Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance

Abstract

Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of the tumor microenvironment (TME), leading to important advancements toward a much deeper understanding of how tumor microenvironment heterogeneity contributes to cancer progression and therapeutic resistance. These technologies are able to integrate data from molecular genomic, transcriptomic, proteomics, and metabolomics studies of cells at a single-cell resolution scale that give rise to the full cellular and molecular complexity in the TME. Understanding the complex and sometimes reciprocal relationships among cancer cells, CAFs, immune cells, and ECs has led to novel insights into their immense heterogeneity in functions, which can have important consequences on tumor behavior. In-depth studies have uncovered immune evasion mechanisms, including the exhaustion of T cells and metabolic reprogramming in response to hypoxia from cancer cells. Single-cell multi-omics also revealed resistance mechanisms, such as stromal cell-secreted factors and physical barriers in the extracellular matrix. Future studies examining specific metabolic pathways and targeting approaches to reduce the heterogeneity in the TME will likely lead to better outcomes with immunotherapies, drug delivery, etc., for cancer treatments. Future studies will incorporate multi-omics data, spatial relationships in tumor micro-environments, and their translation into personalized cancer therapies. This review emphasizes how single-cell multi-omics can provide insights into the cellular and molecular heterogeneity of the TME, revealing immune evasion mechanisms, metabolic reprogramming, and stromal cell influences. These insights aim to guide the development of personalized and targeted cancer therapies, highlighting the role of TME diversity in shaping tumor behavior and treatment outcomes.

Keywords: cancer therapeutic resistance; immune evasion; metabolic reprogramming; personalized cancer therapy; single-cell multi-omics; tumor microenvironment (TME).

Figure 1

The TME components and their interactions. The TME comprises CAFs, which modify the ECM and secrete growth factors; immune-suppressive cells like myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs); and anti-tumor immune cells such as CD4/CD8 T cells and NK cells, whose activity is often hindered. Additionally, endothelial cells, pericytes, and blood vessels support angiogenesis and metastasis, while lymphatic vessels assist in metastasis and immune regulation. Adipocytes and mesenchymal stromal cells contribute metabolic support, promoting tumor growth, while neurons emphasize the growing role of neuro-immune interactions. This complex network demonstrates how the TME shapes tumor behavior and resistance to therapy.

Figure 2

Key processes in tumor progression and therapeutic resistance. The illustration highlights five critical processes within the TME that drive tumor progression and resistance to therapy: (A) EMT-driven invasiveness, (B) VEGF-promoted angiogenesis, (C) immune evasion through immune cell manipulation, (D) ECM restructuring leading to metastasis, and (E) the development of resistance due to hypoxia and ECM changes.

Figure 3

Heterogeneity in the TME and cancer-associated fibroblasts (CAFs). The figure showcases the diverse cell types in the TME, including myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs) with distinct roles; the dual nature of immune cells like CTLs and Tregs; and the role of abnormal endothelial cells in fostering an environment conducive to tumor growth.

Figure 4

Immune evasion mechanisms in the tumor microenvironment (TME). (A) Immune checkpoint inhibition: Tumor cells exploit immune checkpoints, such as PD-1/PD-L1 interactions, to suppress T cell activation and evade immune responses. This pathway directly impairs effector T cell function, allowing tumors to grow unchecked. (B) Immunosuppressive cytokines and growth factors in TME: Tumor-secreted factors, including TGF-β, IL-10, and VEGF, induce differentiation of immune-suppressive cell populations such as regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). These cells release reactive oxygen species (ROS) and other suppressive signals, further promoting immune suppression and hindering T cell-mediated tumor elimination.

Figure 5

The tumor microenvironment (TME) and therapeutic resistance. This figure highlights the complex ways the tumor microenvironment (TME) contributes to therapeutic resistance. The TME, made up of cancer-associated fibroblasts (CAFs), immune cells, and the extracellular matrix (ECM), poses significant barriers to treatment. CAFs alter the ECM using cytokines like IL-6 and TGF-β, creating a physical barrier that hampers drug delivery while triggering survival pathways through integrin receptors. In nutrient-deprived areas, hypoxia-induced factors (HIFs) weaken the effectiveness of radiotherapy and chemotherapy by promoting drug efflux and resistance. The TME also recruits immune-suppressive cells like myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs), which release IL-10 and TGF-β, further stalling the immune response and increasing resistance to treatment. Additionally, CAFs communicate directly with tumor cells through gap junctions, helping the tumor thrive. These interlinked mechanisms within the TME highlight the complexity of cancer resistance, presenting crucial targets for overcoming therapeutic challenges.

Figure 6

Targeting the TME for cancer therapy. This figure outlines major therapeutic strategies for addressing the tumor microenvironment (TME) in cancer treatment. (1) Immune checkpoint inhibitors (ICIs): anti-PD-1 antibodies block PD-1/PD-L1 interactions, boosting T cell activation and promoting tumor cell death. (2) Targeting cancer-associated fibroblasts (CAFs): galunisertib, a drug that blocks TGF-β signaling, prevents fibroblasts from turning into CAFs, thereby reducing the tumor’s support system. (3) Anti-angiogenesis: bevacizumab targets VEGF to halt abnormal blood vessel formation, restoring normal vasculature and enhancing drug delivery. (4) Modulating ECM: the enzyme PEGPH20 breaks down hyaluronan in the ECM, allowing better drug penetration into the tumor’s core. (5) Targeting immune cells: reprogramming myeloid-derived suppressor cells (MDSCs) via drugs that target the CCR2 pathway can alleviate immunosuppression and restore a robust anti-tumor immune response. These strategies, taken together, offer a comprehensive approach to overcoming the protective barriers of the TME and improving cancer treatment outcomes.

Figure 7

The applications of single-cell multi-omics. This illustration highlights how single-cell multi-omics analysis is revolutionizing cancer research and personalized medicine. By analyzing patient-derived samples with multi-layered approaches (genomics, transcriptomics, proteomics, and metabolomics), researchers gain deep insights into the TME, exposing cellular diversity and the molecular pathways which are driving cancer progression and drug resistance. Key applications include detecting biomarkers, mapping tumor diversity, overcoming treatment resistance, and enabling personalized treatment strategies.