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血清 microRNA 特征鉴定及建立胰腺导管腺癌患者风险分层的列线图

Identification of Serum miRNA Signature and Establishment of a Nomogram for Risk Stratification in Patients With Pancreatic Ductal Adenocarcinoma.

机构信息

Center for Gastrointestinal Research and Center for Translational Genomics and Oncology, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX.

Division of Biostatistics and Bioinformatics, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL.

出版信息

Ann Surg. 2022 Jan 1;275(1):e229-e237. doi: 10.1097/SLA.0000000000003945.

Abstract

OBJECTIVE

The aim of the study was to perform mRNA-miRNA regulatory network analyses to identify a miRNA panel for molecular subtype identification and stratification of high-risk patients with pancreatic ductal adenocarcinoma (PDAC).

BACKGROUND

Recent transcriptional profiling effort in PDAC has led to the identification of molecular subtypes that associate with poor survival; however, their clinical significance for risk stratification in patients with PDAC has been challenging.

METHODS

By performing a systematic analysis in The Cancer Genome Atlas and International Cancer Genome Consortium cohorts, we discovered a panel of miRNAs that associated with squamous and other poor molecular subtypes in PDAC. Subsequently, we used logistic regression analysis to develop models for risk stratification and Cox proportional hazard analysis to determine survival prediction probability of this signature in multiple cohorts of 433 patients with PDAC, including a tissue cohort (n = 199) and a preoperative serum cohort (n = 51).

RESULTS

We identified a panel of 9 miRNAs that were significantly upregulated (miR-205-5p and -934) or downregulated (miR-192-5p, 194-5p, 194-3p, 215-5p, 375-3p, 552-3p, and 1251-5p) in PDAC molecular subtypes with poor survival [squamous, area under the receiver operating characteristic curve (AUC) = 0.90; basal, AUC = 0.89; and quasimesenchymal, AUC = 0.83]. The validation of this miRNA panel in a tissue clinical cohort was a significant predictor of overall survival (hazard ratio = 2.48, P < 0.0001), and this predictive accuracy improved further in a risk nomogram which included key clinicopathological factors. Finally, we were able to successfully translate this miRNA predictive signature into a liquid biopsy-based assay in preoperative serum specimens from PDAC patients (hazard ratio: 2.85, P = 0.02).

CONCLUSION

We report a novel miRNA risk-stratification signature that can be used as a noninvasive assay for the identification of high-risk patients and potential disease monitoring in patients with PDAC.

摘要

目的

本研究旨在进行 mRNA-miRNA 调控网络分析,以确定用于鉴定胰腺导管腺癌 (PDAC) 分子亚型和高危患者分层的 miRNA 面板。

背景

PDAC 的最近转录谱分析工作导致了与不良生存相关的分子亚型的鉴定;然而,它们在 PDAC 患者的风险分层中的临床意义具有挑战性。

方法

通过在 The Cancer Genome Atlas 和 International Cancer Genome Consortium 队列中进行系统分析,我们发现了一个与 PDAC 中的鳞状和其他不良分子亚型相关的 miRNA 面板。随后,我们使用逻辑回归分析来开发风险分层模型,并使用 Cox 比例风险分析来确定该特征在包括组织队列 (n=199) 和术前血清队列 (n=51) 在内的 433 名 PDAC 患者的多个队列中的生存预测概率。

结果

我们确定了一个由 9 个 miRNA 组成的面板,这些 miRNA 在 PDAC 分子亚型中显著上调 (miR-205-5p 和 -934) 或下调 (miR-192-5p、194-5p、194-3p、215-5p、375-3p、552-3p 和 1251-5p),这些亚型的生存预后较差[鳞状、受试者工作特征曲线 (AUC) 下面积为 0.90;基底、AUC = 0.89;准间质、AUC = 0.83]。在组织临床队列中验证该 miRNA 面板是总生存的显著预测因子 (风险比 = 2.48,P < 0.0001),并且在包含关键临床病理因素的风险列线图中,这种预测准确性进一步提高。最后,我们能够成功地将这种 miRNA 预测特征转化为 PDAC 患者术前血清标本中的液体活检检测 (风险比:2.85,P = 0.02)。

结论

我们报告了一种新的 miRNA 风险分层特征,可作为鉴定高危患者和 PDAC 患者潜在疾病监测的非侵入性检测方法。

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