利用卵巢癌干细胞特异性基因表达谱进行针对性药物初步筛选

Specific gene expression profiling of stem cells in ovarian cancer for preliminary targeted drug screening

目的综合分析卵巢癌中各干细胞特异性基因表达谱，发现其共同的表达特征，以期筛选具有逆转肿瘤细胞干细胞特性的小分子化合物。方法从NCBIGEO数据库中获取卵巢癌细胞系、患者来源的卵巢癌干细胞与各非干性卵巢癌细胞的全基因组表达谱，进行整合比对分析，并以8例进展期卵巢癌细胞与正常卵巢上皮细胞的差异基因表达谱为校正，获得差异表达基因。利用GeneSifter软件解析卵巢癌细胞的干性特征并建立分子标签，使用连通图法筛选具有逆转此类分子标签的小分子化合物。结果进展期卵巢癌患者来源的卵巢癌细胞相比正常人卵巢上皮细胞、卵巢癌细胞系OVCAR．3来源的多细胞球相比OVCAR．3细胞、卵巢癌细胞系IGROV1来源的侧群细胞相比非侧群细胞、进展期卵巢癌患者腹水细胞来源的侧群细胞相比腹水总体细胞差异表达的基因数分别为6053、6495、1347、509个，均满足差异基因表达在1．5倍以上且￡检验P值〈0．05。其中NGFI．A结合蛋白1（NAB1）等为共同上调的关键基因，S蛋白1（PROS1）、雌激素介导的乳腺癌生长调节因子1（GREB1）、Kruppe1相似因子9（KLF9）和线粒体肿瘤抑制因子1（MTUS1）等为共同下调基因。筛选出SC．560、disu1firam、thapsigargin、escu1etin、cinchonine等18种小分子化合物具有逆转卵巢癌细胞干性的潜在药理特性。结论初步揭示了各卵巢癌细胞中共有的干性差异表达基因及其特异调控网络，为筛选卵巢癌干细胞靶向药物提供了依据。

Objective To comprehensively analyze the specific gene expression profile of stem cells in ovarian cancer and the common features, thus to identify the small molecules that may avert the stemness of ovarian cancer cells. Methods The genome wide expression profiles of ovarian cancer cell lines, ovarian cancer stem ceils （OVCSCs） from patients with ovarian cancer and non-stem cancer cells derived from NCBI GEO bank were collected and compared. This was followed by adjustment with the cancer ceils derived from 8 patients with progressive ovarian cancer and normal ovarian epithelial cells to capture the differential expression genes for subsequent interpretation of the stemness and establishment of molecular tags via GeneSifter software, and to screen small molecules that may suppress the expression of molecular tags of OVCSCs by using connectivity map. Results The number of genes with differential expression was 6053 for ovarian cancer ceils derived from progressive ovarian cancer compared with normal ovarian epithelial cells, 6495 for multiple cellular spheroid cells derived from the OVCAR-3 cells line compared with OVCAR-3 cells, 1347 for the side population cells compared with non-side population cells of ovarian cancercell line IGROV1, and 509 for the side population cells compared with the total cell populations derived from the ascites in patients with progressive ovarian cancer （all differences 〉 1.5 fold, t test P value〈0.05 ）. Among above genes, the NGFI-A binding protein 1 （NAB1） was the key up-regulated gene, whilst the protein S alpha （PROSI）, growth regulation by estrogen in breast cancer 1 （GREB1）, Kruppel-like factor 9 （KLF9） and mitochondrial tumor suppressor 1 （MTUS1） genes were down-regulated. A total of 18 small molecules with potential pharmacological properties of averting the sternness of OVCSCs, i.e. SC-560, disulfiram, thapsigargin, esculetin and cinchonine, were identified. Conclusion The primary elucidation of sternness genes with differential expression in ovarian cancer and their specific regulation networks may offer the rationale for identifying targeted drugs for OVCSCs.