BACKGROUND: Immune infiltration of breast tumours is associated with clinical 
outcome. However, past work has not accounted for the diversity of functionally 
distinct cell types that make up the immune response. The aim of this study was 
to determine whether differences in the cellular composition of the immune 
infiltrate in breast tumours influence survival and treatment response, and 
whether these effects differ by molecular subtype.
METHODS AND FINDINGS: We applied an established computational approach 
(CIBERSORT) to bulk gene expression profiles of almost 11,000 tumours to infer 
the proportions of 22 subsets of immune cells. We investigated associations 
between each cell type and survival and response to chemotherapy, modelling 
cellular proportions as quartiles. We found that tumours with little or no 
immune infiltration were associated with different survival patterns according 
to oestrogen receptor (ER) status. In ER-negative disease, tumours lacking 
immune infiltration were associated with the poorest prognosis, whereas in 
ER-positive disease, they were associated with intermediate prognosis. Of the 
cell subsets investigated, T regulatory cells and M0 and M2 macrophages emerged 
as the most strongly associated with poor outcome, regardless of ER status. 
Among ER-negative tumours, CD8+ T cells (hazard ratio [HR] = 0.89, 95% CI 
0.80-0.98; p = 0.02) and activated memory T cells (HR 0.88, 95% CI 0.80-0.97; p 
= 0.01) were associated with favourable outcome. T follicular helper cells (odds 
ratio [OR] = 1.34, 95% CI 1.14-1.57; p < 0.001) and memory B cells (OR = 1.18, 
95% CI 1.0-1.39; p = 0.04) were associated with pathological complete response 
to neoadjuvant chemotherapy in ER-negative disease, suggesting a role for 
humoral immunity in mediating response to cytotoxic therapy. Unsupervised 
clustering analysis using immune cell proportions revealed eight subgroups of 
tumours, largely defined by the balance between M0, M1, and M2 macrophages, with 
distinct survival patterns by ER status and associations with patient age at 
diagnosis. The main limitations of this study are the use of diverse platforms 
for measuring gene expression, including some not previously used with 
CIBERSORT, and the combined analysis of different forms of follow-up across 
studies.
CONCLUSIONS: Large differences in the cellular composition of the immune 
infiltrate in breast tumours appear to exist, and these differences are likely 
to be important determinants of both prognosis and response to treatment. In 
particular, macrophages emerge as a possible target for novel therapies. 
Detailed analysis of the cellular immune response in tumours has the potential 
to enhance clinical prediction and to identify candidates for immunotherapy.