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Comprehensive profiling of biological processes reveals two major prognostic subtypes in breast cancer.

Authors :
Chen F
Gao S
Wang F
Ma J
Zhang M
Lv M
Zhou Q
Fu Z
Lu C
Yin H
Source :
Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine [Tumour Biol] 2016 Mar; Vol. 37 (3), pp. 3365-70. Date of Electronic Publication: 2015 Oct 07.
Publication Year :
2016

Abstract

Heterogeneity is the major obstacle to breast cancer target therapy. Classification of breast cancer with significant biological process may reduce the influence of heterogeneity of intrinsic tumor. We used survival analysis to filter 95 gene sets and classify 638 breast cancer samples into two subtypes based on those gene sets associated with prognosis. Clinical outcome of two subtypes were evaluated with disease-free survival, distant metastasis-free survival, and overall survival levels in three databases and ER+, PR+ HER2+, and TNBC groups. We established a novel classification with 95 prognostic gene sets. In the training and validation cohorts, the subtype 1 was characterized by significant gene sets associated with regulation of metabolic process and enzyme activity and predicted obviously improved clinical outcome than subtype 2, which was enriched by tumor cell division, mitosis, and cell cycle-related gene sets (Pā€‰<ā€‰0.05). When evaluated prognostic impact of subtypes in ER+, PR+ HER2+, and TNBC groups, we found that patients in subtype 1 showed better prognosis in ER+ and PR+ groups (Pā€‰<ā€‰0.05) but had no difference from prognosis of subtype 2 in HER2+ and TNBC groups. These findings may have implications in understanding of breast cancer and filtering effective therapeutic strategies for targeted therapy.

Details

Language :
English
ISSN :
1423-0380
Volume :
37
Issue :
3
Database :
MEDLINE
Journal :
Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine
Publication Type :
Academic Journal
Accession number :
26446459
Full Text :
https://doi.org/10.1007/s13277-015-4173-9