Senologie - Zeitschrift für Mammadiagnostik und -therapie 2017; 14(02): A1-A53
DOI: 10.1055/s-0037-1602475
Abstracts
Georg Thieme Verlag KG Stuttgart · New York

Subtype-specific prognostic impact of different gene-expression signatures in node-negative breast cancer

AS Heimes
1   Universitätsmedizin Mainz, Frauenklinik, Mainz, Deutschland
,
K Madjar
2   TU Dortmund, Fakultät Statistik, Dortmund, Deutschland
,
B Hellwig
2   TU Dortmund, Fakultät Statistik, Dortmund, Deutschland
,
MJ Battista
1   Universitätsmedizin Mainz, Frauenklinik, Mainz, Deutschland
,
K Almstedt
1   Universitätsmedizin Mainz, Frauenklinik, Mainz, Deutschland
,
S Gebhard
1   Universitätsmedizin Mainz, Frauenklinik, Mainz, Deutschland
,
W Brenner
1   Universitätsmedizin Mainz, Frauenklinik, Mainz, Deutschland
,
J Rahnenführer
2   TU Dortmund, Fakultät Statistik, Dortmund, Deutschland
,
A Hasenburg
1   Universitätsmedizin Mainz, Frauenklinik, Mainz, Deutschland
,
JG Hengstler
3   TU Dortmund, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Deutschland
,
M Schmidt
1   Universitätsmedizin Mainz, Frauenklinik, Mainz, Deutschland
› Author Affiliations
Further Information

Publication History

Publication Date:
09 May 2017 (online)

 

Background:

The role of different subtypes of immune cells is still a matter of debate.

Methods:

We compared the prognostic relevance for MFS of a B-cell signature (BS), a T-cell signature (TS) and an immune check-point signature (CPS) in node-negative breast cancer using mRNA expression. Microarray based gene-expression data were analyzed in six previously published cohorts of node-negative breast cancer patients not treated with adjuvant therapy (n = 824). The prognostic relevance of the individual immune markers was assessed using univariate analysis. The amount of independent prognostic information provided by each immune signature was then compared using a likelihood ratio statistic in the whole cohort as well as in different molecular subtypes.

Results:

Univariate Cox regression in the whole cohort revealed prognostic significance of CD4 (HR 0.66, CI 0.50 – 0.87, p = 0.004), CXCL13 (HR 0.86, CI 0.81 – 0.92, p < 0.001), CD20 (HR 0.76, CI 0.64 – 0.89, p = 0.001), IgκC (HR 0.81, CI 0.75 – 0.88, p < 0.001) and CTLA-4 (HR 0.67, CI 0.46 – 0.97, p = 0.032). Multivariate analyses of the immune signatures showed that both TS (p < 0.001) and BS (p < 0.001) showed a significant prognostic information in the whole cohort. After accounting for clinical-pathological variables TS (p < 0.001), BS p < 0.05) and CPS (p < 0.05) had an independent effect for MFS. In subgroup analyses, the prognostic effect of immune cells was most pronounced in HER2+ BC: BS as well as TS showed a strong association with MFS when included first in the model (p < 0.001).

Conclusion:

Immune signatures provide additional prognostic information over clinical-pathological variables in node negative breast cancer.