt's lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) are pathologically and clinically distinct subtypes of aggressive non-Hodgkin B-cell lymphoma. To learn more about their biology, we employed metabolomic and proteomic methods to study both established cell lines as well as cryopreserved and formalin-fixed paraffin-embedded (FFPE) tissue sections of BL and DLBCL. Strikingly, NMR analyses revealed DLBCL cell lines to produce and secrete significantly (padj = 1.72 × 10-22) more pyruvic acid than BL cell lines. This finding could be reproduced by targeted GC/MS analyses of cryopreserved tissue sections of BL and DLBCL cases. Enrichment analysis of an overlapping set of N = 2315 proteins, that had been quantified by nanoLC-SWATH-MS in BL and DLBCL cultured cells and cryosections, supported the observed difference in pyruvic acid content, as glycolysis and pyruvate metabolism were downregulated, while one-carbon metabolism was upregulated in BL compared to DLBCL. Furthermore, 92.1% of the overlapping significant proteins showed the same direction of regulation in cryopreserved and FFPE material. Proteome data are available via ProteomeXchange with identifier PXD004936.

High-Dimensional Profiling for Computational Diagnosis.

New technologies allow for high-dimensional profiling of patients. For instance, genome-wide gene expression analysis in tumors or in blood is feasible with microarrays, if all transcripts are known, or even without this restriction using high-throughput RNA sequencing. Other technologies like NMR finger printing allow for high-dimensional profiling of metabolites in blood or urine. Such technologies for high-dimensional patient profiling represent novel possibilities for molecular diagnostics. In clinical profiling studies, researchers aim to predict disease type, survival, or treatment response for new patients using high-dimensional profiles. In this process, they encounter a series of obstacles and pitfalls. We review fundamental issues from machine learning and recommend a procedure for the computational aspects of a clinical profiling study.

Synergy of interleukin 10 and toll-like receptor 9 signalling in B cell proliferation: Implications for lymphoma pathogenesis.

A network of autocrine and paracrine signals defines B cell homeostasis and is thought to be involved in transformation processes. Investigating interactions of these microenvironmental factors and their relation to proto-oncogenes as c-Myc (MYC) is fundamental to understand the biology of B cell lymphoma. Therefore, B cells with conditional MYC expression were stimulated with CD40L, insulin-like growth factor 1, α-IgM, Interleukin-10 (IL10) and CpG alone or in combination. The impact of forty different interventions on cell proliferation was investigated in MYC deprived cells and calculated by linear regression. Combination of CpG and IL10 led to a strong synergistic activation of cell proliferation (S-phase/doubling of total cell number) comparable to cells with high MYC expression. A synergistic up-regulation of CDK4, CDK6 and CCND3 expression by IL10 and CpG treatment was causal for this proliferative effect as shown by qRT-PCR analysis and inhibition of the CDK4/6 complex by PD0332991. Furthermore, treatment of stimulated MYC deprived cells with MLN120b, ACHP, Pyridone 6 or Ruxolitinib showed that IL10/CpG induced proliferation and CDK4 expression were JAK/STAT3 and IKK/NF-κB dependent. This was further supported by STAT3 and p65/RELA knockdown experiments, showing strongest effects on cell proliferation and CDK4 expression after double knockdown. Additionally, chromatin immunoprecipitation revealed a dual binding of STAT3 and p65 to the proximal promotor of CDK4 after IL10/CpG treatment. Therefore, the observed synergism of IL10R and TLR9 signalling was able to induce proliferation in a comparable way as aberrant MYC and might play a role in B cell homeostasis or transformation.

A Metabolome-Wide Association Study of Kidney Function and Disease in the General Population.

Small molecules are extensively metabolized and cleared by the kidney. Changes in serum metabolite concentrations may result from impaired kidney function and can be used to estimate filtration (e.g., the established marker creatinine) or may precede and potentially contribute to CKD development. Here, we applied a nontargeted metabolomics approach using gas and liquid chromatography coupled to mass spectrometry to quantify 493 small molecules in human serum. The associations of these molecules with GFR estimated on the basis of creatinine (eGFRcr) and cystatin C levels were assessed in ≤1735 participants in the KORA F4 study, followed by replication in 1164 individuals in the TwinsUK registry. After correction for multiple testing, 54 replicated metabolites significantly associated with eGFRcr, and six of these showed pairwise correlation (r≥0.50) with established kidney function measures: C-mannosyltryptophan, pseudouridine, N-acetylalanine, erythronate, myo-inositol, and N-acetylcarnosine. Higher C-mannosyltryptophan, pseudouridine, and O-sulfo-L-tyrosine concentrations associated with incident CKD (eGFRcr <60 ml/min per 1.73 m(2)) in the KORA F4 study. In contrast with serum creatinine, C-mannosyltryptophan and pseudouridine concentrations showed little dependence on sex. Furthermore, correlation with measured GFR in 200 participants in the AASK study was 0.78 for both C-mannosyltryptophan and pseudouridine concentration, and highly significant associations of both metabolites with incident ESRD disappeared upon adjustment for measured GFR. Thus, these molecules may be alternative or complementary markers of kidney function. In conclusion, our study provides a comprehensive list of kidney function-associated metabolites and highlights potential novel filtration markers that may help to improve the estimation of GFR.

Data Normalization of (1)H NMR Metabolite Fingerprinting Data Sets in the Presence of Unbalanced Metabolite Regulation.

Data normalization is an essential step in NMR-based metabolomics. Conducted properly, it improves data quality and removes unwanted biases. The choice of the appropriate normalization method is critical and depends on the inherent properties of the data set in question. In particular, the presence of unbalanced metabolic regulation, where the different specimens and cohorts under investigation do not contain approximately equal shares of up- and down-regulated features, may strongly influence data normalization. Here, we demonstrate the suitability of the Shapiro-Wilk test to detect such unbalanced regulation. Next, employing a Latin-square design consisting of eight metabolites spiked into a urine specimen at eight different known concentrations, we show that commonly used normalization and scaling methods fail to retrieve true metabolite concentrations in the presence of increasing amounts of glucose added to simulate unbalanced regulation. However, by learning the normalization parameters on a subset of nonregulated features only, Linear Baseline Normalization, Probabilistic Quotient Normalization, and Variance Stabilization Normalization were found to account well for different dilutions of the samples without distorting the true spike-in levels even in the presence of marked unbalanced metabolic regulation. Finally, the methods described were applied successfully to a real world example of unbalanced regulation, namely, a set of plasma specimens collected from patients with and without acute kidney injury after cardiac surgery with cardiopulmonary bypass use.

Identification of Plasma Metabolites Prognostic of Acute Kidney Injury after Cardiac Surgery with Cardiopulmonary Bypass.

Acute kidney injury (AKI) is a frequent complication after cardiopulmonary bypass, but early detection of postoperative AKI remains challenging. Protein biomarkers predict AKI excellently in homogeneous cohorts but are less reliable in patients suffering from various comorbidities. We employed nuclear magnetic resonance spectroscopy in a prospective study of 85 adult cardiac surgery patients to identify metabolites prognostic of AKI in plasma specimens collected 24 h after surgery. Postoperative AKI of stages 1-3, as defined by the Acute Kidney Injury Network (AKIN), developed in 33 cases. A random forests classifier trained on the NMR spectra prognosticated AKI across all stages, with an average accuracy of 80 ± 0.9% and an area under the receiver operating characteristic curve of 0.87 ± 0.01. Prognostications were based, on average, on 24 ± 2.8 spectral features. Among the set of discriminative ions and molecules identified were Mg(2+), lactate, and the glucuronide conjugate of propofol. Using creatinine, Mg(2+), and lactate levels to derive an AKIN index score, we found AKIN 1 disease to be largely indistinguishable from AKIN 0, in concordance with the rather mild nature of AKIN 1 disease.

Distinct metabolic differences between various human cancer and primary cells.

Recent years have seen resurging interest in cancer cell metabolism and the role of secreted cancer metabolites in modulating the tumor stroma. Using a combination of nontargeted and targeted LC and GC-MS methods, the exometabolomes of three leukemia, two melanoma, three renal cell carcinoma, two colorectal adenocarcinoma, four hepatocellular carcinoma, three breast cancer, two bladder carcinoma, and one glioblastoma cell line, as well as five primary cultures of human melanocytes, hepatocytes, monocytes, CD4 and CD8 lymphocytes, that had been all cultivated under identical conditions, were investigated. Unsupervised affinity propagation clustering of the metabolic footprints yielded five distinct clusters that grouped the investigated cell cultures mainly according to the tissue of origin. A common expected feature of all neoplastic cells was high lactate production. Extracellular arginine and nicotinamide were major discriminants between normal and neoplastic hepatocytes. Further, significant differences in the assimilation of di- and tripeptides were observed. This finding appears to underscore the importance of peptides for meeting the increased bioenergetic and biosynthetic demands of many cancers.

New aspects of an old drug--diclofenac targets MYC and glucose metabolism in tumor cells.

Non-steroidal anti-inflammatory drugs such as diclofenac exhibit potent anticancer effects. Up to now these effects were mainly attributed to its classical role as COX-inhibitor. Here we show novel COX-independent effects of diclofenac. Diclofenac significantly diminished MYC expression and modulated glucose metabolism resulting in impaired melanoma, leukemia, and carcinoma cell line proliferation in vitro and reduced melanoma growth in vivo. In contrast, the non-selective COX inhibitor aspirin and the COX-2 specific inhibitor NS-398 had no effect on MYC expression and glucose metabolism. Diclofenac significantly decreased glucose transporter 1 (GLUT1), lactate dehydrogenase A (LDHA), and monocarboxylate transporter 1 (MCT1) gene expression in line with a decrease in glucose uptake and lactate secretion. A significant intracellular accumulation of lactate by diclofenac preceded the observed effect on gene expression, suggesting a direct inhibitory effect of diclofenac on lactate efflux. While intracellular lactate accumulation impairs cellular proliferation and gene expression, it does not inhibit MYC expression as evidenced by the lack of MYC regulation by the MCT inhibitor α-cyano-4-hydroxycinnamic acid. Finally, in a cell line with a tetracycline-regulated c-MYC gene, diclofenac decreased proliferation both in the presence and absence of c-MYC. Thus, diclofenac targets tumor cell proliferation via two mechanisms, that is inhibition of MYC and lactate transport. Based on these results, diclofenac holds potential as a clinically applicable MYC and glycolysis inhibitor supporting established tumor therapies.

Diclofenac inhibits lactate formation and efficiently counteracts local immune suppression in a murine glioma model.

Lactate formation in highly proliferative tumors such as malignant gliomas is associated with poor survival and contributes to the suppression of local immunity. Here, we report that diclofenac used at nontoxic concentrations significantly decreased lactate production in murine glioma cells and inhibited the expression of lactate dehydrogenase-A in vitro. Lactate reduction was accompanied by a dose-dependent inhibition of cell growth and a cell cycle arrest at the G2/M checkpoint. In the presence of diclofenac, murine bone marrow-derived dendritic cells (DCs) showed enhanced IL-12, but decreased IL-10 secretion on Toll-like receptor stimulation with R848 that correlated with reduced lactate levels in the glioma cell coculture and a blockade of signal transducers and activators of transcription 3 phosphorylation. In vivo, diclofenac treatment diminished intratumoral lactate levels and resulted in a significant delay of glioma growth. Ex vivo analyses revealed that tumor-infiltrating DCs regained their capacity to produce IL-12 on R848 stimulation. Moreover, diclofenac reduced the number of tumor-infiltrating regulatory T cells and impaired the upregulation of the Treg activation marker CD25. Nevertheless, a single intratumoral injection of R848 combined with diclofenac failed to induce an additional survival advantage in glioma-bearing mice. Further analyses illustrated that the presence of diclofenac during T-cell activation compromised INF-γ production and T-cell proliferation, indicating that immunotherapeutic approaches have to be carefully timed when combined with diclofenac. In summary, diclofenac appears as an attractive agent for targeting lactate production and counteracting local immune suppression in malignant gliomas.

Targeting melanoma metastasis and immunosuppression with a new mode of melanoma inhibitory activity (MIA) protein inhibition.

Melanoma is the most aggressive form of skin cancer, with fast progression and early dissemination mediated by the melanoma inhibitory activity (MIA) protein. Here, we discovered that dimerization of MIA is required for functional activity through mutagenesis of MIA which showed the correlation between dimerization and functional activity. We subsequently identified the dodecapeptide AR71, which prevents MIA dimerization and thereby acts as a MIA inhibitor. Two-dimensional nuclear magnetic resonance (NMR) spectroscopy demonstrated the binding of AR71 to the MIA dimerization domain, in agreement with in vitro and in vivo data revealing reduced cell migration, reduced formation of metastases and increased immune response after AR71 treatment. We believe AR71 is a lead structure for MIA inhibitors. More generally, inhibiting MIA dimerization is a novel therapeutic concept in melanoma therapy.

Early changes in the liver-soluble proteome from mice fed a nonalcoholic steatohepatitis inducing diet.

Despite the increasing incidence of nonalcoholic steatohepatitis (NASH) with the rise in lifestyle-related diseases such as the metabolic syndrome, little is known about the changes in the liver proteome that precede the onset of inflammation and fibrosis. Here, we investigated early changes in the liver-soluble proteome of female C57BL/6N mice fed an NASH-inducing diet by 2D-DIGE and nano-HPLC-MS/MS. In parallel, histology and measurements of hepatic content of triglycerides, cholesterol and intermediates of the methionine cycle were performed. Hepatic steatosis manifested itself after 2 days of feeding, albeit significant changes in the liver-soluble proteome were not evident before day 10 in the absence of inflammatory or fibrotic signs. Proteomic alterations affected mainly energy and amino acid metabolism, detoxification processes, urea cycle, and the one-carbon/S-adenosylmethionine pathways. Additionally, intermediates of relevant affected pathways were quantified from liver tissue, confirming the findings from the proteomic analysis.