背景:胰腺导管腺癌(PDAC)具有破坏性预后。临床病理参数和分子作为预后因素的表现仍然有限且不一致。本研究旨在构建一个多分子生物标志物组,以更准确地预测PDAC患者手术切除后的预后。
方法:首先,一种新颖的计算策略,在生物信息学预测(CIPHER)的基础上整合来自组学和文献的预后证据来生成网络,旨在系统地识别潜在的高置信度PDAC相关的预后候选者。对605例切除的PDAC患者的标本进行回顾性收集,在组织微阵列中对23个候选物进行免疫组织化学检测,以构建多分子组。最后,小组在两个独立的队列中进行了验证.
结果:根据构建的五分子面板,在发展队列中,高危患者的疾病特异性生存率(DSS)显著低于低危患者(HR2.15,95CI1.51-3.05,P<0.0001;AUC0.67).在两个验证队列中,两组之间也观察到相似的显著差异(HR3.18和3.31,95CI1.89-5.37和1.78-6.16,所有P<0.0001;AUC0.72和0.73).在多变量分析中,该小组是在每个队列中具有显著性的唯一预测指标.此外,它对长期生存的预测能力,高于其单个成分,通过与传统的临床病理变量相结合,可以在很大程度上增强。最后,辅助化疗(ACT)仅在高危患者中与更好的DSS相关,单变量和多变量,在所有的队列中。
结论:通过系统的基于网络的策略开发的新的预后小组在预测PDAC患者的手术后生存方面具有很强的能力。此外,小组定义的高危患者可能从ACT中获益更多.
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a devastating prognosis. The performance of clinicopathologic parameters and molecules as prognostic factors remains limited and inconsistent. The present
study aimed to construct a multi-molecule biomarker panel to more accurately predict post-resectional prognosis of PDAC patients.
METHODS: Firstly, a novel computational strategy integrating prognostic evidence from omics and literature on the basis of bioinformatics prediction (CIPHER) to generate the network, was designed to systematically identify potential high-confidence PDAC-related prognostic candidates. After specimens from 605 resected PDAC patients were retrospectively collected, 23 candidates were detected immunohistochemically in tissue-microarrays for the development cohort to construct a multi-molecule panel. Lastly, the panel was validated in two independent cohorts.
RESULTS: According to the constructed five-molecule panel, disease-specific survival (DSS) was significantly poorer in high-risk patients than in low-risk ones in development cohort (HR 2.15, 95%CI 1.51-3.05, P<0.0001; AUC 0.67). In two validation cohorts, similar significant differences between the two groups were also observed (HR 3.18 and 3.31, 95%CI 1.89-5.37 and 1.78-6.16, All P<0.0001; AUC 0.72 and 0.73). In multivariate analyses, this panel was the sole prognosticator that was significant in each cohort. Furthermore, its predictive power for long-term survival, higher than its individual constituents, could be largely enhanced by combination with traditional clinicopathological variables. Finally, adjuvant chemotherapy (ACT) correlated with better DSS only in high-risk patients, uni- and multi-variately, in all the cohorts.
CONCLUSIONS: The novel prognostic panel developed by a systematically network-based strategy presents strong ability in prediction of post-resectional survival of PDAC patients. Furthermore, panel-defined high-risk patients might benefit more from ACT.