癌症相关成纤维细胞（CAF）-癌细胞串扰（CCCT）在肿瘤微环境塑造和免疫治疗反应中发挥着重要作用。目前的预后指标不足以准确评估头颈鳞状细胞癌（HNSCC）患者的免疫治疗反应。本研究旨在开发CCCT相关基因预后指数（CCRGPI），用于评估HNSCC患者的预后和对免疫检查点抑制剂（ICI）治疗的反应。两种细胞模型，成纤维细胞-癌细胞间接共培养（FCICC）模型和构建成纤维细胞-癌细胞类器官（FC-类器官）模型以可视化成纤维细胞和癌细胞之间的串扰。基于 HNSCC scRNA-seq 数据集，使用 R 包 CellChat 进行细胞通讯分析，以识别参与 CCCT 的基因对。然后应用最小绝对收缩和选择算子（LASSO）回归来进一步细化这些基因对的选择。随后对选定的基因对进行逐步回归以开发 CCRGPI。我们进一步进行了全面分析，以确定不同 CCRGPI 亚组中与 ICI 治疗相关的分子和免疫特征以及预后。最后，利用连接图（CMap）分析和分子对接筛选潜在的治疗药物。 FCICC和FC-类器官模型表明癌细胞促进成纤维细胞活化成CAF，CAF增强癌细胞的侵袭，CCCT有点异质。 CCRGPI 是基于 4 个基因对开发的：IGF1-IGF1R、LGALS9-CD44、SEMA5A-PLXNA1 和 TNXB-SDC1。此外，高 CCRGPI 评分被认为是总生存期 (OS) 的不利预后因素。此外，高 CCRGPI 与 P53 通路的激活、高 TP53 突变率以及 ICI 治疗的获益降低呈正相关，但与各种免疫细胞（如 CD4 T 细胞、CD8 T 细胞、和B细胞。此外，Ganetespib 被确定为 HNSCC 联合治疗的潜在药物。CCRGPI 可以可靠地预测 HSNCC 患者的预后和免疫治疗反应，并可能有助于指导 HNSCC 患者的个体化治疗。© 2024。作者。

Cancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role in tumor microenvironment shaping and immunotherapy response. Current prognostic indexes are insufficient to accurately assess immunotherapy response in patients with head and neck squamous cell carcinoma (HNSCC). This study aimed to develop a CCCT-related gene prognostic index (CCRGPI) for assessing the prognosis and response to immune checkpoint inhibitor (ICI) therapy of HNSCC patients.Two cellular models, the fibroblast-cancer cell indirect coculture (FCICC) model, and the fibroblast-cancer cell organoid (FC-organoid) model, were constructed to visualize the crosstalk between fibroblasts and cancer cells. Based on a HNSCC scRNA-seq dataset, the R package CellChat was used to perform cell communication analysis to identify gene pairs involved in CCCT. Least absolute shrinkage and selection operator (LASSO) regression was then applied to further refine the selection of these gene pairs. The selected gene pairs were subsequently subjected to stepwise regression to develop CCRGPI. We further performed a comprehensive analysis to determine the molecular and immune characteristics, and prognosis associated with ICI therapy in different CCRGPI subgroups. Finally, the connectivity map (CMap) analysis and molecular docking were used to screen potential therapeutic drugs.FCICC and FC-organoid models showed that cancer cells promoted the activation of fibroblasts into CAFs, that CAFs enhanced the invasion of cancer cells, and that CCCT was somewhat heterogeneous. The CCRGPI was developed based on 4 gene pairs: IGF1-IGF1R, LGALS9-CD44, SEMA5A-PLXNA1, and TNXB-SDC1. Furthermore, a high CCRGPI score was identified as an adverse prognostic factor for overall survival (OS). Additionally, a high CCRGPI was positively correlated with the activation of the P53 pathway, a high TP53 mutation rate, and decreased benefit from ICI therapy but was inversely associated with the abundance of various immune cells, such as CD4+ T cells, CD8+ T cells, and B cells. Moreover, Ganetespib was identified as a potential drug for HNSCC combination therapy.The CCRGPI is reliable for predicting the prognosis and immunotherapy response of HSNCC patients and may be useful for guiding the individualized treatment of HNSCC patients.© 2024. The Author(s).