卵巢癌中的单基因预后生物标志物：一项荟萃分析。
Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis.
作者信息
Willis Scooter, Villalobos Victor M, Gevaert Olivier, Abramovitz Mark, Williams Casey, Sikic Branimir I, Leyland-Jones Brian
机构信息
Dept. of Molecular and Experimental Medicine, Avera Cancer Institute, Sioux Falls, SD, United States of America.
Division of Medical Oncology, UC Denver, Denver, CO, United States of America.
出版信息
PLoS One. 2016 Feb 17;11(2):e0149183. doi: 10.1371/journal.pone.0149183. eCollection 2016.
PURPOSE
To discover novel prognostic biomarkers in ovarian serous carcinomas.
METHODS
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.
RESULTS
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).
CONCLUSION
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.
目的
在卵巢浆液性癌中发现新的预后生物标志物。
方法
对TCGA和HAS卵巢队列中的所有单基因探针进行荟萃分析，以确定可能的生物标志物，使用Cox回归作为总生存的连续变量。采用Stouffer法按p值对基因进行排序，并使用Benjamini-Hochberg法选择错误发现率（FDR）<.05的具有统计学意义的基因。
结果
12个mRNA高表达的基因对预后不良具有预后价值，FDR<.05（AXL、APC、RAB11FIP5、C19orf2、CYBRD1、PINK1、LRRN3、AQP1、DES、XRCC4、BCHE和ASAP3）。20个mRNA低表达的基因对预后不良具有预后价值，FDR<.05（LRIG1、SLC33A1、NUCB2、POLD3、ESR2、GOLPH3、XBP1、PAXIP1、CYB561、POLA2、CDH1、GMNN、SLC37A4、FAM174B、AGR2、SDR39U1、MAGT1GJB1、SDF2L1和C9orf82）。
结论
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素或调节因子提供见解，应在未来的研究中进行评估。高表达预示预后不良的基因可能是已知拮抗剂或抑制剂的治疗靶点。此外，这些基因可以组合成一个预后多基因特征，并在未来的卵巢队列中进行测试。
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