Analysis of long non-coding RNA expression profiles in ovarian cancer.
Analysis of long non-coding RNA expression profiles in ovarian cancer.
复制标题
卵巢癌中长非编码 RNA 表达谱的分析。
DOI：
10.3892/ol.2017.6283
复制
发表时间：
2017-08
期刊：
影响因子：
2.9
通讯作者：
Li C
中科院分区：
文献类型：
--
作者：
Shen L;Liu W;Cui J;Li J;Li C
卵巢癌是女性健康的主要威胁之一。在早期阶段识别癌症病例并为患者选择有效的治疗药物具有挑战性。关于长链非编码RNA（lncRNA）的研究数量正在迅速增加;大量证据表明lncRNA在致癌和肿瘤抑制机制中至关重要。因此，在本研究中，考虑了卵巢癌中lncRNA的表达。对基因表达综合数据库中所有现有的卵巢癌微阵列数据集进行了评估，其中两个符合本研究的标准;这些数据集被指定为训练集和验证集。建立了一种重新注释管道方法来注释来自现有探针集的lncRNA。当比较卵巢癌与正常卵巢组织时，基于它们在训练集中分类组织的组合能力，鉴定了来自RefSeq数据库的七种lncRNA，并使用验证集进行了验证。对7种已鉴定的lncRNA的分子功能的研究可能有助于理解卵巢癌的发生;它们也可能是新的卵巢癌生物标志物的候选者。
Ovarian cancer is one of the major threats to female health. Identifying cancer cases at an early stage and selecting effective therapeutic drugs for patients is challenging. The number of studies concerning long non-coding RNAs (lncRNAs) is increasing rapidly; there is a large body of evidence indicating that lncRNAs are crucial in oncogenic and tumor-suppression mechanisms. Therefore, in the present study, lncRNA expression in ovarian cancer was considered. All of the existing ovarian cancer microarray datasets in the Gene Expression Omnibus database were assessed and two met the criteria for the present study; these were designated the training and validation sets. A re-annotation pipeline method was established to annotate lncRNAs from existing probe sets. When comparing ovarian cancer with normal ovarian tissues, seven lncRNAs from the RefSeq database, based on their combined ability to classify tissue in the training set, were identified and validated with the validation set. Research into the molecular functions of the seven identified lncRNAs may contribute to the understanding of ovarian cancer oncogenesis; they may also be candidates for novel ovarian cancer biomarkers.
登录
查看更多内容
影响因子：
5.4
作者：
Kornienko AE;Guenzl PM;Barlow DP;Pauler FM
通讯作者：
Pauler FM
影响因子：
2.9
作者：
Shen X;Yue M;Meng F;Zhu J;Zhu X;Jiang Y
通讯作者：
Jiang Y
影响因子：
4.8
作者：
Zhou, Yunli;Zhong, Ying;Klibanski, Anne
通讯作者：
Klibanski, Anne
影响因子：
3.7
作者：
Elgaaen, Bente Vilming;Olstad, Ole Kristoffer;Gautvik, Kaare M.
通讯作者：
Gautvik, Kaare M.
影响因子：
168.9
作者：
Michiels, S;Koscielny, S;Hill, C
通讯作者：
Hill, C