Namkung Junghyun, Kwon Wooil, Choi Yonwhan, Yi Sung Gon, Han Sangjo, Kang Mee Joo, Kim Sun-Whe, Park Taesung, Jang Jin-Young
Bioinformatics Tech. Lab, Healthcare group, Future Technology R&D Division, SK Telecom, Co., Seoul, Korea.
Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea.
J Gastroenterol Hepatol. 2016 Jun;31(6):1160-7. doi: 10.1111/jgh.13253.
Altered microRNAs (miRNA) expression, a typical feature of many cancers, is reportedly associated with prognosis according to several studies. Although numerous studies on miRNAs in pancreatic ductal adenocarcinoma have also attempted to identify prognostic biomarkers, more large-scale clinical studies are needed to establish the clinical significance of the results. Present study aimed to identify prognosis-related molecular subtypes of primary pancreas tumors using miRNA expression profiling.
Expression profiles of 1733 miRNAs were obtained by using microarray analysis of 104 pancreatic tumors of Korean patients. To detect subgroups informative in predicting the patient's prognosis, we applied unsupervised clustering methods and then analyzed the association of the molecular subgroups with survival time. Then, we constructed a classifier to predict the subgroup using penalized regression models.
We have determined three pancreatic ductal adenocarcinoma tumor subtypes associated with prognosis based on miRNA expression profiles. These subtypes showed significantly different survival time for patients with the same clinical conditions. This demonstrates that our prognostic molecular subgroup has independent prognostic utility. The molecular subtypes can be predicted with a classifier of 19 miRNAs. Of the 19 signature miRNAs, miR-106b-star, miR-324-3p, and miR-615 were related to a p53 canonical pathway, and miR-324, miR-145-5p, miR-26b-5p, and miR-574-3p were related to a Cox-2 centered pathway.
Our prognostic molecular subtypes demonstrated that miRNA profiles could be used as prognostic markers. Additionally, we have constructed a classifier that may be used to determine the molecular subgroup of new patient sample data. Further studies are needed for validation.
据多项研究报道，微小RNA（miRNA）表达改变是许多癌症的典型特征，与预后相关。尽管关于胰腺导管腺癌中miRNA的众多研究也试图鉴定预后生物标志物，但仍需要更多大规模临床研究来确定结果的临床意义。本研究旨在通过miRNA表达谱鉴定原发性胰腺肿瘤的预后相关分子亚型。
通过对104例韩国患者的胰腺肿瘤进行微阵列分析，获得了1733种miRNA的表达谱。为了检测对预测患者预后有信息价值的亚组，我们应用了无监督聚类方法，然后分析了分子亚组与生存时间的关联。然后，我们构建了一个分类器，使用惩罚回归模型来预测亚组。
基于miRNA表达谱，我们确定了三种与预后相关的胰腺导管腺癌肿瘤亚型。这些亚型在相同临床条件下的患者生存时间有显著差异。这表明我们的预后分子亚组具有独立的预后效用。可以用19种miRNA的分类器预测分子亚型。在这19种标志性miRNA中，miR-106b-star、miR-324-3p和miR-615与p53经典通路相关，而miR-324、miR-145-5p、miR-26b-5p和miR-574-3p与以Cox-2为中心的通路相关。
我们的预后分子亚型表明，miRNA谱可作为预后标志物。此外，我们构建了一个分类器，可用于确定新患者样本数据的分子亚组。需要进一步研究进行验证。
