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Series GSE158309 Query DataSets for GSE158309
Status Public on Sep 22, 2020
Title Prognostic significance of interferon-γ and its signaling pathway in early breast cancer depends on the molecular subtypes
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Interferons are crucial for adaptive immunity and play an important role in the immune landscape of breast cancer. Using microarray-based gene expression analysis, we examined the subtype specific prognostic significance of interferon-γ (IFN-γ) as a single gene as well as an IFN-γ signature covering the signaling pathway in 461 breast cancer patients. Prognostic significance of IFN-γ as well as the IFN-γ signature for metastasis-free survival (MFS) were examined using Kaplan Meier as well as univariate and multivariate Cox regression analyses in the whole cohort and in different molecular subtypes. Kaplan Meier curves and univariate Cox regression analyses showed that the prognostic significance of IFN-γ as a single gene was limited to basal-like breast cancer (P=0.033). In contrast, the IFN-γ associated gene signature was a significant prognostic factor in the whole cohort (HR 1.554; 95%CI 1.1099-2.199; P=0.013) as well as in the luminal B (P=0.007) and HER2-positive (P=0.033) molecular subtype with borderline significance in basal-like breast cancer(P=0.050). In multivariate analysis, the IFN-γ signature retained its independent prognostic significance (HR 2.287; 95% CI: 1.410-3.633;P<0.001) in the entire cohort. These results underline the subtype-dependent prognostic influence of the immune system in early breast cancer.
 
Overall design 461 patients with early breast cancer, who received surgery between 1986 to 2000 at the Department of Gynecology and Obstetrics of the University Medical Center Mainz, entered the study. We included all consecutive patients with an adequate amount of fresh-frozen tumor tissue available for successful Affymetrix microarray analysis.

***CEL files not available for 109 patients
 
Contributor(s) Schmidt M, Gehrmann M
Citation(s) 33003293, 36289918
Submission date Sep 21, 2020
Last update date Nov 02, 2022
Contact name Marcus Schmidt
E-mail(s) Marcus.Schmidt@unimedizin-mainz.de
Organization name Universitätsmedizin Mainz
Department Universitäres Centrum für Tumorerkrankungen
Street address Langenbeckstr. 1
City Mainz
ZIP/Postal code 55131
Country Germany
 
Platforms (1)
GPL96 [HG-U133A] Affymetrix Human Genome U133A Array
Samples (461)
GSM4796814 BC2248: primary breast cancer patient 1
GSM4796815 BC2254: primary breast cancer patient 2
GSM4796816 BC2256: primary breast cancer patient 3
Relations
BioProject PRJNA664784

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE158309_RAW.tar 1.1 Gb (http)(custom) TAR (of CEL)
Processed data included within Sample table

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