Akiyoshi Hirayama

Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases including cardiovascular, renal, and autoimmune diseases, viral and bacterial infections and, importantly, cancers. Saliva-based diagnostics, particularly those based on metabolomics technology, are emerging and offer a promising clinical strategy, characterizing the association between salivary analytes and a particular disease. Here, we conducted a comprehensive metabolite analysis of saliva samples obtained from 215 individuals (69 oral, 18 pancreatic and 30 breast cancer patients, 11 periodontal disease patients and 87 healthy controls) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS). We identified 57 principal metabolites that can be used to accurately predict the probability of being affected by each individual disease. Although small but significant correlations were found between the known patient characteristics and the quantified metabolites, the profiles manifested relatively higher concentrations of most of the metabolites detected in all three cancers in comparison with those in people with periodontal disease and control subjects. This suggests that cancer-specific signatures are embedded in saliva metabolites. Multiple logistic regression models yielded high area under the receiver-operating characteristic curves (AUCs) to discriminate healthy controls from each disease. The AUCs were 0.865 for oral cancer, 0.973 for breast cancer, 0.993 for pancreatic cancer, and 0.969 for periodontal diseases. The accuracy of the models was also high, with cross-validation AUCs of 0.810, 0.881, 0.994, and 0.954, respectively. Quantitative information for these 57 metabolites and their combinations enable us to predict disease susceptibility. These metabolites are promising biomarkers for medical screening. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-009-0178-y) contains supplementary material, which is available to authorized users.

Most cancer cells predominantly produce energy by glycolysis rather than oxidative phosphorylation via the tricarboxylic acid (TCA) cycle, even in the presence of an adequate oxygen supply (Warburg effect). However, little has been reported regarding the direct measurements of global metabolites in clinical tumor tissues. Here, we applied capillary electrophoresis time-of-flight mass spectrometry, which enables comprehensive and quantitative analysis of charged metabolites, to simultaneously measure their levels in tumor and grossly normal tissues obtained from 16 colon and 12 stomach cancer patients. Quantification of 94 metabolites in colon and 95 metabolites in stomach involved in glycolysis, the pentose phosphate pathway, the TCA and urea cycles, and amino acid and nucleotide metabolisms resulted in the identification of several cancer-specific metabolic traits. Extremely low glucose and high lactate and glycolytic intermediate concentrations were found in both colon and stomach tumor tissues, which indicated enhanced glycolysis and thus confirmed the Warburg effect. Significant accumulation of all amino acids except glutamine in the tumors implied autophagic degradation of proteins and active glutamine breakdown for energy production, i.e., glutaminolysis. In addition, significant organ-specific differences were found in the levels of TCA cycle intermediates, which reflected the dependency of each tissue on aerobic respiration according to oxygen availability. The results uncovered unexpectedly poor nutritional conditions in the actual tumor microenvironment and showed that capillary electrophoresis coupled to mass spectrometry-based metabolomics, which is capable of quantifying the levels of energy metabolites in tissues, could be a powerful tool for the development of novel anticancer agents that target cancer-specific metabolism.

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disease characterized by selective degeneration of dopaminergic neurons in the substantia nigra (SN). The familial form of PD, PARK2, is caused by mutations in the parkin gene. parkin-knockout mouse models show some abnormalities, but they do not fully recapitulate the pathophysiology of human PARK2. RESULTS: Here, we generated induced pluripotent stem cells (iPSCs) from two PARK2 patients. PARK2 iPSC-derived neurons showed increased oxidative stress and enhanced activity of the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. iPSC-derived neurons, but not fibroblasts or iPSCs, exhibited abnormal mitochondrial morphology and impaired mitochondrial homeostasis. Although PARK2 patients rarely exhibit Lewy body (LB) formation with an accumulation of α-synuclein, α-synuclein accumulation was observed in the postmortem brain of one of the donor patients. This accumulation was also seen in the iPSC-derived neurons in the same patient. CONCLUSIONS: Thus, pathogenic changes in the brain of a PARK2 patient were recapitulated using iPSC technology. These novel findings reveal mechanistic insights into the onset of PARK2 and identify novel targets for drug screening and potential modified therapies for PD.

Significance Metabolic reprogramming is one of the hallmarks of cancer. However, the underlying mechanisms that regulate cancer metabolism are poorly understood. Here we performed multiomics-based analysis of paired normal–tumor tissues from patients with colorectal cancer, which revealed that the protooncogene protein MYC regulated global metabolic reprogramming of colorectal cancer by modulating 215 metabolic reactions. Importantly, this metabolic reprogramming occurred in a manner not associated with specific gene mutations in colorectal carcinogenesis. For many years, small-molecule or biologic inhibitors of MYC have been required. Here we demonstrate that knockdown of MYC downstream pyrimidine synthesis genes contributes to the suppression of colorectal cancer cell proliferation similar to MYC, and thus pyrimidine synthesis pathways could be potential targets for colorectal cancer therapy.

Metabolic changes in response to histidine starvation were observed in histidine-auxotrophic Escherichia coli using a capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS)-based metabolomics technique. Prior to the analysis, we prepared an E. coli metabolome list of 727 metabolites reported in the literature. An improved method for metabolite extraction was developed, which resulted in higher extraction efficiency in phosphate-rich metabolites, e.g., ATP and GTP. Based on the results, 375 charged, hydrophilic intermediates in primary metabolisms were analysed simultaneously, providing quantitative data of 198 metabolites. We confirmed that the intracellular levels of intermediates in histidine biosynthesis are rapidly accumulated in response to a drop in histidine level under histidine-starved conditions. Simultaneously, disciplined responses were observed in the glycolysis, tricarboxylic acid cycle, and amino acid and nucleotide biosynthesis pathways as regulated by amino acid starvation.