High-Resolution Magic-Angle-Spinning NMR in Revealing Hepatoblastoma Hallmarks.

Cancer is one of the leading causes of death in children and adolescents worldwide; among the types of liver cancer, hepatoblastoma (HBL) is the most common in childhood. Although it affects only two to three individuals in a million, it is mostly asymptomatic at diagnosis, so by the time it is detected it has already advanced. There are specific recommendations regarding HBL treatment, and ongoing studies to stratify the risks of HBL, understand the pathology, and predict prognostics and survival rates. Although magnetic resonance imaging spectroscopy is frequently used in diagnostics of HBL, high-resolution magic-angle-spinning (HR-MAS) NMR spectroscopy of HBL tissues is scarce. Using this technique, we studied the alterations among tissue metabolites of ex vivo samples from (a) HBL and non-cancer liver tissues (NCL), (b) HBL and adjacent non-tumor samples, and (c) two regions of the same HBL samples, one more centralized and the other at the edge of the tumor. It was possible to identify metabolites in HBL, then metabolites from the HBL center and the border samples, and link them to altered metabolisms in tumor tissues, highlighting their potential as biochemical markers. Metabolites closely related to liver metabolisms such as some phospholipids, triacylglycerides, fatty acids, glucose, and amino acids showed differences between the tissues.

Metabolomics by NMR Combined with Machine Learning to Predict Neoadjuvant Chemotherapy Response for Breast Cancer.

Neoadjuvant chemotherapy (NACT) is offered to patients with operable or inoperable breast cancer (BC) to downstage the disease. Clinical responses to NACT may vary depending on a few known clinical and biological features, but the diversity of responses to NACT is not fully understood. In this study, 80 women had their metabolite profiles of pre-treatment sera analyzed for potential NACT response biomarker candidates in combination with immunohistochemical parameters using Nuclear Magnetic Resonance (NMR). Sixty-four percent of the patients were resistant to chemotherapy. NMR, hormonal receptors (HR), human epidermal growth factor receptor 2 (HER2), and the nuclear protein Ki67 were combined through machine learning (ML) to predict the response to NACT. Metabolites such as leucine, formate, valine, and proline, along with hormone receptor status, were discriminants of response to NACT. The glyoxylate and dicarboxylate metabolism was found to be involved in the resistance to NACT. We obtained an accuracy in excess of 80% for the prediction of response to NACT combining metabolomic and tumor profile data. Our results suggest that NMR data can substantially enhance the prediction of response to NACT when used in combination with already known response prediction factors.

Circulating Metabolites as Biomarkers of Disease in Patients with Mesial Temporal Lobe Epilepsy.

A major challenge in the clinical management of patients with mesial temporal lobe epilepsy (MTLE) is identifying those who do not respond to antiseizure medication (ASM), allowing for the timely pursuit of alternative treatments such as epilepsy surgery. Here, we investigated changes in plasma metabolites as biomarkers of disease in patients with MTLE. Furthermore, we used the metabolomics data to gain insights into the mechanisms underlying MTLE and response to ASM. We performed an untargeted metabolomic method using magnetic resonance spectroscopy and multi- and univariate statistical analyses to compare data obtained from plasma samples of 28 patients with MTLE compared to 28 controls. The patients were further divided according to response to ASM for a supplementary and preliminary comparison: 20 patients were refractory to treatment, and eight were responsive to ASM. We only included patients using carbamazepine in combination with clobazam. We analyzed the group of patients and controls and found that the profiles of glucose (p = 0.01), saturated lipids (p = 0.0002), isoleucine (p = 0.0001), ß-hydroxybutyrate (p = 0.0003), and proline (p = 0.02) were different in patients compared to controls (p < 0.05). In addition, we found some suggestive metabolites (without enough predictability) by multivariate analysis (VIP scores > 2), such as lipoproteins, lactate, glucose, unsaturated lipids, isoleucine, and proline, that might be relevant to the process of pharmacoresistance in the comparison between patients with refractory and responsive MTLE. The identified metabolites for the comparison between MTLE patients and controls were linked to different biological pathways related to cell-energy metabolism and pathways related to inflammatory processes and the modulation of neurotransmitter release and activity in MTLE. In conclusion, in addition to insights into the mechanisms underlying MTLE, our results suggest that plasma metabolites may be used as disease biomarkers. These findings warrant further studies exploring the clinical use of metabolites to assist in decision-making when treating patients with MTLE.

A Metabonomic View on Wilms Tumor by High-Resolution Magic-Angle Spinning Nuclear Magnetic Resonance Spectroscopy.

Pediatric cancer NMR-metabonomics might be a powerful tool to discover modified biochemical pathways in tumor development, improve cancer diagnosis, and, consequently, treatment. Wilms tumor (WT) is the most common kidney tumor in young children whose genetic and epigenetic abnormalities lead to cell metabolism alterations, but, so far, investigation of metabolic pathways in WT is scarce. We aimed to explore the high-resolution magic-angle spinning nuclear magnetic resonance (HR-MAS NMR) metabonomics of WT and normal kidney (NK) samples. For this study, 14 WT and 7 NK tissue samples were obtained from the same patients and analyzed. One-dimensional and two-dimensional HR-MAS NMR spectra were processed, and the one-dimensional NMR data were analyzed using chemometrics. Chemometrics enabled us to elucidate the most significant differences between the tumor and normal tissues and to discover intrinsic metabolite alterations in WT. The metabolic differences in WT tissues were revealed by a validated PLS-DA applied on HR-MAS T2-edited 1H-NMR and were assigned to 16 metabolites, such as lipids, glucose, and branched-chain amino acids (BCAAs), among others. The WT compared to NK samples showed 13 metabolites with increased concentrations and 3 metabolites with decreased concentrations. The relative BCAA concentrations were decreased in the WT while lipids, lactate, and glutamine/glutamate showed increased levels. Sixteen tissue metabolites distinguish the analyzed WT samples and point to altered glycolysis, glutaminolysis, TCA cycle, and lipid and BCAA metabolism in WT. Significant variation in the concentrations of metabolites, such as glutamine/glutamate, lipids, lactate, and BCAAs, was observed in WT and opened up a perspective for their further study and clinical validation.

Metabolomics in degenerative brain diseases.

Among the most studied diseases that affect the central nervous system are Parkinson's, Alzheimer's, and Huntington's diseases, but the lack of effective biomarkers, accurate diagnosis, and precise treatment for each of them is currently an issue. Due to the contribution of biomarkers in supporting diagnosis, many recent efforts have focused on their identification and validation at the beginning or during the progression of the mental illness. Metabolome reveals the metabolic processes that result from protein activities under the guided gene expression and environmental factors, either in healthy or pathological conditions. In this context, metabolomics has proven to be a valuable approach. Currently, magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the most commonly used bioanalytical techniques for metabolomics. MS-assisted profiling is considered the most versatile technique, and the NMR is the most reproductive. However, each one of them has its drawbacks. In this review, we summarized several alterations in metabolites that have been reported for these three classic brain diseases using MS and NMR-based research, which might suggest some possible biomarkers to support the diagnosis and/or new targets for their treatment.

A case series of platelet rich plasma in chronic venous ulcers.

INTRODUCTION: Venous ulcers are the most common type of leg wounds (80%) and the main cause is chronic venous insufficiency. Autologous platelet-rich plasma (PRP) is a potential wound healing treatment due to its great variety of growth factors. The aim of this study was to describe in a case series the results of poor-leukocyte PRP (P-PRP) or saline for the treatment of chronic non-healing ulcers of the lower extremity. METHODS: Eight patients were treated according to the topical therapy: saline solution or P-PRP gel. All patients used double compression stocks and were assisted by a vascular practitioner for up to 12 months or until wound healing. The treatment was performed weekly with cleaning of the affected area, macroscopic evaluation (area measurement and photos) and P-PRP or saline application, and closure with Tegaderm®. Trial Registration: Retrospectively approved by Brazilian Clinical Trials, register number RBR-7zhgb3 (http://www.ensaiosclinicos.gov.br/rg/RBR-7zhgb3/). RESULTS: All patients showed signs of wound healing with a reduction in wound size and ulcer numbers, but more evident with P-PRP application. CONCLUSIONS: The results suggested that P-PRP presented a better result when compared to saline solution in the healing process of long clinical course chronic venous ulcers, when associated to compressive stocks and topical care.

GLS2 is protumorigenic in breast cancers.

Many types of cancers have a well-established dependence on glutamine metabolism to support survival and growth, a process linked to glutaminase 1 (GLS) isoforms. Conversely, GLS2 variants often have tumor-suppressing activity. Triple-negative (TN) breast cancer (testing negative for estrogen, progesterone, and Her2 receptors) has elevated GLS protein levels and reportedly depends on exogenous glutamine and GLS activity for survival. Despite having high GLS levels, we verified that several breast cancer cells (including TN cells) express endogenous GLS2, defying its role as a bona fide tumor suppressor. Moreover, ectopic GLS2 expression rescued cell proliferation, TCA anaplerosis, redox balance, and mitochondrial function after GLS inhibition by the small molecule currently in clinical trials CB-839 or GLS knockdown of GLS-dependent cell lines. In several cell lines, GLS2 knockdown decreased cell proliferation and glutamine-linked metabolic phenotypes. Strikingly, long-term treatment of TN cells with another GLS-exclusive inhibitor bis-2'-(5-phenylacetamide-1,3,4-thiadiazol-2-yl)ethyl sulfide (BPTES) selected for a drug-resistant population with increased endogenous GLS2 and restored proliferative capacity. GLS2 was linked to enhanced in vitro cell migration and invasion, mesenchymal markers (through the ERK-ZEB1-vimentin axis under certain conditions) and in vivo lung metastasis. Of concern, GLS2 amplification or overexpression is linked to an overall, disease-free and distant metastasis-free worse survival prognosis in breast cancer. Altogether, these data establish an unforeseen role of GLS2 in sustaining tumor proliferation and underlying metastasis in breast cancer and provide an initial framework for exploring GLS2 as a novel therapeutic target.

Metabolomic Biomarkers in Mental Disorders: Bipolar Disorder and Schizophrenia.

Psychiatric disorders are some of the most impairing human diseases. Among them, bipolar disorder and schizophrenia are the most common. Both have complicated diagnostics due to their phenotypic, biological, and genetic heterogeneity, unknown etiology, and the underlying biological pathways, and molecular mechanisms are still not completely understood. Given the multifactorial complexity of these disorders, identification and implementation of metabolic biomarkers would assist in their early detection and diagnosis and facilitate disease monitoring and treatment responses. To date, numerous studies have utilized metabolomics to better understand psychiatric disorders, and findings from these studies have begun to converge. In this chapter, we briefly describe some of the metabolomic biomarkers found in these two disorders.

Guanylate-binding protein-1 is a potential new therapeutic target for triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is characterized by a lack of estrogen and progesterone receptor expression (ESR and PGR, respectively) and an absence of human epithelial growth factor receptor (ERBB2) amplification. Approximately 15-20% of breast malignancies are TNBC. Patients with TNBC often have an unfavorable prognosis. In addition, TNBC represents an important clinical challenge since it does not respond to hormone therapy. METHODS: In this work, we integrated high-throughput mRNA sequencing (RNA-Seq) data from normal and tumor tissues (obtained from The Cancer Genome Atlas, TCGA) and cell lines obtained through in-house sequencing or available from the Gene Expression Omnibus (GEO) to generate a unified list of differentially expressed (DE) genes. Methylome and proteomic data were integrated to our analysis to give further support to our findings. Genes that were overexpressed in TNBC were then curated to retain new potentially druggable targets based on in silico analysis. Knocking-down was used to assess gene importance for TNBC cell proliferation. RESULTS: Our pipeline analysis generated a list of 243 potential new targets for treating TNBC. We finally demonstrated that knock-down of Guanylate-Binding Protein 1 (GBP1 ), one of the candidate genes, selectively affected the growth of TNBC cell lines. Moreover, we showed that GBP1 expression was controlled by epidermal growth factor receptor (EGFR) in breast cancer cell lines. CONCLUSIONS: We propose that GBP1 is a new potential druggable therapeutic target for treating TNBC with enhanced EGFR expression.

Peracetic Acid Depolymerization of Biorefinery Lignin for Production of Selective Monomeric Phenolic Compounds.

Lignin is the largest source of renewable material with an aromatic skeleton. However, due to the recalcitrant and heterogeneous nature of the lignin polymer, it has been a challenge to effectively depolymerize lignin and produce high-value chemicals with high selectivity. In this study, a highly efficient lignin-to-monomeric phenolic compounds (MPC) conversion method based on peracetic acid (PAA) treatment was reported. PAA treatment of two biorefinery lignin samples, diluted acid pretreated corn stover lignin (DACSL) and steam exploded spruce lignin (SESPL), led to complete solubilization and production of selective hydroxylated monomeric phenolic compounds (MPC-H) and monomeric phenolic acid compounds (MPC-A) including 4-hydroxy-2-methoxyphenol, p-hydroxybenzoic acid, vanillic acid, syringic acid, and 3,4-dihydroxybenzoic acid. The maximized MPC yields obtained were 18 and 22 % based on the initial weight of the lignin in SESPL and DACSL, respectively. However, we found that the addition of niobium pentoxide catalyst to PAA treatment of lignin can significantly improve the MPC yields up to 47 %. The key reaction steps and main mechanisms involved in this new lignin-to-MPC valorization pathway were investigated and elucidated.