論文

Overcoming resistance to immune checkpoint inhibitors is an important issue in patients with non-small-cell lung cancer (NSCLC). Transcriptome analysis shows that adenocarcinoma can be divided into three molecular subtypes: terminal respiratory unit (TRU), proximal proliferative (PP), and proximal inflammatory (PI), and squamous cell carcinoma (LUSQ) into four. However, the immunological characteristics of these subtypes are not fully understood. In this study, we investigated the immune landscape of NSCLC tissues in molecular subtypes using a multi-omics dataset, including tumor-infiltrating leukocytes (TILs) analyzed using flow cytometry, RNA sequences, whole exome sequences, metabolomic analysis, and clinicopathologic findings. In the PI subtype, the number of TILs increased and the immune response in the tumor microenvironment (TME) was activated, as indicated by high levels of tertiary lymphoid structures, and high cytotoxic marker levels. Patient prognosis was worse in the PP subtype than in other adenocarcinoma subtypes. Glucose transporter 1 (GLUT1) expression levels were upregulated and lactate accumulated in the TME of the PP subtype. This could lead to the formation of an immunosuppressive TME, including the inactivation of antigen-presenting cells. The TRU subtype had low biological malignancy and "cold" tumor-immune phenotypes. Squamous cell carcinoma (LUSQ) did not show distinct immunological characteristics in its respective subtypes. Elucidation of the immune characteristics of molecular subtypes could lead to the development of personalized immune therapy for lung cancer. Immune checkpoint inhibitors could be an effective treatment for the PI subtype. Glycolysis is a potential target for converting an immunosuppressive TME into an antitumorigenic TME in the PP subtype.

The activation and expansion of T cells that recognize cancer cells is an essential aspect to antitumor immunity. Tumors may escape destruction by the immune system through ectopic expression of inhibitory immune ligands typically exemplified by the PD-L1/PD-1 pathway. Here, we reveal another facet of tumor evasion from T cell surveillance. By secretome profiling of necrotic tumor cells, we identified an oncometabolite spermidine as a unique inhibitor of T cell receptor (TCR) signaling. Mechanistically, spermidine causes the downregulation of the plasma membrane cholesterol levels, resulting in the suppression of TCR clustering. Using syngeneic mouse models, we show that spermidine is abundantly detected in the tumor immune microenvironment (TIME) and that administration of the polyamine synthesis inhibitor effectively enhanced CD8+ T cell–dependent antitumor responses. Further, the combination of the polyamine synthesis inhibitor with anti-PD-1 immune checkpoint antibody resulted in a much stronger antitumor immune response. This study reveals an aspect of immunosuppressive TIME, wherein spermidine functions as a metabolic T cell checkpoint that may offer a unique approach for promoting tumor immunotherapy.

Cancer cachexia is a complex metabolic disorder accounting for ~20% of cancer-related deaths, yet its metabolic landscape remains unexplored. Here, we report a decrease in B vitamin-related liver enzymes as a hallmark of systemic metabolic changes occurring in cancer cachexia. Metabolomics of multiple mouse models highlights cachexia-associated reductions of niacin, vitamin B6, and a glycine-related subset of one-carbon (C1) metabolites in the liver. Integration of proteomics and metabolomics reveals that liver enzymes related to niacin, vitamin B6, and glycine-related C1 enzymes dependent on B vitamins decrease linearly with their associated metabolites, likely reflecting stoichiometric cofactor-enzyme interactions. The decrease of B vitamin-related enzymes is also found to depend on protein abundance and cofactor subtype. These metabolic/proteomic changes and decreased protein malonylation, another cachexia feature identified by protein post-translational modification analysis, are reflected in blood samples from mouse models and gastric cancer patients with cachexia, underscoring the clinical relevance of our findings.

Decitabine (DAC) is clinically used to treat myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Our genome-wide CRISPR-dCas9 activation screen using MDS-derived AML cells indicates that mitotic regulation is critical for DAC resistance. DAC strongly induces abnormal mitosis (abscission failure or tripolar mitosis) in human myeloid tumors at clinical concentrations, especially in those with TP53 mutations or antecedent hematological disorders. This DAC-induced mitotic disruption and apoptosis are significantly attenuated in DNMT1-depleted cells. In contrast, overexpression of Dnmt1, but not the catalytically inactive mutant, enhances DAC-induced mitotic defects in myeloid tumors. We also demonstrate that DAC-induced mitotic disruption is enhanced by pharmacological inhibition of the ATR-CLSPN-CHK1 pathway. These data challenge the current assumption that DAC inhibits leukemogenesis through DNMT1 inhibition and subsequent DNA hypomethylation and highlight the potent activity of DAC to disrupt mitosis through aberrant DNMT1-DNA covalent bonds.

Histone methyltransferase SETD1A is critical for acute myeloid leukemia (AML) cell survival, but the molecular mechanism driving SETD1A gene regulation remains elusive. To delineate the role of SETD1A, we utilize a protein degrader technology to induce rapid SETD1A degradation in AML cell lines. SETD1A degradation results in immediate downregulation of transcripts associated with DNA repair and heme biosynthesis pathways. CRISPR-based functional analyses and metabolomics reveal an essential role of SETD1A to maintain mitochondrial respiration in AML cells. These SETD1A targets are enriched in head-to-head (H2H) genes. SETD1A degradation disrupts a non-enzymatic SETD1A domain-dependent cyclin K function, increases the Ser5P RNA polymerase II (RNAPII) at the transcriptional start site (TSS), and induces the promoter-proximal pausing of RNAPII in a strand-specific manner. This study reveals a non-enzymatic role for SETD1A in transcriptional pause release and provides insight into the mechanism of RNAPII pausing and its function in cancer.

Cardiovascular disease is the most common comorbidity in patients with chronic kidney disease (CKD), affecting both their prognosis and quality of life. Cardiac fibrosis is common in patients with CKD with left ventricular diastolic dysfunction, and it is associated with increased risk of heart failure and mortality. Recent evidence suggests that high salt intake activates immune responses associated with local accumulation of sodium. We reported that high salt intake promotes cardiac inflammation in subtotal nephrectomized (Nx) mice. We investigated the effects of administration of MR16-1, a rat anti-mouse monoclonal interleukin (IL)-6 receptor antibody, in Nx mice with salt loading (Nx-salt). Expression of monocyte chemoattractant protein-1, tumor necrosis factor-α, IL-1β, and IL-6 mRNAs and macrophage infiltration was significantly reduced in the heart of Nx-salt mice treated with MR16-1 (Nx-salt-MR16-1) compared with Nx-salt mice treated with control rat rat IgG1 (Nx-salt-rat IgG1). Correspondingly, cardiac fibrosis was significantly attenuated in Nx-salt-MR16-1 mice compared with Nx-salt-rat IgG1 mice. Furthermore, in the heart of Nx-salt-MR16-1 mice, expression of mRNA for nicotinamide adenine dinucleotide phosphate oxidase-2, an oxidative stress marker, was significantly downregulated compared with Nx-salt-rat IgG1 mice. Increases in cardiac metabolites, including histidine and γ-butyrobetaine, were also reversed by IL-6 blockade treatment. In conclusion, IL-6 blockade exerts anti-inflammatory, antifibrotic, and partial antioxidative effects in the heart of Nx-salt mice.NEW & NOTEWORTHY In the present study, IL-6 blockade exerted anti-inflammatory, antifibrotic, and partial antioxidative effects on the hearts of mice with CKD on a high-salt diet. Therefore, IL-6 potentially mediates cardiac fibrosis induced by high salt intake in patients with CKD, a finding with therapeutic implications. Of note, the next therapeutic implication may simply be the reinforcement of low-salt diets or diuretics and further research on the anti-inflammatory effects of these measures rather than IL-6 blockade with high-salt diet.

Cancer-derived small extracellular vesicles (sEVs) are multifunctional particles with a lipid bilayer structure that are involved in cancer progression, such as malignant proliferation, distant metastasis, and cancer immunity evasion. The separation protocol used to isolate sEVs is an important process and thus, several have been developed, including ultracentrifugation (UC), size exclusion chromatography (SEC), and affinity purification using antibodies against sEV surface antigens. However, the effects of different separation methods on sEV components have not been adequately examined. Here, we developed a semi-automated system for collecting sEVs by combining SEC and preparative high-performance liquid chromatography and applied it to metabolome analysis. The developed SEC system could recover sEVs more efficiently and non-destructively than UC, suggesting that it is an appropriate recovery method for metabolic analysis and reflects biological conditions. Furthermore, using the developed SEC system, we performed metabolome analysis of sEVs from isocitrate dehydrogenase 1 (IDH)-mutated human colon HCT116 cells, which produce the oncogenic metabolite, 2-hydroxyglutaric acid (2-HG). IDH1-mutated HCT116 cells released significantly more sEVs than wild-type (WT) cells. The metabolomic profiles of IDH1 mutant and WT cells showed distinct differences between the cells and their sEVs. Notably, in IDH mutant cells, large amounts of 2-HG were detected not only in cells, but also in sEVs. These results indicate that the SEC system we developed has wide potential applications in sEVs research.

A high-salt diet significantly impacts various diseases, ilncluding cancer and immune diseases. Recent studies suggest that the high-salt/hyperosmotic environment in the body may alter the chronic properties of cancer and immune cells in the disease context. However, little is known about the acute metabolic changes in hyperosmotic stress. Here, we found that hyperosmotic stress for a few minutes induces Warburg-like metabolic remodeling in HeLa and Raw264.7 cells and suppresses fatty acid oxidation. Regarding Warburg-like remodeling, we determined that the pyruvate dehydrogenase phosphorylation status was altered bidirectionally (high in hyperosmolarity and low in hypoosmolarity) to osmotic stress in isolated mitochondria, suggesting that mitochondria themselves have an acute osmosensing mechanism. Additionally, we demonstrate that Warburg-like remodeling is required for HeLa cells to maintain ATP levels and survive under hyperosmotic conditions. Collectively, our findings suggest that cells exhibit acute metabolic remodeling under osmotic stress via the regulation of pyruvate dehydrogenase phosphorylation by direct osmosensing within mitochondria.

Cancer cells coordinate the mTORC1 signals and the related metabolic pathways to robustly and rapidly grow in response to nutrient conditions. Although a CNC-family transcription factor NRF3 promotes cancer development, the biological relevance between NRF3 function and mTORC1 signals in cancer cells remains unknown. Hence, we showed that NRF3 contributes to cancer cell viability through mTORC1 activation in response to amino acids, particularly arginine. NRF3 induced SLC38A9 and RagC expression for the arginine-dependent mTORC1 recruitment onto lysosomes, and it also enhanced RAB5-mediated bulk macropinocytosis and SLC7A1-mediated selective transport for arginine loading into lysosomes. Besides, the inhibition of the NRF3–mTORC1 axis impaired mitochondrial function, leading to cancer cell apoptosis. Consistently, the aberrant upregulation of the axis caused tumor growth and poor prognosis. In conclusion, this study sheds light on the unique function of NRF3 in arginine-dependent mTORC1 activation and the pathophysiological aspects of the NRF3–mTORC1 axis in cancer development.

Insulin regulates various cellular metabolic processes by activating specific isoforms of the Akt family of kinases. Here, we elucidated metabolic pathways that are regulated in an Akt2-dependent manner. We constructed a transomics network by quantifying phosphorylated Akt substrates, metabolites, and transcripts in C2C12 skeletal muscle cells with acute, optogenetically induced activation of Akt2. We found that Akt2-specific activation predominantly affected Akt substrate phosphorylation and metabolite regulation rather than transcript regulation. The transomics network revealed that Akt2 regulated the lower glycolysis pathway and nucleotide metabolism and cooperated with Akt2-independent signaling to promote the rate-limiting steps in these processes, such as the first step of glycolysis, glucose uptake, and the activation of the pyrimidine metabolic enzyme CAD. Together, our findings reveal the mechanism of Akt2-dependent metabolic pathway regulation, paving the way for Akt2-targeting therapeutics in diabetes and metabolic disorders.

Interactions between various molecular species in biological phenomena give rise to numerous networks. The investigation of these networks, including their statistical and biochemical interactions, supports a deeper understanding of biological phenomena. The clustering of nodes associated with molecular species and enrichment analysis is frequently applied to examine the biological significance of such network structures. However, these methods focus on delineating the function of a node. As such, in-depth investigations of the edges, which are the connections between the nodes, are rarely explored. In the current study, we aimed to investigate the functions of the edges rather than the nodes. To accomplish this, for each network, we categorized the edges and defined the edge type based on their biological annotations. Subsequently, we used the edge type to compare the network structures of the metabolome and transcriptome in the livers of healthy (wild-type) and obese (ob/ob) mice following oral glucose administration (OGTT). The findings demonstrate that the edge type can facilitate the characterization of the state of a network structure, thereby reducing the information available through datasets containing the OGTT response in the metabolome and transcriptome.

Oncometabolites, such as D/L-2-hydroxyglutarate (2HG), have directly been implicated in carcinogenesis; however, the underlying molecular mechanisms remain poorly understood. Here, we showed that the levels of the L-enantiomer of 2HG (L2HG) were specifically increased in colorectal cancer (CRC) tissues and cell lines compared with the D-enantiomer of 2HG (D2HG). In addition, L2HG increased the expression of ATF4 and its target genes by activating the mTOR pathway, which subsequently provided amino acids and improved the survival of CRC cells under serum deprivation. Downregulating the expression of L-2-hydroxyglutarate dehydrogenase (L2HGDH) and oxoglutarate dehydrogenase (OGDH) increased L2HG levels in CRC, thereby activating mTOR-ATF4 signaling. Furthermore, L2HGDH overexpression reduced L2HG-mediated mTOR-ATF4 signaling under hypoxia, whereas L2HGDH knockdown promoted tumor growth and amino acid metabolism in vivo. Together, these results indicate that L2HG ameliorates nutritional stress by activating the mTOR-ATF4 axis and thus could be a potential therapeutic target for CRC.

Choline supplies methyl groups for regeneration of methionine and the methyl donor S-adenosylmethionine in the liver. Here, we report that the catabolism of membrane phosphatidylcholine (PC) into water-soluble glycerophosphocholine (GPC) by the phospholipase/lysophospholipase PNPLA8-PNPLA7 axis enables endogenous choline stored in hepatic PC to be utilized in methyl metabolism. PNPLA7-deficient mice show marked decreases in hepatic GPC, choline, and several metabolites related to the methionine cycle, accompanied by various signs of methionine insufficiency, including growth retardation, hypoglycemia, hypolipidemia, increased energy consumption, reduced adiposity, increased fibroblast growth factor 21 (FGF21), and an altered histone/DNA methylation landscape. Moreover, PNPLA8-deficient mice recapitulate most of these phenotypes. In contrast to wild-type mice fed a methionine/choline-deficient diet, both knockout strains display decreased hepatic triglyceride, likely via reductions of lipogenesis and GPC-derived glycerol flux. Collectively, our findings highlight the biological importance of phospholipid catabolism driven by PNPLA8/PNPLA7 in methyl group flux and triglyceride synthesis in the liver.

High-throughput metabolomics has enabled the development of large-scale cohort studies. Long-term studies require multiple batch-based measurements, which require sophisticated quality control (QC) to eliminate unexpected bias to obtain biologically meaningful quantified metabolomic profiles. Liquid chromatography–mass spectrometry was used to analyze 10,833 samples in 279 batch measurements. The quantified profile included 147 lipids including acylcarnitine, fatty acids, glucosylceramide, lactosylceramide, lysophosphatidic acid, and progesterone. Each batch included 40 samples, and 5 QC samples were measured for 10 samples of each. The quantified data from the QC samples were used to normalize the quantified profiles of the sample data. The intra- and inter-batch median coefficients of variation (CV) among the 147 lipids were 44.3% and 20.8%, respectively. After normalization, the CV values decreased by 42.0% and 14.7%, respectively. The effect of this normalization on the subsequent analyses was also evaluated. The demonstrated analyses will contribute to obtaining unbiased, quantified data for large-scale metabolomics.

Background: Driver alterations may represent novel candidates for driver gene-guided therapy; however, intrahepatic cholangiocarcinoma (ICC) with multiple genomic aberrations makes them intractable. Therefore, the pathogenesis and metabolic changes of ICC need to be understood to develop new treatment strategies. We aimed to unravel the evolution of ICC and identify ICC-specific metabolic characteristics to investigate the metabolic pathway associated with ICC development using multiregional sampling to encompass the intra- and inter-tumoral heterogeneity. Methods: We performed the genomic, transcriptomic, proteomic and metabolomic analysis of 39-77 ICC tumour samples and eleven normal samples. Further, we analysed their cell proliferation and viability. Results: We demonstrated that intra-tumoral heterogeneity of ICCs with distinct driver genes per case exhibited neutral evolution, regardless of their tumour stage. Upregulation of BCAT1 and BCAT2 indicated the involvement of 'Val Leu Ile degradation pathway'. ICCs exhibit the accumulation of ubiquitous metabolites, such as branched-chain amino acids including valine, leucine, and isoleucine, to negatively affect cancer prognosis. We revealed that this metabolic pathway was almost ubiquitously altered in all cases with genomic diversity and might play important roles in tumour progression and overall survival. Conclusions: We propose a novel ICC onco-metabolic pathway that could enable the development of new therapeutic interventions.

Capillary electrophoresis-mass spectrometry (CE-MS) has emerged as a powerful new tool for comprehensive analysis of charged compounds. In this review, we provide a general description of the application of CE-MS in metabolome analysis, including the separation modes of CE, various interfaces and the mass spectrometers used. We also discuss strategies for sample pretreatment, data processing and peak identification, which are important processes in metabolome analysis. In addition, we highlight a number of new techniques to improve metabolite extraction, peak resolution and sensitivity. Finally, we provide some general conclusions and future perspectives.

Introduction: Advances in metabolomics have significantly improved cancer detection, diagnosis, treatment, and prognosis. Objectives: To investigate the relationship between metabolic tumor volume (MTV) using 2-deoxy-2-[18F]fluoro-D-glucose (FDG) positron emission tomography (PET)/ computed tomography (CT) and metabolomics data in patients with colorectal cancer (CRC). Methods: The metabolome in tumor tissues was analyzed using capillary electrophoresis time-of-flight mass spectrometry in 33 patients with newly diagnosed CRC who underwent FDG PET/CT before treatment and had tumor tissue post-surgery. Based on the FDG PET data, MTV was calculated and was dichotomized according to the median value, and tumors were divided into low-MTV and high-MTV tumors. Metabolomics data were compared between the low-MTV and high-MTV tumors. Results: The levels of most glycolysis-related metabolites were not different between low-MTV and high-MTV tumors. The level of component of the initial part of the tricarboxylic acid (TCA) cycle, citrate, was significantly lower in the high-MTV tumor than in the low-MTV tumor. The TCA intermediate succinate level was significantly higher in the high-MTV tumor than in the low-MTV tumor. In contrast, the TCA intermediate fumarate level was significantly lower in the high-MTV tumor than in the low-MTV tumor. The levels of many amino acids were significantly higher in the high-MTV tumor than in the low-MTV tumor. Conclusions: Although preliminary, these results suggest that tumors with high FDG metabolism in CRC may obtain more energy by using a reverse reaction of the TCA cycle and amino-acid metabolism. However, further research is required to clarify this relationship. Keywords: Colorectal cancer; FDG; Metabolome; PET/CT.

Objective: We investigated the metabolic changes in pancreatic ductal adenocarcinoma to identify the mechanisms of treatment response of neoadjuvant chemoradiation therapy. Methods: Frozen tumor and non-neoplastic pancreas tissues were prospectively obtained from 88 patients with pancreatic ductal adenocarcinoma who underwent curative-intent surgery. Sixty-two patients received neoadjuvant chemoradiation therapy and 26 patients did not receive neoadjuvant therapy (control group). Comprehensive analysis of metabolites in tumor and non-neoplastic pancreatic tissue was performed by capillary electrophoresis-mass spectrometry. Results: Capillary electrophoresis-mass spectrometry detected 90 metabolites for analysis among more than 500 ionic metabolites quantified. There were significant differences in 27 tumor metabolites between the neoadjuvant chemoradiation therapy and control groups. There were significant differences in eight metabolites [1-MethylnNicotinamide, Carnitine, Glucose, Glutathione (red), N-acetylglucosamine 6-phosphate, N-acetylglucosamine 1-phosphate, UMP, Phosphocholine] between good responder and poor responder for neoadjuvant chemoradiation therapy. Among these metabolites, phosphocholine, Carnitine and Glutathione were associated with recurrence-free survival only in the neoadjuvant chemoradiation therapy group. Microarray confirmed marked gene suppression of choline transporters [CTL1-4 (SLC44A1-44A4)] in pancreatic ductal adenocarcinoma tissue of neoadjuvant chemoradiation therapy group. Conclusion: The present study identifies several important metabolic consequences and potential neoadjuvant chemoradiation therapy targets in pancreatic ductal adenocarcinoma. Choline metabolism is one of the key pathways involved in recurrence of the patients with pancreatic ductal adenocarcinoma who received neoadjuvant chemoradiation therapy.

Synthetic phosphate-derived functional groups are important for controlling the function of bioactive molecules in vivo. Herein we describe the development of a new type of biocompatible phosphate analog, a fluorophosphoramidate (FPA) functional group that has characteristic P-F and P-N bonds. We found that FPA with a primary amino group was relatively unstable in aqueous solution and was converted to a monophosphate, while FPA with a secondary amino group was stable. Furthermore, by improving the molecular design of FPA, we developed a reaction in which a secondary amino group is converted to a primary amino group in the intracellular environment and clarified that the FPA group functions as a phosphate prodrug of nucleoside. Various FPA-gemcitabine derivatives were synthesized and their toxicity to cancer cells were evaluated. One of the FPA-gemcitabine derivatives showed superior toxicity compared with gemcitabine and its ProTide prodrug, which methodology is widely used in various nucleoside analogs, including anti-cancer and anti-virus drugs.

As the worldwide prevalence of colorectal cancer (CRC) increases, it is vital to reduce its morbidity and mortality through early detection. Saliva-based tests are an ideal noninvasive tool for CRC detection. Here, we explored and validated salivary biomarkers to distinguish patients with CRC from those with adenoma (AD) and healthy controls (HC). Saliva samples were collected from patients with CRC, AD, and HC. Untargeted salivary hydrophilic metabolite profiling was conducted using capillary electrophoresis–mass spectrometry and liquid chromatography–mass spectrometry. An alternative decision tree (ADTree)-based machine learning (ML) method was used to assess the discrimination abilities of the quantified metabolites. A total of 2,602 unstimulated saliva samples were collected from subjects with CRC (n = 231), AD (n = 54), and HC (n = 2,317). Data were randomly divided into training (n = 1,301) and validation datasets (n = 1,301). The clustering analysis showed a clear consistency of aberrant metabolites between the two groups. The ADTree model was optimized through cross-validation (CV) using the training dataset, and the developed model was validated using the validation dataset. The model discriminating CRC + AD from HC showed area under the receiver operating characteristic curves (AUC) of 0.860 (95% confidence interval [CI]: 0.828-0.891) for CV and 0.870 (95% CI: 0.837-0.903) for the validation dataset. The other model discriminating CRC from AD + HC showed an AUC of 0.879 (95% CI: 0.851-0.907) and 0.870 (95% CI: 0.838 - 0.902), respectively. Salivary metabolomics combined with ML demonstrated high accuracy and versatility in detecting CRC.