Journal of Cell Biology and Metabolism

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Rapid Communication - Journal of Cell Biology and Metabolism (2025) Volume 7, Issue 2

Single-Cell Transcriptomics Reveals Metabolic Heterogeneity in Tumor Microenvironments

Wagne Avi*

Department of Biology, University of Heidelberg, Heidelberg, Germany.

*Corresponding Author:
Wagne Avi
Department of Biology
University of Heidelberg
Heidelberg, Germany.
E-mail: Avi@mbl.de

Received: 03-Apr-2025, Manuscript No. AACBM-25-164637; Editor assigned: 04-Apr-2025, PreQC No. AACBM-25-1646375(PQ); Reviewed: 18-Apr-2025, QC No AACBM-25-1646375; Revised: 21-Apr-2025, Manuscript No. AACBM-25-1646375(R); Published: 28-Apr-2025, DOI:10.35841/aacbm-7.2.259

Citation: Avi W. Single-cell transcriptomics reveals metabolic heterogeneity in tumor microenvironments. J Cell Biol Metab. 2025;7(2):259.

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Introduction

Single-cell transcriptomics has revolutionized the study of cancer biology by enabling the high-resolution analysis of gene expression at the individual cell level. Unlike bulk sequencing methods, which average signals across mixed populations, single-cell techniques uncover cellular diversity within tumors and their surrounding microenvironments. One of the most striking insights from this technology is the revelation of profound metabolic heterogeneity among tumor cells and their supporting stromal and immune counterparts. This variability plays a critical role in tumor progression, treatment resistance, and disease recurrence [1, 2].

Tumors are composed not only of malignant cells but also of a diverse array of non-cancerous cells, including fibroblasts, endothelial cells, and infiltrating immune cells. These cells coexist within a complex and often hostile microenvironment characterized by hypoxia, nutrient deprivation, and immune surveillance. Single-cell transcriptomic data reveal that tumor and stromal cells adapt to these stressors through distinct metabolic programs tailored to their local context and functional roles [3, 4].

Within the same tumor, malignant cells may exhibit differential expression of genes involved in glycolysis, oxidative phosphorylation, lipid metabolism, or amino acid biosynthesis. For example, subsets of cancer cells in hypoxic regions upregulate glycolytic enzymes to support anaerobic energy production, while others near blood vessels may rely more on mitochondrial respiration. This spatially driven metabolic plasticity contributes to the tumor’s ability to survive fluctuating conditions and evade targeted therapies [5].

Moreover, tumor-associated immune cells such as macrophages and T cells also display metabolic diversity that correlates with their activation states and functional phenotypes. Immunosuppressive cells often adopt a lipid metabolism-oriented profile, while pro-inflammatory cells lean toward glycolysis. This metabolic rewiring affects their ability to attack tumor cells, creating pockets of immune privilege within the tumor microenvironment [6, 7].

Single-cell studies have also illuminated the metabolic roles of cancer-associated fibroblasts (CAFs), which can support tumor growth by secreting nutrients or modulating extracellular matrix composition. Some CAF subsets exhibit enhanced oxidative metabolism and contribute to the remodeling of the tumor niche, thereby promoting cancer cell invasiveness and resistance to therapy [8].

These discoveries have profound implications for precision oncology. By mapping the metabolic landscape of tumors at single-cell resolution, researchers can identify vulnerable cell populations and develop strategies that target metabolic dependencies unique to specific cellular subtypes. This approach holds promise for overcoming the limitations of one-size-fits-all metabolic therapies, which often fail due to intratumoral heterogeneity [9].

Furthermore, integrating single-cell transcriptomics with spatial transcriptomics and metabolomics provides an even more detailed view of tumor ecology. This integration allows for the direct correlation of gene expression with metabolic activity in situ, offering insights into how metabolic programs are influenced by the physical and chemical properties of the tumor microenvironment [10].

Conclusion

In conclusion, single-cell transcriptomics has revealed that metabolic heterogeneity is a defining feature of the tumor microenvironment. This variability underlies the adaptability and resilience of tumors, contributing to disease progression and therapeutic resistance. By understanding these diverse metabolic states at the single-cell level, researchers and clinicians can develop more precise, context-specific interventions aimed at disrupting the metabolic networks that fuel cancer.

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