In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.

to wild-type DPD. Moreover, the band patterns observed in the immunoblots of blue native gels indicated that DPD dimerization is required for enzymatic activity in DPD.Thus, the detection of rare DPYD variants might facilitate severe adverse effect prediction of 5-FU-based chemotherapy in the Japanese population.

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The evaluation of Cytochrome P450 (CYP) enzymatic activity is essential to estimate drug pharmacokinetics. Numerous CYP allelic variants have been identified; the functional characterisation of these variants is required for their application in precision medicine. Results from heterologous expression systems using mammalian cells can be integrated in in vivo studies; however, other systems such as E. coli, bacteria, yeast, and baculoviruses are generally used owing to the difficulty in expressing high CYP levels in mammalian cells. Here, by optimising transfection and supplementing conditions, we developed a heterologous expression system using 293FT cells to evaluate the enzymatic activities of three CYP isoforms (CYP1A2, CYP2C9, and CYP3A4). Moreover, we established co-expression with cytochrome P450 oxidoreductase and cytochrome b5. This expression system would be a potential complementary or beneficial alternative approach for the pharmacokinetic evaluation of clinically used and developing drugs in vitro.

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Activating mutations in KEAP1-NRF2 are frequently found in tumours of the lung, oesophageous and liver, where they are associated with aggressive growth, resistance to cancer therapies, and low overall survival. Despite the fact that NRF2 is a validated driver of tumorigenesis and chemotherapeutic resistance, there are currently no approved drugs which can inhibit its activity. Therefore, there is an urgent clinical need to identify NRF2-selective cancer therapies. To this end, we developed a novel synthetic lethal assay, based on fluorescently labelled isogenic wild-type and Keap1 knockout cell lines, in order to screen for compounds which selectively kill cells in an NRF2-dependent manner. Through this approach, we identified three compounds based on the geldanamycin scaffold which display synthetic lethality with NRF2. Mechanistically, we show that NRF2 target genes metabolize the quinone-containing geldanamycin compounds into more potent HSP90 inhibitors, which enhances their cytotoxicity while simultaneously restricting the synthetic lethal effect to cells with aberrant NRF2 activity. As all three of the geldanamycin-derived compounds have been used in clinical trials, they represent ideal candidates for drug repositioning to target the currently untreatable NRF2 activity in cancer.

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Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.