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Key Points Along with other 'omics' approaches, metabolomics — the comprehensive analysis of all metabolites in a system — represents a change from the traditional analysis of single genes, transcripts, proteins or metabolites Improvements in analytical techniques and pattern-recognition methods have led to a rise in the numbers of untargeted and targeted metabolic studies that are being performed Understanding metabolic changes that are specifically associated with the pathogenesis of autoimmune diseases should lead to novel insights into disease mechanisms and to new strategies for treatment of rheumatic diseases The feasibility of metabolomics for biomarker discovery in rheumatology is supported by the assumption that metabolites are important players in biological systems and that diseases cause disruption of metabolic pathways In the setting of inflammatory diseases, metabolic profiling has potential applications in diagnosis, monitoring and defining disease pathogenesis. This Review focuses on metabolomic studies in rheumatic diseases, including discussion of state-of-the-art technologies, recent insights into disease mechanisms and treatment targets, and the feasibility of metabolomics for biomarker discovery. Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases.

Sacituzumab Govitecan (SG) is an antibody-drug conjugate that has demonstrated efficacy in patients with TROP-2 expressing epithelial cancers. In a xenograft model of intracranial breast cancer, SG inhibited tumor growth and increased mouse survival. We conducted a prospective window-of-opportunity trial (NCT03995706) at the University of Texas Health Science Center at San Antonio to examine the intra-tumoral concentrations and intracranial activity of SG in patients undergoing craniotomy for breast cancer with brain metastases (BCBM) or recurrent glioblastoma (rGBM). We enrolled 25 patients aged ≥18 years diagnosed with BCBM and rGBM to receive a single intravenous dose of SG at 10 mg/kg given one day before resection and continued on days 1 and 8 of 21-day cycles following recovery. The PFS was 8 months and 2 months for BCBM and rGBM cohorts, respectively. The OS was 35.2 months and 9.5 months, respectively. Grade≥3 AE included neutropenia (28%), hypokalemia (8%), seizure (8%), thromboembolic event (8%), urinary tract infection (8%) and muscle weakness of the lower limb (8%). In post-surgical tissue, the median total SN-38 was 249.8 ng/g for BCBM and 104.5 ng/g for rGBM, thus fulfilling the primary endpoint. Biomarker analysis suggests delivery of payload by direct release at target site and that hypoxic changes do not drive indirect release. Secondary endpoint of OS was 35.2 months for the BCBM cohort and 9.5 months for rGBM. Non-planned exploratory endpoint of ORR was 38% for BCBM and 29%, respectively. Exploratory endpoint of Trop-2 expression was observed in 100% of BCBM and 78% of rGBM tumors. In conclusion, SG was found to be well tolerated with adequate penetration into intracranial tumors and promising preliminary activity within the CNS. Trial Registration: Trial (NCT03995706) enrolled at Clinical Trials.gov as Neuro/Sacituzumab Govitecan/Breast Brain Metastasis/Glioblastoma/Ph 0: https://clinicaltrials.gov/study/NCT03995706?cond=NCT03995706 . Sacituzumab Govitecan, TROP-2 targeted antibody drug conjugate, is effective for the treatment of breast cancer, but its potential utility for the treatment of breast cancer brain metastasis and recurrent glioblastoma is unclear. Here, the authors present a window-of-opportunity phase 0 trial reporting the central nervous system penetrance and intracranial efficacy of Sacituzumab Govitecan.

Background Fatty acid synthase (FASN) expression is associated with a more aggressive breast cancer phenotype and is regulated downstream of receptor tyrosine kinase (RTK) signaling pathways. Recently, post transcriptional regulation of lipogenic transcripts have been demonstrated as being mediated downstream of serine-arginine rich protein kinase 2 (SRPK2), which acts to phosphorylate serine-arginine rich splicing factors (SRSFs), resulting in RNA binding and various RNA regulatory processes. Though post-transcriptional regulation of FASN has been studied previously, the upstream mediators of these pathways have not been elucidated. Methods Western blotting and RT-qPCR were utilized to demonstrate alterations in FASN and mRNA expression upon modulation of the IGF-1-mTORC1-SRPK2 pathway by small molecule inhibitors or RNAi mediated silencing. RNA stability was accessed by using the transcriptional inhibitor actinomycin-D followed by RT-qPCR. Further, we employed RNA-immunoprecipitation to demonstrate the direct binding of SRSF-1 to FASN transcripts. Results In the current study, we demonstrated an IGF-1 induced increase in FASN mRNA and protein expression that was attenuated by mTORC1 inhibition. This mTORC1 inhibition also resulted in decreases in total and nuclear p-SRPK2 in response to IGF-1 exposure. Upon SRPK2 knockdown and inhibition, we observed a decrease in FASN protein and mRNA stability, respectively, in response to IGF-1 exposure that was specific to triple negative and HER2+ breast cancer cell lines. As we explored further, IGF-1 exposure resulted in an altered localization of eGFP expressed SRSF-1, pEGFP-SRSF-1 that was rescued upon both SRPK2 knockdown and mTORC1 inhibition. Further, we observed an increase binding of SRSF-1 to FASN RNA upon IGF-1 exposure, which was abrogated by SRPK2 knockdown. Conclusion These current findings establish a potential IGF-1-mTORC1-SRPK2-FASN axis in breast cancer, which could be a potential therapeutic target for cancers that overexpress FASN and components of the IGF-1R pathway.

Background RNA-binding proteins (RBPs) function as master regulators of gene expression. Alterations in RBP expression and function are often observed in cancer and influence critical pathways implicated in tumor initiation and growth. Identification and characterization of oncogenic RBPs and their regulatory networks provide new opportunities for targeted therapy. Results We identify the RNA-binding protein SERBP1 as a novel regulator of glioblastoma (GBM) development. High SERBP1 expression is prevalent in GBMs and correlates with poor patient survival and poor response to chemo- and radiotherapy. SERBP1 knockdown causes delay in tumor growth and impacts cancer-relevant phenotypes in GBM and glioma stem cell lines. RNAcompete identifies a GC-rich region as SERBP1-binding motif; subsequent genomic and functional analyses establish SERBP1 regulation role in metabolic routes preferentially used by cancer cells. An important consequence of these functions is SERBP1 impact on methionine production. SERBP1 knockdown decreases methionine levels causing a subsequent reduction in histone methylation as shown for H3K27me3 and upregulation of genes associated with neurogenesis, neuronal differentiation, and function. Further analysis demonstrates that several of these genes are downregulated in GBM, potentially through epigenetic silencing as indicated by the presence of H3K27me3 sites. Conclusions SERBP1 is the first example of an RNA-binding protein functioning as a central regulator of cancer metabolism and indirect modulator of epigenetic regulation in GBM. By bridging these two processes, SERBP1 enhances glioma stem cell phenotypes and contributes to GBM poorly differentiated state.

Fatty acid profiling on gas chromatography–mass spectrometry (GC–MS) platforms is typically performed offline by manually derivatizing and analyzing small batches of samples. A GC–MS system with a fully integrated robotic autosampler can significantly improve sample handling, standardize data collection, and reduce the total hands-on time required for sample analysis. In this study, we report an optimized high-throughput GC–MS-based methodology that utilizes trimethyl sulfonium hydroxide (TMSH) as a derivatization reagent to convert fatty acids into fatty acid methyl esters. An automated online derivatization method was developed, in which the robotic autosampler derivatizes each sample individually and injects it into the GC–MS system in a high-throughput manner. This study investigated the robustness of automated TMSH derivatization by comparing fatty acid standards and lipid extracts, derivatized manually in batches and online automatically from four biological matrices. Automated derivatization improved reproducibility in 19 of 33 fatty acid standards, with nearly half of the 33 confirmed fatty acids in biological samples demonstrating improved reproducibility when compared to manually derivatized samples. In summary, we show that the online TMSH-based derivatization methodology is ideal for high-throughput fatty acid analysis, allowing rapid and efficient fatty acid profiling, with reduced sample handling, faster data acquisition, and, ultimately, improved data reproducibility.

Background Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients’ metabolomic profiles in blood, utilizing 1 H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA). Methods Nineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700 MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS. Results Analysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-α synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels. Conclusion The relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA.

The tumor microenvironment is emerging as an important therapeutic target. Most studies, however, are focused on the protein components, and relatively little is known of how the microenvironmental metabolome might influence tumor survival. In this study, we examined the metabolic profiles of paired bone marrow (BM) and peripheral blood (PB) samples from 10 children with acute lymphoblastic leukemia (ALL). BM and PB samples from the same patient were collected at the time of diagnosis and after 29 days of induction therapy, at which point all patients were in remission. We employed two analytical platforms, high-resolution magnetic resonance spectroscopy and gas chromatography-mass spectrometry, to identify and quantify 102 metabolites in the BM and PB. Standard ALL therapy, which includes l-asparaginase, completely removed circulating asparagine, but not glutamine. Statistical analyses of metabolite correlations and network reconstructions showed that the untreated BM microenvironment was characterized by a significant network-level signature: a cluster of highly correlated lipids and metabolites involved in lipid metabolism (p<0.006). In contrast, the strongest correlations in the BM upon remission were observed among amino acid metabolites and derivatives (p<9.2 × 10(-10)). This study provides evidence that metabolic characterization of the cancer niche could generate new hypotheses for the development of cancer therapies.

High-throughput screening of a natural compound library was performed to identify the most efficacious combinatorial treatment on prostate cancer. Ursolic acid, curcumin and resveratrol were selected for further analyses and administered in vivo via the diet, either alone or in combination, in a mouse allograft model of prostate cancer. All possible combinations of these natural compounds produced synergistic effects on tumor size and weight, as predicted in the screens. A subsequent untargeted metabolomics and metabolic flux analysis using isotopically labeled glutamine indicated that the compound combinations modulated glutamine metabolism. In addition, ASCT2 levels and STAT3, mTORC1 and AMPK activity were modulated to a greater extent by the combinations compared to the individual compounds. Overall, this approach can be useful for identifying synergistic combinations of natural compounds for chemopreventive and therapeutic interventions. Prostate cancer: Combination of natural compounds limits tumor growth Combinations of two molecules found naturally in edible plants synergistically help reduce tumor growth in a mouse model of prostate cancer. Stefano Tiziani and John DiGiovanni from the University of Texas at Austin, and colleagues screened a library of 142 natural compounds for the effects of each molecule, alone or in combination, on the viability of cells from mouse and human prostate cancer cell lines. Amongst other promising combinations, the researchers identified ursolic acid and curcumin as the most promising combination for inhibiting tumor growth. (These compounds are found naturally in apple peels and turmeric, respectively.) In mice with implanted prostate tumors, the two compounds synergistically reduced tumor volume and weight, while in cell culture the researchers showed that the compound-combination strategy modulated metabolism of a critical amino acid and other cell signaling pathways.

Perturbing redox homeostasis potentially constitutes a selective cancer-killing strategy. An engineered human enzyme, cyst(e)inase that degrades extracellular cysteine ( l -Cys) and cystine (CSSC) leading to depletion of intracellular l -Cys and glutathione (GSH) was evaluated for its effects on pancreatic cancer cell lines. Cyst(e)inase caused oxidative stress and apoptosis in only Panc1 cells, whereas MIA-PaCa2 and BxPC3 cells demonstrated survival under conditions of cyst(e)inase-mediated l -Cys depletion through maintenance of mitochondrial metabolism and lower levels of reactive oxygen species (ROS). A correlation was also observed between thioredoxin 1 protein levels and resistance to cyst(e)inase treatment. Notably, cyst(e)inase in combination with auranofin, a thioredoxin reductase inhibitor, caused a synergistic increase in mitochondrial ROS and apoptosis and inhibition of mitophagy in the more resistant cells. In addition, auranofin treatment sensitized the more resistant pancreatic cancer xenografts to cyst(e)inase without systemic toxicity. These data provide strong rationale to further investigate therapeutic strategies that target multiple antioxidant pathways for treatment of pancreatic ductal adenocarcinoma.

To maintain core body temperature in cold conditions, mammals activate a complex multi-organ metabolic response for heat production. White adipose tissue (WAT) primarily functions as an energy reservoir, while brown adipose tissue (BAT) is activated during cold exposure to generate heat from nutrients. Both BAT and WAT undergo specific metabolic changes during acute cold exposure. Here, we use an untargeted metabolomics approach to characterize the initial metabolic response to cold exposure in multiple adipose tissue depots in mice. Results demonstrate dramatically distinct metabolic responses during cold exposure in BAT and WAT. Amino acids, nucleotide pathways, and metabolites involved in redox regulation were greatly affected 4 hours post-exposure in BAT, while no polar metabolites were observed to significantly change in WAT depots up to 6 hours post exposure. Lipid metabolism was activated early (2 hours) in both BAT and the subcutaneous WAT depots, with the most striking change being observed in the modulation of diglyceride and monoglyceride levels in BAT. Overall, these data provide a timeline of global thermogenic metabolism in adipose depots during acute cold exposure. We have highlighted differences in visceral and subcutaneous WAT thermogenic metabolism and demonstrate the distinct metabolism of BAT during cold exposure.