Singh Dinesh, Febbo Phillip G, Ross Kenneth, Jackson Donald G, Manola Judith, Ladd Christine, Tamayo Pablo, Renshaw Andrew A, D'Amico Anthony V, Richie Jerome P, Lander Eric S, Loda Massimo, Kantoff Philip W, Golub Todd R, Sellers William R
Department of Adult Oncology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Cancer Cell. 2002 Mar;1(2):203-9. doi: 10.1016/s1535-6108(02)00030-2.
Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly correlated with the state of tumor differentiation as measured by Gleason score. Moreover, a model using gene expression data alone accurately predicted patient outcome following prostatectomy. These results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis.
前列腺肿瘤在组织学和临床上都是癌症中异质性最强的肿瘤之一。微阵列表达分析用于确定整体生物学差异是否是前列腺癌常见病理特征的基础,并识别可能预测该疾病临床行为的基因。虽然未发现年龄、血清前列腺特异性抗原(PSA)以及局部侵犯指标与表达存在相关性,但却鉴定出了一组与通过Gleason评分衡量的肿瘤分化状态密切相关的基因。此外,仅使用基因表达数据的模型就能准确预测前列腺切除术后的患者预后。这些结果支持了这样一种观点,即前列腺癌的临床行为与诊断时可检测到的潜在基因表达差异相关。