Breast cancer classification and prognosis based on gene expression profiles from a population-based study - PubMed (original) (raw)

Breast cancer classification and prognosis based on gene expression profiles from a population-based study

Christos Sotiriou et al. Proc Natl Acad Sci U S A. 2003.

Abstract

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.

PubMed Disclaimer

Figures

Fig. 1.

Fig. 1.

Dendrogram of 99 breast cancer specimens analyzed by hierarchical clustering analysis using 706 probe elements selected for the high variability across all tumors (see Materials and Methods). The tumors were separated into two main groups mainly associated with ER status as determined by the ligand-binding (LB) assay and confirmed by immunohistochemistry (IHC). The dendrogram further branched into smaller subgroups within the ER+ and ER-classes based on their basal and luminal characteristics: Her-2/neu subgroup, dark blue; basal-like 1 subgroup, pink; basal-like 2 subgroup, yellow; luminal-like 1 subgroup, light blue; luminal-like 2 subgroup, red; and luminal-like 3 subgroup, green. Black bars represent ER+ tumors assessed by IHC (a), ER+ tumors assessed by LB assay (b), grade 3 (c), and node-positive tumors (d).

Fig. 2.

Fig. 2.

RFS and BCS analysis of the 99 breast cancer patients based on the gene expression cluster analysis classification. RFS (A) and BCS (B) of the predominantly ER- and predominantly ER+ clusters (the Her-2/neu and basal-like 1 and 2 subgroups were considered in one group and the luminal-like subgroups 1, 2, and 3 were considered in the other group). RFS (C) and BCS (D) of the Her-2/neu and basal-like 1 and 2 subgroups. RFS (E) and BCS (F) of the luminal-like 1, 2, and 3 subgroups.

Similar articles

Cited by

References

    1. Liu, E. T. & Sotiriou, C. (2002) Breast Cancer Res. 4, 141-144. - PMC - PubMed
    1. Sorlie, T., Perou, C. M., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M. B., van de Rijn, M., Jeffrey, S. S., et al. (2001) Proc. Natl. Acad. Sci. USA 98, 10869-10874. - PMC - PubMed
    1. van't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) Nature 415, 530-536. - PubMed
    1. Gruvberger, S., Ringner, M., Chen, Y., Panavally, S., Saal, L. H., Borg, A., Ferno, M., Peterson, C. & Meltzer, P. S. (2001) Cancer Res. 61, 5979-5984. - PubMed
    1. West, M., Blanchette, C., Dressman, H., Huang, E., Ishida, S., Spang, R., Zuzan, H., Olson, J. A. J., Marks, J. R. & Nevins, J. R. (2001) Proc. Natl. Acad. Sci. USA 98, 11462-11467. - PMC - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources