Poor-prognosis estrogen receptor-positive breast cancer identified by histopathologic subclassification

Webster, Lucy R., Lee, Shu-Fen, Ringland, Clare, Morey, Adrienne L., Hanby, Andrew M., Morgan, Graeme, Byth, Karen, Mote, Patricia A., Provan, Pamela J., Ellis, Ian O., Green, Andrew R., Lamoury, Gillian, Ravdin, Peter, Clarke, Christine L., Ward, Robyn L., Balleine, Rosemary L. and Hawkins, Nicholas J. (2008) Poor-prognosis estrogen receptor-positive breast cancer identified by histopathologic subclassification. Clinical Cancer Research, 14 20: 6625-6633. doi:10.1158/1078-0432.CCR-08-0701


Author Webster, Lucy R.
Lee, Shu-Fen
Ringland, Clare
Morey, Adrienne L.
Hanby, Andrew M.
Morgan, Graeme
Byth, Karen
Mote, Patricia A.
Provan, Pamela J.
Ellis, Ian O.
Green, Andrew R.
Lamoury, Gillian
Ravdin, Peter
Clarke, Christine L.
Ward, Robyn L.
Balleine, Rosemary L.
Hawkins, Nicholas J.
Title Poor-prognosis estrogen receptor-positive breast cancer identified by histopathologic subclassification
Journal name Clinical Cancer Research   Check publisher's open access policy
ISSN 1078-0432
1557-3265
Publication date 2008-10-15
Sub-type Article (original research)
DOI 10.1158/1078-0432.CCR-08-0701
Open Access Status Not yet assessed
Volume 14
Issue 20
Start page 6625
End page 6633
Total pages 9
Place of publication Philadelphia, PA, United States
Publisher American Association for Cancer Research
Language eng
Formatted 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.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Medicine Publications
 
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