Supplementary materials for the paper "Integrating Single-cell and Bulk RNA Sequencing Data Reveals the Prognostic and Therapeutic Value of Cancer-associated Fibroblasts for Metastatic Head and Neck Squamous Cell Carcinoma"

HNSCC metastasis shows unfavorable prognosis and CAFs are indispensable but remain unexplored. Using R packages, the DEGsof fibroblast cluster and bulk RNA-seq datawere identified and subjected to enrichment analysis. Thesetwo datasets were integrated to define CAF-related genesand established a CAF-based prognostic model by Cox regression analysis. HNSCC patients were divided into low- and high-risk groups via risk score, accompanied by immune characteristics, drug response and candidate drugs analysis. Target gene expression was verified via tissue microarry, while FaDu cellswere used to test the inhibitory effects of candidate drug on cell viability and invasion of HNSCC. The DEGsof CAFs and TCGA data were identified and they were integrated to discover 57 CAF-related genes. We established a prognosticmodel of 8 CAF-related genes for metastatic HNSCC with low- and high-risk groups. Larger sensitivity to immunotherapy was suggested in low-risk group, while CAF-related genes were strongly linked with immune cells and checkpoints. Drug response analysis had predicted 10 potential drugs susceptible to targeted therapy. VCANwas elevated in HNSCC tissues with lymph node involvementand identified as a target gene of gefitinib. Importantly, gefitinib displayed obvious inhibitory effects on FaDu cells proliferation and invasion. Our study established an innovative prognostic model of metastatic HNSCC based on CAF-related genes, gained a comprehensive understanding of their anticipated and experimental roles in prognosis value and therapeutic outcome, thereby shedding light on the significance of CAFs in metastatic HNSCC prognosis and accurate therapy.