Integrated single-cell and bulk RNA sequencing reveals prognostic and immunotherapy-associated myofibroblastic cancer-associated fibroblast subtypes in head and neck squamous cell carcinoma
Abstract
Background
Cancer-associated fibroblasts (CAFs) represent a profoundly influential and dynamic stromal cell population within the tumor microenvironment (TME), playing critical and multifaceted roles in various aspects of the pathogenesis and progression of head and neck squamous cell carcinoma (HNSCC). These roles are far from passive; CAFs actively engage in shaping the fundamental architecture of the TME, notably contributing to the formation of a tumor-permissive extracellular matrix (ECM) structure that facilitates cancer cell invasion and metastasis. Beyond structural remodeling, CAFs are intimately involved in fostering angiogenesis, the development of new blood vessels that supply oxygen and nutrients to the burgeoning tumor, and critically, they contribute to the complex immune and metabolic reprogramming of the TME, creating an immunosuppressive and metabolically favorable milieu for cancer cell survival and proliferation. Given their pervasive involvement in these critical aspects of HNSCC biology, this comprehensive study was specifically designed to delve into the intricate properties of CAFs. The primary objective was to thoroughly examine the inherent plasticity and metabolic heterogeneity of CAF populations identified within HNSCC patients, specifically assessing how these characteristics might fluctuate or be altered in the dynamic context of therapeutic intervention, comparing their states both before and after the administration of immunotherapy. Understanding these changes is crucial for optimizing treatment strategies and predicting patient response.
Methods
To achieve the ambitious objectives of this study, a sophisticated and integrative bioinformatics approach was employed, combining both single-cell and bulk RNA sequencing (RNA-seq) analyses. This methodology allowed for a high-resolution examination of gene expression patterns at both the individual cell level and across bulk tissue samples, providing a comprehensive view of CAF heterogeneity and function. The analyses were based on publicly available, high-quality datasets, including GSE195832, GSE65868, and the extensive HNSCC cohort from The Cancer Genome Atlas (TCGA). To comprehensively characterize the functional plasticity and transcriptionally diverse nature of the newly categorized CAF subtypes, specialized bioinformatic tools were utilized. The DoRothEA tool was employed to infer the activity of transcription factors, providing insights into regulatory networks, while the scMetabolism package facilitated a detailed analysis of metabolic pathway activity at single-cell resolution. Following the initial categorization and functional assessment, a crucial step involved examining the precise relationship between genes specifically and highly expressed within the myofibroblast-like cancer-associated fibroblast (myCAF) subtype and their influence on patient prognosis. This was rigorously assessed through both univariate and multivariate statistical analyses, enabling the identification of independent prognostic markers. Furthermore, to understand the broader impact of myCAFs on the TME, their influence on immune cell modulation was meticulously analyzed using the Seurat and clusterProfiler packages, revealing how these specific CAF subtypes shape the local immune landscape. Finally, to explore potential therapeutic vulnerabilities and strategies pertinent to HNSCC, the study leveraged existing pharmacological datasets, specifically the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing datasets. These resources provided valuable information on the sensitivity of cancer cells to a wide array of compounds, allowing for the identification of drugs potentially effective against HNSCC, especially in the context of myCAF prevalence.
Results
The integrated single-cell RNA sequencing analysis yielded a high-resolution cellular landscape, successfully annotating a total of seven distinct cell types based on their gene expression profiles, which were further grouped into 11 discrete cellular clusters. Within this detailed cellular map, the diverse population of cancer-associated fibroblasts was further refined and re-categorized into three principal and functionally distinct subtypes: inflammatory cancer-associated fibroblasts (iCAFs), characterized by their cytokine-producing and pro-inflammatory roles; proliferating cancer-associated fibroblasts (pCAFs), notable for their high proliferative capacity; and myofibroblast-like cancer-associated fibroblasts (myCAFs), distinguished by their contractile and extracellular matrix-remodeling properties. A particularly salient finding emerged regarding the dynamic changes in CAF composition following immunotherapy: the percentage of myCAFs was notably reduced in HNSCC patients after receiving immunotherapy, suggesting a potential shift in the CAF landscape in response to treatment. The inherent functional plasticity of the CAFs was comprehensively confirmed by the diverse array of enriched biological pathways identified across the different subtypes, highlighting their adaptability and varied contributions to tumor biology. Specifically, the myCAFs were found to be intimately associated with critical cellular processes such as DNA repair mechanisms, oxidative phosphorylation (reflecting their metabolic activity), and the regulation of genes by transcription factor E2F targets, indicating their involvement in cell cycle progression and proliferation. Moreover, the myCAF subtype emerged as the most prognostically relevant among the identified CAF populations in HNSCC, with its prevalence or specific gene expression signature strongly correlating with patient outcomes. These myCAFs were also found to play a significant role in modulating the composition and activity of various immune cells within the HNSCC tumor microenvironment, further solidifying their central role in shaping the anti-tumor immune response. In terms of therapeutic implications, a higher myCAF score was paradoxically related to higher half-maximal inhibitory concentration (IC50) values for certain drugs, including D-4476, GW-583340, spautin-1, and VER-155008, suggesting that tumors rich in myCAFs might be less responsive to these agents. Conversely, a higher myCAF score was associated with *lower* IC50 values for JTE-607, TG100-115, ML320, and TGX-221, indicating potential therapeutic vulnerabilities. Crucially, and directly linking back to the background objective, patients exhibiting lower myCAF scores demonstrated a more favorable and robust response to immunotherapy, suggesting that the abundance of this specific CAF subtype could serve as a predictive biomarker for immunotherapy efficacy.
Conclusions
This extensive and high-resolution study, leveraging the power of integrated single-cell and bulk RNA sequencing analyses, has provided unprecedented insights into the inherent plasticity and significant metabolic heterogeneity displayed by cancer-associated fibroblasts within the intricate tumor microenvironment of head and neck squamous cell carcinoma. The identification and characterization of distinct CAF subtypes, particularly the myCAFs, and their dynamic changes in response to immunotherapy, represent a critical advancement. Our comprehensive findings not only deepen our fundamental understanding of the complex interplay between tumor cells and their stromal partners but also hold immense potential to significantly contribute to a more nuanced comprehension of the variable immunotherapy responses observed in HNSCC patients. By recognizing the prognostic and immunomodulatory roles of specific CAF subtypes, this research paves the way for the development of more personalized and effective therapeutic strategies, potentially involving the targeting of CAFs to enhance the efficacy of existing treatments and improve patient outcomes in HNSCC.
Keywords: Head and neck squamous cell carcinoma (HNSCC); bulk RNA sequencing (bulk RNA-seq); cancer-associated fibroblasts (CAFs); immunotherapy; single-cell RNA sequencing (scRNA-seq).