Yang Jian, Tang Yuchen, Wang Jie, Yu Chengqing, Li Haoran, Yi Bin, Li Ye, Zhou Jian, Zhang Zixiang
Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Gland Surg. 2022 Oct;11(10):1697-1711. doi: 10.21037/gs-22-517.
Pancreatic cancer (PC) is a highly malignant tumor associated with low survival rates. It is challenging to predict the survival of surgically resected patients with PC. A prognostic staging tool could be beneficial to guide treatments and also aid post-treatment surveillance. This study aimed to identify tissue-based DNA methylation risk-score model to predict the prognosis of surgically resected pancreatic cancer patients.
We performed a monocentric, retrospective study that included 50 patients with stage I-II PC from The First Affiliated Hospital of Soochow University (SU cohort). Both tumor and adjacent normal tissues were obtained from each patient and subjected to capture-based targeted methylation profiling.
In total, 1,162 DNA methylation blocks (DMBs) were differentially methylated in tumor tissues compared with adjacent long-distance tissues (P<0.05). Least Absolute Shrinkage and Selection Operator (LASSO) and stepwise regression analyses revealed a significant correlation between the methylation signature (risk score) and overall survival (OS). Patients in the high-risk group showed significantly poorer OS than those in the low-risk group in the survival analysis [P≤0.001; area under curve (AUC) at 1 year, 0.789; AUC at 2 years, 0.852]. The risk score was also validated using clinical and methylation data of 166 PC patients from The Cancer Genome Atlas pancreatic ductal adenocarcinoma (TCGA-PDAC) dataset. Patients in the high-risk group showed significantly poorer OS than those in the low-risk group (P=0.004; AUC at 1 years, 0.677; AUC at 3 years, 0.611). When clinical parameters were considered, the risk score was the only independent prognostic parameter (P<0.001) in the Cox regression analysis. Furthermore, low-risk patients had higher levels of immune infiltration, anti-tumor immune activation, and increased sensitivity to gemcitabine and paclitaxel. In contrast, high-risk patients had lower mutation rates and benefited more from cisplatin.
In our study, we constructed and validated a tissue-based DNA methylation risk-score model to predict prognosis and identify PC patients with a high mortality risk at the time of surgery. This model might provide a tissue-based prognostic assessment tool for clinicians to aid their treatment decision-making.
胰腺癌（PC）是一种高度恶性的肿瘤，生存率较低。预测接受手术切除的PC患者的生存情况具有挑战性。一种预后分期工具可能有助于指导治疗并辅助治疗后监测。本研究旨在确定基于组织的DNA甲基化风险评分模型，以预测接受手术切除的胰腺癌患者的预后。
我们进行了一项单中心回顾性研究，纳入了苏州大学附属第一医院的50例I-II期PC患者（SU队列）。从每位患者获取肿瘤组织和相邻正常组织，并进行基于捕获的靶向甲基化分析。
与相邻远距离组织相比，肿瘤组织中共有1162个DNA甲基化区域（DMBs）存在差异甲基化（P<0.05）。最小绝对收缩和选择算子（LASSO）及逐步回归分析显示甲基化特征（风险评分）与总生存期（OS）之间存在显著相关性。生存分析中，高风险组患者的OS明显低于低风险组患者[P≤0.001；1年时曲线下面积（AUC）为0.789；2年时AUC为0.852]。还使用来自癌症基因组图谱胰腺导管腺癌（TCGA-PDAC）数据集的166例PC患者的临床和甲基化数据对风险评分进行了验证。高风险组患者的OS明显低于低风险组患者（P=0.004；1年时AUC为0.6,77；3年时AUC为0.611）。在Cox回归分析中，当考虑临床参数时，风险评分是唯一的独立预后参数（P<0.001）。此外，低风险患者的免疫浸润水平、抗肿瘤免疫激活水平较高，对吉西他滨和紫杉醇的敏感性增加。相比之下，高风险患者的突变率较低，从顺铂治疗中获益更多。
在我们的研究中，我们构建并验证了一种基于组织的DNA甲基化风险评分模型，以预测预后并识别手术时具有高死亡风险的PC患者。该模型可能为临床医生提供一种基于组织的预后评估工具，以帮助他们进行治疗决策。
