Transcriptomic immunologic signature associated with favorable clinical outcome in basal-like breast tumors

Most patients with early stage triple negative breast cancer (TNBC) receive adjuvant chemotherapy. Activation of the immune system is associated with tumor response and may help identify TNBC with favorable outcome. Gene expression data were obtained from the GEO Dataset GDS2250/GSE3744. Affymetrix...

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Bibliographic Details
Published in:PloS one 2017-05, Vol.12 (5), p.e0175128-e0175128
Main Authors: Martínez-Canales, Sandra, Cifuentes, Francisco, López De Rodas Gregorio, Miguel, Serrano-Oviedo, Leticia, Galán-Moya, Eva María, Amir, Eitan, Pandiella, Atanasio, Győrffy, Balázs, Ocaña, Alberto
Format: Article
Language:English
Subjects:
Abnormalities
Adhesion
Adjuvant chemotherapy
Alterations
Amplification
Antibodies
Antigens
Apoptosis
Bioinformatics
Biology and Life Sciences
Breast cancer
Breast Neoplasms - genetics
Breast Neoplasms - immunology
Cancer
Cancer therapies
Care and treatment
CD8 antigen
Cell activation
Cell interactions
Cell surface
Chemotherapy
Circuits
Clinical outcomes
Clinical trials
Computer architecture
Computer programs
Cytotoxicity
Datasets
Developmental stages
Differentiation
Enrichment
Female
Gene expression
Genomics
Health risks
Hospitals
Humans
Immune response
Immune system
Immunoglobulins
Immunotherapy
Inhibition
Jaw
Kinases
Lymphocytes
Medical prognosis
Medical research
Medicine and Health Sciences
Membrane proteins
Metastases
Mutation
Proteins
Quality
Regulators
Risk
Signal transduction
Survival
Survival analysis
Toxicity
Transcriptome
Treatment Outcome
Tumors
Up-Regulation
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Summary:Most patients with early stage triple negative breast cancer (TNBC) receive adjuvant chemotherapy. Activation of the immune system is associated with tumor response and may help identify TNBC with favorable outcome. Gene expression data were obtained from the GEO Dataset GDS2250/GSE3744. Affymetrix CEL files were downloaded and analyzed with Affymetrix Transcriptome Analysis Console 3.0. Functional genomics was implemented with David Bioinformatics Resources 6.8. Data contained at Oncomine were used to identify genes upregulated in basal-like cancer compared to normal breast tissue. Data contained at cBioportal were used to assess for molecular alterations. The KMPlotter online tool, METABRIC and GSE25066 datasets were used to associate gene signatures with clinical outcome. 1564 upregulated genes were identified as differentially expressed between normal and basal-like tumors. Of these, 16 genes associated with immune function were linked with clinical outcome. HLA-C, HLA-F, HLA-G and TIGIT were associated with both improved relapse-free survival (RFS) and overall survival (OS). The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0175128