Gene co-expression network reveals shared modules predictive of stage and grade in serous ovarian cancers.
Gene co-expression network reveals shared modules predictive of stage and grade in serous ovarian cancers.
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基因共表达网络揭示了预测浆液性卵巢癌分期和分级的共享模块
DOI：
10.18632/oncotarget.17785
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发表时间：
2017-06-27
期刊：
影响因子：
--
通讯作者：
Zhu T
中科院分区：
文献类型：
--
作者：
Sun Q;Zhao H;Zhang C;Hu T;Wu J;Lin X;Luo D;Wang C;Meng L;Xi L;Li K;Hu J;Ma D;Zhu T
浆液性卵巢癌(SOC)是最致命的妇科癌症。临床研究表明，肿瘤的分期和分级与临床预后有关。识别有意义的共表达基因簇或与分期或分级相关的代表性生物标志物可能有助于揭示肿瘤发生和癌症发展的机制，并有助于预测SOC患者的预后。因此，我们进行了加权基因共表达网络分析，并基于三个公共微阵列数据集(GSE26193、GSE9891和TCGA)计算了模块-性状相关性，其中包括788个样本和10402个基因。我们检测到与所有建模数据集显著共享的一个或多个临床特征相关的四个模块，并确定了一个与阶段相关的模块和一个与级别相关的模块。分析表明，MMP2、COL3A1、COL1A2、FBN1、COL5A1、COL5A2和AEBP1是与分期相关的顶端中枢基因，CDK1、Bub1、BUB1B、BIRC5、AURKB、CENPA和CDC20是与级别相关的顶端中枢基因。对涉及HUB基因的调控网络的基因和途径浓缩分析表明，细胞外基质相互作用和有丝分裂信号通路是肿瘤分期和分级的关键决定因素。在五个独立的数据集中验证了基因表达模块与肿瘤分期或分级之间的关系。这些结果可能会发展成一个更客观的评分系统，以改善对SOC结果的预测。
Serous ovarian cancer (SOC) is the most lethal gynecological cancer. Clinical studies have revealed an association between tumor stage and grade and clinical prognosis. Identification of meaningful clusters of co-expressed genes or representative biomarkers related to stage or grade may help to reveal mechanisms of tumorigenesis and cancer development, and aid in predicting SOC patient prognosis. We therefore performed a weighted gene co-expression network analysis (WGCNA) and calculated module-trait correlations based on three public microarray datasets (GSE26193, GSE9891, and TCGA), which included 788 samples and 10402 genes. We detected four modules related to one or more clinical features significantly shared across all modeling datasets, and identified one stage-associated module and one grade-associated module. Our analysis showed that MMP2, COL3A1, COL1A2, FBN1, COL5A1, COL5A2, and AEBP1 are top hub genes related to stage, while CDK1, BUB1, BUB1B, BIRC5, AURKB, CENPA, and CDC20 are top hub genes related to grade. Gene and pathway enrichment analyses of the regulatory networks involving hub genes suggest that extracellular matrix interactions and mitotic signaling pathways are crucial determinants of tumor stage and grade. The relationships between gene expression modules and tumor stage or grade were validated in five independent datasets. These results could potentially be developed into a more objective scoring system to improve prediction of SOC outcomes.
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影响因子：
12.3
作者：
Fang H;Gough J
通讯作者：
Gough J
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
FOXM1上皮卵巢癌中FOXM1过表达的遗传决定因素以及对细胞周期进程的功能贡献。
影响因子：
--
作者：
Barger CJ;Zhang W;Hillman J;Stablewski AB;Higgins MJ;Vanderhyden BC;Odunsi K;Karpf AR
通讯作者：
Karpf AR
影响因子：
14.9
作者：
Jensen LJ;Kuhn M;Stark M;Chaffron S;Creevey C;Muller J;Doerks T;Julien P;Roth A;Simonovic M;Bork P;von Mering C
通讯作者：
von Mering C
影响因子：
4.3
作者：
Langfelder P;Luo R;Oldham MC;Horvath S
通讯作者：
Horvath S