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Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases. Spatial metabolomics are used to describe the location and chemistry of small molecules involved in metabolic phenotypes. Here, Conroy et al. present a bioinformatic pipeline to analyze MALDI data and show that it can be used to identify actionable targets such as glycogen in fibrotic lungs of both human and mice.

Delivering isotopic tracers for metabolic studies in rodents without overt stress is challenging. Current methods achieve low label enrichment in proteins and lipids. Here, we report noninvasive introduction of 13 C 6 -glucose via a stress-free, ad libitum liquid diet. Using NMR and ion chromatography-mass spectrometry, we quantify extensive 13 C enrichment in products of glycolysis, the Krebs cycle, the pentose phosphate pathway, nucleobases, UDP-sugars, glycogen, lipids, and proteins in mouse tissues during 12 to 48 h of 13 C 6 -glucose feeding. Applying this approach to patient-derived lung tumor xenografts (PDTX), we show that the liver supplies glucose-derived Gln via the blood to the PDTX to fuel Glu and glutathione synthesis while gluconeogenesis occurs in the PDTX. Comparison of PDTX with ex vivo tumor cultures and arsenic-transformed lung cells versus xenografts reveals differential glucose metabolism that could reflect distinct tumor microenvironment. We further found differences in glucose metabolism between the primary PDTX and distant lymph node metastases. Isotope tracer administration for probing metabolism in vivo is important to assess metabolic functions in a relevant physiological setting. Here, the authors report a non-invasive method of administering 13 C 6 - glucose to mouse models via liquid diet feeding to achieve deep metabolic network coverage.

Alzheimer’s disease (AD) is an unremitting neurodegenerative disorder characterized by cerebral amyloid-β (Aβ) accumulation and gradual decline in cognitive function. Changes in brain energy metabolism arise in the preclinical phase of AD, suggesting an important metabolic component of early AD pathology. Neurons and astrocytes function in close metabolic collaboration, which is essential for the recycling of neurotransmitters in the synapse. However, this crucial metabolic interplay during the early stages of AD development has not been sufficiently investigated. Here, we provide an integrative analysis of cellular metabolism during the early stages of Aβ accumulation in the cerebral cortex and hippocampus of the 5xFAD mouse model of AD. Our electrophysiological examination revealed an increase in spontaneous excitatory signaling in the 5xFAD hippocampus. This hyperactive neuronal phenotype coincided with decreased hippocampal tricarboxylic acid (TCA) cycle metabolism mapped by stable 13 C isotope tracing. Particularly, reduced astrocyte TCA cycle activity and decreased glutamine synthesis led to hampered neuronal GABA synthesis in the 5xFAD hippocampus. In contrast, the cerebral cortex of 5xFAD mice displayed an elevated capacity for oxidative glucose metabolism, which may suggest a metabolic compensation in this brain region. We found limited changes when we explored the brain proteome and metabolome of the 5xFAD mice, supporting that the functional metabolic disturbances between neurons and astrocytes are early primary events in AD pathology. In addition, synaptic mitochondrial and glycolytic function was selectively impaired in the 5xFAD hippocampus, whereas non-synaptic mitochondrial function was maintained. These findings were supported by ultrastructural analyses demonstrating disruptions in mitochondrial morphology, particularly in the 5xFAD hippocampus. Collectively, our study reveals complex regional and cell-specific metabolic adaptations in the early stages of amyloid pathology, which may be fundamental for the progressing synaptic dysfunctions in AD.

Background Cerebral glucose hypometabolism is consistently observed in individuals with Alzheimer’s disease (AD), as well as in young cognitively normal carriers of the Ε4 allele of Apolipoprotein E (APOE), the strongest genetic predictor of late-onset AD. While this clinical feature has been described for over two decades, the mechanism underlying these changes in cerebral glucose metabolism remains a critical knowledge gap in the field. Methods Here, we undertook a multi-omic approach by combining single-cell RNA sequencing (scRNAseq) and stable isotope resolved metabolomics (SIRM) to define a metabolic rewiring across astrocytes, brain tissue, mice, and human subjects expressing APOE4. Results Single-cell analysis of brain tissue from mice expressing human APOE revealed E4-associated decreases in genes related to oxidative phosphorylation, particularly in astrocytes. This shift was confirmed on a metabolic level with isotopic tracing of 13 C-glucose in E4 mice and astrocytes, which showed decreased pyruvate entry into the TCA cycle and increased lactate synthesis. Metabolic phenotyping of E4 astrocytes showed elevated glycolytic activity, decreased oxygen consumption, blunted oxidative flexibility, and a lower rate of glucose oxidation in the presence of lactate. Together, these cellular findings suggest an E4-associated increase in aerobic glycolysis (i.e. the Warburg effect). To test whether this phenomenon translated to APOE4 humans, we analyzed the plasma metabolome of young and middle-aged human participants with and without the Ε4 allele, and used indirect calorimetry to measure whole body oxygen consumption and energy expenditure. In line with data from E4-expressing female mice, a subgroup analysis revealed that young female E4 carriers showed a striking decrease in energy expenditure compared to non-carriers. This decrease in energy expenditure was primarily driven by a lower rate of oxygen consumption, and was exaggerated following a dietary glucose challenge. Further, the stunted oxygen consumption was accompanied by markedly increased lactate in the plasma of E4 carriers, and a pathway analysis of the plasma metabolome suggested an increase in aerobic glycolysis. Conclusions Together, these results suggest astrocyte, brain and system-level metabolic reprogramming in the presence of APOE4, a ‘Warburg like’ endophenotype that is observable in young females decades prior to clinically manifest AD.

Metabolites, lipids, and glycans are fundamental but interconnected classes of biomolecules that form the basis of the metabolic network. These molecules are dynamically channeled through multiple pathways that govern cellular physiology and pathology. Here, we present a framework for the simultaneous spatial analysis of the metabolome, lipidome, and glycome from a single tissue section using mass spectrometry imaging. This workflow integrates a computational platform, the Spatial Augmented Multiomics Interface (Sami), which enables multiomics integration, high-dimensional clustering, spatial anatomical mapping of matched molecular features, and metabolic pathway enrichment. To demonstrate the utility of this approach, we applied Sami to evaluate metabolic diversity across distinct brain regions and to compare wild-type and Ps19 Alzheimer’s disease (AD) mouse models. Our findings reveal region-specific metabolic demands in the normal brain and highlight metabolic dysregulation in the Ps19 model, providing insights into the biochemical alterations associated with neurodegeneration. Clarke et al. presents a framework for spatial analysis of the metabolome, lipidome, and glycome from a single tissue section using mass spectrometry imaging. Applying this approach, they revealed region-specific metabolic diversity and dysregulation in both normal and diseased mouse brains.

Background Cancer cells have a different metabolic profile compared to normal cells. The Warburg effect (increased aerobic glycolysis) and glutaminolysis (increased mitochondrial activity from glutamine catabolism) are well known hallmarks of cancer and are accompanied by increased lactate production, hyperpolarized mitochondrial membrane and increased production of reactive oxygen species. Methods In this study we target the Warburg effect with dichloroacetate (DCA) and the increased mitochondrial activity of glutaminolysis with arsenic trioxide (ATO) in breast cancer cells, measuring cell proliferation, cell death and mitochondrial characteristics. Results The combination of DCA and ATO was more effective at inhibiting cell proliferation and inducing cell death than either drug alone. We examined the effect of these treatments on mitochondrial membrane potential, reactive oxygen species production and ATP levels and have identified new molecular mechanisms within the mitochondria for both ATO and DCA: ATO reduces mitochondrial function through the inhibition of cytochrome C oxidase (complex IV of the electron transport chain) while DCA up-regulates ATP synthase β subunit expression. The potentiation of ATO cytotoxicity by DCA is correlated with strong suppression of the expression of c-Myc and HIF-1α, and decreased expression of the survival protein Bcl-2. Conclusion This study is the first to demonstrate that targeting two key metabolic hallmarks of cancer is an effective anti-cancer strategy with therapeutic potential.

The glycolytic phenotype is a widespread phenomenon in solid cancer forms, including breast cancer. Dichloroacetate (DCA) has recently been proposed as a novel and relatively non-toxic anti-cancer agent that can reverse the glycolytic phenotype in cancer cells through the inhibition of pyruvate dehydrogenase kinase. We have examined the effect of DCA against breast cancer cells, including in a highly metastatic in vivo model. The growth of several breast cancer cell lines was found to be inhibited by DCA in vitro. Further examination of 13762 MAT rat mammary adenocarcinoma cells found that reversal of the glycolytic phenotype by DCA correlated with the inhibition of proliferation without any increase in cell death. This was despite a small but significant increase in caspase 3/7 activity, which may sensitize cancer cells to other apoptotic triggers. In vivo, DCA caused a 58% reduction in the number of lung metastases observed macroscopically after injection of 13762 MAT cells into the tail vein of rats (P = 0.0001, n ≥ 9 per group). These results demonstrate that DCA has anti-proliferative properties in addition to pro-apoptotic properties, and can be effective against highly metastatic disease in vivo, highlighting its potential for clinical use.

Glycogen dysregulation is a hallmark of aging, and aberrant glycogen drives metabolic reprogramming and pathogenesis in multiple diseases. However, glycogen heterogeneity in healthy and diseased tissues remains largely unknown. Herein, we describe a method to define spatial glycogen architecture in mouse and human tissues using matrix‐assisted laser desorption/ionization mass spectrometry imaging. This assay provides robust and sensitive spatial glycogen quantification and architecture characterization in the brain, liver, kidney, testis, lung, bladder, and even the bone. Armed with this tool, we interrogated glycogen spatial distribution and architecture in different types of human cancers. We demonstrate that glycogen stores and architecture are heterogeneous among diseases. Additionally, we observe unique hyperphosphorylated glycogen accumulation in Ewing sarcoma, a pediatric bone cancer. Using preclinical models, we correct glycogen hyperphosphorylation in Ewing sarcoma through genetic and pharmacological interventions that ablate in vivo tumor growth, demonstrating the clinical therapeutic potential of targeting glycogen in Ewing sarcoma. Synopsis Development of a MALDI‐based assay for the spatial quantification of microenvironmental glycogen and glycogen biochemical architecture. Hyperphosphorylated glycogen was discovered in human Ewing sarcoma. Targeting tumor‐specific glycogen may be a potential therapeutic approach for Ewing sarcoma. Development of a MALDI‐based assay for the spatial quantification of microenvironmental glycogen. Ultra‐sensitivity allows visualization of glycogen in previously unknown but distinct cellular layers in multiple human tissues. Identification of glycogen‐rich and glycogen‐poor tumors such as Ewing sarcoma and prostate cancer, respectively. Targeting Ewing sarcoma glycogen by different modalities blunted tumor growth in immunodeficient mice. Graphical Abstract Development of a MALDI‐based assay for the spatial quantification of microenvironmental glycogen and glycogen biochemical architecture. Hyperphosphorylated glycogen was discovered in human Ewing sarcoma. Targeting tumor‐specific glycogen may be a potential therapeutic approach for Ewing sarcoma.

Metabolic reprogramming has been recognized as one of the major mechanisms that fuel tumor initiation and progression. Our previous studies demonstrate that activation of Drp1 promotes fatty acid oxidation and downstream Wnt signaling. Here we investigate the role of Drp1 in regulating glycogen metabolism in colon cancer. Knockdown of Drp1 decreases mitochondrial respiration without increasing glycolysis. Analysis of cellular metabolites reveals that the levels of glucose-6-phosphate, a precursor for glycogenesis, are significantly elevated whereas pyruvate and other TCA cycle metabolites remain unchanged in Drp1 knockdown cells. Additionally, silencing Drp1 activates AMPK to stimulate the expression glycogen synthase 1 (GYS1) mRNA and promote glycogen storage. Using 3D organoids from Apc f/f /Villin-Cre ERT2 models, we show that glycogen levels are elevated in tumor organoids upon genetic deletion of Drp1. Similarly, increased GYS1 expression and glycogen accumulation are detected in xenograft tumors derived from Drp1 knockdown colon cancer cells. Functionally, increased glycogen storage provides survival advantage to Drp1 knockdown cells. Co-targeting glycogen phosphorylase-mediated glycogenolysis sensitizes Drp1 knockdown cells to chemotherapy drug treatment. Taken together, our results suggest that Drp1-loss activates glucose uptake and glycogenesis as compensative metabolic pathways to promote cell survival. Combined inhibition of glycogen metabolism may enhance the efficacy of chemotherapeutic agents for colon cancer treatment.

Immune checkpoint inhibitors (ICIs) have transformed cancer care but are frequently associated with immune-related adverse events (irAEs), complicating treatment. This retrospective cohort study analyzed 9193 adult patients from the OneFlorida+ Clinical Research Network who received ICIs between 2018 and 2022, aiming to identify risk factors for irAEs and evaluate their incidence, severity, and clinical impact. Among the 6,526 patients included in the final analysis, 56.2% developed irAEs within 1 year, including 284 hospitalized cases. Multivariable logistic regression revealed that younger age (18–29), female sex, and comorbidities such as myocardial infarction, heart failure, and renal disease increased irAE risk, while dementia and recent chemotherapy were associated with lower risk. Patients receiving CTLA-4 + PD(L)1 combination therapy had a 35% higher risk of irAEs than those treated with PD-1 inhibitors alone. Breast and hematologic cancers conferred elevated risk, whereas brain cancer was linked to reduced risk. Kaplan–Meier and cumulative incidence analyses demonstrated that irAE severity significantly impacted time to onset ( P  = 0.038), and overall survival was worse in patients who developed irAEs ( P  < 0.0001). Treatment regimen influenced irAE-free survival in multi-site cancers and overall survival in kidney cancer, highlighting the need for tailored irAE risk stratification.