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Background <p>Tobacco exposure contributes to the development and progression of head and neck squamous cell carcinoma (HNSCC) through genomic damage and alterations in the tumor microenvironment. Cancer-associated fibroblasts (CAFs) are important stromal components of the tumor microenvironment, but the relationships among smoking background, CAF-related transcriptional programs, and clinical outcomes in HNSCC remain incompletely understood. We aimed to characterize CAF-related transcriptional programs in HNSCC and evaluate their prognostic relevance in the context of smoking status.</p> Methods <p>We integrated scRNA-seq data with bulk RNA-seq analyses from TCGA-HNSC, in which smoking-background differential expression analyses were used for candidate-gene discovery. Using hdWGCNA, we identified CAF-associated gene modules and constructed a smoking-related CAF 11-gene (SRCAF-11) signature using machine-learning approaches. We evaluated the signature using external cohorts, immune deconvolution analyses, and SHAP-based feature interpretation. We also modulated <i>INHBA</i> expression in HNSCC cell lines to assess its effects on proliferation, migration, invasion, and EMT-related features.</p> Results <p>We identified five transcriptionally distinct CAF subtypes. Matrix-remodeling CAFs (matCAFs) showed extracellular matrix-related features, and higher MuSiC-inferred matCAF relative abundance was associated with poorer survival. Smoker and non-smoker tumors did not differ significantly in MuSiC-inferred CAF-subtype proportions, whereas smoker tumors showed enrichment of EMT- and extracellular matrix-remodeling-related transcriptional programs. The SRCAF-11 signature stratified overall survival across retrospective HNSCC cohorts. <i>INHBA</i> emerged as a major contributor to the model and was preferentially expressed in matCAFs. High <i>INHBA</i> expression was associated with lower inferred immune activity and increased EMT-related transcriptional features in malignant epithelial cells. In vitro, modulation of <i>INHBA</i> expression altered HNSCC cell proliferation, migration, invasion, epithelial and mesenchymal marker expression, and E-cadherin localization.</p> Conclusion <p>The SRCAF-11 signature showed prognostic stratification capability across retrospective HNSCC cohorts. <i>INHBA</i> was identified as a major model feature associated with p-EMT-related transcriptional characteristics. These findings support a context-dependent association between smoking status, CAF-related transcriptional programs, and aggressive tumor phenotypes in HNSCC. Further mechanistic and spatial validation is required.</p>

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Multi-omics characterization of CAF-related transcriptional programs reveals a smoking-context-informed 11-gene prognostic signature in HNSCC

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月5日

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  • Tao Shi,
  • Yuqing Wang,
  • Lisheng Yu,
  • Yixin Zhao

摘要

Background

Tobacco exposure contributes to the development and progression of head and neck squamous cell carcinoma (HNSCC) through genomic damage and alterations in the tumor microenvironment. Cancer-associated fibroblasts (CAFs) are important stromal components of the tumor microenvironment, but the relationships among smoking background, CAF-related transcriptional programs, and clinical outcomes in HNSCC remain incompletely understood. We aimed to characterize CAF-related transcriptional programs in HNSCC and evaluate their prognostic relevance in the context of smoking status.

Methods

We integrated scRNA-seq data with bulk RNA-seq analyses from TCGA-HNSC, in which smoking-background differential expression analyses were used for candidate-gene discovery. Using hdWGCNA, we identified CAF-associated gene modules and constructed a smoking-related CAF 11-gene (SRCAF-11) signature using machine-learning approaches. We evaluated the signature using external cohorts, immune deconvolution analyses, and SHAP-based feature interpretation. We also modulated INHBA expression in HNSCC cell lines to assess its effects on proliferation, migration, invasion, and EMT-related features.

Results

We identified five transcriptionally distinct CAF subtypes. Matrix-remodeling CAFs (matCAFs) showed extracellular matrix-related features, and higher MuSiC-inferred matCAF relative abundance was associated with poorer survival. Smoker and non-smoker tumors did not differ significantly in MuSiC-inferred CAF-subtype proportions, whereas smoker tumors showed enrichment of EMT- and extracellular matrix-remodeling-related transcriptional programs. The SRCAF-11 signature stratified overall survival across retrospective HNSCC cohorts. INHBA emerged as a major contributor to the model and was preferentially expressed in matCAFs. High INHBA expression was associated with lower inferred immune activity and increased EMT-related transcriptional features in malignant epithelial cells. In vitro, modulation of INHBA expression altered HNSCC cell proliferation, migration, invasion, epithelial and mesenchymal marker expression, and E-cadherin localization.

Conclusion

The SRCAF-11 signature showed prognostic stratification capability across retrospective HNSCC cohorts. INHBA was identified as a major model feature associated with p-EMT-related transcriptional characteristics. These findings support a context-dependent association between smoking status, CAF-related transcriptional programs, and aggressive tumor phenotypes in HNSCC. Further mechanistic and spatial validation is required.