Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Department of Cardiothoracic Surgery, The Second People's Hospital of Yibin, Yibin, Sichuan, China.
Environ Toxicol. 2024 May;39(5):2803-2816. doi: 10.1002/tox.24155. Epub 2024 Jan 29.
The relationship between DNA damage repair (DDR) and cancer is intricately intertwined; however, its specific role in esophageal squamous cell carcinoma (ESCC) remains enigmatic.
Employing single-cell analysis, we delineated the functionality of DDR-related genes within the tumor microenvironment (TME). A diverse array of scoring mechanisms, including AUCell, UCell, singscore, ssgsea, and AddModuleScore, were harnessed to scrutinize the activity of DDR-related genes across different cell types. Differential pathway alterations between high-and low-DDR activity cell clusters were compared. Furthermore, leveraging multiple RNA-seq datasets, we constructed a robust DDR-associated signature (DAS), and through integrative multiomics analysis, we explored differences in prognosis, pathways, mutational landscapes, and immunotherapy predictions among distinct DAS groups.
Notably, high-DDR activity cell subpopulations exhibited markedly enhanced cellular communication. The DAS demonstrated uniformity across multiple datasets. The low-DAS group exhibited improved prognoses, accompanied by heightened immune infiltration and elevated immune checkpoint expression. SubMap analysis of multiple immunotherapy datasets suggested that low-DAS group may experience enhanced immunotherapy responses. The "oncopredict" R package analyzed and screened sensitive drugs for different DAS groups.
Through the integration of single-cell and bulk RNA-seq data, we have developed a DAS associated with prognosis and immunotherapy response. This signature holds promise for the future stratification and personalized treatment of ESCC patients in clinical settings.
DNA 损伤修复 (DDR) 与癌症之间的关系错综复杂,但它在食管鳞状细胞癌 (ESCC) 中的具体作用仍不清楚。
我们采用单细胞分析方法,描绘了 DDR 相关基因在肿瘤微环境 (TME) 中的功能。利用 AUCell、UCell、singscore、ssgsea 和 AddModuleScore 等多种评分机制,研究了不同细胞类型中 DDR 相关基因的活性。比较了高和低 DDR 活性细胞簇之间的差异途径改变。此外,我们利用多个 RNA-seq 数据集构建了稳健的 DDR 相关特征 (DAS),并通过整合多组学分析,探讨了不同 DAS 组之间的预后、通路、突变景观和免疫治疗预测的差异。
高 DDR 活性细胞亚群表现出明显增强的细胞通讯。DAS 在多个数据集上具有一致性。低 DAS 组表现出改善的预后,伴随着更高的免疫浸润和免疫检查点表达水平。对多个免疫治疗数据集的 SubMap 分析表明,低 DAS 组可能对免疫治疗有更强的反应。“oncopredict”R 包分析和筛选了不同 DAS 组的敏感药物。
通过整合单细胞和批量 RNA-seq 数据,我们开发了一个与预后和免疫治疗反应相关的 DAS。该特征有望在未来对 ESCC 患者进行分层和个性化治疗。