Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis.
Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis.
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DOI：
10.1371/journal.pone.0149183
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Leyland-Jones B
中科院分区：
文献类型：
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作者：
Willis S;Villalobos VM;Gevaert O;Abramovitz M;Williams C;Sikic BI;Leyland-Jones B
发现卵巢浆液性癌新的预后标志物。使用考克斯回归作为总生存期的连续变量，对TCGA和HAS卵巢队列中的所有单基因探针进行荟萃分析，以鉴定可能的生物标志物。使用Stouffer方法通过p值对基因进行排序，并使用Benjamini-Hochberg方法选择统计学显著性，其中错误发现率（FDR）<0.05。具有高mRNA表达的12个基因是FDR <.05的不良结果的预后（AXL、APC、RAB 11FIP5、C19orf2、CYBRD1、PINK1、LRRN3、AQP1、DES、XRCC4、BCHE和ASAP3）。具有低mRNA表达的20个基因是具有FDR <.05的不良结果的预后（LRIG1、SLC33A1、NUCB 2、P0LD 3、ESR2、GOLPH 3、XBP1、PAXIP1、CYB561、P0LA 2、CDH1、GMNN、SLC37A4、FAM174B、AGR2、SDR39U1、MAGT 1、GJB 1、SDF 2L1和C9orf82）。一项对所有单基因的荟萃分析确定了32个候选生物标志物在卵巢浆液性癌中的可能作用。这些基因可以为卵巢癌的驱动因子或调节因子提供深入了解，并应在未来的研究中进行评估。具有高表达指示不良结果的基因是已知拮抗剂或抑制剂的可能的治疗靶点。此外，这些基因可以组合成一个预后多基因签名，并在未来的卵巢队列中进行测试。
To discover novel prognostic biomarkers in ovarian serous carcinomas. A meta-analysis of all single genes probes in the TCGA and HAS ovarian cohorts was performed to identify possible biomarkers using Cox regression as a continuous variable for overall survival. Genes were ranked by p-value using Stouffer’s method and selected for statistical significance with a false discovery rate (FDR) <.05 using the Benjamini-Hochberg method. Twelve genes with high mRNA expression were prognostic of poor outcome with an FDR <.05 (AXL, APC, RAB11FIP5, C19orf2, CYBRD1, PINK1, LRRN3, AQP1, DES, XRCC4, BCHE, and ASAP3). Twenty genes with low mRNA expression were prognostic of poor outcome with an FDR <.05 (LRIG1, SLC33A1, NUCB2, POLD3, ESR2, GOLPH3, XBP1, PAXIP1, CYB561, POLA2, CDH1, GMNN, SLC37A4, FAM174B, AGR2, SDR39U1, MAGT1, GJB1, SDF2L1, and C9orf82). A meta-analysis of all single genes identified thirty-two candidate biomarkers for their possible role in ovarian serous carcinoma. These genes can provide insight into the drivers or regulators of ovarian cancer and should be evaluated in future studies. Genes with high expression indicating poor outcome are possible therapeutic targets with known antagonists or inhibitors. Additionally, the genes could be combined into a prognostic multi-gene signature and tested in future ovarian cohorts.