Poor-prognosis Estrogen Receptor-positive breast cancer identified by histopathologic subclassification

Lucy Webster, Shu-Fen Lee, Clare Ringland, Adrienne L. Morey, Andrew M. Hanby, Graeme Morgan, Karen Byth, Patricia A. Mote, Pamela J. Provan, Ian O. Ellis, R. Green Andrew, Gillian Lamoury, Peter Ravdin, Christine L. Clarke, Robyn L. Ward, Rosemary L. Balleine, Nicholas J. Hawkins

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

PURPOSE: Identification of biologically and clinically distinct breast cancer subtypes could improve prognostic assessment of primary tumors. The characteristics of "molecular" breast cancer subtypes suggest that routinely assessed histopathologic features in combination with limited biomarkers may provide an informative classification for routine use. EXPERIMENTAL DESIGN: Hierarchical cluster analysis based on components of histopathologic grade (tubule formation, nuclear pleomorphism, and mitotic score), expression of ER, cytokeratin 5/6, and HER2 amplification identified four breast cancer subgroups in a cohort of 270 cases. Cluster subgroup membership was compared with observed and Adjuvant! Online predicted 10-year survival. Survival characteristics were confirmed in an independent cohort of 300 cases assigned to cluster subgroups using a decision tree model. RESULTS: Four distinct breast cancer cluster subgroups (A-D) were identified that were analogous to molecular tumor types and showed a significant association with survival in both the original and validation cohorts (P < 0.001). There was a striking difference between survival for patients in cluster subgroups A and B with ER(+) breast cancer (P < 0.001). Outcome for all tumor types was well estimated by Adjuvant! Online, with the exception of cluster B ER(+) cancers where Adjuvant! Online was too optimistic. CONCLUSIONS: Breast cancer subclassification based on readily accessible pathologic features could improve prognostic assessment of ER(+) breast cancer.
Original languageEnglish
Pages (from-to)6625-6633
Number of pages9
JournalClinical Cancer Research
Volume14
Issue number20
DOIs
Publication statusPublished - 2008

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