Mary Babb Randolph Cancer Center/Community Medicine, West Virginia University, Morgantown, WV 26506-9300, USA.
Oncol Rep. 2010 Aug;24(2):489-94. doi: 10.3892/or_00000883.
Epidemiological studies indicate an increased risk of subsequent primary ovarian cancer from women with breast cancer. We have recently identified a 28-gene expression signature that predicts, with high accuracy, the clinical course in a large population of breast cancer patients. This prognostic gene signature also accurately predicts response to chemotherapy commonly used for treating breast cancer, including CMF, Tamoxifen, Paclitaxel, Docetaxel and Doxorubicin (Adriamycin), in a panel of 60 cancer cell lines of nine different tissue origins. This prompted us to investigate whether this prognostic gene signature could also predict clinical outcome in other cancer types of epithelial origins, including ovarian cancer (n=124), colon tumors (n=74) and lung adenocarcinomas (n=442). The results show that the gene expression signature contributes significantly more accurate (P<0.05; compared with random prediction) prognostic information in multiple cancer types independent of established clinical parameters. Furthermore, the functional pathway analysis with curated database delineated a biological network with tight connections between the signature genes and numerous well established cancer hallmarks, indicating important roles of this prognostic gene signature in tumor genesis and progression.
流行病学研究表明,乳腺癌女性发生原发性卵巢癌的风险增加。我们最近确定了一个 28 基因表达特征,可以高精度地预测大量乳腺癌患者的临床病程。该预后基因特征还可以准确预测包括 CMF、他莫昔芬、紫杉醇、多西紫杉醇和阿霉素(多柔比星)在内的常用化疗药物对 60 种不同组织来源的癌症细胞系的反应,这促使我们研究该预后基因特征是否也可以预测其他上皮来源的癌症类型的临床结果,包括卵巢癌(n=124)、结肠癌(n=74)和肺腺癌(n=442)。结果表明,该基因表达特征在多个癌症类型中独立于既定临床参数提供了更准确的预后信息(P<0.05;与随机预测相比)。此外,通过精心整理的数据库进行的功能途径分析描绘了一个具有签名基因和许多既定癌症标志之间紧密联系的生物学网络,表明该预后基因特征在肿瘤发生和进展中具有重要作用。