Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Digital twins for in vivo metabolic flux estimations in patients with brain cancer II

ABSTRACT: Recent advancements in metabolic flux estimations in vivo are limited to preclinical models, primarily due to challenges in tissue sampling, tumor microenvironment heterogeneity, and non-steady state conditions. To address these limitations and enable flux estimation in human patients, we developed two machine learning-based frameworks. First, the digital twin framework integrates first-principles stoichiometric and isotopic simulations with convolutional neural networks to estimate fluxes in patient bulk samples. Second, the 13C-scMFA framework combines patient scRNA-seq data with 13C-isotope tracing, allowing single-cell-level flux quantification. These studies allow quantification of metabolic activity in neoplastic glioma cells, revealing frequently elevated purine synthesis and serine uptake compared to non-malignant cells. Our models also identify metabolic heterogeneity among patients and mice with brain cancer, in turn predicting treatment responses to metabolic inhibitors. Our frameworks advance in vivo metabolic flux analysis, may lead to novel metabolic therapies, and identify biomarkers for metabolism-directed therapies in patients.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE311464 | GEO | 2025/11/29

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Digital twins for in vivo metabolic flux estimations in patients with brain cancer

Project description:Recent advancements in metabolic flux estimations in vivo are limited to preclinical models, primarily due to challenges in tissue sampling, tumor microenvironment heterogeneity, and non-steady state conditions. To address these limitations and enable flux estimation in human patients, we developed two machine learning-based frameworks. First, the digital twin framework integrates first-principles stoichiometric and isotopic simulations with convolutional neural networks to estimate fluxes in patient bulk samples. Second, the 13C-scMFA framework combines patient scRNA-seq data with 13C-isotope tracing, allowing single-cell-level flux quantification. These studies allow quantification of metabolic activity in neoplastic glioma cells, revealing frequently elevated purine synthesis and serine uptake compared to non-malignant cells. Our models also identify metabolic heterogeneity among patients and mice with brain cancer, in turn predicting treatment responses to metabolic inhibitors. Our frameworks advance in vivo metabolic flux analysis, may lead to novel metabolic therapies, and identify biomarkers for metabolism-directed therapies in patients.

2025-11-28 | GSE311151 | GEO

Integrated metabolic and transcriptomic analysis of the duckweed Lemna gibba growing under photomixotrophic conditions: Metabolic adjustments to different nitrogen sources

Project description:Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown in a photomixotrophic mode in liquid media under continuous light with 13C-labeled glucose as a carbon source. Two different conditions (nitrate vs. glutamine as nitrogen source) were compared by quantification of growth kinetics, metabolite levels, metabolic flux and transcript abundance.

2023-09-14 | GSE153602 | GEO

Digital twins for in vivo metabolic flux estimations in patients with brain cancer

Project description:Digital twins for in vivo metabolic flux estimations in patients with brain cancer

| PRJNA1368712 | ENA

Digital twins for in vivo metabolic flux estimations in patients with brain cancer II

Project description:Digital twins for in vivo metabolic flux estimations in patients with brain cancer II

| PRJNA1369501 | ENA

Transcriptome- and fluxome-guided metabolic engineering of 3-hydroxypropionic acid production in Saccharomyces cerevisiae

Project description:In this study, we analyse a high 3HP producing strain of Saccharomyces cerevisiae through 13C metabolic flux and transcriptomic analyses. The engineered strain saw upregulation across glycolysis and the pentose phosphate pathway compared to the reference strain. Our analysis of the transcriptomic data produce a strategy that successfully increased 3HP titres.

2022-08-30 | E-MTAB-7819 | biostudies-arrayexpress

Glucose catabolism via a partially cyclic pentose phosphate pathway in Gluconobacter oxydans 621H: a combined fluxomics and transcriptomics analysis

Project description:In this study, the distribution and regulation of periplasmic and cytoplasmic carbon fluxes in Gluconobacter oxydans 621H with glucose were studied by 13C-based metabolic flux analysis (13C-MFA) in combination with transcriptomics and enzyme assays. For 13C-MFA, cells were cultivated with specifically 13C-labeled glucose and intracellular metabolites were analyzed for their labeling pattern by LC-MS. In growth phase I, 90% of the glucose was oxidized periplasmatically to gluconate and partially further oxidized to 2-ketogluconate. Of the glucose taken up by the cells, 9% was phosphorylated to glucose 6-phosphate, whereas 91% was oxidized by cytoplasmic glucose dehydrogenase to gluconate. Additional gluconate was taken up into the cells by transport. Of the cytoplasmic gluconate, 70% was oxidized to 5-ketogluconate and 30% was phosphorylated to 6-phosphogluconate. In growth phase II, 87% of gluconate was oxidized to 2-ketogluconate in the periplasm and 13% was taken up by the cells and almost completely converted to 6-phosphogluconate. Since G. oxydans lacks phosphofructokinase, glucose 6-phosphate can only be metabolized via the oxidative pentose phosphate pathway (PPP) or the Entner-Doudoroff pathway (EDP). 13C-MFA showed that 6-phosphogluconate is catabolized primarily via the oxidative PPP in both phase I and II (62% and 93%) and demonstrated a cyclic carbon flux through the oxidative PPP. The transcriptome comparison revealed an increased expression of PPP genes in growth phase II, which was supported by enzyme activity measurements and correlated with the increased PPP flux in phase II. Moreover, genes possibly related to a general stress response displayed increased expression in growth phase II. The transcriptome comparisons of G. oxydans growth phase II vs. growth phase I were repeated independently three times in biological replicates resulting in 3 hybridizations as termed by sample 1 to 3.

2013-02-13 | E-GEOD-42223 | biostudies-arrayexpress

Jallet2024 - Isotopic model of ethanolamine metabolism in E. coli

Project description:Isotopic model of ethanolamine metabolism in E. coli, used for 13C-flux calculations.

2024-06-28 | MODEL2403010002 | BioModels

Global 13C tracing and metabolic flux analysis of intact human liver tissue ex vivo

Project description:Liver metabolism is central to human physiology and influences the pathogenesis of common metabolic diseases. Yet, our understanding of human liver metabolism remains incomplete, with much of current knowledge based on animal or cell culture models that do not fully recapitulate human physiology. Here, we performed in-depth measurement of metabolism in intact human liver tissue ex vivo using global 13C tracing, non-targeted mass spectrometry and model-based metabolic flux analysis. Cultured liver tissue exhibited normal anatomical structure and retained canonical liver functions such as glucose production, albumin and VLDL synthesis at near-physiological rates. Isotope tracing with a highly 13C-labeled medium generated 13C enrichment in hundreds of compounds, allowing qualitative assessment of a wide range of metabolic pathways within a single experiment. This confirmed well-known features of liver metabolism, but also revealed unexpected metabolic activities such as de novo creatine synthesis and branched-chain amino acid transamination, where human liver appears to differ from rodent models. Metabolic flux analysis identified glycogenolysis as the main source of glucose production, which could be suppressed by pharmacological inhibition of glycogen phosphorylase. Glucose production ex vivo also correlated with donor plasma glucose, suggesting that cultured liver tissue retains individual metabolic phenotypes. Moreover, liver tissue responded to postprandial levels of nutrients and insulin by suppressing glucose production and increasing nutrient uptake. Isotope tracing ex vivo allows measuring human liver metabolism with great depth and resolution in an experimentally tractable system.

2024-07-08 | GSE271041 | GEO

Tumour sampling conditions perturb the metabolic landscape of clear cell renal cell carcinoma

Project description:Human isotopic tracer studies are fast becoming the gold standard model to study cancer metabolism in vivo. Analysed tissues are typically retrieved after surgical resection, which exposes them to a variable extent of warm ischaemia. Although standardised protocols are emerging, the effects of sampling conditions on the tissue metabolome remain understudied. Here, we perform a 13C-glucose study coupled with metabolomic, transcriptomic, and proteomic profiling in patients with clear cell renal cell carcinoma (ccRCC) to assess the metabolic profile of tissues sampled intraoperatively, when blood supply is intact, versus post-surgical resection, which exposes the tissue to ischaemia. We show that ischaemia significantly affects the metabolic landscape of ccRCC, masking some critical features, such as suppressed gluconeogenesis. Furthermore, in orthotopic ccRCC-derived xenografts, we identified that prolonged exposure to ischaemia disrupts the tissue metabolome stability. Therefore, minimising tissue ischaemia is pivotal in accurately profiling cancer metabolism in these important and resource-intense patient studies.

2025-08-31 | GSE274774 | GEO

Glucose catabolism via a partially cyclic pentose phosphate pathway in Gluconobacter oxydans 621H: a combined fluxomics and transcriptomics analysis

2013-02-13 | GSE42223 | GEO