Department of Oncology, Institute of Basic Medicine, The First Affiliated Hospital of Shandong First Medical University, No. 18877 Jingshi Road, Jinan 250062, China.
Department of Outpatient, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440, Ji Yan Road, Jinan 250117, China.
Biosci Rep. 2020 Nov 27;40(11). doi: 10.1042/BSR20202911.
Ovarian cancer causes high mortality rate worldwide, and despite numerous attempts, the outcome for patients with ovarian cancer are still not well improved. Microarray-based gene expressional analysis provides with valuable information for discriminating functional genes in ovarian cancer development and progression. However, due to the differences in experimental design, the results varied significantly across individual datasets.
In the present study, the data of gene expression in ovarian cancer were downloaded from Gene Expression Omnibus (GEO) and 16 studies were included. A meta-analysis based gene expression analysis was performed to identify differentially expressed genes (DEGs). The most differentially expressed genes in our meta-analysis were selected for gene expression and gene function validation.
A total of 972 DEGs with P-value < 0.001 were identified in ovarian cancer, including 541 up-regulated genes and 431 down-regulated genes, among which 92 additional DEGs were found as gained DEGs. Top five up- and down-regulated genes were selected for the validation of gene expression profiling. Among these genes, up-regulated CD24 molecule (CD24), SRY (sex determining region Y)-box transcription factor 17 (SOX17), WFDC2, epithelial cell adhesion molecule (EPCAM), innate immunity activator (INAVA), and down-regulated aldehyde oxidase 1 (AOX1) were revealed to be with consistent expressional patterns in clinical patient samples of ovarian cancer. Gene functional analysis demonstrated that up-regulated WFDC2 and INAVA promoted ovarian cancer cell migration, WFDC2 enhanced cell proliferation, while down-regulated AOX1 was functional in inducing cell apoptosis of ovarian cancer.
Our study shed light on the molecular mechanisms underlying the development of ovarian cancer, and facilitated the understanding of novel diagnostic and therapeutic targets in ovarian cancer.
卵巢癌在全球范围内导致高死亡率，尽管进行了众多尝试，患者的预后仍然没有得到很好的改善。基于微阵列的基因表达分析为鉴别卵巢癌发生和发展中的功能基因提供了有价值的信息。然而，由于实验设计的差异，个体数据集之间的结果差异很大。
本研究从基因表达综合数据库（GEO）下载了卵巢癌的基因表达数据，共纳入 16 项研究。采用基于荟萃分析的基因表达分析来识别差异表达基因（DEGs）。我们的荟萃分析中选择最差异表达的基因进行基因表达和基因功能验证。
在卵巢癌中鉴定出了共 972 个具有 P 值<0.001 的差异表达基因，包括 541 个上调基因和 431 个下调基因，其中 92 个额外的差异表达基因被认为是获得性差异表达基因。选择了前五个上调和下调基因进行基因表达谱验证。在这些基因中，上调的 CD24 分子（CD24）、性别决定区 Y-盒转录因子 17（SOX17）、WFDC2、上皮细胞黏附分子（EPCAM）、固有免疫激活物（INAVA）和下调的醛氧化酶 1（AOX1）在卵巢癌患者的临床样本中表现出一致的表达模式。基因功能分析表明，上调的 WFDC2 和 INAVA 促进卵巢癌细胞迁移，WFDC2 增强细胞增殖，而下调的 AOX1 则可诱导卵巢癌细胞凋亡。
本研究阐明了卵巢癌发生发展的分子机制，有助于理解卵巢癌新的诊断和治疗靶点。
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