Diet–Microbiota–Immune Interactions in Hepatocellular Carcinoma: An Immunometabolic and Spatial Perspective
Abstract
1. Introduction
2. Nutritional Inputs Shaping the Gut–Liver Axis
2.1. Macronutrient Effects: Lipids, Proteins, and Carbohydrates
2.2. Micronutrients and Bioactives: Vitamins and Polyphenols
2.3. Nutrient Sensing and Signal Integration: AMPK, mTOR, PPAR, and SIRT1
3. Microbial Metabolites as Mediators of Nutritional Signaling
3.1. Short-Chain Fatty Acids (SCFAs)
3.2. Bile Acids (FXR/TGR5 Link)
3.3. Tryptophan Metabolites and the AhR Pathway
3.4. Polyphenol and Lipid-Derived Metabolites
4. Conceptual Framework of Spatial Immunometabolism in Hepatocellular Carcinoma (HCC)
5. Spatial Cellular and Immune Niches in Hepatocellular Carcinoma
5.1. Spatial Heterogeneity in Liver Tissue
5.2. Immune Cell Spatial Niches
5.3. Spatial Omics in Hepatocellular Carcinoma (HCC)
6. Mechanistic Pathways Connecting Diet-Derived Metabolites and Spatial Immunity
6.1. FXR and TGR5
6.2. AHR Pathway
6.3. Nrf2/NF-κB Axis
6.4. AMPK/mTOR Signaling
6.5. Epigenetic and Redox Interactions
7. Nutritional and Microbiota-Based Interventions to Reprogram the HCC Immunometabolome
7.1. Probiotics
7.2. Prebiotics
7.3. Functional Foods and Phytochemicals
7.4. Diet Composition Interventions
7.5. Personalized Nutrition Strategies
8. Emerging Technologies to Map and Manipulate the Nutritional Immunometabolome
8.1. Spatial Metabolomics and Lipidomics
8.2. Imaging Mass Cytometry
8.3. Multi-Omics Integration
8.4. Computational Modeling and Artificial Intelligence
9. Translational Perspectives for Nutritional Immunotherapy in Hepatocellular Carcinoma
9.1. Concept of Nutritional Immunotherapy
9.2. Biomarkers and Diagnostics
9.3. Synergy with Immunotherapy
10. Conclusions
11. Future Clinical Directions
- Nutritional modulation based on mechanistic understanding should replace non-specific dietary recommendations, and interventions should be designed to influence major immunometabolic circuits such as AMPK-mTOR, FXR/TGR5, AhR, and redox-epigenetic signals in HCC.
- Nutritional conditioning of antitumor immunity represents a promising strategy to improve antitumor immune responsiveness to immune checkpoint inhibitors by promoting mitochondrial metal homeostasis, improving effector T-cell metabolic performance, and inhibiting immunosuppressive pathways in the tumor microenvironment.
- Gut microbiota composition, circulating microbial metabolites, and host immunometabolic profiles can inform precision nutrition approaches that stratify patients and enable tailored dietary interventions according to disease stage and etiology.
- Diet-derived microbial metabolites, including short-chain fatty acids, bile acid derivatives, and tryptophan catabolites, have the potential to be non-invasive biomarkers for measuring immune competence, disease progression, and therapeutic response.
- Hepatic immune and metabolic zonation should be considered as part of spatially informed intervention strategies, as the nutritional modulation of immune-excluded or metabolically dysregulated tumor niches may be feasible.
- Integrative models based on artificial intelligence can support adaptive nutrition interventions, which can be achieved by combining dietary, microbial, metabolomic, and immune data, and optimizing therapeutic interventions dynamically.
- Clinical trials need to be redesigned to consider nutrition and microbiota modulation as active therapeutic variables in order to demonstrate causality and accelerate clinical translation.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| ACOT12 | Acetyl-CoA thioesterase 12 |
| ACSS2 | Acyl-CoA synthetase short-chain family member 2 |
| AhR | Aryl hydrocarbon receptor |
| AMPK | AMP-activated protein kinase |
| ARNT | AhR nuclear translocator |
| BMI | Body mass index |
| BTB | Broad-complex, Tramtrack and Bric-à-brac domain |
| CAF | Cancer-associated fibroblast |
| CD8+ | Cluster of differentiation 8-positive T cell |
| CT | Computed tomography |
| CTL | Cytotoxic T lymphocyte |
| CTLA-4 | Cytotoxic T-lymphocyte-associated protein 4 |
| CXCL11 | C-X-C motif chemokine ligand 11 |
| CYP1A1 | Cytochrome P450 family 1 subfamily A member 1 |
| CYP1A2 | Cytochrome P450 family 1 subfamily A member 2 |
| CYP1B1 | Cytochrome P450 family 1 subfamily B member 1 |
| CYP8B1 | Cholesterol 12α-hydroxylase |
| DCA | Deoxycholic acid |
| DFS | Disease-free survival |
| DLG | Asp-Leu-Gly motif |
| DNA | Deoxyribonucleic acid |
| ER | Endoplasmic reticulum |
| ETGE | Glu-Thr-Gly-Glu motif |
| FXR | Farnesoid X receptor |
| GEMs | Genome-scale metabolic models |
| GM-CSF | Granulocyte-macrophage colony-stimulating factor |
| H3K9Ac | Histone H3 lysine 9 acetylation |
| HCC | Hepatocellular carcinoma |
| HDAC | Histone deacetylase |
| HIF | Hypoxia-inducible factor |
| IDO1 | Indoleamine 2,3-dioxygenase 1 |
| IFN-γ | Interferon gamma |
| IL-17A | Interleukin 17A |
| IL-22 | Interleukin 22 |
| IMC | Imaging Mass Cytometry |
| ICI | Immune checkpoint inhibitor |
| ILC3 | Type 3 innate lymphoid cell |
| IVR | Intervening region |
| Keap1 | Kelch-like ECH-associated protein 1 |
| LPS | Lipopolysaccharide |
| MASLD | Metabolically-dysfunction-associated steatotic liver disease |
| MAT1A | Methionine adenosyltransferase 1A |
| MAT2A | Methionine adenosyltransferase 2A |
| MCT-1 | Monocarboxylate transporter 1 |
| MDSC | Myeloid-derived suppressor cell |
| MLCK | Myosin light chain kinase |
| mRNA | Messenger RNA |
| mTOR | Mechanistic target of rapamycin |
| NADPH | Nicotinamide adenine dinucleotide phosphate |
| NF-κB | Nuclear factor kappa B |
| NK | Natural killer |
| NOX | NADPH oxidase |
| Nrf2 | Nuclear factor erythroid 2-related factor 2 |
| ORR | Objective response rate |
| OS | Overall survival |
| PAS | Per-ARNT-Sim |
| PD-1 | Programmed cell death protein 1 |
| PD-L1 | Programmed death-ligand 1 |
| PNI | Prognostic nutritional index |
| PGE2 | Prostaglandin E2 |
| PUFA | Polyunsaturated fatty acid |
| RBX1 | RING-box protein 1 |
| ROS | Reactive oxygen species |
| SAM | S-adenosyl-L-methionine |
| SCFA | Short-chain fatty acid |
| SIRT3 | Sirtuin 3 |
| SPM | Specialized pro-resolving mediator |
| TGR5 | Takeda G protein-coupled receptor 5 |
| TLR4 | Toll-like receptor 4 |
| TME | Tumor microenvironment |
| Treg | Regulatory T cell |
| XRE | Xenobiotic response element |
References
- Scarlata, G.G.M.; Cicino, C.; Spagnuolo, R.; Marascio, N.; Quirino, A.; Matera, G.; Dumitrașcu, D.; Luzza, F.; Abenavoli, L. Impact of diet and gut microbiota changes in the development of hepatocellular carcinoma. Hepatoma Res. 2024, 10, 19. [Google Scholar] [CrossRef] [Scilit]
- Devarbhavi, H.; Asrani, S.K.; Arab, J.P.; Nartey, Y.A.; Pose, E.; Kamath, P.S. Global burden of liver disease: 2023 update. J. Hepatol. 2023, 79, 516–537. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Peiseler, M.; Tacke, F. Inflammatory mechanisms underlying nonalcoholic steatohepatitis and the transition to hepatocellular carcinoma. Cancers 2021, 13, 730. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Lin, J.; Rao, D.; Zhang, M.; Gao, Q. Metabolic reprogramming in the tumor microenvironment of liver cancer. J. Hematol. Oncol. 2024, 17, 6. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Hu, N.; Li, H.; Tao, C.; Xiao, T.; Rong, W. The Role of Metabolic Reprogramming in the Tumor Immune Microenvironment: Mechanisms and Opportunities for Immunotherapy in Hepatocellular Carcinoma. Int. J. Mol. Sci. 2024, 25, 5584. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Yang, J.; He, J.; Feng, Y.; Xiang, M. Obesity contributes to hepatocellular carcinoma development via immunosuppressive microenvironment remodeling. Front. Immunol. 2023, 14, 1166440. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Moretti, H.; Cioccoloni, G.; Perucha, E. Immunometabolism in cancer: A systemic perspective. Front. Immunol. 2025, 16, 1656776. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Siemińska, I.; Lenart, M. Immunometabolism of Innate Immune Cells in Gastrointestinal Cancer. Cancers 2025, 17, 1467. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Pan, D.; Bao, Y.; Lu, X.; Gu, Q.; Zhang, Y.; Zheng, Y. Short-chain fatty acids regulate hepatocellular carcinoma progression: A metabolic perspective on tumor immunity (Review). Int. J. Mol. Med. 2025, 56, 214. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Llopis, J.M.L.; Brown, D.; Saiz, B. Chenopodium quinoa and Salvia hispanica provide immunonutritional agonists to ameliorate hepatocarcinoma severity under a high-fat diet. Nutrients 2020, 12, 1946. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Kumar, A.R.; Nair, B.; Kamath, A.J.; Nath, L.R.; Calina, D.; Sharifi-Rad, J. Impact of gut microbiota on metabolic dysfunction-associated steatohepatitis and hepatocellular carcinoma: Pathways, diagnostic opportunities and therapeutic advances. Eur. J. Med. Res. 2024, 29, 485. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Monti, E.; Vianello, C.; Leoni, I.; Galvani, G.; Lippolis, A.; D’Amico, F.; Roggiani, S.; Stefanelli, C.; Turroni, S.; Fornari, F. Gut Microbiome Modulation in Hepatocellular Carcinoma: Preventive Role in NAFLD/NASH Progression and Potential Applications in Immunotherapy-Based Strategies. Cells 2025, 14, 84. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Lee, J.J.X.; Liu, L.; Kwa, S.W.T.; Lee, S.Y.; Tai, D.; Lee, J. 60P Longitudinal dynamics of the gut microbiome and dietary associations in immunotherapy-treated hepatobiliary cancer patients. ESMO Open 2025, 10, 105635. [Google Scholar] [CrossRef] [Scilit]
- Maher, S. Microbiome–Immune Interplay in Colorectal and Hepatocellular Carcinomas. SN Compr. Clin. Med. 2025, 7, 254. [Google Scholar] [CrossRef] [Scilit]
- Scarpellini, E.; Scarcella, M.; Tack, J.F.; Scarlata, G.G.M.; Zanetti, M.; Abenavoli, L. Gut Microbiota and Metabolic Dysfunction-Associated Steatotic Liver Disease. Antioxidants 2024, 13, 1386. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Carloni, S.; Strati, F. The Gut Vascular Barrier: Linking the Intestinal Environment with Blood Circulation; Springer: Cham, Switzerland, 2025; pp. 57–74. [Google Scholar] [CrossRef] [Scilit]
- Man, A.W.C.; Zhou, Y.; Xia, N.; Li, H. Involvement of gut microbiota, microbial metabolites and interaction with polyphenol in host immunometabolism. Nutrients 2020, 12, 3054. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Ju, Y.; Xu, K.; Chen, X.; Wu, T.; Yuan, Y. Metabolic-immune microenvironment crosstalk mediating ICI resistance in MASH-HCC. Trends Endocrinol. Metab. 2025, 37, 262–276. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Xiao, Y.; Li, Y.; Zhao, H. Spatiotemporal metabolomic approaches to the cancer-immunity panorama: A methodological perspective. Mol. Cancer 2024, 23, 202. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Jee, Y.M.; Lee, J.Y.; Ryu, T. Chronic Inflammation and Immune Dysregulation in Metabolic-Dysfunction-Associated Steatotic Liver Disease Progression: From Steatosis to Hepatocellular Carcinoma. Biomedicines 2025, 13, 1260. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Wang, R.; Tang, D.; Wu, L.; Ou, L.; Ding, L.; Jiang, J.; Wu, Y. Bielong Ruangan decoction inhibits tumor growth and improves immune response in a hepatocellular carcinoma mouse model through gut microbiota. Int. J. Biochem. Cell Biol. 2026, 190, 106873. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Chen, S.; Zhang, Y.; Li, X.; Zhang, Y.; Zeng, Y. Driving innovations in cancer research through spatial metabolomics: A bibliometric review of trends and hotspot. Front. Immunol. 2025, 16, 1589943. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Li, H.; Zhang, J.; Shi, Y.; Wang, H.; Yang, R.; Wu, S.; Li, Y.; Yang, X.; Liu, Q.; Sun, L. Identification of matrix stiffness-related molecular subtypes in HCC via integrating multi-omics analysis and machine learning algorithms. J. Transl. Med. 2025, 23, 716. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Puri, M. Spatial Computational Hepatic Molecular Biomarker Reveals LSEC Role in Midlobular Liver Zonation Fibrosis in DILI and NASH Liver Injury. Int. J. Transl. Med. 2024, 4, 208–223. [Google Scholar] [CrossRef] [Scilit]
- Panday, R.; Monckton, C.P.; Khetani, S.R. The Role of Liver Zonation in Physiology, Regeneration, and Disease. Semin. Liver Dis. 2022, 42, 1–16. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Halpern, K.B.; Shenhav, R.; Matcovitch-Natan, O.; Tóth, B.; Lemze, D.; Golan, M.; Massasa, E.E.; Baydatch, S.; Landen, S.; Moor, A.E.; et al. Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature 2017, 542, 352–356. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Guillot, A.; Tacke, F. Spatial dimension of macrophage heterogeneity in liver diseases. eGastroenterology 2023, 1, e000003. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Guilliams, M.; Bonnardel, J.; Haest, B.; Vanderborght, B.; Wagner, C.; Remmerie, A.; Bujko, A.; Martens, L.; Thoné, T.; Browaeys, R.; et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell 2022, 185, 379–396.e38. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Krenkel, O.; Tacke, F. Liver macrophages in tissue homeostasis and disease. Nat. Rev. Immunol. 2017, 17, 306–321. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Lawal, G.; Xiao, Y.; Rahnemai-Azar, A.A.; Tsilimigras, D.I.; Kuang, M.; Bakopoulos, A.; Pawlik, T.M. The Immunology of Hepatocellular Carcinoma. Vaccines 2021, 9, 1184. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Huang, W.; Rui, K.; Wang, X.; Peng, N.; Zhou, W.; Shi, X.; Lu, L.; Hu, D.; Tian, J. The aryl hydrocarbon receptor in immune regulation and autoimmune pathogenesis. J. Autoimmun. 2023, 138, 103049. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Chen, T.Y.; You, L.; Hardillo, J.A.U.; Chien, M.P. Spatial Transcriptomic Technologies. Cells 2023, 12, 2042. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Wang, F.; Huang, Y.-S.; Wu, H.-X.; Wang, Z.-X.; Jin, Y.; Yao, Y.-C.; Chen, Y.-X.; Zhao, Q.; Chen, S.; He, M.-M.; et al. Genomic temporal heterogeneity of circulating tumour DNA in unresectable metastatic colorectal cancer under first-line treatment. Gut 2022, 71, 1340–1349. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zhang, Q.; He, Y.; Luo, N.; Patel, S.J.; Han, Y.; Gao, R.; Modak, M.; Carotta, S.; Haslinger, C.; Kind, D.; et al. Landscape and Dynamics of Single Immune Cells in Hepatocellular Carcinoma. Cell 2019, 179, 829–845.e20. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Yin, Z.; Dong, C.; Jiang, K.; Xu, Z.; Li, R.; Guo, K.; Shao, S.; Wang, L. Heterogeneity of cancer-associated fibroblasts and roles in the progression, prognosis, and therapy of hepatocellular carcinoma. J. Hematol. Oncol. 2019, 12, 101. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Ramachandran, P.; Matchett, K.P.; Dobie, R.; Wilson-Kanamori, J.R.; Henderson, N.C. Single-cell technologies in hepatology: New insights into liver biology and disease pathogenesis. Nat. Rev. Gastroenterol. Hepatol. 2020, 17, 457–472. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Adapa, S.R.; Porshe, S.; Talada, D.P.; Nywening, T.M.; Anderson, M.L.; Shaw, T.I.; Jiang, R.H.Y. Spatial Transcriptomics Reveals Distinct Architectures but Shared Vulnerabilities in Primary and Metastatic Liver Tumors. Cancers 2025, 17, 3210. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Liu, Y.; Dong, G.; Yu, J.; Liang, P. Integrative Analysis of Single-Cell and Spatial Transcriptomics Reveals Intratumor Heterogeneity Shaping the Tumor Microenvironment in Hepatocellular Carcinoma. Livers 2025, 5, 62. [Google Scholar] [CrossRef] [Scilit]
- Affo, S.; Yu, L.X.; Schwabe, R.F. The Role of Cancer-Associated Fibroblasts and Fibrosisin Liver Cancer. Annu. Rev. Pathol. Mech. Dis. 2017, 12, 153–186. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Tong, W.; Wang, T.; Bai, Y.; Yang, X.; Han, P.; Zhu, L.; Zhang, Y.; Shen, Z. Spatial transcriptomics reveals tumor-derived SPP1 induces fibroblast chemotaxis and activation in the hepatocellular carcinoma microenvironment. J. Transl. Med. 2024, 22, 840. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Kong, Z.; Li, Z.; Cui, X.Y.; Wang, J.; Xu, M.; Liu, Y.; Chen, J.; Ni, S.; Zhang, Z.; Fan, X.; et al. CTR-FAPI PET Enables Precision Management of Medullary Thyroid Carcinoma. Cancer Discov. 2025, 15, 316–328. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Lin, S.; Wang, S.; Wang, P.; Tang, C.; Wang, Z.; Chen, L.; Luo, G.; Chen, H.; Liu, Y.; Feng, B.; et al. Bile acids and their receptors in regulation of gut health and diseases. Prog. Lipid Res. 2023, 89, 101210. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Guak, H.; Krawczyk, C.M. Implications of cellular metabolism for immune cell migration. Immunology 2020, 161, 200–208. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Song, G.; Xie, Y.; Yi, L.; Cheng, W.; Jia, H.; Shi, W.; Liu, Q.; Fang, L.; Xue, S.; Liu, D.; et al. Bile acids affect intestinal barrier function through FXR and TGR. Front. Med. 2025, 12, 1607899. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Maruyama, T.; Miyamoto, Y.; Nakamura, T.; Tamai, Y.; Okada, H.; Sugiyama, E.; Nakamura, T.; Itadani, H.; Tanaka, K. Identification of membrane-type receptor for bile acids (M-BAR). Biochem. Biophys. Res. Commun. 2002, 298, 714–719. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Hofmann, A.F.; Hagey, L.R. Bile acids: Chemistry, pathochemistry, biology, pathobiology, and therapeutics. Cell. Mol. Life Sci. 2008, 65, 2461–2483. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Jiang, C.; Xie, C.; Lv, Y.; Li, J.; Krausz, K.W.; Shi, J.; Brocker, C.N.; Desai, D.; Amin, S.G.; Bisson, W.H.; et al. Intestine-selective farnesoid X receptor inhibition improves obesity-related metabolic dysfunction. Nat. Commun. 2015, 6, 10166. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zhang, Y.; Edwards, P.A. FXR signaling in metabolic disease. FEBS Lett. 2008, 582, 10–18. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Huang, S.; Wu, Y.; Zhao, Z.; Wu, B.; Sun, K.; Wang, H.; Qin, L.; Bai, F.; Leng, Y.; Tang, W.; et al. A new mechanism of obeticholic acid on NASH treatment by inhibiting NLRP3 inflammasome activation in macrophage. Metab. Clin. Exp. 2021, 120, 154797. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Coppola, C.P.; Gosche, J.R.; Arrese, M.; Ancowitz, B.; Madsen, J.; Vanderhoof, J.; Shneider, B.L. Molecular analysis of the adaptive response of intestinal bile acid transport after ileal resection in the rat. Gastroenterology 1998, 115, 1172–1178. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Pols, T.W.H.; Noriega, L.G.; Nomura, M.; Auwerx, J.; Schoonjans, K. The bile acid membrane receptor TGR5 as an emerging target in metabolism and inflammation. J. Hepatol. 2011, 54, 1263–1272. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Schaap, F.G.; Trauner, M.; Jansen, P.L.M. Bile acid receptors as targets for drug development. Nat. Rev. Gastroenterol. Hepatol. 2014, 11, 55–67. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Keitel, V.; Häussinger, D. Role of TGR5 (GPBAR1) in Liver Disease. Semin. Liver Dis. 2018, 38, 333–339. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Wang, Y.D.; Chen, W.D.; Yu, D.; Forman, B.M.; Huang, W. The G-Protein-coupled bile acid receptor, Gpbar1 (TGR5), negatively regulates hepatic inflammatory response through antagonizing nuclear factor kappa light-chain enhancer of activated B cells (NF-κB) in mice. Hepatology 2011, 54, 1421–1432. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Kuhre, R.E.; Wewer Albrechtsen, N.J.; Larsen, O.; Jepsen, S.L.; Balk-Møller, E.; Andersen, D.B.; Deacon, C.F.; Schoonjans, K.; Reimann, F.; Gribble, F.M.; et al. Bile acids are important direct and indirect regulators of the secretion of appetite- and metabolism-regulating hormones from the gut and pancreas. Mol. Metab. 2018, 11, 84–95. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Watanabe, M.; Houten, S.M.; Mataki, C.; Christoffolete, M.A.; Kim, B.W.; Sato, H.; Messaddeq, N.; Harney, J.W.; Ezaki, O.; Kodama, T.; et al. Bile acids induce energy expenditure by promoting intracellular thyroid hormone activation. Nature 2006, 439, 484–489. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Song, M.; Zhang, F.; Fu, Y.; Yi, X.; Feng, S.; Liu, Z.; Deng, D.; Yang, Q.; Yu, M.; Zhu, C.; et al. Tauroursodeoxycholic acid (TUDCA) improves intestinal barrier function associated with TGR5-MLCK pathway and the alteration of serum metabolites and gut bacteria in weaned piglets. J. Anim. Sci. Biotechnol. 2022, 13, 73. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Stevens, E.A.; Mezrich, J.D.; Bradfield, C.A. The aryl hydrocarbon receptor: A perspective on potential roles in the immune system. Immunology 2009, 127, 299–311. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Tian, J.; Feng, Y.; Fu, H.; Xie, H.Q.; Jiang, J.X.; Zhao, B. The Aryl Hydrocarbon Receptor: A Key Bridging Molecule of External and Internal Chemical Signals. Environ. Sci. Technol. 2015, 49, 9518–9531. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Ikuta, T.; Tachibana, T.; Watanabe, J.; Yoshida, M.; Yoneda, Y.; Kawajiri, K. Nucleocytoplasmic shuttling of the aryl hydrocarbon receptor. J. Biochem. 2000, 127, 503–509. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Fujii-Kuriyama, Y.; Mimura, J. Molecular mechanisms of AhR functions in the regulation of cytochrome P450 genes. Biochem. Biophys. Res. Commun. 2005, 338, 311–317. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Liu, D.; Ray, B.; Neavin, D.R.; Zhang, J.; Athreya, A.P.; Biernacka, J.M.; Bobo, W.V.; Hall-Flavin, D.K.; Skime, M.K.; Zhu, H.; et al. Beta-defensin 1, aryl hydrocarbon receptor and plasma kynurenine in major depressive disorder: Metabolomics-informed genomics. Transl. Psychiatry 2018, 8, 10. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Liu, D.; Qin, S.; Ray, B.; Kalari, K.R.; Wang, L.; Weinshilboum, R.M. Single Nucleotide Polymorphisms (SNPs) Distant from xenobiotic response elements can modulate aryl hydrocarbon receptor function: SNP-dependent CYP1A1 induction. Drug Metab. Dispos. 2018, 46, 1372–1381. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Trofimiuk-Müldner, M.; Domagała, B.; Sokołowski, G.; Skalniak, A.; Hubalewska-Dydejczyk, A. AIP gene germline variants in adult Polish patients with apparently sporadic pituitary macroadenomas. Front. Endocrinol. 2023, 14, 1098367. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Saito, R.; Suzuki, T.; Hiramoto, K.; Asami, S.; Naganuma, E.; Suda, H.; Iso, T.; Yamamoto, H.; Morita, M.; Baird, L.; et al. Characterizations of Three Major Cysteine Sensors of Keap1 in Stress Response. Mol. Cell. Biol. 2016, 36, 271–284. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Liu, T.; Lv, Y.F.; Zhao, J.L.; You, Q.D.; Jiang, Z.Y. Regulation of Nrf2 by phosphorylation: Consequences for biological function and therapeutic implications. Free Radic. Biol. Med. 2021, 168, 129–141. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Jain, R.; Vora, L.; Nathiya, D.; Khatri, D.K. Nrf2–Keap1 Pathway and NLRP3 Inflammasome in Parkinson’s Disease: Mechanistic Crosstalk and Therapeutic Implications. Mol. Neurobiol. 2026, 63, 91. [Google Scholar] [CrossRef] [Scilit]
- Mossmann, D.; Park, S.; Hall, M.N. mTOR signalling and cellular metabolism are mutual determinants in cancer. Nat. Rev. Cancer 2018, 18, 744–757. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Wang, N.; Wang, B.; Maswikiti, E.P.; Yu, Y.; Song, K.; Ma, C.; Han, X.; Ma, H.; Deng, X.; Yu, R.; et al. AMPK–a key factor in crosstalk between tumor cell energy metabolism and immune microenvironment? Cell Death Discov. 2024, 10, 237. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Torres Acosta, M.A.; Gurkan, J.K.; Liu, Q.; Mambetsariev, N.; Flores, C.R.; Helmin, K.A.; Joudi, A.M.; Morales-Nebreda, L.; Cheng, K.; Abdala-Valencia, H.; et al. AMPK is necessary for Treg functional adaptation to microenvironmental stress during malignancy and viral pneumonia. J. Clin. Investig. 2025, 135, e179572. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Marafie, S.K.; Al-Mulla, F.; Abubaker, J. mTOR: Its Critical Role in Metabolic Diseases, Cancer, and the Aging Process. Int. J. Mol. Sci. 2024, 25, 6141. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Smiles, W.J.; Ovens, A.J.; Kemp, B.E.; Galic, S.; Petersen, J.; Oakhill, J.S. New developments in AMPK and mTORC1 cross-talk. Essays Biochem. 2024, 68, 321–336. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Keerthana, C.K.; Rayginia, T.P.; Shifana, S.C.; Anto, N.P.; Kalimuthu, K.; Isakov, N.; Anto, R.J. The role of AMPK in cancer metabolism and its impact on the immunomodulation of the tumor microenvironment. Front. Immunol. 2023, 14, 1114582. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zhang, T.; Wang, X.; Alexander, P.G.; Feng, P.; Zhang, J. An Analysis of AMPK and Ferroptosis in Cancer: A Potential Regulatory Axis. Front. Biosci. Landmark Ed. 2025, 30, 36618. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Chen, W.; Zhao, H.; Li, Y. Mitochondrial dynamics in health and disease: Mechanisms and potential targets. Signal Transduct. Target. Ther. 2023, 8, 333. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Alasadi, A.; Fadhil, N.; Chen, S. Deciphering the critical roles of the AMPK/mTOR signaling pathway in cancer cell metabolism (Review). World Acad. Sci. J. 2025, 7, 103. [Google Scholar] [CrossRef] [Scilit]
- Negm, S.H. Novel therapeutic strategies targeting gut microbiota to treat diseases. In The Gut Microbiota in Health and Disease; E-Publishing Inc.: New York, NY, USA, 2023; pp. 133–141. [Google Scholar] [CrossRef] [Scilit]
- Pathak, A.; Tomar, S.; Pathak, S. Epigenetics and Cancer: A Comprehensive Review. Asian Pac. J. Cancer Biol. 2023, 8, 75–89. [Google Scholar] [CrossRef] [Scilit]
- Jorgenson, T.C.; Zhong, W.; Oberley, T.D. Redox imbalance and biochemical changes in cancer. Cancer Res. 2013, 73, 6118–6123. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Bayo, J.; Fiore, E.J.; Dominguez, L.M.; Real, A.; Malvicini, M.; Rizzo, M.; Atorrasagasti, C.; García, M.G.; Argemi, J.; Martinez, E.D.; et al. A comprehensive study of epigenetic alterations in hepatocellular carcinoma identifies potential therapeutic targets. J. Hepatol. 2019, 71, 78–90. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Jühling, F.; Hamdane, N.; Crouchet, E.; Li, S.; El Saghire, H.; Mukherji, A.; Fujiwara, N.; Oudot, M.A.; Thumann, C.; Saviano, A.; et al. Targeting clinical epigenetic reprogramming for chemoprevention of metabolic and viral hepatocellular carcinoma. Gut 2021, 70, 157–169. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Wang, R.; Jin, Y.; Yao, X.H.; Fan, W.; Zhang, J.; Cao, Y.; Li, J. A novel mechanism of the M1-M2 methionine adenosyltransferase switch-mediated hepatocellular carcinoma metastasis. Mol. Carcinog. 2018, 57, 1201–1212. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Lu, M.; Zhu, W.W.; Wang, X.; Tang, J.J.; Zhang, K.L.; Yu, G.Y.; Shao, W.Q.; Lin, Z.F.; Wang, S.H.; Lu, L.; et al. ACOT12-Dependent Alteration of Acetyl-CoA Drives Hepatocellular Carcinoma Metastasis by Epigenetic Induction of Epithelial-Mesenchymal Transition. Cell Metab. 2019, 29, 886–900.e5. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Sutendra, G.; Kinnaird, A.; Dromparis, P.; Paulin, R.; Stenson, T.H.; Haromy, A.; Hashimoto, K.; Zhang, N.; Flaim, E.; Michelakis, E.D. A nuclear pyruvate dehydrogenase complex is important for the generation of Acetyl-CoA and histone acetylation. Cell 2014, 158, 84–97. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Sun, L.; Kong, Y.; Cao, M.; Zhou, H.; Li, H.; Cui, Y.; Fang, F.; Zhang, W.; Li, J.; Zhu, X.; et al. Decreased expression of acetyl-CoA synthase 2 promotes metastasis and predicts poor prognosis in hepatocellular carcinoma. Cancer Sci. 2017, 108, 1338–1346. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Vodnala, S.K.; Eil, R.; Kishton, R.J.; Sukumar, M.; Yamamoto, T.N.; Ha, N.H.; Lee, P.H.; Shin, M.; Patel, S.J.; Yu, Z.; et al. T cell stemness and dysfunction in tumors are triggered by a common mechanism. Science 2019, 363, eaau0135. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Piskounova, E.; Agathocleous, M.; Murphy, M.M.; Hu, Z.; Huddlestun, S.E.; Zhao, Z.; Leitch, A.M.; Johnson, T.M.; DeBerardinis, R.J.; Morrison, S.J. Oxidative stress inhibits distant metastasis by human melanoma cells. Nature 2015, 527, 186–191. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Forman, H.J.; Zhang, H. Targeting oxidative stress in disease: Promise and limitations of antioxidant therapy. Nat. Rev. Drug Discov. 2021, 20, 689–709. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Mao, C.; Liu, X.; Zhang, Y.; Lei, G.; Yan, Y.; Lee, H.; Koppula, P.; Wu, S.; Zhuang, L.; Fang, B.; et al. DHODH-mediated ferroptosis defence is a targetable vulnerability in cancer. Nature 2021, 593, 586–590. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Ilango, S.; Paital, B.; Jayachandran, P.; Padma, P.R.; Nirmaladevi, R. Epigenetic alterations in cancer. Front. Biosci. Landmark Ed. 2020, 25, 1058–1109. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Tang, D.; Chen, X.; Kang, R.; Kroemer, G. Ferroptosis: Molecular mechanisms and health implications. Cell Res. 2021, 31, 107–125. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Lushchak, V.I. Free radicals, reactive oxygen species, oxidative stress and its classification. Chem.-Biol. Interact. 2014, 224, 164–175. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Elsayed, S.A.; Harrypersad, S.; Sahyon, H.A.; El-Magd, M.A.; Walsby, C.J. Ruthenium(II)/(III) DMSO-based complexes of 2-aminophenyl benzimidazole with in vitro and in vivo anticancer activity. Molecules 2020, 25, 4284. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zhang, X.; Ma, L.; Wang, J. Cross-Regulation Between Redox and Epigenetic Systems in Tumorigenesis: Molecular Mechanisms and Clinical Applications. Antioxid. Redox Signal. 2023, 39, 445–471. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Ren, S.; Zhang, Y.; Wang, X.; Su, J.; Wang, X.; Yuan, Z.; He, X.; Guo, S.; Chen, Y.; Deng, S.; et al. Emerging insights into the gut microbiota as a key regulator of immunity and response to immunotherapy in hepatocellular carcinoma. Front. Immunol. 2025, 16, 1526967. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Cazzetta, V.; Franzese, S.; Carenza, C.; Della Bella, S.; Mikulak, J.; Mavilio, D. Natural killer–dendritic cell interactions in liver cancer: Implications for immunotherapy. Cancers 2021, 13, 2184. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Hu, M.; Xu, Y.; Zhou, H.; He, X. Gut microbial metabolites of amino acids in liver diseases. Gut Microbes 2025, 17, 2586328. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Nassar, N.; Khan, I.M.; Abd Elaziz, M.N.; Alali, K.; Nassar, R.; Wang, Z. Gut Microbiota and Dietary Modulation in Osteonecrosis: Mechanistic Insights and Food-Based Therapeutic Strategies. Food Sci. Hum. Wellness 2026. [Google Scholar] [CrossRef] [Scilit]
- Zhang, F.; Lo, E.K.K.; Chen, C.; Lee, J.C.Y.; Felicianna Ismaiah, M.J.; Leung, H.K.M.; Tsang, D.H.L.; El-Nezami, H. Probiotics Mixture, Prohep: A Potential Adjuvant for Low-Dose Sorafenib in Metabolic Dysfunction–Associated Steatotic Liver Disease–Associated Hepatocellular Carcinoma Suppression Through Modulating Gut Microbiota. Probiotics Antimicrob. Proteins 2025, 18, 956–972. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Song, Y.; Lau, H.C.H.; Zhang, X.; Yu, J. Bile acids, gut microbiota, and therapeutic insights in hepatocellular carcinoma. Cancer Biol. Med. 2024, 21, 144–162. [Google Scholar] [CrossRef] [Scilit]
- Khan, I.M.; Nassar, N.; Chang, H.; Khan, S.; Cheng, M.; Wang, Z.; Xiang, X. The microbiota: A key regulator of health, productivity, and reproductive success in mammals. Front. Microbiol. 2024, 15, 1480811. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Kanmani, P.; Kim, H. Protective effects of lactic acid bacteria against TLR4 induced inflammatory response in hepatoma HepG2 cells through modulation of toll-like receptor negative regulators of mitogen-activated protein kinase and NF-κB signaling. Front. Immunol. 2018, 9, 1537. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Rekha, K.; Venkidasamy, B.; Samynathan, R.; Nagella, P.; Rebezov, M.; Khayrullin, M.; Ponomarev, E.; Bouyahya, A.; Sarkar, T.; Shariati, M.A.; et al. Short-chain fatty acid: An updated review on signaling, metabolism, and therapeutic effects. Crit. Rev. Food Sci. Nutr. 2024, 64, 2461–2489. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Luo, W.; Li, R.; Pan, C.; Luo, C. Gut microbiota–derived metabolites in immunomodulation and gastrointestinal cancer immunotherapy. Front. Immunol. 2025, 16, 1710880. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Xiang, Y.; Du, A.; Wang, Z.; Pan, H.; Yuan, K. Short-chain fatty acids in the tumor microenvironment: From molecular mechanisms to cancer therapy. Theranostics 2025, 16, 1143–1163. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Markowiak-Kopeć, P.; Śliżewska, K. The effect of probiotics on the production of short-chain fatty acids by human intestinal microbiome. Nutrients 2020, 12, 1107. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Long, C.; Zhou, X.; Xia, F.; Zhou, B. Intestinal Barrier Dysfunction and Gut Microbiota in Non-Alcoholic Fatty Liver Disease: Assessment, Mechanisms, and Therapeutic Considerations. Biology 2024, 13, 243. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Salvi, P.S.; Cowles, R.A. Butyrate and the intestinal epithelium: Modulation of proliferation and inflammation in homeostasis and disease. Cells 2021, 10, 1775. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zhang, M.; Huang, X.; Zhang, Y.; Yu, M.; Yuan, X.; Xu, Y.; Ma, L.; Wang, X.; Xing, H. Gut microbial metabolite butyrate suppresses hepatocellular carcinoma growth via CXCL11-dependent enhancement of natural killer cell infiltration. Gut Microbes 2025, 17, 2519706. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Shen, X.; Zhao, D.; Wang, F.; Li, X.; Sun, K.; Du, H.; Song, S.; Nie, L.; Wang, C. Dietary intervention reshapes gut microbiota and lipid metabolism to enhance anti-tumor immunity and prognosis in hepatocellular carcinoma: A randomized controlled trial. BMC Cancer 2026, 26, 42. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Xiong, H.H.; Lin, S.Y.; Chen, L.L.; Ouyang, K.H.; Wang, W.J. The Interaction between Flavonoids and Intestinal Microbes: A Review. Foods 2023, 12, 320. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Al-Harbi, S.A.; Abdulrahman, A.O.; Zamzami, M.A.; Khan, M.I. Urolithins: The Gut Based Polyphenol Metabolites of Ellagitannins in Cancer Prevention, a Review. Front. Nutr. 2021, 8, 647582. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Mohamed, N.; Hussein, S.; El- Senosi, Y.; Emam, M.; Moustafa, S. Chemotherapeutic and antiangiogenic activity of Ginger and Ginger nanoparticles in hepatocarcinogenesis -induced in rats via activation of miRNA-29 and attenuation of FGF2/HGF/TGF-β1 signaling pathways. Benha Vet. Med. J. 2024, 46, 63–70. [Google Scholar] [CrossRef] [Scilit]
- Landete, J.M. Dietary Intake of Natural Antioxidants: Vitamins and Polyphenols. Crit. Rev. Food Sci. Nutr. 2013, 53, 706–721. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Bi, C.; Xiao, G.; Liu, C.; Yan, J.; Chen, J.; Si, W.; Zhang, J.; Liu, Z. Molecular Immune Mechanism of Intestinal Microbiota and Their Metabolites in the Occurrence and Development of Liver Cancer. Front. Cell Dev. Biol. 2021, 9, 702414. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Maliha, A.; Tahsin, M.; Fabia, T.Z.; Rahman, S.M.; Rahman, M.M. Pro-resolving metabolites: Future of the fish oil supplements. J. Funct. Foods 2024, 121, 106439. [Google Scholar] [CrossRef] [Scilit]
- Calder, P.C. Omega-3 fatty acids and inflammatory processes: From molecules to man. Biochem. Soc. Trans. 2017, 45, 1105–1115. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- D’Eliseo, D.; Velotti, F. Omega-3 fatty acids and cancer cell cytotoxicity: Implications for multi-targeted cancer therapy. J. Clin. Med. 2016, 5, 15. [Google Scholar] [CrossRef] [Scilit]
- Tsigalou, C.; Tsolou, A.; Stavropoulou, E.; Konstantinidis, T.; Zafiriou, E.; Dardiotis, E.; Tsirogianni, A.; Bogdanos, D. Unraveling the intricate dance of the Mediterranean diet and gut microbiota in autoimmune resilience. Front. Nutr. 2024, 11, 1383040. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- De Filippis, F.; Pellegrini, N.; Vannini, L.; Jeffery, I.B.; La Storia, A.; Laghi, L.; Serrazanetti, D.I.; Di Cagno, R.; Ferrocino, I.; Lazzi, C.; et al. High-level adherence to a Mediterranean diet beneficially impacts the gut microbiota and associated metabolome. Gut 2016, 65, 1812–1821. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Sibilio, P.; De Smaele, E.; Paci, P.; Conte, F. Integrating multi-omics data: Methods and applications in human complex diseases. Biotechnol. Rep. 2025, 48, e00938. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Hasin, Y.; Seldin, M.; Lusis, A. Multi-omics approaches to disease. Genome Biol. 2017, 18, 83. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Karczewski, K.J.; Snyder, M.P. Integrative omics for health and disease. Nat. Rev. Genet. 2018, 19, 299–310. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Roadmap Epigenomics Consortium; Kundaje, A.; Meuleman, W.; Ernst, J.; Bilenky, M.; Yen, A.; Heravi-Moussavi, A.; Kheradpour, P.; Zhang, Z.; Wang, J.; et al. Integrative analysis of 111 reference human epigenomes. Nature 2015, 518, 317–329. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Rappoport, N.; Shamir, R. Multi-omic and multi-view clustering algorithms: Review and cancer benchmark. Nucleic Acids Res. 2018, 46, 10546–10562. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Subramanian, I.; Verma, S.; Kumar, S.; Jere, A.; Anamika, K. Multi-omics Data Integration, Interpretation, and Its Application. Bioinform. Biol. Insights 2020, 14, 1177932219899051. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Aghdam, M.M.; Rezagholizadeh, L.; Fazaeli, A.; Moradi, A.; Ojarudi, M. Nutritional modulation of metabolic signaling within the tumor microenvironment for cancer therapy. Mol. Cell. Biochem. 2026, 481, 1155–1182. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Bersanelli, M.; Mosca, E.; Remondini, D.; Giampieri, E.; Sala, C.; Castellani, G.; Milanesi, L. Methods for the integration of multi-omics data: Mathematical aspects. BMC Bioinform. 2016, 17, S15. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Vahabi, N.; Michailidis, G. Unsupervised Multi-Omics Data Integration Methods: A Comprehensive Review. Front. Genet. 2022, 13, 854752. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Rabi, B.S.; Khtar, H.; El-Far, A.H.; Albadawy, R. Gut Microbiome profile prediction for Nonalcoholic Fatty Liver disease patients based on Artificial Intelligence Techniques. Benha J. Appl. Sci. 2025, 10, 87–95. [Google Scholar] [CrossRef] [Scilit]
- Heinken, A.; Basile, A.; Hertel, J.; Thinnes, C.; Thiele, I. Genome-Scale Metabolic Modeling of the Human Microbiome in the Era of Personalized Medicine. Annu. Rev. Microbiol. 2021, 75, 199–222. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Heinken, A.; Basile, A.; Thiele, I. Advances in constraint-based modelling of microbial communities. Curr. Opin. Syst. Biol. 2021, 27, 100346. [Google Scholar] [CrossRef] [Scilit]
- Walakira, A.; Skubic, C.; Nadižar, N.; Rozman, D.; Režen, T.; Mraz, M.; Moskon, M. Integrative computational modeling to unravel novel potential biomarkers in hepatocellular carcinoma. Comput. Biol. Med. 2023, 159, 106957. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Greathouse, K.L.; Choudhury, A. Precision nutrition and the gut microbiome: Harnessing AI to revolutionize cancer prevention and therapy. Cell Host Microbe 2025, 33, 766–776. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Noorbakhsh, J.; Foroughi pour, A.; Chuang, J. Emerging AI approaches for cancer spatial omics. GigaScience 2025, 14, giaf128. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Colonna, G. Advancing Liver Cancer Treatment through Dynamic Genomics and Systems Biology: A Path Toward Personalized Oncology. DNA 2026, 6, 6. [Google Scholar] [CrossRef] [Scilit]
- Chen, C.; Su, Q.; Zi, M.; Hua, X.; Zhang, Z. Harnessing gut microbiota for colorectal cancer therapy: From clinical insights to therapeutic innovations. npj Biofilms Microbiomes 2025, 11, 190. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Sharma, A.; Seow, J.J.W.; Dutertre, C.A.; Pai, R.; Blériot, C.; Mishra, A.; Wong, R.M.M.; Singh, G.S.N.; Sudhagar, S.; Khalilnezhad, S.; et al. Onco-fetal Reprogramming of Endothelial Cells Drives Immunosuppressive Macrophages in Hepatocellular Carcinoma. Cell 2020, 183, 377–394.e21. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zheng, Y.; Wang, S.; Cai, J.; Ke, A.; Fan, J. The progress of immune checkpoint therapy in primary liver cancer. Biochim. Biphysica Acta-Rev. Cancer 2021, 1876, 188638. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Bai, J.; Liang, P.; Li, Q.; Feng, R.; Liu, J. Cancer Immunotherapy—Immune Checkpoint Inhibitors in Hepatocellular Carcinoma. Recent Pat. Anti-Cancer Drug Discov. 2021, 16, 239–248. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Saha, S.; Shalova, I.N.; Biswas, S.K. Metabolic regulation of macrophage phenotype and function. Immunol. Rev. 2017, 280, 102–111. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Boothby, M.; Rickert, R.C. Metabolic Regulation of the Immune Humoral Response. Immunity 2017, 46, 743–755. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Whelan, R. The Role of Amino Acids in the Immune System—A Special Focus on Broilers; Engormix: Fort Lauderdale, FL, USA, 2019; Available online: https://en.engormix.com/poultry-industry/amino-acids-poultry-nutrition/the-role-amino-acids_a43647/ (accessed on 20 March 2026).
- Yaqoob, P.; Calder, P.C. Fatty acids and immune function: New insights into mechanisms. Br. J. Nutr. 2007, 98, S41–S45. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Nicolaou, A.; Mauro, C.; Urquhart, P.; Marelli-Berg, F. Polyunsaturated fatty acid-derived lipid mediators and T cell function. Front. Immunol. 2014, 5, 75. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- de Oliveira, S.; Houseright, R.A.; Graves, A.L.; Golenberg, N.; Korte, B.G.; Miskolci, V.; Huttenlocher, A. Metformin modulates innate immune-mediated inflammation and early progression of NAFLD-associated hepatocellular carcinoma in zebrafish. J. Hepatol. 2019, 70, 710–721. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Pinato, D.J.; North, B.V.; Sharma, R. A novel, externally validated inflammation-based prognostic algorithm in hepatocellular carcinoma: The prognostic nutritional index (PNI). Br. J. Cancer 2012, 106, 1439–1445. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Chan, A.W.H.; Chan, S.L.; Wong, G.L.H.; Wong, V.W.S.; Chong, C.C.N.; Lai, P.B.S.; Chan, H.L.; To, K.F. Prognostic Nutritional Index (PNI) Predicts Tumor Recurrence of Very Early/Early Stage Hepatocellular Carcinoma After Surgical Resection. Ann. Surg. Oncol. 2015, 22, 4138–4148. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Schreiber, R.D.; Old, L.J.; Smyth, M.J. Cancer immunoediting: Integrating immunity’s roles in cancer suppression and promotion. Science 2011, 331, 1565–1570. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Chew, V.; Lai, L.; Pan, L.; Lim, C.J.; Li, J.; Ong, R.; Chua, C.; Leong, J.Y.; Lim, K.H.; Toh, H.C.; et al. Delineation of an immunosuppressive gradient in hepatocellular carcinoma using high-dimensional proteomic and transcriptomic analyses. Proc. Natl. Acad. Sci. USA 2017, 114, E5900–E5909. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Waldron, T.J.; Quatromoni, J.G.; Karakasheva, T.A.; Singhal, S.; Rustgi, A.K. Myeloid derived suppressor cells targets for therapy. OncoImmunology 2013, 2, e24117. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Prasad, Y.R.; Anakha, J.; Pande, A.H. Treating liver cancer through arginine depletion. Drug Discov. Today 2024, 29, 103940. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Pu, W.; Zhang, H.; Huang, X.; Tian, X.; He, L.; Wang, Y.; Zhang, L.; Liu, Q.; Li, Y.; Li, Y.; et al. Mfsd2a+ hepatocytes repopulate the liver during injury and regeneration. Nat. Commun. 2016, 7, 13369. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Hu, J.; Locasale, J.W.; Bielas, J.H.; O’Sullivan, J.; Sheahan, K.; Cantley, L.C.; Vander Heiden, M.G.; Vitkup, D. Heterogeneity of tumor-induced gene expression changes in the human metabolic network. Nat. Biotechnol. 2013, 31, 522–529. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Ben-Shem, A.; Papai, G.; Schultz, P. Architecture of the multi-functional SAGA complex and the molecular mechanism of holding TBP. FEBS J. 2021, 288, 3135–3147. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Zeng, Z.; Lan, J.; Lei, S.; Yang, Y.; He, Z.; Xue, Y.; Chen, T. Simultaneous inhibition of ornithine decarboxylase 1 and pyruvate kinase M2 exerts synergistic effects against hepatocellular carcinoma cells. OncoTargets Ther. 2020, 13, 11697–11709. [Google Scholar] [CrossRef] [Scilit] [PubMed]
- Gamrath, L.; Pedersen, T.B.; Møller, M.V.; Volmer, L.M.; Holst-Christensen, L.; Vestermark, L.W.; Donskov, F. Role of the Microbiome and Diet for Response to Cancer Checkpoint Immunotherapy: A Narrative Review of Clinical Trials. Curr. Oncol. Rep. 2025, 27, 45–58. [Google Scholar] [CrossRef] [Scilit] [PubMed]



| Nutrient | Microbial Interaction | Key Metabolites | Effects on Hepatic Immunity | Key References |
|---|---|---|---|---|
| Omega-3 fatty acids | Enhances Akkermansia and Lactobacillus abundance and supports anti-inflammatory microbial profiles | Resolvins, protectins | Promotes anti-inflammatory macrophage polarization; reduces IL-6 production | [15] |
| Dietary fiber | Promotes SCFA-producing bacteria and increases microbial fermentation | Butyrate, acetate | Induces Treg differentiation; inhibits NF-κB activation | [9] |
| Vitamin D | Strengthens gut barrier integrity and modulates gut microbial composition | 25(OH)D | Reduces endotoxemia; enhances T cell tolerance | [5] |
| Polyphenols | Enriches beneficial microbes and promotes microbial biotransformation | Phenolic acids | Activates Nrf2 signaling; inhibits NF-κB-mediated inflammation | [17] |
| Selenium | Regulates oxidative stress responses and microbial redox balance | Selenoproteins | Modulates macrophage antioxidant responses | [15] |
| Branched-chain amino acids (BCAAs) | Alters microbial fermentation and amino acid metabolism | Indole derivatives | Enhances mitochondrial oxidation; modulates AhR activity | [18] |
| Metabolite Class | Dietary Source | Microbial Pathway | Immune Modulation in HCC | Mechanistic Target | Key References |
|---|---|---|---|---|---|
| Short-chain fatty acids (SCFAs; acetate, propionate, butyrate) | Dietary fiber and complex polysaccharides | Microbial fermentation by Firmicutes and Bacteroidetes | Modulate hepatic immune homeostasis through effects on regulatory T-cell balance, inflammatory signaling, and hepatic stellate cell activation | GPR41, GPR43, GPR109A; HDAC inhibition; AMPK activation | [9,10,15,20] |
| Secondary bile acids (DCA, LCA) | Dietary fat and cholesterol | Bile salt hydrolase-mediated deconjugation and microbial dehydroxylation | Regulate macrophage activity and metabolic homeostasis; chronic exposure induces oxidative stress, DNA damage, and pro-tumorigenic signaling | FXR; TGR5 | [5,11,14,19,21] |
| Tryptophan-derived indole metabolites (IPA, IAld, IAA) | Protein-rich foods and legumes | Indole production by Lactobacillus, Bacteroides, and Clostridium species | Promote intestinal barrier integrity, induce IL-22 signaling, and reduce hepatic inflammation; dysregulated metabolism contributes to immune suppression in the tumor microenvironment | AhR; IDO1 | [4,7,16,18] |
| Polyphenol-derived metabolites (urolithins, phenolic acids) | Fruits, vegetables, tea | Microbial biotransformation by Eubacterium ramulus and Clostridium species | Activate antioxidant pathways, enhance cytotoxic T-cell activity, and suppress inflammatory signaling | Nrf2; SIRT1 | [3,6,10,17] |
| Lipid-derived microbial metabolites (CLA, oxylipins) | Polyunsaturated fatty acid-rich foods | Fatty-acid modification by Lactobacillus species | Regulate macrophage polarization and induce apoptosis in hepatocytes, contributing to immunometabolic reprogramming | PPAR-γ | [14,19] |
| Intervention/Model | Experimental Model | Main Mechanism | Immunometabolic Effect | Outcome | Reference |
|---|---|---|---|---|---|
| Probiotic supplementation (Lactobacillus, Bifidobacterium, Akkermansia muciniphila) | Experimental HCC models | Restoration of gut microbial balance and reduced LPS translocation | Reduced TLR4-mediated inflammation and improved immune regulation | Suppressed tumor-promoting inflammatory signaling | [34,69] |
| SCFA-producing microbiota/butyrate | Murine HCC models | HDAC inhibition and metabolic reprogramming | Enhanced CD8+ T-cell activity and anti-inflammatory macrophage polarization | Improved antitumor immune responses | [34,104] |
| Acetate-mediated immune modulation | Experimental HCC and PD-1 blockade models | Suppression of IL-17A signaling | Reduced immunosuppressive signaling and improved cytotoxic T-cell infiltration | Enhanced responsiveness to immunotherapy | [105] |
| Prebiotic supplementation (inulin, resistant starch, fructo-oligosaccharides) | Experimental liver disease/HCC models | Increased SCFA production and epithelial barrier integrity | Reduced systemic inflammation and microbial translocation | Delayed inflammatory progression associated with hepatocarcinogenesis | [107] |
| Polyphenol-rich dietary interventions | Experimental HCC models | Activation of Nrf2 signaling and suppression of NF-κB pathways | Reduced oxidative stress and inflammatory macrophage activation | Attenuated tumor-promoting inflammatory signaling | [113,115] |
| Omega-3 polyunsaturated fatty acids (PUFAs) | Experimental HCC models | Modulation of COX-2/PGE2 signaling and fatty acid oxidation | Enhanced CD8+ T-cell metabolic function and reduced inflammatory signaling | Improved antitumor immune microenvironment | [118] |
| Caloric restriction/intermittent fasting | Experimental HCC models | AMPK activation and mTOR inhibition | Reduced MDSC proliferation and enhanced immune stress resistance | Improved immunometabolic regulation | [127] |
| Study Type/Population | Nutritional or Microbiota-Related Variable | Biomarker/Outcome | Main Finding | Clinical Implication | Reference |
|---|---|---|---|---|---|
| HCC patients undergoing curative resection | Prognostic Nutritional Index (PNI) | Overall survival (OS), disease-free survival (DFS) | Lower PNI was associated with poorer survival outcomes | Nutritional and immune status may influence prognosis in HCC | [148] |
| Patients with advanced HCC | Sarcopenia assessed by CT imaging | Survival and treatment outcome | Sarcopenia correlated with disease severity and reduced survival | Imaging-based nutritional assessment may improve risk stratification | [97] |
| HCC patients receiving immunotherapy | Immune-metabolic tumor microenvironment | ICI responsiveness | Metabolic dysregulation and immune exhaustion were linked to reduced immunotherapy response | Nutritional/metabolic interventions may improve ICI efficacy | [139,140] |
| Patients with chronic liver disease/HCC | Gut microbiota diversity and SCFA production | Inflammation and immune regulation | Reduced microbial diversity and altered SCFA production were associated with inflammatory progression | Microbiota-targeted nutritional approaches may support immune homeostasis | [110] |
| Clinical/translational studies in HCC | Mediterranean-style dietary patterns | Systemic inflammation and metabolic regulation | Anti-inflammatory dietary patterns were associated with improved metabolic and immune profiles | Diet composition may support prevention and adjunctive therapeutic strategies | [119] |
| HCC patients receiving combined therapies | Nutritional status and immune biomarkers | Immunotherapy responsiveness | Nutritional and immune parameters may predict treatment responsiveness | Precision nutrition approaches may support personalized HCC management | [30,157] |
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Salem, A.E.; Nassar, N.; Emam, S.M.; Negm, S.H.; Talib, W.H.; Raposa, B. Diet–Microbiota–Immune Interactions in Hepatocellular Carcinoma: An Immunometabolic and Spatial Perspective. Nutrients 2026, 18, 1911. https://doi.org/10.3390/nu18121911
Salem AE, Nassar N, Emam SM, Negm SH, Talib WH, Raposa B. Diet–Microbiota–Immune Interactions in Hepatocellular Carcinoma: An Immunometabolic and Spatial Perspective. Nutrients. 2026; 18(12):1911. https://doi.org/10.3390/nu18121911
Chicago/Turabian StyleSalem, Asmaa E., Nourhan Nassar, Shimaa M. Emam, Shaimaa H. Negm, Wamidh H. Talib, and Bence Raposa. 2026. "Diet–Microbiota–Immune Interactions in Hepatocellular Carcinoma: An Immunometabolic and Spatial Perspective" Nutrients 18, no. 12: 1911. https://doi.org/10.3390/nu18121911
APA StyleSalem, A. E., Nassar, N., Emam, S. M., Negm, S. H., Talib, W. H., & Raposa, B. (2026). Diet–Microbiota–Immune Interactions in Hepatocellular Carcinoma: An Immunometabolic and Spatial Perspective. Nutrients, 18(12), 1911. https://doi.org/10.3390/nu18121911

