Gene expression profiling of breast cell lines identifies potential new basal markers

被引:437
作者
Charafe-Jauffret, E
Ginestier, C
Monville, F
Finetti, P
Adélaïde, J
Cervera, N
Fekairi, S
Xerri, L
Jacquemier, J
Birnbaum, D
Bertucci, F
机构
[1] Inst J Paoli I Calmettes, Marseille Canc Inst, Mol Oncol Lab, UMR599,Inserm, F-13009 Marseille, France
[2] Inst J Paoli I Calmettes, Dept BioPathol, Marseille, France
[3] Univ Mediterranee, UFR Med, Marseille, France
[4] Inst Paoli Calmettes, INSERM, UMR599, Dept Med Oncol,Marseille Canc Inst, Marseille, France
关键词
basal; breast cancer; DNA microarray; epithelium; expression profiling; luminal; breast cell lines;
D O I
10.1038/sj.onc.1209254
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
A better molecular characterization of breast cell lines (BCL) may help discover new markers to apply to tumour samples. We performed gene and protein expression pro. ling of 31 BCL using whole-genome DNA microarrays and immunohistochemistry (IHC) on 'cell microarrays' (CMA), respectively. Global hierarchical clustering discriminated two groups of BCL: group I corresponded to luminal cell lines, group II to basal and mesenchymal cell lines. Correlations with centroids calculated from a published 'intrinsic 500-gene set' assigned 15 cell lines as luminal, eight as basal and four as mesenchymal. A set of 1.233 genes was differentially expressed between basal and luminal samples. Mesenchymal and basal subtypes were rather similar and discriminated by only 227 genes. The expression of 10 proteins (CAV1, CD44, EGFR, MET, ETS1, GATA3, luminal cytokeratin CK19, basal cytokeratin CK5/6, CD10, and ERM protein moesin) encoded by luminal vs basal discriminator genes confirmed the subtype classification and the validity of the identified markers. Our BCL basal/luminal signature correctly re-classified the published series of tumour samples that originally served to identify the molecular subtypes, suggesting that the identified markers should be useful for tumour classification and might represent promising targets for disease management.
引用
收藏
页码:2273 / 2284
页数:12
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