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IntroductionSubcellular compartmentalization enables eukaryotic cells to carry out different reactions at the same time, resulting in different metabolite pools in the subcellular compartments. Thus, mutations affecting the mitochondrial energy metabolism could cause different metabolic alterations in mitochondria compared to the cytoplasm. Given that the metabolite pool in the cytosol is larger than that of other subcellular compartments, metabolic profiling of total cells could miss these compartment-specific metabolic alterations.ObjectivesTo reveal compartment-specific metabolic differences, mitochondria and the cytoplasmic fraction of baker’s yeast Saccharomyces cerevisiae were isolated and subjected to metabolic profiling.MethodsMitochondria were isolated through differential centrifugation and were analyzed together with the remaining cytoplasm by gas chromatography–mass spectrometry (GC–MS) based metabolic profiling.ResultsSeventy-two metabolites were identified, of which eight were found exclusively in mitochondria and sixteen exclusively in the cytoplasm. Based on the metabolic signature of mitochondria and of the cytoplasm, mutants of the succinate dehydrogenase (respiratory chain complex II) and of the FOF1-ATP-synthase (complex V) can be discriminated in both compartments by principal component analysis from wild-type and each other. These mitochondrial oxidative phosphorylation machinery mutants altered not only citric acid cycle related metabolites but also amino acids, fatty acids, purine and pyrimidine intermediates and others.ConclusionBy applying metabolomics to isolated mitochondria and the corresponding cytoplasm, compartment-specific metabolic signatures can be identified. This subcellular metabolomics analysis is a powerful tool to study the molecular mechanism of compartment-specific metabolic homeostasis in response to mutations affecting the mitochondrial metabolism.

Yeast cells respond to heat stress by remodeling their gene expression, resulting in the changes of the corresponding proteins and metabolites. Compared to the intensively investigated transcriptome and proteome, the metabolic response to heat stress is not sufficiently characterized. Mitochondria have been recognized to play an essential role in heat stress tolerance. Given the compartmentalization of the cell, it is not clear if the heat stress-induced metabolic response occurs in mitochondria or in the cytosol. Therefore, a compartment-specific metabolite analysis was performed to analyze the heat stress-induced metabolic response in mitochondria and the cytoplasm. In this work, the isolated mitochondria and the cytoplasm of yeast cells grown at permissive temperature and cells adapting to heat stress were subjected to mass spectrometry-based metabolomics. Over a hundred metabolites could be identified, covering amino acid metabolism, energy metabolism, arginine metabolism, purine and pyrimidine metabolism, and others. Highly accumulated citrulline and reduced arginine suggested remodeled arginine metabolism. A stable isotope-labeled experiment was performed to analyze the heat stress-induced metabolic remodeling of the arginine metabolism, identifying activated de novo ornithine biosynthesis to support arginine and spermidine synthesis. The short-term increased spermidine and trehalose suggest their important roles as heat stress markers. These data provide metabolic clues of heat stress-induced metabolic remodeling, which helps in understanding the heat stress response.

Purpose Dioxygenases are oxidoreductase enzymes with roles in metabolic pathways necessary for aerobic life. 4-hydroxyphenylpyruvate dioxygenase-like protein (HPDL), encoded by HPDL , is an orphan paralogue of 4-hydroxyphenylpyruvate dioxygenase (HPD), an iron-dependent dioxygenase involved in tyrosine catabolism. The function and association of HPDL with human diseases remain unknown. Methods We applied exome sequencing in a cohort of over 10,000 individuals with neurodevelopmental diseases. Effects of HPDL loss were investigated in vitro and in vivo, and through mass spectrometry analysis. Evolutionary analysis was performed to investigate the potential functional separation of HPDL from HPD. Results We identified biallelic variants in HPDL in eight families displaying recessive inheritance. Knockout mice closely phenocopied humans and showed evidence of apoptosis in multiple cellular lineages within the cerebral cortex. HPDL is a single-exonic gene that likely arose from a retrotransposition event at the base of the tetrapod lineage, and unlike HPD, HPDL is mitochondria-localized. Metabolic profiling of HPDL mutant cells and mice showed no evidence of altered tyrosine metabolites, but rather notable accumulations in other metabolic pathways. Conclusion The mitochondrial localization, along with its disrupted metabolic profile, suggests HPDL loss in humans links to a unique neurometabolic mitochondrial infantile neurodegenerative condition.

Metabolomics has expanded from cellular to subcellular level to elucidate subcellular compartmentalization. By applying isolated mitochondria to metabolome analysis, the hallmark of mitochondrial metabolites has been unraveled, showing compartment-specific distribution and regulation of metabolites. This method was employed in this work to study a mitochondrial inner membrane protein Sym1, whose human ortholog MPV17 is related to mitochondria DNA depletion syndrome. Gas chromatography–mass spectrometry-based metabolic profiling was combined with targeted liquid chromatography–mass spectrometry analysis to cover more metabolites. Furthermore, we applied a workflow employing ultra-high performance liquid chromatography–quadrupole time of flight mass spectrometry with a powerful chemometrics platform, focusing on only significantly changed metabolites. This workflow highly reduced the complexity of acquired data without losing metabolites of interest. Consequently, forty-one novel metabolites were identified in addition to the combined method, of which two metabolites, 4-guanidinobutanal and 4-guanidinobutanoate, were identified for the first time in Saccharomyces cerevisiae. With compartment-specific metabolomics, we identified sym1Δ cells as lysine auxotroph. The highly reduced carbamoyl-aspartate and orotic acid indicate a potential role of the mitochondrial inner membrane protein Sym1 in pyrimidine metabolism.

XD14 is a 4-acyl pyrrole derivative, which was discovered by a high-throughput virtual screening experiment. XD14 inhibits bromodomain and extra-terminal domain (BET) proteins (BRD2, BRD3, BRD4 and BRDT) and consequently suppresses cell proliferation. In this study, metabolic profiling reveals the molecular effects in the human breast cancer cell line MCF-7 (Michigan Cancer Foundation-7) treated by XD14. A three-day time series experiment with two concentrations of XD14 was performed. Gas chromatography-mass spectrometry (GC-MS) was applied for untargeted profiling of treated and non-treated MCF-7 cells. The gained data sets were evaluated by several statistical methods: analysis of variance (ANOVA), clustering analysis, principle component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). Cell proliferation was strongly inhibited by treatment with 50 µM XD14. Samples could be discriminated by time and XD14 concentration using PLS-DA. From the 117 identified metabolites, 67 were significantly altered after XD14 treatment. These metabolites include amino acids, fatty acids, Krebs cycle and glycolysis intermediates, as well as compounds of purine and pyrimidine metabolism. This massive intervention in energy metabolism and the lack of available nucleotides could explain the decreased proliferation rate of the cancer cells.

The massive data generated by the Internet of Things (IoT) are considered of high business value, and data mining algorithms can be applied to IoT to extract hidden information from data. In this paper, we give a systematic way to review data mining in knowledge view, technique view, and application view, including classification, clustering, association analysis, time series analysis and outlier analysis. And the latest application cases are also surveyed. As more and more devices connected to IoT, large volume of data should be analyzed, the latest algorithms should be modified to apply to big data. We reviewed these algorithms and discussed challenges and open research issues. At last a suggested big data mining system is proposed.

Objectives The decision on trade-off between the chance of salvage and the risk of serious toxicity in locally recurrent nasopharyngeal carcinoma (lrNPC) is a dilemma both to the clinician and patients. This study aimed to evaluate the efficacy of our watch-and-wait (W-W) strategy by receiving low-intensity maintenance treatment (LIMT) in lrNPC patients who achieved objective response after immune checkpoint inhibitors plus chemotherapy (ICI-chemotherapy), and explore the possibility of sparing or delaying local treatment. Methods LrNPC patients who were treated in our institution from January 2022 to May 2023 were candidates for this study. All enrolled patients would receive protocolized ICI-chemotherapy followed by LIMT alone (W-W approach) without immediate local treatment. The objective response rate (ORR), progression free survival (PFS), overall survival (OS) and safety profile were evaluated. Results Twenty-six lrNPC patients were included, 18 patients (69.2%) achieved objective response after ICI-chemotherapy, and continued with LIMT, 17 of them (17/18, 94.4%) maintained a state of disease remission without requiring local treatment, only one patient experienced PD during LIMT. Six patients remained in SD at the completion of ICI-chemotherapy, two patients experienced PD during ICI-chemotherapy. The 2-year OS and PFS were 87.8% and 64.0%, respectively. Reported adverse events were all manageable and no severe treatment-emergent adverse event were detected. Conclusions For patients achieving response after ICI-chemotherapy, a “W-W” approach by continuing with LIMT, eschewing immediate local therapy, may be a viable option. Well-designed, prospective trials with conventional approaches involving earlier local treatment in comparison are essential to confirm the benefit of this innovative approach.

Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor, and investigating the immunorelated genes is essential. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, an immunoprognosis model was constructed to identify four hub genes with moderate predictive values for the prognosis of ccRCC patients. These four genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltration could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of three hub genes were associated with tumor progression ( P <0.1). In conclusion, four genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.

Lung adenocarcinoma (LADC) exhibits high spatial heterogeneity, with distinct spatial variations in pathological features. The distribution of tertiary lymphoid structures (TLS) in LADC is uneven, and different TLS characteristics play unique roles. To investigate the correlation between TLS features and other pathological characteristics, particularly tumor spread through air spaces (STAS), we analyzed TLS and other pathological features on whole-slide images stained with HE and CD20/CD23. Additionally, the 14-Gene assay was used to assess prognostic risk. Among 388 enrolled LADC patients, 226 (58.2%) were TLS-positive. TLS showed a negative correlation with various adverse pathological features, with boundary-area TLS demonstrating the strongest correlation with STAS quantity ( r = -0.324, P  < 0.001). Multivariate Cox analysis identified boundary-area TLS as an independent prognostic factor for recurrence-free survival (HR = 0.856, 95% CI  = 0.759–0.966, P  = 0.026), while mature TLS was an independent factor for overall survival (HR = 0.841, 95% CI  = 0.717–0.988, P  = 0.035). High-density TLS at the tumor boundary was associated with low-risk stratification by the 14-Gene assay ( P  = 0.013). This study highlights the negative correlation between TLS and STAS, especially in boundary areas, and emphasizes the impact of tumor microenvironment spatial characteristics on clinical outcomes. Assessment of spatial heterogeneity in LADC facilitates precise risk stratification for patients.

Fibroblast Growth Factor Receptor (FGFR) signaling is linked with tumor progression and tumor immunoevasion, yet the potential effect of FGFR signature on the prognosis of patient with colorectal cancer (CRC) and response to immune therapy remains elusive. The fibroblast growth factor receptor risk signature (FRS) was identified through single-cell RNA sequencing, bulk RNA sequencing, and machine learning techniques. Signaling enrichment analyses were conducted using Gene Set Enrichment Analysis (GSEA) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Drugs targeting the FRS were predicted using the Cancer Therapeutics Response Portal (CTRP) and PRISM databases. The analysis of T cell function and the tumor microenvironment (TME) was performed using flow cytometry. In this study, we characterized the FRS in cancer patients with CRC. By integrating advanced techniques, we identified the FRS and revealed the intricate molecular landscape and diversity of the FRS within the TME. Notably, the FRS effectively predicted unfavorable prognosis and resistance to immunotherapy in CRC patients. Furthermore, PHA-793887, identified as a potential FRS inhibitor by the CTRP and PRISM databases, significantly restructured the immunosuppressive TME and enhanced the antitumor immune response, resulting in a reduced tumor burden in the MC38 murine tumor model. Together, these data support FRS positively correlates with poor prognosis and therapy resistance. The PHA-793887 could be a potential FRS inhibitor to improving the effectiveness of CRC management via bolstering antitumor immunity.