Metabolic reprogramming in the post-metastatic tumor microenvironment: multi-omics insights into determinants of immunotherapy response

TL;DR

This paper explores how metabolic changes in tumors after metastasis affect immunotherapy response and how multi-omics can help develop better treatments.

Contribution

The paper provides new insights into how metabolic reprogramming interacts with immune regulation in metastatic tumors using multi-omics approaches.

Findings

Metabolic shifts like glycolysis and ferroptosis contribute to an immunosuppressive tumor environment.

Multi-omics technologies help identify biomarkers and metabolic-immune signatures for precision immunotherapy.

Combining metabolic inhibitors with immunotherapy could enhance treatment efficacy and overcome resistance.

Abstract

Metabolic reprogramming has emerged as a central determinant of immune modulation in the post-metastatic tumor immune microenvironment (TIME). Alterations in glycolysis and lactate accumulation, lipid metabolic rewiring, metal-dependent cell death pathways such as ferroptosis and cuproptosis, and the tryptophan–IDO1–kynurenine axis collectively contribute to an immunosuppressive niche that drives tumor progression and therapeutic resistance. These metabolic shifts are not isolated events but are intricately connected with immune-regulatory networks, profoundly influencing the efficacy of immunotherapy. Advances in multi-omics technologies—including metabolomics, proteomics, single-cell sequencing, and spatial omics—have provided unprecedented resolution to decode these complex interactions, enabling the identification of predictive biomarkers, delineation of metabolic–immune signatures, and discovery of therapeutic vulnerabilities. Integrating these multi-layered datasets has paved the way for precision medicine strategies that tailor immunotherapy to patient-specific metabolic and immune contexts. Therapeutically, combining metabolic inhibitors with immune checkpoint blockade, exploiting ferroptosis or cuproptosis to enhance tumor immunogenicity, or modulating amino acid metabolism to reverse immune tolerance are promising strategies to overcome resistance and expand patient benefit. Looking forward, the integration of multi-omics-guided biomarkers, AI-driven analytics, and advanced delivery systems such as nanoparticles and engineered exosomes will accelerate the translation of these insights into clinical practice. Decoding the metabolism–immunity crosstalk through multi-omics not only advances our understanding of metastatic cancer biology but also paves the way for next-generation personalized and adaptive therapies that promise to enhance immunotherapy efficacy, prolong survival, and improve the quality of life for patients with advanced cancers.

Figures