Cluster tree and expression image

Figure 3. Context, Stability, and Prognostic Value of Fibroblast CSR in Breast Cancer

(A) Expression patterns of CSR genes in a group of breast carcinomas and normal breast tissue previously described in Perou et al. (2000 ). Genes and samples were organized by hierarchical clustering. The serum response of each gene is indicated on the right bar (red shows induced; green shows repressed by serum). Note the biphasic pattern of expression that allows each tumor sample to be classified as °ƒactivated°± or °ƒquiescent°± based on the expression of the CSR genes. The previously identified tumor phenotype (color code) and p53 status (solid black box shows mutated; white box shows wild-type) are shown. Pairs of tumor samples from the same patient, obtained before and after surgery and chemotherapy, are connected by black lines under the dendrogram. Two primary tumor lymph-node metastasis pairs from the same patient are connected by purple lines.

(B) (not shown)

Link between the Gene Expression Signature of Fibroblast Serum Response and Cancer Progression

To investigate the stability and consistency of the serum response signature in individual tumors and to explore its clinical implications, we examined CSR gene expression in a group of locally advanced breast cancers with extensive clinical and molecular data ( Perou et al. 2000 ;Geisler et al. 2001 ;Sorlie et al. 2001 ). As shown in Figure 3 A, the expression profiles of the CSR genes were biphasic, allowing a natural separation of these tumors into two classes. Interestingly, in 18 out of 20 paired tumor samples obtained from the same patients before and after excisional biopsy and chemotherapy, the CSR expression phenotypes were consistent between the two samples. Thus, the wound-related expression program appears to be an intrinsic property of each tumor and not easily extinguished.

Chang, H. Y., Sneddon, J. B., Alizadeh, A. A., Sood, R., West, R. B., Montgomery, K., et al. (2004). Gene Expression Signature of Fibroblast Serum Response Predicts Human Cancer Progression: Similarities between Tumors and Wounds. PLoS Biology, 2(2).

Full paper (PDF)

Shows mixing of a columned image with an aligned cluster tree above it. (RPF)

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