Breast cancer classification and prognosis based on gene expression profiles from a population-based study
Breast cancer classification and prognosis based on gene expression profiles from a population-based study
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DOI：
10.1073/pnas.1732912100
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发表时间：
2003-09-02
影响因子：
11.1
通讯作者：
Liu, ET
中科院分区：
文献类型：
--
作者：
Sotiriou, C;Neo, SY;Liu, ET
在99例淋巴结阴性和淋巴结阳性乳腺癌患者中，从cDNA微阵列产生的综合基因表达模式与详细的临床病理特征和临床结果相关。基因表达模式与雌激素受体（ER）状态密切相关，与分级中度相关，但与绝经状态、淋巴结状态或肿瘤大小无关。分层聚类分析将肿瘤分为两个主要组的基础上，他们的ER状态，以及相关的基础和管腔特征。考克斯比例风险回归分析确定了16个与无复发生存率显著相关的基因，严格的显著性水平为0.001，以解释多重比较。在231个先前由其他人报道的基因中[van 't Veer，L. J.，等人（2002）Nature 415，530-536]与存活相关，93个探针元件与在本研究中使用的阵列上表示的7，650个探针元件的组重叠。基于93个探针元素的层次聚类分析将我们的人群分为两个不同的亚组，具有不同的无复发生存率（P < 0.03）。在本研究中，这93个探针元件显示与无复发生存率显著的单变量关联（P < 0.05），其数目为14个，代表11个独特基因。参与细胞周期、DNA复制和染色体稳定性的基因在各种预后不良组中持续升高。此外，谷胱甘肽S-转移酶M3在这两项研究中都是重要的生存标志物。当与其他阵列研究一起进行时，我们的结果突出了与基因表达谱一致的生物学和临床相关性。
Comprehensive gene expression patterns generated from cDNA microarrays were correlated with detailed clinico-pathological characteristics and clinical outcome in an unselected group of 99 node-negative and node-positive breast cancer patients. Gene expression patterns were found to be strongly associated with estrogen receptor (ER) status and moderately associated with grade, but not associated with menopausal status, nodal status, or tumor size. Hierarchical cluster analysis segregated the tumors into two main groups based on their ER status, which correlated well with basal and luminal characteristics. Cox proportional hazards regression analysis identified 16 genes that were significantly associated with relapse-free survival at a stringent significance level of 0.001 to account for multiple comparisons. Of 231 genes previously reported by others [van't Veer, L. J., et aL (2002) Nature 415, 530-536] as being associated with survival, 93 probe elements overlapped with the set of 7,650 probe elements represented on the arrays used in this study. Hierarchical cluster analysis based on the set of 93 probe elements segregated our population into two distinct subgroups with different relapse-free survival (P < 0.03). The number of these 93 probe elements showing significant univariate association with relapse-free survival (P < 0.05) in the present study was 14, representing 11 unique genes. Genes involved in cell cycle, DNA replication, and chromosomal stability were consistently elevated in the various poor prognostic groups. In addition, glutathione S-transferase M3 emerged as an important survival marker in both studies. When taken together with other array studies, our results highlight the consistent biological and clinical associations with gene expression profiles.