Zhang Chaoyi, Tang Rong, Yang Jianhui, Chen Yueyue, Li Yangyi, Zhou Cong, Wang Wei, Yu Xian-Jun, Xu Jin
Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, People's Republic of China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People's Republic of China.
Discov Oncol. 2025 Apr 8;16(1):491. doi: 10.1007/s12672-025-02293-w.
The DNA damage response (DDR) has a major impact on the development and progression of pancreatic ductal adenocarcinoma (PDAC). Investigating biomarkers linked to the DDR may facilitate prognostic assessment and prediction of immunological characteristics for patients with PDAC.
The single-cell RNA sequencing (scRNA-seq) dataset GSE212966 was obtained from the GEO database, whereas the bulk RNA-seq data were sourced from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analyses were used to select genes to construct a prognostic risk model. Finally, the correlations of the model score with drug sensitivity, immunological checkpoints, and immune infiltration were assessed.
We used 16 DDR marker genes to construct a predictive model. Furthermore, we established that the model had strong performance in both the training and validation cohorts. For PDAC, the model risk score served as an independent predictor of prognosis. There were notable differences in the proportions of the immune cells in the tumor microenvironment and drug sensitivity between the high and low risk score groups. The study confirmed that the risk score model is useful for predicting the immunotherapy response. Our experiments verified that knockdown of LY6D inhibits cell proliferation, promotes apoptosis and DNA damage.
Our creative integration of bulk RNA sequencing and scRNA-seq data allowed us to construct a DDR-related prognostic model. Our model can be used to predict the immunological features, treatment response and prognosis of PDAC with a relatively high degree of accuracy.
DNA损伤反应（DDR）对胰腺导管腺癌（PDAC）的发生和发展具有重大影响。研究与DDR相关的生物标志物可能有助于PDAC患者的预后评估和免疫特征预测。
单细胞RNA测序（scRNA-seq）数据集GSE212966取自GEO数据库，而批量RNA-seq数据则来自癌症基因组图谱（TCGA）和基因型-组织表达（GTEx）数据库。使用最小绝对收缩和选择算子（LASSO）及单变量Cox回归分析来选择基因以构建预后风险模型。最后，评估模型评分与药物敏感性、免疫检查点和免疫浸润的相关性。
我们使用16个DDR标记基因构建了一个预测模型。此外，我们确定该模型在训练和验证队列中均具有强大的性能。对于PDAC，模型风险评分可作为预后的独立预测指标。高风险评分组和低风险评分组在肿瘤微环境中的免疫细胞比例和药物敏感性方面存在显著差异。该研究证实风险评分模型可用于预测免疫治疗反应。我们的实验证实，敲低LY6D可抑制细胞增殖、促进细胞凋亡和DNA损伤。
我们对批量RNA测序和scRNA-seq数据的创新性整合使我们能够构建一个与DDR相关的预后模型。我们的模型可用于以相对较高的准确度预测PDAC的免疫特征、治疗反应和预后。
