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建立用于胰腺腺癌患者风险分层的4-miRNA预后模型。

Establishment of a 4-miRNA Prognostic Model for Risk Stratification of Patients With Pancreatic Adenocarcinoma.

作者信息

Gong Xun, Liu Yuchen, Zheng Chenglong, Tian Peikai, Peng Minjie, Pan Yihang, Li Xiaowu

机构信息

Department of Hepatobiliary Surgery, Shenzhen Key Laboratory, Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University, Shenzhen, China.

College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China.

出版信息

Front Oncol. 2022 Feb 3;12:827259. doi: 10.3389/fonc.2022.827259. eCollection 2022.

Abstract

Pancreatic adenocarcinomas (PAADs) often remain undiagnosed until later stages, limiting treatment options and leading to poor survival. The lack of robust biomarkers complicates PAAD prognosis, and patient risk stratification remains a major challenge. To address this issue, we established a panel constructed by four miRNAs (miR-4444-2, miR-934, miR-1301 and miR-3655) based on The Cancer Genome Atlas (TCGA) and Human Cancer Metastasis Database (HCMDB) to predicted the prognosis of PAAD patients. Then, a risk prediction model of these four miRNAs was constructed by using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) regression analysis. This model stratified TCGA PAAD cohort into the low-risk and high-risk groups based on the panel-based risk score, which was significantly associated with 1-, 2-, 3-year OS (AUC=0.836, AUC=0.844, AUC=0.952, respectively). The nomogram was then established with a robust performance signature for predicting prognosis compared to clinical characteristics of pancreatic cancer (PC) patients, including age, gender and clinical stage. Moreover, two GSE data were validated the expressions of 4 miRNAs with prognosis/survival outcome in PC. In the external clinical sample validation, the high-risk group with the upregulated expressions of miR-934/miR-4444-2 and downregulated expressions of miR-1301/miR-3655 were indicated a poor prognosis. Furthermore, the cell counting kit-8 (CCK-8) assay, clone formation, transwell and wound healing assay also confirmed the promoting effect of miR-934/miR-4444-2 and the inhibiting effect of miR-1301/miR-3655 in PC cell proliferation and migration. Taken together, we identified a new 4-miRNA risk stratification model could be used in predicting prognosis in PAAD.

摘要

胰腺腺癌(PAADs)通常在晚期才被诊断出来,这限制了治疗选择并导致生存率低下。缺乏可靠的生物标志物使PAAD的预后变得复杂,患者风险分层仍然是一项重大挑战。为了解决这个问题,我们基于癌症基因组图谱(TCGA)和人类癌症转移数据库(HCMDB)建立了一个由四个微小RNA(miR-4444-2、miR-934、miR-1301和miR-3655)组成的panel,以预测PAAD患者的预后。然后,通过使用Cox回归分析和最小绝对收缩与选择算子(LASSO)回归分析构建了这四个微小RNA的风险预测模型。该模型根据基于panel的风险评分将TCGA PAAD队列分为低风险和高风险组,其与1年、2年、3年总生存期显著相关(AUC分别为0.836、0.844、0.952)。然后建立了列线图,与胰腺癌(PC)患者的临床特征(包括年龄、性别和临床分期)相比,其具有用于预测预后的强大性能特征。此外,两个GSE数据验证了PC中4个微小RNA的表达与预后/生存结果的关系。在外部临床样本验证中,miR-934/miR-4444-2表达上调且miR-1301/miR-3655表达下调的高风险组显示预后不良。此外,细胞计数试剂盒-8(CCK-8)试验、克隆形成试验、transwell试验和伤口愈合试验也证实了miR-934/miR-4444-2对PC细胞增殖和迁移的促进作用以及miR-1301/miR-3655的抑制作用。综上所述,我们确定了一种新的4-微小RNA风险分层模型可用于预测PAAD的预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3dc/8851918/31950e03a69b/fonc-12-827259-g001.jpg

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