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Characterization of tumor metabolism with spatial information contributes to our understanding of complex cancer metabolic reprogramming, facilitating the discovery of potential metabolic vulnerabilities that might be targeted for tumor therapy. However, given the metabolic variability and flexibility of tumors, it is still challenging to characterize global metabolic alterations in heterogeneous cancer. Here, we propose a spatially resolved metabolomics approach to discover tumor-associated metabolites and metabolic enzymes directly in their native state. A variety of metabolites localized in different metabolic pathways were mapped by airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) in tissues from 256 esophageal cancer patients. In combination with in situ metabolomics analysis, this method provided clues into tumor-associated metabolic pathways, including proline biosynthesis, glutamine metabolism, uridine metabolism, histidine metabolism, fatty acid biosynthesis, and polyamine biosynthesis. Six abnormally expressed metabolic enzymes that are closely associated with the altered metabolic pathways were further discovered in esophageal squamous cell carcinoma (ESCC). Notably, pyrroline-5-carboxylate reductase 2 (PYCR2) and uridine phosphorylase 1 (UPase1) were found to be altered in ESCC. The spatially resolved metabolomics reveal what occurs in cancer at the molecular level, from metabolites to enzymes, and thus provide insights into the understanding of cancer metabolic reprogramming.

Glioma stem cells (GSCs) contribute to therapy resistance and poor outcomes for glioma patients. A significant feature of GSCs is their ability to grow in an acidic microenvironment. However, the mechanism underlying the rewiring of their metabolism in low pH remains elusive. Here, using metabolomics and metabolic flux approaches, we cultured GSCs at pH 6.8 and pH 7.4 and found that cells cultured in low pH exhibited increased de novo purine nucleotide biosynthesis activity. The overexpression of glucose-6-phosphate dehydrogenase, encoded by G6PD or H6PD , supports the metabolic dependency of GSCs on nucleotides when cultured under acidic conditions, by enhancing the pentose phosphate pathway (PPP). The high level of reduced glutathione (GSH) under acidic conditions also causes demand for the PPP to provide NADPH. Taken together, upregulation of G6PD/H6PD in the PPP plays an important role in acidic-driven purine metabolic reprogramming and confers a predilection toward glioma progression. Our findings indicate that targeting G6PD/H6PD, which are closely related to glioma patient survival, may serve as a promising therapeutic target for improved glioblastoma therapeutics. An integrated metabolomics and metabolic flux analysis, as well as considering microenvironment and cancer stem cells, provide a precise insight into understanding cancer metabolic reprogramming.

Cardiovascular and metabolic disease (CMD) remains a main cause of premature death worldwide. Berberine (BBR), a lipid-lowering botanic compound with diversified potency against metabolic disorders, is a promising candidate for ameliorating CMD. The liver is the target of BBR so that liver-site accumulation could be important for fulfilling its therapeutic effect. In this study a rational designed micelle (CTA-Mic) consisting of α-tocopheryl hydrophobic core and on-site detachable polyethylene glycol-thiol shell is developed for effective liver deposition of BBR. The bio-distribution analysis proves that the accumulation of BBR in liver is increased by 248.8% assisted by micelles. Up-regulation of a range of energy-related genes is detectable in the HepG2 cells and in vivo. In the high fat diet-fed mice, BBR-CTA-Mic intervention remarkably improves metabolic profiles and reduces the formation of aortic arch plaque. Our results provide proof-of-concept for a liver-targeting strategy to ameliorate CMD using natural medicines facilitated by Nano-technology. Berberine has lipid-lowering effects and other metabolic benefits, but it presents with poor bioavailability. Here the authors conjugate berberine to liver-targeting nanoparticles, and show increased accumulation of berberine in the liver, improved metabolic profiles and reduced atherosclerotic plaques in mice.

“Gray zone” thyroid follicular tumors are difficult to diagnose, especially when distinguishing between benign follicular thyroid adenoma (FTA) and malignant carcinoma (FTC). Thus, proper classification of thyroid follicular diseases may improve clinical prognosis. In this study, the diagnostic performance of metabolite enzymes was evaluated using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to build a classification model for thyroid follicular tumor characteristics among 24 samples. We analyzed metabolic enzyme marker expression in an independent validation set of 133 cases and further evaluated the potential biological behavior of 19 thyroid borderline lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than FTC (p < 0.001). The metabolic enzyme panel, which included FA synthase and Ca2+-independent PLA2, was further validated in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the ROC, sensitivity, and specificity: 73.6%, 82.1%, and 60.6%, respectively). The findings indicate that AFAIDESI-MSI, in combination with low metabolic enzyme expression, could play a role in the diagnosis of thyroid follicular borderline tumors for strict follow-up.

Organs collaborate to maintain metabolic homeostasis in mammals. Spatial metabolomics makes strides in profiling the metabolic landscape, yet can not directly inspect the metabolic crosstalk between tissues. Here, we introduce an approach to comprehensively trace the metabolic fate of 13 C-nutrients within the body and present a robust computational tool, MSITracer, to deep-probe metabolic activity in a spatial manner. By discerning spatial distribution differences between isotopically labeled metabolites from ambient mass spectrometry imaging-based isotope tracing data, this approach empowers us to characterize fatty acid metabolic crosstalk between the liver and heart, as well as glutamine metabolic exchange across the kidney, liver, and brain. Moreover, we disclose that tumor burden significantly influences the host’s hexosamine biosynthesis pathway, and that the glucose-derived glutamine released from the lung as a potential source for tumor glutamate synthesis. The developed approach facilitates the systematic characterization of metabolic activity in situ and the interpretation of tissue metabolic communications in living organisms. Organ metabolic crosstalk is vital but challenging to trace. Here, the authors present MSITracer, a computational tool for spatial isotope tracing that reveals inter-organ crosstalk, such as liver–heart fatty acid metabolism and lung-derived glutamine catabolism in tumors.

Diabetic cardiomyopathy (DCM) is a metabolic disease and a leading cause of heart failure among people with diabetes. Mass spectrometry imaging (MSI) is a versatile technique capable of combining the molecular specificity of mass spectrometry (MS) with the spatial information of imaging. In this study, we used MSI to visualize metabolites in the rat heart with high spatial resolution and sensitivity. We optimized the air flow-assisted desorption electrospray ionization (AFADESI)-MSI platform to detect a wide range of metabolites, and then used matrix-assisted laser desorption ionization (MALDI)-MSI for increasing metabolic coverage and improving localization resolution. AFADESI-MSI detected 214 and 149 metabolites in positive and negative analyses of rat heart sections, respectively, while MALDI-MSI detected 61 metabolites in negative analysis. Our study revealed the heterogenous metabolic profile of the heart in a DCM model, with over 105 region-specific changes in the levels of a wide range of metabolite classes, including carbohydrates, amino acids, nucleotides, and their derivatives, fatty acids, glycerol phospholipids, carnitines, and metal ions. The repeated oral administration of ferulic acid during 20 weeks significantly improved most of the metabolic disorders in the DCM model. Our findings provide novel insights into the molecular mechanisms underlying DCM and the potential of ferulic acid as a therapeutic agent for treating this condition.

Casper, a type of transparent mutant-line zebrafish, was generated to overcome the opaque trunk of an adult zebrafish for tumor modeling to realize real-time visualization of transplanted cells in vivo. However, the molecular information at the metabolic level has not received much attention. Herein, a spatially resolved metabolomics method based on an airflow-assisted desorption electrospray ionization–mass spectrometry imaging (AFADESI-MSI) system for whole-body zebrafish was used to investigate small molecules and the distribution of adult casper (Mitfaw2/w2, roya9/a9) and the differences from wild-type zebrafish. Finally, the spatial distribution information of more than 1500 endogenous ions was obtained in positive and negative detection modes, and 186 metabolites belonging to a variety of structural categories were identified or annotated. Compared with wild-type samples, 85 variables, including 37 known metabolites, were screened out. In addition, the disordered metabolic pathways caused by the genetic mutation were excavated, involving downregulation of purine metabolism and arachidonic acid metabolism, upregulation of glycerophospholipid metabolism, and biosynthesis of unsaturated fatty acids. All these results were observed in the most intuitive way through MSI. This study revealed important metabolic characteristics of and perturbation in adult casper zebrafish, and provides indispensable fundamental knowledge for tumor research based on it.

Distinguishing breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS) is a key step in breast surgery, especially to determine whether DCIS is associated with tumor cell micro-invasion. However, there is currently no reliable method to obtain molecular information for breast tumor analysis during surgery. Here, we present a novel air flow-assisted ionization (AFAI) mass spectrometry imaging method that can be used in ambient environments to differentiate breast cancer by analyzing lipids. In this study, we demonstrate that various subtypes and histological grades of IDC and DCIS can be discriminated using AFAI-MSI: phospholipids were more abundant in IDC than in DCIS, whereas fatty acids were more abundant in DCIS than in IDC. The classification of specimens in the subtype and grade validation sets showed 100% and 78.6% agreement with the histopathological diagnosis, respectively. Our work shows the rapid classification of breast cancer utilizing AFAI-MSI. This work suggests that this method could be developed to provide surgeons with nearly real-time information to guide surgical resections.

Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease. Tubular abnormalities may precede glomerular pathology and indicate functional progression of DKD. Here, we find glucagon injection exacerbates lipid accumulation and renal injury, in addition to causing morphological changes in proximal tubules, podocytes, and mitochondria in the early phase of DKD in mice. However, the specific knockdown or knockout of Gcgr in renal tubular epithelial cells almost completely halts DKD development. In contrast to the effect of short-term glucagon stimulation, long-term glucagon exposure leads to the reversal of glucagon action (glucagon reversal) in proximal tubular epithelial cells (PTECs), which is characterized by reduced energy production and an increase in lipogenesis through Gcgr-PKA-Creb-mTORC1 pathway. Accordingly, anti-GCGR antibody treatment strongly blocks the pathogenesis of DKD induced by both type 2 and type 1 diabetes. Thus, our results highlight a previously unrecognized role of glucagon/Gcgr signaling in PTEC lipogenesis and DKD. Diabetic kidney disease (DKD) is the leading cause of end-stage kidney failure. This study shows that prolonged glucagon exacerbates lipid accumulation, promoting renal injury in early DKD, rather than lipid oxidation. Targeting glucagon signaling significantly inhibits DKD progression.

The pathological diagnosis of benign and malignant follicular thyroid tumors remains a major challenge using the current histopathological technique. To improve diagnosis accuracy, spatially resolved metabolomics analysis based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) technique was used to establish a molecular diagnostic strategy for discriminating four pathological types of thyroid tumor. Without any specific labels, numerous metabolite features with their spatial distribution information can be acquired by AFADESI-MSI. The underlying metabolic heterogeneity can be visualized in line with the cellular heterogeneity in native tumor tissue. Through micro-regional feature extraction and in situ metabolomics analysis, three sets of metabolic biomarkers for the visual discrimination of benign follicular adenoma and differentiated thyroid carcinomas were discovered. Additionally, the automated prediction of tumor foci was supported by a diagnostic model based on the metabolic profile of 65 thyroid nodules. The model prediction accuracy was 83.3% when a test set of 12 independent samples was used. This diagnostic strategy presents a new way of performing in situ pathological examinations using small molecular biomarkers and provides a model diagnosis for clinically indeterminate thyroid tumor cases.