Expression Profiles and Clinical Significance of MicroRNAs in Papillary Renal Cell Carcinoma: A STROBE-Compliant Observational Study.
Expression Profiles and Clinical Significance of MicroRNAs in Papillary Renal Cell Carcinoma: A STROBE-Compliant Observational Study.
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DOI：
10.1097/md.0000000000000767
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发表时间：
2015-04
期刊：
影响因子：
1.6
通讯作者：
Jia RP
中科院分区：
文献类型：
--
作者：
Ge YZ;Xu LW;Xu Z;Wu R;Xin H;Zhu M;Lu TZ;Geng LG;Liu H;Zhou CC;Yu P;Zhao YC;Hu ZK;Zhao Y;Zhou LH;Wu JP;Li WC;Zhu JG;Jia RP
乳头状肾细胞癌（pRCC）是肾癌的第二种最常见的亚型。本研究分析了pRCC中microRNA（miRNA）的表达谱，旨在探讨miRNA表达与pRCC进展及预后的关系。从癌症基因组图谱数据集中确定了总共163名未经治疗的原发性pRCC患者，并将其纳入这项回顾性观察性研究。根据肿瘤-淋巴结-转移信息对miRNA表达谱进行分级，并在组织学亚型之间进行比较。此外，在Kaplan-Meier生存率以及单变量和多变量考克斯回归分析的帮助下，应用训练-验证方法来鉴定具有预后价值的miRNA。最后，应用在线大卫（Database for Annotation，Visualization，and Integrated Discover）程序，利用3种计算算法（PicTar、TargetScan和米兰达）预测的乳腺癌相关miRNA的靶基因进行途径富集分析。在进展相关的miRNA谱中，分别选择了26种用于病理分期、28种用于病理T、16种用于淋巴结状态、3种用于转移状态和32种用于组织学类型的miRNA。在训练阶段，12种miRNA的表达水平（mir-134，mir-379，mir-127，mir-452，mir-199 a，mir-200 c，mir-141，mir-3074，mir-1468，mir-181 c，mir-1180和mir-34 a）与患者存活显著相关，而mir-200 c，mir-127，mir-34 a，多因素考克斯回归分析显示mir-181 c是pRCC的独立预后因素。随后，mir-200 c、mir-127和mir-34 a在验证阶段被证实与患者生存率显著相关。最后，靶基因预测分析确定了mir-200 c的总共113个靶基因、mir-127的37个靶基因和mir-34 a的180个靶基因，从而进一步产生了15个分子通路。我们的结果确定了与pRCC的进展和侵袭性相关的特异性miRNA，并且3种miRNA（mir-200 c、mir-127和mir-34 a）是pRCC有希望的预后因子。
Supplemental Digital Content is available in the text Papillary renal cell carcinoma (pRCC) is the second most prevalent subtype of kidney cancers. In the current study, we analyzed the global microRNA (miRNA) expression profiles in pRCC, with the aim to evaluate the relationship of miRNA expression with the progression and prognosis of pRCC. A total of 163 treatment-naïve primary pRCC patients were identified from the Cancer Genome Atlas dataset and included in this retrospective observational study. The miRNA expression profiles were graded by tumor-node-metastasis information, and compared between histologic subtypes. Furthermore, the training-validation approach was applied to identify miRNAs of prognostic values, with the aid of Kaplan–Meier survival, and univariate and multivariate Cox regression analyses. Finally, the online DAVID (Database for Annotation, Visualization, and Integrated Discover) program was applied for the pathway enrichment analysis with the target genes of prognosis-associated miRNAs, which were predicted by 3 computational algorithms (PicTar, TargetScan, and Miranda). In the progression-related miRNA profiles, 26 miRNAs were selected for pathologic stage, 28 for pathologic T, 16 for lymph node status, 3 for metastasis status, and 32 for histologic types, respectively. In the training stage, the expression levels of 12 miRNAs (mir-134, mir-379, mir-127, mir-452, mir-199a, mir-200c, mir-141, mir-3074, mir-1468, mir-181c, mir-1180, and mir-34a) were significantly associated with patient survival, whereas mir-200c, mir-127, mir-34a, and mir-181c were identified by multivariate Cox regression analyses as potential independent prognostic factors in pRCC. Subsequently, mir-200c, mir-127, and mir-34a were confirmed to be significantly correlated with patient survival in the validation stage. Finally, target gene prediction analysis identified a total of 113 target genes for mir-200c, 37 for mir-127, and 180 for mir-34a, which further generated 15 molecular pathways. Our results identified the specific miRNAs associated with the progression and aggressiveness of pRCC, and 3 miRNAs (mir-200c, mir-127, and mir-34a) as promising prognostic factors of pRCC.