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Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis

Srikanth Nagalla1, Jeff W Chou2, Mark C Willingham3, Jimmy Ruiz1, James P Vaughn4, Purnima Dubey3, Timothy L Lash56, Stephen J Hamilton-Dutoit7, Jonas Bergh89, Christos Sotiriou10, Michael A Black11 and Lance D Miller4*

Author Affiliations

1 Section of Hematology & Oncology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA

2 Department of Biostatistical Sciences, Wake Forest Public Health Sciences, Medical Center Boulevard, Winston-Salem, NC, 27157, USA

3 Department of Pathology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA

4 Department of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA

5 Department of Epidemiology & Prevention, Wake Forest University Health Sciences, Medical Center Boulevard, Winston-Salem, NC, 27157, USA

6 Department of Clinical Epidemiology, Aarhus University Hospital, Noerrebrogade 44, DK-8000 Aarhus C, Denmark

7 Institute of Pathology, Aarhus University Hospital, Noerrebrogade 44, DK-8000 Aarhus C, Denmark

8 Department of Oncology-Pathology, Cancer Center Karolinska, Radiumhemmet, Karolinska Institutet and University Hospital, S-171 76, Stockholm, Sweden

9 University of Manchester, Paterson Institute for Cancer Research, Wilmslow Road, Manchester, M20 4BX, UK

10 Université Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000 Brussels, Belgium

11 Department of Biochemistry, Otago School of Medical Sciences, University of Otago, 710 Cumberland Street, Dunedin, 9016, New Zealand

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Genome Biology 2013, 14:R34 doi:10.1186/gb-2013-14-4-r34

Published: 29 April 2013

Abstract

Background

Gene expression signatures indicative of tumor proliferative capacity and tumor-immune cell interactions have emerged as principal biology-driven predictors of breast cancer outcomes. How these signatures relate to one another in biological and prognostic contexts remains to be clarified.

Results

To investigate the relationship between proliferation and immune gene signatures, we analyzed an integrated dataset of 1,954 clinically annotated breast tumor expression profiles randomized into training and test sets to allow two-way discovery and validation of gene-survival associations. Hierarchical clustering revealed a large cluster of distant metastasis-free survival-associated genes with known immunological functions that further partitioned into three distinct immune metagenes likely reflecting B cells and/or plasma cells; T cells and natural killer cells; and monocytes and/or dendritic cells. A proliferation metagene allowed stratification of cases into proliferation tertiles. The prognostic strength of these metagenes was largely restricted to tumors within the highest proliferation tertile, though intrinsic subtype-specific differences were observed in the intermediate and low proliferation tertiles. In highly proliferative tumors, high tertile immune metagene expression equated with markedly reduced risk of metastasis whereas tumors with low tertile expression of any one of the three immune metagenes were associated with poor outcome despite higher expression of the other two metagenes.

Conclusions

These findings suggest that a productive interplay among multiple immune cell types at the tumor site promotes long-term anti-metastatic immunity in a proliferation-dependent manner. The emergence of a subset of effective immune responders among highly proliferative tumors has novel prognostic ramifications.

Keywords:
Breast cancer; gene signatures; hierarchical clustering; immune metagene; intrinsic subtypes; metagene tertiles; multivariable analysis; prognosis; proliferation metagene; survival analysis