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基于基因表达谱的乳腺癌预后分子分类

[Prognostic molecular classification of breast cancers based on gene expression profiling].

作者信息

Feng Yu-Mei, Li Xiao-Qing, Sun Boo-Cun, Gao Xu-Chen, Gu Lin, Niu Yun, Hao Xi-Shan

机构信息

Department of Biochemistry & Molecular Biology, Tianjin Cancer Hospital & Institute, Breast Cancer Prevention and Treatment Key Laboratory of Ministry of Education, Tianjin Medical University, Tianjing 21 300060, China.

出版信息

Zhonghua Zhong Liu Za Zhi. 2006 Dec;28(12):900-6.

Abstract

OBJECTIVE

To screen a set of gene markers related to metastasis and prognosis of breast cancer by comparison of gene expression profiles of primary breast cancers with distant metastasis to the cases without distant metastasis within 3 years follow-up, and to explore the clinical significance of those gene expression in prognostic molecular classification of breast cancer patients.

METHODS

5 cases with distant metastasis and 5 cases without distant metastasis within 3 years follow-up were used as training cases to compare their gene expression profiles by Oligo microarray hybridization containing 21 329 human functional genes. K-mean supervised cluster was done for 10 training cases and additional 20 testing cases based on the set of differential genes. "Leave-one-out" was used to eliminate useless genes to obtain optimal gene set that was used for prognostic molecular classification of breast cancer patients.

RESULTS

The different genes screened out from gene expression profiling of primary breast cancers with and without distant metastasis could classify breast cancer patients into two sub-groups. All patients with distant metastasis were included in the "poor prognosis group" (7/10), whereas there were no case showing distant metastasis in the "good prognosis group" (0/20), with a statistically significant difference by exact probability test (P =0. 03). In the set of 104 optimal genes, all 5 genes involved in cell adhesion and migration were up-regulated in cases with distant metastasis, all 2 genes related to immune response of host were down-regulated, 11 genes related to cell growth and metabolism were up-regulated and 14 down-regulated, and 15 genes related to cell signal transduction were significantly changed.

CONCLUSION

A set of genes involved in cell adhesion and migration, cell growth and metabolism, immune response mechanism, cell signal transduction were screened out by comparing gene expression profiles of primary breast cancers with and without distant metastasis within 3 years follow-up, showing highlight in prognostic molecular classification of breast cancer patients and hopeful would benefit to choose patient-tailored therapy strategies.

摘要

目的

通过比较原发性乳腺癌伴远处转移与3年内无远处转移病例的基因表达谱,筛选出一组与乳腺癌转移和预后相关的基因标志物,并探讨这些基因表达在乳腺癌患者预后分子分类中的临床意义。

方法

选取5例有远处转移和5例3年内无远处转移的病例作为训练病例,采用含21329个人类功能基因的寡核苷酸微阵列杂交技术比较其基因表达谱。基于差异基因集对10例训练病例和另外20例测试病例进行K均值监督聚类。采用“留一法”剔除无用基因,获得用于乳腺癌患者预后分子分类的最佳基因集。

结果

从原发性乳腺癌伴和不伴远处转移的基因表达谱中筛选出的差异基因可将乳腺癌患者分为两个亚组。所有有远处转移的患者均归入“预后不良组”(7/10),而“预后良好组”中无远处转移病例(0/20),经确切概率检验差异有统计学意义(P =0.03)。在104个最佳基因集中,5个与细胞黏附和迁移相关的基因在有远处转移的病例中均上调,2个与宿主免疫反应相关的基因均下调,11个与细胞生长和代谢相关基因上调,14个下调,15个与细胞信号转导相关基因有显著变化。

结论

通过比较原发性乳腺癌伴和不伴3年内远处转移的基因表达谱,筛选出一组涉及细胞黏附和迁移、细胞生长和代谢、免疫反应机制、细胞信号转导的基因,在乳腺癌患者预后分子分类中显示出优势,有望有助于选择个体化治疗策略。

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