Huang Lei, Han Quanli, Zhao Liangchao, Wang Zhikuan, Dai Guanghai, Shi Yan
Department of Gastroenterology, National Clinical Research Center for Digestive Diseases, Shanghai Institute of Pancreatic Diseases, The First Affiliated Hospital of Naval Medical University/Changhai Hospital, Naval Medical University, Shanghai, China.
Changhai Clinical Research Unit,National Key Laboratory of Immunity and Inflammation, The First Affiliated Hospital of Naval Medical University/Changhai Hospital, Naval Medical University, Shanghai, China.
Ann Surg. 2025 Apr 1;281(4):632-644. doi: 10.1097/SLA.0000000000006610. Epub 2024 Dec 16.
To develop and validate a signature to precisely predict prognosis in pancreatic ductal adenocarcinoma (PDAC) undergoing resection and adjuvant chemotherapy.
PDAC is largely heterogeneous and responds discrepantly to treatment.
A total of 551 consecutive patients with PDAC from 3 different cohorts of tertiary centers were initially enrolled. Genetic events of the 4 most commonly mutated genes in PDAC and expressions of 12 PI3K/AKT/mammalian target of rapamycin (mTOR) pathway markers were examined. A 9-feature signature for the prediction of chemotherapy benefits was constructed in the training cohort using the least absolute shrinkage and selection operator Cox regression model and validated in 2 independent cohorts.
Utilizing the least absolute shrinkage and selection operator model, a predictive and prognostic signature, named ChemoResist, was established based on KRAS single nucleotide variant (SNV), phosphatase and tensin homologue (PTEN), and mTOR expressions, and 6 clinicopathologic features. Significant differences in survival were observed between high and low-ChemoResist patients receiving chemotherapy in both the training [median overall survival (OS), 17 vs 42 months, P < 0.001; median disease-free survival (DFS), 10 vs 23 months, P < 0.001] and validation cohorts (median OS, 18 vs 35 months, P = 0.034; median DFS, 11 vs 20 months, P = 0.028). The ChemoResist classifier also significantly differentiated patient survival in whole patients regardless of chemotherapy. Multivariable-adjusted analysis substantiated the ChemoResist signature as an independent predictive and prognostic factor. For predicting 2-year OS, the ChemoResist classifier had significantly higher areas under the curve than TNM stage (0.788 vs 0.636, P < 0.001), other clinicopathologic characteristics (0.505-0.668), and single molecular markers (0.507-0.591) in the training cohort. Furthermore, patients with low ChemoResist scores exhibited a more favorable response to adjuvant chemotherapy compared with those with high ChemoResist scores (hazard ratio for OS: training, 0.22 vs 0.57; validation, 0.26 vs 0.50; hazard ratio for DFS: training, 0.35 vs 0.54; validation, 0.18 vs 0.59). The ChemoResist signature was further validated in the total cohort undergoing R0 resection.
The ChemoResist signature could precisely predict survival in PDAC undergoing resection and chemotherapy, and its predictive value surpassed the TNM stage and other clinicopathologic factors. Moreover, the ChemoResist classifier could assist with identifying patients who would more likely benefit from adjuvant chemotherapy.
开发并验证一种可精确预测接受手术切除及辅助化疗的胰腺导管腺癌（PDAC）患者预后的特征标志物。
PDAC具有高度异质性，对治疗反应差异较大。
最初纳入了来自3个不同三级中心队列的551例连续的PDAC患者。检测了PDAC中4个最常发生突变基因的遗传事件以及12种PI3K/AKT/雷帕霉素哺乳动物靶蛋白（mTOR）通路标志物的表达。在训练队列中使用最小绝对收缩和选择算子Cox回归模型构建了一个用于预测化疗获益的9特征标志物，并在2个独立队列中进行验证。
利用最小绝对收缩和选择算子模型，基于KRAS单核苷酸变异（SNV）、磷酸酶和张力蛋白同源物（PTEN）、mTOR表达以及6种临床病理特征，建立了一种预测性和预后性的特征标志物，命名为ChemoResist。在训练队列[中位总生存期（OS），17个月对42个月，P<0.001；中位无病生存期（DFS），10个月对23个月，P<0.001]和验证队列（中位OS，18个月对35个月，P=0.034；中位DFS，11个月对20个月，P=0.028）中，接受化疗的高ChemoResist评分患者和低ChemoResist评分患者的生存情况存在显著差异。无论是否接受化疗，ChemoResist分类器在全体患者中也能显著区分患者的生存情况。多变量调整分析证实ChemoResist特征标志物是一个独立的预测和预后因素。在训练队列中，对于预测2年OS，ChemoResist分类器的曲线下面积显著高于TNM分期（0.788对0.636，P<0.001）、其他临床病理特征（0.505 - 0.668）以及单个分子标志物（0.507 - 0.591）。此外，与高ChemoResist评分患者相比，低ChemoResist评分患者对辅助化疗的反应更有利（OS的风险比：训练队列，0.22对0.57；验证队列，0.26对0.50；DFS的风险比：训练队列，0.35对0.54；验证队列，0.18对0.59）。ChemoResist特征标志物在接受R0切除的总队列中进一步得到验证。
ChemoResist特征标志物可精确预测接受手术切除及化疗的PDAC患者的生存情况，其预测价值超过TNM分期和其他临床病理因素。此外，ChemoResist分类器可帮助识别更可能从辅助化疗中获益的患者。
