Metabolic regulation of the immune system in health and diseases: mechanisms and interventions

Hu, Tengyue; Liu, Chang-Hai; Lei, Min; Zeng, Qingmin; Li, Li; Tang, Hong; Zhang, Nannan

doi:10.1038/s41392-024-01954-6

Cited by 6 publications

References 570 publications

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Deciphering Metabolic Pathways and Protein-Protein Interaction Networks in Ankylosing Spondylitis through Single-Cell RNA Sequencing

Yarıcı,

Karabekmez

2024

Preprint

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Ankylosing Spondylitis (AS) is a common autoimmune disease affecting spinal joints and causing chronic pain. Understanding the roles of different cell types in AS can facilitate the development of effective treatments. In this study, we analyzed scRNA-seq data of peripheral blood mononuclear cells (PBMC) from AS patients and healthy controls collected from the literature. Using the GIMME algorithm, we created genome-scale metabolic models for each cell type to analyze reaction fluxes varying between patient and healthy conditions. Our findings revealed increased purine metabolism flux, fatty acid degradation, and glycolysis in CD14 monocytes, CD4 memory, CD4 naive, and CD8 T cells in AS patients compared to healthy individuals. Additionally, by integrating multi-omics approaches we generated cell-type-specific protein-protein interaction (PPI) networks, uncovering 63 rewired hubs across nine cell types. RPS11 emerged as the most significant hub, essential in translation and there are evidences in the literature that implicate it in AS. These results provide a detailed understanding of the metabolic and protein interaction changes in specific immune cell types in AS, highlighting RPS11 as a critical regulatory hub that could serve as a potential biomarker or therapeutic target for developing more precise and effective treatments.

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Deciphering Metabolic Pathways and Protein-Protein Interaction Networks in Ankylosing Spondylitis through Single-Cell RNA Sequencing

Yarıcı,

Karabekmez

2024

Preprint

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Immunogenic shift of arginine metabolism triggers systemic metabolic and immunological reprogramming to prevent HER2+ breast cancer

Sharma,

Fernando,

Zheng

et al. 2024

Preprint

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Arginine metabolism in tumors is often shunted into the pathway producing pro-tumor and immune suppressive polyamines (PAs), while downmodulating the alternative nitric oxide (NO) synthesis pathway. Aiming to correct arginine metabolism in tumors, arginine deprivation therapy and inhibitors of PA synthesis have been developed. Despite some therapeutic advantages, these approaches have often yielded severe side effects, making it necessary to explore an alternative strategy. We previously reported that supplementing SEP, the endogenous precursor of BH4 (the essential NO synthase cofactor), could correct arginine metabolism in tumor cells and tumor-associated macrophages (TAMs) and induce their metabolic and phenotypic reprogramming. We saw that oral SEP treatment effectively suppressed the growth of HER2-positive mammary tumors in animals. SEP also has no reported dose-dependent toxicity in clinical trials for metabolic disorders. In the present study, we report that a long-term use of SEP in animals susceptible to HER2-positive mammary tumors effectively prevented tumor occurrence. These SEP-treated animals had undergone reprogramming of the systemic metabolism and immunity, elevating total T cell counts in the circulation and bone marrow. Given that bone marrow-resident T cells are mostly memory T cells, it is plausible that chronic SEP treatment promoted memory T cell formation, leading to a potent tumor prevention. These findings suggest the possible roles of the SEP/BH4/NO axis in promoting memory T cell formation and its potential therapeutic utility for preventing HER2-positive breast cancer.

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Signature of immune-related metabolic genes predicts the prognosis of hepatocellular carcinoma

Zhuo,

Xia,

Lan

et al. 2024

Front. Immunol.

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IntroductionThe majority of liver cancer cases (90%) are attributed to hepatocellular carcinoma (HCC), which exhibits significant heterogeneity and an unfavorable prognosis. Modulating the immune response and metabolic processes play a crucial role in both the prevention and treatment of HCC. However, there is still a lack of comprehensive understanding regarding the immune-related metabolic genes that can accurately reflect the prognosis of HCC.MethodsIn order to address this issue, we developed a prognostic prediction model based on immune and metabolic genes. To evaluate the accuracy of our model, we performed survival analyses including Kaplan-Meier (K-M) curve and time-dependent receiver operating characteristic (ROC) curve. Furthermore, we compared the predictive performance of our risk model with existing models. Finally, we validated the accuracy of our risk model using mouse models with in situ transplanted liver cancer.ResultsBy conducting lasso regression analysis, we identified four independent prognostic genes: fatty acid binding protein 6 (FABP6), phosphoribosyl pyrophosphate amidotransferase (PPAT), spermine synthase (SMS), and dihydrodiol dehydrogenase (DHDH). Based on these findings, we constructed a prognostic model. Survival analysis revealed that the high-risk group had significantly lower overall survival (OS) rates. Besides that, the ROC curve demonstrated the effective prognostic capability of our risk model for hepatocellular carcinoma (HCC) patients. Furthermore, through animal experiments, we validated the accuracy of our model by showing a correlation between high-risk scores and poor prognosis in tumor development.DiscussionIn conclusion, our prognostic model surpasses those solely based on immune genes or metabolic genes in terms of accuracy. We observed variations in prognosis among different risk groups, accompanied by distinct immune and metabolic characteristics. Therefore, our model provides an original evaluation index for personalized clinical treatment strategies targeting HCC patients.

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Metabolic regulation of the immune system in health and diseases: mechanisms and interventions

Cited by 6 publications

References 570 publications

Deciphering Metabolic Pathways and Protein-Protein Interaction Networks in Ankylosing Spondylitis through Single-Cell RNA Sequencing

Deciphering Metabolic Pathways and Protein-Protein Interaction Networks in Ankylosing Spondylitis through Single-Cell RNA Sequencing

Immunogenic shift of arginine metabolism triggers systemic metabolic and immunological reprogramming to prevent HER2+ breast cancer

Signature of immune-related metabolic genes predicts the prognosis of hepatocellular carcinoma

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