Spatial Profiling of the Head and Neck Squamous Cell Carcinoma Microenvironment: Reshaping Our Understanding and Therapeutic Opportunities

3.1. Malignant Cell Subtypes and Their Spatial Distribution

As revealed by these high-resolution approaches, HNSCC exhibits significant heterogeneity at the cellular level, encompassing both molecular and spatial dimensions [31]. For instance, malignant epithelial cells in HNSCC do not exist only as discrete subtypes but instead occupy a continuum of phenotypic states, particularly along the epithelial–mesenchymal transition (EMT) gradient [9,10]. Spatial omics has shown that dominant malignant cell populations often retain a core epithelial phenotype, characterized by strong intercellular adhesion and high proliferative activity, and are mainly located within the tumor core (TC) [32]. Conversely, cells co-expressing epithelial and mesenchymal markers and exhibiting partial epithelial–mesenchymal transition (pEMT) features are often enriched at the invasive tumor margins [33]. This precise spatial distribution, revealed by spatial technologies, suggests that pEMT directly promotes local tissue invasion and dissemination. Moreover, malignant cells with cancer stem cell–like characteristics—often associated with EMT programs and therapeutic resistance—are not randomly distributed across the tumor [34]. They tend to cluster in specific microenvironments, such as around blood vessels or in hypoxic regions, where spatial interactions with stromal cells support their maintenance [35,36]. Therefore, the spatial organization of HNSCC, spanning the proliferative core to the invasive edge enriched with pEMT and stem cell–like populations, reflects a functional tumor ecosystem that underlies tumor progression and therapeutic resistance.

3.2. Immune Cell Populations and Spatial Organization

The spatial organization of the immune microenvironment is a fundamental regulatory determinant of immune and therapeutic responses in head and neck squamous cell carcinoma, extending beyond the mere presence of immune cells. As highlighted by Fu et al., the formation of tertiary lymphoid structures (TLS) at the tumor-stroma interface is a key structural feature that promotes the coordinated T-cell and B-cell activation and is associated with improved patient prognosis [37]. Li et al. further clarified the functional importance of TLS, suggesting that specific CD4+ T-cell populations within mature TLS may act as core regulatory factors that activate and maintain T-cell and B-cell responses in tumors, thereby providing a potential mechanistic basis for their clinical benefit [38]. Nevertheless, such antitumor immunity is often counteracted by spatially organized immunosuppressive mechanisms. However, this anti-tumor immunity is often antagonized by the immunosuppressive mechanism of spatial organization. In HNSCC, immune escape often arises from spatial antagonism, whereby the function of CD8+ T cells is suppressed through regulatory interactions with cancer-associated fibroblasts [39,40]. This suppression is further exacerbated by an increased spatial ratio of regulatory T cells (Tregs) to CD8+ T cells, as well as the presence of CD56^dim NK cells and M2 polarized macrophages, all of which are enriched within specific microenvironmental niches, thereby impairing effective antitumor immune responses [5,41]. Importantly, this immune microenvironment is not static; instead, it undergoes substantial spatial remodeling during disease recurrence, which can significantly diminish therapeutic efficacy. Watermann et al. confirmed that recurrent HNSCC exhibits significant alterations in the tumor immune microenvironment (TIME), characterized by a marked decrease in CD8+ T cells and B lymphocytes, along with a relative increase in neutrophils and macrophages [42]. In summary, deciphering the spatial organization of immune interactions including the localization of immunosuppressive cells relative to cytotoxic immune activity and the physical barriers that restrict T cell infiltration is critical for developing spatially informed immunotherapies capable of reprogramming the immunosuppressive HNSCC microenvironment.

3.3. Stromal Components and Their Spatial Niches

In addition to the immune components, stromal components, particularly CAFs, are key architects of the HNSCC tumor microenvironment and play a crucial role in shaping its physical structure and functional state [43]. CAFs do not constitute a single homogeneous cell population; rather, they exhibit substantial heterogeneity, with distinct subtypes occupying specific spatial niches and driving different aspects of tumor biology [44]. In HNSCC, several key CAF subpopulations have been identified, including myofibroblastic CAFs (myCAFs), which are typically located within the tumor core and contribute to the formation of a dense extracellular matrix; inflammatory CAFs (iCAFs), which are generally found at the tumor periphery and secrete cytokines and growth factors that promote inflammation and angiogenesis; and antigen-presenting CAFs (apCAFs), which can directly interact with immune cells [45]. This article comprehensively outlines the spatial and functional heterogeneity of these CAF subpopulations, which is a key resource for understanding their unique contributions to the TME (Table 3).

Beyond these basic classifications, emerging studies in spatial cancer research have begun to elucidate the specific roles of distinct CAF subtypes in the progression of HNSCC. For instance, Liu et al. demonstrated, through integrated single-cell and spatial transcriptomic analyses, that POSTN-positive CAFs promote cancer cell metastasis via epithelial–mesenchymal transition (EMT), thereby facilitating lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC), the major subtype of HNSCC [16]. In another spatially resolved study, Li et al. identified IFN-induced MHC-IhiGal9⁺CAFs, which form an immunosuppressive microenvironment that captures CD8+ T cells and weakens their cytotoxic function in the TME [40]. Wang et al. further demonstrated the clinical significance of specific CAF subgroups, showing that SFRP2^+ CAFs were associated with enhanced tumor development and poorer survival outcomes in patients with HNSCC [46]. Overall, these findings highlight the critical role of spatially distinct CAF subtypes in driving tumor invasion and immune evasion. Therefore, analyzing the spatial and functional specialization of CAF subgroups, including their coordinated microenvironments that regulate immunosuppression, extracellular matrix remodeling, and metastasis, is essential for developing new therapies that can effectively disrupt these pathological ecosystems in HNSCC.

3.4. Vascular and Lymphatic Endothelial Cells in the TME

In HNSCC, blood and lymphatic vessels are active regulators of the tumor microenvironment and play crucial roles in immunosuppression and metastasis [47,48]. Tumor-associated endothelial cells exhibit distinct functional phenotypes characterized by altered expression of adhesion molecules, growth factor receptors, and immunomodulatory ligands [49]. Through the upregulated secretion of factors such as vascular endothelial growth factor A (VEGFA) and CXCL12, they promote the development of vascular abnormalities and increased permeability, which contribute to hypoxia and establish both physical and chemokine-mediated barriers that restrict CD8+ T cell infiltration [50,51]. Evidence suggests that lymphatic endothelial cells may also contribute to the apoptosis of activated T cells by upregulating PD-L1 and presenting FAS ligand, thereby promoting tumor immune escape. At the same time, their strategic localization at the invasive tumor margin further facilitates tumor cell dissemination to regional lymph nodes [52,53]. Recent single-cell and spatial transcriptomic studies have further revealed substantial heterogeneity among endothelial cells, identifying specialized subpopulations with distinct transcriptional programs that support processes such as angiogenesis, immunomodulation, and therapeutic resistance [54]. In summary, these findings reposition endothelial cells from passive conduits to active regulators of tumor progression, highlighting the importance of vascular normalization and targeted inhibition of endothelial immune checkpoints as potential treatment strategies for HNSCC.

The studies discussed in this section collectively demonstrate that the HNSCC tumor microenvironment is not a random mixture of cells but a highly organized ecosystem composed of specialized functional niches. To synthesize these spatial relationships, a conceptual model is proposed that maps key cellular components to their distinct topological environment (Figure 1). The figure maps key cellular components, including malignant cells, cancer stem cells, T cells, B cells, macrophages, cancer-associated fibroblasts, and associated vasculature, to their distinct topological environments within the HNSCC TME. This comprehensive spatial framework, which integrates the diverse elements discussed in Section 3.1, Section 3.2, Section 3.3 and Section 3.4, lays the necessary foundation for understanding the intercellular communication network to be discussed in the next section.

4.1. The Spatially Organized Immune Landscape: Beyond Cold and Hot

Current spatial studies of HNSCC have refined the classic “hot” and “cold” immune classification, revealing that immune phenotype depends not only on immune-cell density but also on coordinated spatial interactions between immune cells and specific stromal components [55,56]. The “hot” immune phenotype, often represented by HPV-positive tumors, is characterized by the presence of structured TLS. Importantly, these microenvironments are enriched in CCL19-positive fibroblasts, which are spatially associated with CD4-positive T cells and B cells, thereby supporting coordinated antitumor immune responses and contributing to improved immunotherapy efficacy [56]. In contrast, the “cold” immune phenotype, more common in HPV-negative tumors, is characterized by spatial exclusion of cytotoxic T cells. This immunosuppressive environment is primarily composed of iCAF, myCAF, and proto-CAF populations, the latter characterized by low expression of canonical myCAF and iCAF marker genes. They are spatially associated with inflammatory monocytes and help form a matrix barrier, thus hindering the infiltration and function of effective T cells [56]. Therefore, the precise topology of these different CAF subtypes is the fundamental determinant of the HNSCC immune microenvironment and its clinical impact.

4.2. Stromal-Immune Interactions: Orchestrating Suppression and Exclusion

In HNSCC, CAFs actively shape the immunosuppressive microenvironment through spatially defined mechanisms. Specific CAF subtypes play specialized roles: POSTN^+ CAFs at the invasive margin form physical ECM barriers that exclude CD8^+ T cells from the tumor nest; MHC-I^hi Gal9^+ CAFs form functional immune traps through ligand–receptor interactions that isolate and suppress T-cell activity; and CXCL13^+ CAFs promote B-cell recruitment and antibody production while also contributing to the activation and subsequent exhaustion of CXCL13^+ CD8^+ T cells within tumor-cell aggregates in nasopharyngeal carcinoma, a subtype of HNSCC [16, 40, 57]. In addition to physical exclusion, apCAFs may promote immunosuppressive microenvironments by altering local T-cell composition, potentially favoring CD4^+ T-cell dominance over CD8^+ T-cell activity, a pattern associated with tumor progression [58]. Simultaneously, iCAFs secrete soluble factors such as CXCL12 and TGF-β, establishing chemokine gradients that recruit regulatory T cells and promote T-cell exhaustion in peri-tumoral regions [59]. Through these spatially defined interactions, CAFs emerge as central regulators of the immunosuppressive stroma in HNSCC. Spatially resolved identification of these distinct CAF populations and their interactions with immune cells is critical. For instance, if spatial data reveal an abundance of POSTN⁺ CAFs that physically exclude T cells, this finding directly suggests a therapeutic strategy combining immune checkpoint inhibitors with CAF targeting agents, such as fibroblast activation protein inhibitors, or extracellular matrix remodeling drugs to overcome the physical barrier and enhance T cell infiltration and function.

4.3. Vascular and Hypoxic Niches: Hubs for Immune Evasion and Therapy Resistance

Abnormal vasculature and hypoxia in HNSCC form distinct spatial microenvironments that contribute to immune escape and therapeutic resistance [60]. Abnormal, leaky blood vessels driven by high VEGFA signaling not only contribute to a hypoxic and acidic microenvironment that directly impairs T cell function but also fail to support effective T cell infiltration, thereby forming a physical barrier that restricts immune cell entry [61]. In these hypoxic perivascular microenvironments, tumor and stromal cells upregulate immunosuppressive metabolites and immune-checkpoint molecules, further suppressing local T-cell activity and promoting niches that support the survival of drug-resistant, stem-cell-like cancer cells [41,50]. Spatial profiling technologies are instrumental in precisely mapping these hypoxic niches and abnormal vascular structures. Identifying such regions within a tumor can directly inform treatment decisions, suggesting combination therapies that include anti-angiogenic agents or hypoxia-modifying drugs alongside immunotherapies to improve oxygenation, normalize vasculature, and enhance immune cell access and function.

4.4. Reconstruction of Global Communication Networks from Spatial Data

The key advantage of spatial biology is its ability to directly reconstruct and quantify intercellular communication networks within intact tissue architecture [62]. By analyzing the co-localization of ligand and receptor mRNAs or proteins, key signaling pathways can be mapped to specific cellular regions [63-65]. For instance, spatial transcriptomics has revealed that in glucose-deficient regions of HNSCC, cancer cell-derived CXCL8 interacts with macrophages to establish a feedforward loop that promotes antioxidant production and confers resistance to nutrient-starvation therapies (anlotinib) [63]. In HPV-negative HNSCC, systematic profiling of ligand-receptor interactions has identified prognostic signaling networks involving ECM and immune regulation. Integration of these networks with histopathological features enables improved risk stratification [64]. In addition, spatial analysis has revealed a mutually exclusive expression pattern between the immune checkpoint B7-H4 (VTCN1) and PD-L1. B7-H4-positive tumor regions show marked exclusion of CD8+ T cells, highlighting its potential as a therapeutic target in immune-cold tumors [65]. Integrating these spatially resolved interactions into global network models not only identifies dominant signaling circuits driving tumor progression but also highlights novel targets for disrupting the pathological ecosystem of HNSCC.

5.1. Immunotherapy

Immune checkpoint inhibitors, particularly PD-1 and PD-L1 blockade, have significantly reshaped the treatment landscape for a subset of patients with HNSCC; however, overall response rates remain limited [66-68]. Spatial omics helps clarify why the efficacy of immune checkpoint inhibitors (ICIs) depends not only on the presence of CD8^+ T cells but also on the spatial organization of multiple immune and stromal cell types within the TME [69]. This refined understanding provided by spatial data directly impacts patient stratification and treatment planning. For instance, the spatial identification of mature, functional TLS within tumors, enriched in CD4+ T cells, memory B cells, and plasma cells, serves as a robust positive spatial predictive biomarker of improved response to immune checkpoint inhibitors [70]. Patients whose tumors exhibit such organized TLS, detectable through spatial profiling, could be prioritized for immunotherapy or considered for de-escalation strategies if a robust response is observed. In contrast, spatial features associated with resistance to immune checkpoint inhibitors often include CD8^+ T cells located close to immunosuppressive components, such as regulatory T cells in perivascular microenvironments or M2-like macrophages in stromal regions [71]. In these cases, spatial analysis directly informs the need for combination strategies, such as adding agents that deplete suppressive cells (e.g., anti-CCL22 to target Tregs) or disrupt physical barriers (e.g., targeting specific CAFs), to reprogram the TME and improve ICI effectiveness. This spatially informed approach moves beyond simple PD-L1 expression or CD8 T cell density, enabling more precise identification of patients likely to benefit from immune checkpoint inhibitors and guiding the design of rational combination therapies for non-responders. In addition, B cells and plasma cells located outside the TLS structure may also acquire tumor-promoting properties, which further illustrates how the spatial environment determines immune function [57]. In summary, the response of HNSCC to immune checkpoint inhibitors reflects a balance between effective immune activation within tertiary lymphoid structures and functional immune suppression within the stromal or vascular microenvironment, and this balance is spatially regulated.

5.2. Targeted Therapies

TP53 is one of the most frequently mutated genes in HNSCC, with mutation rates of approximately 70%, although this prevalence varies significantly depending on factors such as HPV status and anatomical subsite [72,73]. In addition, the EGFR gene is widely altered, with up to 80–90% of HNSCCs exhibiting either overexpression or mutations [74]. Other important alterations include FAT1, PIK3CA, CDKN2A, and NOTCH1, which collectively highlight the therapeutic potential of molecularly informed treatment strategies [75-78]. Despite these molecular alterations, the clinical efficacy of targeted therapies remains suboptimal, highlighting a critical translational gap between genomic profiling and therapeutic success [79,80]. Spatial technologies are revealing that therapeutic response depends not only on mutational status but also on the spatial organization of target-gene expression and protective tumor-microenvironmental ecosystems [32,39]. For instance, spatial transcriptomics analysis of early-onset tongue cancer uncovers both significantly enriched MAPK and JAK-STAT signaling pathways and a distinctive TME characterized by increased plasma cell gene signatures and TLS featuring plasma cell and lymphocyte aggregations, particularly at the invasive front, thereby suggesting the need for customized targeted interventions for these specific molecular subtypes [81]. Similarly, studies of tumor budding have identified NSD1 mutations as negatively correlated with tumor budding and revealed key roles for CAV1 and MMP14. The spatial expression gradients of these proteins from the tumor core to budding regions highlight progressively enhanced invasive processes, which may represent potential therapeutic targets [82].

Further spatial dissection of the tumor leading edge consistently identifies upregulated collagen deposition, CD99 expression, and non-canonical WNT signaling pathways that drive invasion, whereas the tumor core is characterized by Angiopoietin-like protein (ANGPTL) and POSTN-associated signaling modules. This compartment-specific organization suggests a targeted therapeutic strategy that encompasses both the tumor nest and the surrounding stroma [83]. In precancerous lesions, spatial regulation of VEGF signaling, in conjunction with immunosuppressive mononuclear cells, contributes to the formation of a microenvironment that promotes malignant transformation, suggesting a potential target for therapeutic intervention [84]. Notably, integrated multi-omics analysis links POSTN-mediated extracellular-matrix remodeling and CAF-secreted TGF-β with epithelial EMT and LNM in OSCC, suggesting that the POSTN–TGF-β axis may be a potential target for disrupting the metastatic cascade [16]. In summary, these spatially resolved insights extend beyond static mutational profiles to reveal the spatial distribution of actionable signaling pathways and tumor–matrix interactions, thereby providing a framework for the development of mechanism-based combination therapies and context-specific targeted treatments for head and neck squamous cell carcinoma (HNSCC).

5.3. Translational Outlook: Spatial Biomarkers for Clinical Stratification

The clinical translation of spatial genomic research requires distilling complex spatial data into actionable biomarkers to guide patient selection, individualized treatment, and real-time monitoring. Characteristics such as cell subtype, intercellular interaction, ligand-receptor signaling, and spatial co-localization patterns of tumor-associated CAFs represent potential spatial biomarker candidates [85,86]. Specifically, spatial biomarkers derived from immune escape mechanisms, such as the spatial density and precise localization of specific CAF subtypes (e.g., POSTN⁺ CAFs physically excluding T cells), the presence and maturity of TLS (indicating immune competence), or the spatial proximity of CD8⁺ T cells to immunosuppressive myeloid cells (indicating resistance), can serve as powerful tools for patient stratification. These biomarkers can predict response to ICIs, identify patients requiring combination therapies, and guide the selection of appropriate therapeutic partners to overcome specific spatially driven immune escape mechanisms.

Combined with digital pathology and computational image analysis, these features can be automatically and quantitatively assessed in conventional histological specimens, thereby enabling scalable integration into clinical workflows [87-89]. For example, deep learning models that extract spatial features such as tumor infiltrating lymphocyte density, tumor microenvironment heterogeneity, and granulocyte enrichment at the invasive margin from standard hematoxylin and eosin-stained slides have demonstrated strong predictive performance for overall survival benefit from the PI3K inhibitor buparlisib in recurrent and metastatic HNSCC, even outperforming conventional CD3 immunohistochemistry [89]. Digital pathology platforms combined with computational analysis are being utilized to standardize challenging PD-L1 combined positive scoring by objectively quantifying staining intensity and distribution, thereby reducing inter-observer variability and technical discordance between different assay platforms [90]. In addition, a computational pipeline applied to digital pathology slides has successfully identified prognostically relevant spatial markers, such as the spatial distribution pattern of FOXP3 across tumor and stromal compartments, providing a cost-effective strategy for spatial biomarker discovery [91]. In the context of immunotherapy, an AI-driven single-cell spatial biomarker quantifying specific cell-cell interactions within the tumor microenvironment has proven superior to PD-L1 expression alone in predicting progression-free survival and objective response to immune checkpoint inhibitors in advanced non-small cell lung cancer, with potential applicability to HNSCC [87]. These examples collectively highlight the transformative potential of integrating computational pathology with spatial biology to generate robust, automated, and clinically applicable biomarkers. Crucially, validation of these spatial biomarkers in prospective, multicenter clinical trials represents a necessary next step to translate these experimental findings into improved clinical outcomes for patients with HNSCC.

Future multi-center clinical trials should include spatial biomarker endpoints to verify their predictive and prognostic efficacy, evaluate their repeatability on different platforms, and determine their cost-effectiveness. In conclusion, integrating spatial biology into clinical decision-making will bridge the gap between molecular profiling and microenvironment-based therapeutic intervention, providing a new paradigm for individualized treatment of HNSCC.