The TME in lung cancer is characterized by a complex array of immune cells, including TAMs, MDSCs and Tregs, which collectively contribute to an immunosuppressive environment (5) (Fig. 1). TAMs, particularly the M2-polarized subset, secrete interleukin (IL)-10 and transforming growth factor-β (TGF-β) to inhibit antitumor immunity and support tumor progression (5). Similarly, MDSCs impair cytotoxic T-cell function via reactive oxygen species and arginase production (17), and Tregs further reinforce immunosuppression through secretion of immunosuppressive cytokines, such as IL-10 and TGF-β (18). However, studies have highlighted the heterogeneity of these immune cells within the TME (19,20). For example, it has been suggested that TAMs can exhibit both protumorigenic and antitumorigenic functions depending on their spatial distribution and functional orientation within the tumor (21,22). This heterogeneity complicates therapeutic strategies targeting TAMs, as interventions may need to account for their dual roles (23).

Cancer-associated fibroblasts (CAFs) contribute to tumor progression and therapeutic resistance by remodeling the ECM and secreting growth factors such as TGF-β and fibroblast growth factor (FGF) (24) (Fig. 1). Through ECM deposition and cross-linking, CAFs create a physical barrier that impedes drug penetration and immune cell infiltration, while also promoting angiogenesis and metastatic dissemination (25,26). Additionally, the presence of other immune cell subsets, such as natural killer (NK) cells and γδ T cells, has been shown to influence tumor outcomes. NK cells, known for their ability to recognize and lyse tumor cells without prior sensitization, can be impaired in the TME due to factors such as TGF-β and programmed death-ligand 1 (PD-L1) expression (27). γδ T cells, which are involved in both innate and adaptive immunity, have also been shown to serve a role in shaping the TME and affecting therapeutic responses (28).

The ECM undergoes dynamic remodeling in the TME, driven by matrix stiffness, collagen crosslinking and protease activity (29). Matrix metalloproteinases (MMPs) and other proteases degrade the ECM, facilitating tumor invasion and metastasis (30). Additionally, increased matrix stiffness can enhance tumor cell proliferation and resistance to therapy by promoting mechanotransduction pathways (30). These changes in the ECM create a physical barrier that limits drug delivery and contributes to therapeutic resistance.

Soluble factors, such as cytokines (for example, IL-6 and TNF-α), chemokines and growth factors, are critical drivers of TME heterogeneity. IL-6, for example, promotes tumor progression by activating the STAT3 pathway, which enhances cell survival and proliferation (31). TNF-α, while often associated with inflammation, can also contribute to immunosuppression by upregulating PD-L1 expression on tumor cells (31). Growth factors such as vascular endothelial growth factor (VEGF) drive angiogenesis and create an immunosuppressive microenvironment, further complicating therapeutic strategies (32).

Recent studies have identified the presence of intratumoral microbiota within the lung cancer microenvironment, with microbial metabolites influencing oncogenic signaling and immune evasion (33,34). For example, certain bacterial species have been shown to modulate the expression of immune checkpoint molecules, such as PD-L1, thereby enhancing tumor immune evasion (35) (Fig. 1). Furthermore, the role of the gut-lung axis in shaping the lung TME has garnered attention. The gut microbiota can influence systemic immunity and inflammation, which in turn affects the composition and function of the lung microbiota and TME (36). This interplay between the gut and lung may offer novel targets for therapeutic intervention.

Neuronal interactions within the TME have also emerged as a novel area of research (37). Neurotrophic factors and axonogenesis promote tumor innervation, which can enhance tumor growth and metastasis (38). Studies have suggested that neural signaling may influence the secretion of protumorigenic factors, such as TGF-β, and create a permissive environment for tumor progression (39,40) (Fig. 1). Additionally, the involvement of neuronal-derived exosomes in transmitting signals that promote tumor cell survival and therapeutic resistance has been revealed (41), highlighting the importance of understanding the bidirectional communication between neurons and tumor cells in shaping the TME.

The heterogeneity of the lung cancer microenvironment, driven by diverse cellular interactions and dynamic non-cellular components, presents a notable barrier to effective therapy. Understanding these complex interactions is essential for developing targeted approaches that can modulate the TME to enhance treatment efficacy. By addressing the dual roles of immune cells, the fibrotic networks created by CAFs and the physical barriers of the ECM, future therapeutic strategies may be better designed to overcome resistance and improve patient outcomes.

The TME facilitates immune evasion through various mechanisms, including the upregulation of immune checkpoint molecules and the polarization of immune cells (11). PD-L1, a well-known immune checkpoint protein, is often upregulated in lung cancer cells, enabling them to suppress T-cell activity and evade immune detection (43,44) (Fig. 2). Previous studies have also highlighted the role of the lymphocyte-activation gene 3 (LAG-3)/fibrinogen-like protein 1 (FGL1) axis and V-type immunoglobulin domain-containing suppressor of T-cell activation (VISTA) in immune evasion. LAG-3, expressed on exhausted T cells, interacts with FGL1, leading to T-cell dysfunction (45). VISTA, another immune checkpoint molecule, contributes to the immunosuppressive environment by inhibiting T-cell activation (46). TAMs serve a notable role in immune evasion by polarizing toward an M2 phenotype. This polarization is driven by cytokines such as colony stimulating factor 1 (CSF-1), which activates CSF-1 receptor signaling in macrophages (47). However, the extent to which these mechanisms contribute to immune evasion may vary among different lung cancer subtypes and patient populations, necessitating further investigation to clarify their roles and potential therapeutic targets.

Hypoxia is a common feature of the TME, and has marked effects on tumor progression and therapeutic resistance (48) (Fig. 2). Hypoxia-induced autophagy, mediated by hypoxia-inducible factor-1α and BCL-2/adenovirus E1B 19 kDa protein-interacting protein 3, supports the survival of cancer stem cells (CSCs). CSCs are known for their ability to self-renew and differentiate, contributing to tumor heterogeneity and resistance to therapy (49). By maintaining CSC survival, hypoxia-induced autophagy ensures a reservoir of cells capable of repopulating the tumor after treatment.

Lactate, a byproduct of anaerobic metabolism, accumulates in the TME under hypoxic conditions and serves a role in promoting immunosuppression (50) (Fig. 2). Lactate-mediated signaling in stromal cells, such as Notch/C-C motif chemokine ligand 5, fosters an immunosuppressive environment by attracting Tregs and inhibiting the function of cytotoxic T cells (51). This metabolic reprogramming not only supports tumor growth but also creates a barrier to effective immune responses, highlighting the complex interplay between metabolic changes and immune modulation in the TME.

Epigenetic changes within the TME markedly influence tumor progression and therapeutic resistance (42) (Fig. 2). RNA modifications, including m6A, m5C and ac4C, have emerged as critical regulators of mRNA stability and translation. These modifications can affect the expression of immune-related genes, such as PD-L1, STAT1 and IRF7, thereby modulating immune cell function and the overall immune response within the TME (52). For example, m6A methylation of specific mRNA transcripts can enhance their stability and translation efficiency, leading to increased production of proteins involved in immune evasion and tumor promotion (53).

Long non-coding RNAs (lncRNAs) also serve a role in shaping the TME through epigenetic mechanisms (54). Hypoxia-induced lncRNA-HAL has been shown to promote stemness and therapeutic resistance by interacting with chromatin remodeling complexes (55). By altering the epigenetic landscape, lncRNA-HAL contributes to the maintenance of a favorable environment for tumor growth and resistance to treatment (56). Understanding the specific roles of these epigenetic modulators and their interactions within the TME is crucial for developing novel therapeutic strategies aimed at reversing epigenetic changes and enhancing treatment efficacy in lung cancer.

The intricate crosstalk within the TME, involving immune evasion, metabolic reprogramming and epigenetic modulation, creates a complex landscape of resistance mechanisms in lung cancer. By targeting key nodes in these networks, such as immune checkpoint regulation, hypoxia-driven pathways and epigenetic modifiers, novel therapies can be developed to disrupt the supportive role of the TME in tumor progression. These approaches hold promise for enhancing the effectiveness of existing treatments and addressing the challenge of therapeutic resistance.

Resistance to targeted therapies, such as EGFR-tyrosine kinase inhibitors (TKIs), is a notable challenge in lung cancer treatment. One of the key mechanisms underlying this resistance is the activation of alternative signaling pathways. TAMs contribute to resistance against targeted therapies such as EGFR-TKIs by secreting hepatocyte growth factor, which activates the c-MET pathway and bypasses EGFR inhibition (57). Moreover, TAMs and CAFs collaboratively foster a fibrotic niche via ECM remodeling, which physically restricts drug access and activates alternative survival pathways (58,59).

Genetic alterations, including secondary EGFR mutations (such as T790M) and MET amplification, remain key drivers of acquired resistance (60). These changes are often facilitated by a pro-inflammatory TME, which promotes genomic instability and enriches for resistant clones (61).

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape for lung cancer, but resistance to these therapies remains a key issue. Resistance to ICIs can be influenced by various factors within the TME (62). For example, the presence of immunosuppressive cells, such as MDSCs and Tregs, can inhibit the activation and function of cytotoxic T cells. These immunosuppressive cells can be recruited and activated by cytokines such as TGF-β and IL-10, which are often upregulated in the TME. The dense infiltration of MDSCs and Tregs creates a suppressive milieu that limits the efficacy of ICB (63).

Moreover, physical barriers within the TME, such as a dense ECM and poor vascularization, can prevent immune cells from infiltrating the tumor (64). A recent study demonstrated that the ECM stiffness, mediated by collagen crosslinking and MMPs, can physically impede T-cell migration and reduce the delivery of ICIs to their targets. This structural barrier is further exacerbated by the presence of immunosuppressive cytokines, which collectively contribute to the resistance of tumors to immunotherapy (64).

The interplay between targeted therapeutic resistance and immune evasion is complex and can be influenced by the TME. Metabolic changes induced by targeted therapies can alter the TME and contribute to immune resistance (65). For example, hypoxia resulting from tumor growth can lead to the upregulation of PD-L1 and the recruitment of immunosuppressive cells. Additionally, the release of damage-associated molecular patterns from dying cancer cells during targeted therapy can activate innate immune responses that paradoxically promote immunosuppression.

Previous studies have highlighted the role of immune evasion mechanisms in therapeutic resistance (Table I). Utsumi et al (66) demonstrated that AXL-mediated drug resistance in ALK-rearranged NSCLC was enhanced by growth-arrest specific protein 6 from macrophages and MMP11-positive fibroblasts, underscoring the importance of cellular interactions within the TME. Moreover, Peyraud et al (67) utilized spatially resolved transcriptomics to reveal determinants of primary resistance to immunotherapy in NSCLC with mature tertiary lymphoid structures, suggesting that the spatial organization of immune cells may impact therapy outcomes. However, Nishinakamura et al (68) showed that coactivation of innate immune suppressive cells induced acquired resistance against combined Toll-like receptor 7/8 agonist treatment and programmed cell death protein 1 (PD-1) blockade, further illustrating the dynamic nature of immune resistance mechanisms. Notably, large clinical trials, such as KEYNOTE-189, have validated the impact of TME features on immunotherapy response, reinforcing the clinical relevance of these mechanisms (69).

The involvement of specific T-cell subsets in lung cancer resistance mechanisms has garnered attention in previous research. γδ T cells, which are part of the innate-like T-cell population, have been shown to serve a dual role in the TME (70). Some studies have indicated that γδ T cells can mediate antitumor responses through the secretion of IFN-γ and the killing of tumor cells (71,72). However, other research has suggested that γδ T cells may also contribute to immunosuppression by producing immunosuppressive cytokines, such as IL-10 and TGF-β, in the TME, thereby promoting tumor progression and resistance to therapy (73). For example, Liu et al (28) demonstrated that the frequency and function of γδ T cells were altered in patients with lung cancer, and these cells may influence the efficacy of immunotherapy. Additionally, tissue-resident memory T cells (Trm) have been identified as key players in local immune responses. Trm cells persist in tissues long-term and can provide immediate protection against tumor recurrence (74). However, in the context of chronic inflammation and an immunosuppressive TME, Trm cells may lose their function or even promote tumor growth. It has been shown that the expression of checkpoint molecules, such as PD-1 and LAG-3, on Trm cells can limit their antitumor activity, contributing to therapeutic resistance (75).

In addition to T-cell subsets, other immune cells such as innate lymphoid cells (ILCs) have been implicated in shaping the TME and influencing therapeutic outcomes. ILCs, including ILC1s, ILC2s and ILC3s, can regulate tumor inflammation and immune responses through the secretion of cytokines. For example, ILC3s have been reported to promote tumor progression by secreting IL-22, which can enhance tumor cell survival and resistance to therapy (76). Furthermore, the interaction between ILCs and other immune cells, such as macrophages and dendritic cells, can modulate the overall immune response in the TME, affecting the efficacy of immunotherapy (77).

Additionally, paracrine signaling mechanisms between tumor cells and CAFs can synergize with the TME to drive resistance (Table I). Ebid et al (78) investigated the cross-talk signaling between NSCLC cell lines and fibroblasts, demonstrating that this interaction can attenuate the cytotoxic effect of cisplatin. This previous study highlighted the role of CAFs in mediating chemoresistance. Additionally, Zhang et al (79) identified lactate dehydrogenase A as a novel predictor for immunotherapy resistance, linking metabolic reprogramming within the TME to therapy outcomes. Wang et al (80) conducted single-cell transcriptomics analysis and revealed an immunosuppressive network between periostin (POSTN) CAFs and atypical chemokine receptor 1 (ACKR1) endothelial cells (ECs) in TKI-resistant lung cancer, providing insights into the cellular and molecular mechanisms underlying resistance to targeted therapies.

Additionally, genetic alterations within tumor cells can synergize with the TME to drive resistance (Table I). Wang et al (81) showed that SMARCA4 mutations induced tumor cell-intrinsic defects and resistance to immunotherapy, suggesting that genetic alterations within tumor cells may synergize with the TME to drive resistance. Huang et al (82) demonstrated that EGFR mutations can induce suppression of CD8⁺ T cells and anti-PD-1 resistance via the ERK1/2-p90RSK-TGF-β axis, linking genetic alterations to immune evasion mechanisms. Kobayashi et al (83) explored the impact of bevacizumab and microRNA (miR)-200c on epithelial-mesenchymal transition (EMT) and EGFR-TKI resistance in EGFR-mutant lung cancer organoids, suggesting that targeting EMT-related pathways may offer a promising strategy to overcome resistance.

Moreover, advanced multicellular models and combination therapies are being explored to better understand and overcome TME-driven resistance (Table I). Tan et al (84) evaluated drug resistance for EGFR-TKIs in lung cancer using a multicellular lung-on-a-chip model, allowing for a more accurate simulation of the TME and providing valuable data on resistance mechanisms. Pan et al (85) investigated the role of disulfidptosis-related genes in radiotherapy resistance of lung adenocarcinoma, emphasizing the importance of understanding TME-driven resistance across different therapeutic modalities. Han et al (86) showed that osimertinib in combination with anti-angiogenesis therapy may be a promising option for osimertinib-resistant NSCLC, highlighting the potential of combination therapies in overcoming resistance mediated by the TME.

Finally, nanotechnology offers innovative approaches to monitor and manage resistance within the TME (Table I). Shen et al (87) developed an adaptable nanoprobe integrated with quantitative T1-mapping MRI for accurate differential diagnosis of multidrug-resistant lung cancer, offering a novel option for monitoring and managing resistance within the TME. Lu et al (88) showed that reprogramming of TAMs via the STAT3/CD47-signal regulatory protein α axis promoted acquired resistance to EGFR-TKIs in lung cancer, emphasizing the role of immune cell reprogramming in resistance.