Department of Emergency Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Aging (Albany NY). 2024 Sep 26;16(18):12525-12542. doi: 10.18632/aging.206043.
PURPOSE: Proliferation of stromal connective tissue is a hallmark of pancreatic adenocarcinoma (PAAD). The engagement of activated cancer-associated fibroblasts (CAFs) contributes to the progression of PAAD through their involvement in tumor fibrogenesis. However, the prognostic significance of CAF-based risk signature in PAAD has not been explored. METHODS: The single-cell RNA sequencing (scRNA-seq) data sourced from GSE155698 within the Gene Expression Omnibus (GEO) database was supplemented by bulk RNA sequencing data from The Cancer Genome Atlas (TCGA) and microarray data retrieved from the GEO database. The scRNA-seq data underwent processing via the Seurat package to identify distinct CAF clusters utilizing specific CAF markers. Differential gene expression analysis between normal and tumor samples was conducted within the TCGA-PAAD cohort. Univariate Cox regression analysis pinpointed genes associated with CAF clusters, identifying prognostic CAF-related genes. These genes were utilized in LASSO regression to craft a predictive risk signature. Subsequently, integrating clinicopathological traits and the risk signature, a nomogram model was constructed. RESULTS: Our scRNA-seq analysis unveiled four distinct CAF clusters in PAAD, with two linked to PAAD prognosis. Among 207 identified DEGs, 148 exhibited significant correlation with these CAF clusters, forming the basis of a seven-gene risk signature. This signature emerged as an independent predictor in multivariate analysis for PAAD and demonstrated predictive efficacy in immunotherapeutic outcomes. Additionally, a novel nomogram, integrating age and the CAF-based risk signature, exhibited robust predictability and reliability in prognosticating PAAD. Moreover, the risk signature displayed substantial correlations with stromal and immune scores, as well as specific immune cell types. CONCLUSIONS: The prognosis of PAAD can be accurately predicted using the CAF-based risk signature, and a thorough analysis of the PAAD CAF signature may aid in deciphering the patient's immunotherapy response and presenting fresh cancer treatment options.
目的：基质结缔组织的增殖是胰腺导管腺癌（PAAD）的一个标志。激活的癌相关成纤维细胞（CAF）的参与通过参与肿瘤纤维化促进 PAAD 的进展。然而，基于 CAF 的风险特征在 PAAD 中的预后意义尚未得到探索。
方法：从基因表达综合数据库（GEO）中的 GSE155698 中获取的单细胞 RNA 测序（scRNA-seq）数据，通过 Seurat 包进行处理，利用特定的 CAF 标记识别不同的 CAF 簇。利用 TCGA-PAAD 队列中的 bulk RNA 测序数据和从 GEO 数据库中检索的微阵列数据对 scRNA-seq 数据进行补充。在 TCGA-PAAD 队列中对正常和肿瘤样本之间的差异基因表达进行分析。单因素 Cox 回归分析确定与 CAF 簇相关的基因，确定与 CAF 相关的预后基因。这些基因用于 LASSO 回归构建预测风险特征。随后，整合临床病理特征和风险特征构建列线图模型。
结果：我们的 scRNA-seq 分析揭示了 PAAD 中的四个不同的 CAF 簇，其中两个与 PAAD 的预后相关。在 207 个鉴定的差异表达基因中，有 148 个与这些 CAF 簇显著相关，构成了一个七基因风险特征的基础。该特征在多变量分析中成为 PAAD 的独立预测因子，并在免疫治疗结果中显示出预测效力。此外，一个新的列线图，整合了年龄和基于 CAF 的风险特征，在预测 PAAD 方面表现出强大的预测能力和可靠性。此外，该风险特征与基质和免疫评分以及特定的免疫细胞类型有显著相关性。
结论：可以使用基于 CAF 的风险特征准确预测 PAAD 的预后，对 PAAD 的 CAF 特征进行全面分析可能有助于破译患者的免疫治疗反应，并提供新的癌症治疗选择。
Front Oncol. 2023-3-17
Annu Rev Immunol. 2022-4-26
Zotero 插件
