Abstract
In breast cancer (BC), the transcription factor GATA3 is linked to estrogen receptor (ER) alpha biology, and its loss is associated with aggressive tumor features. Little is reported about potential roles and implications of GATA3 independent of ER, and possible relationships to the BC tumor microenvironment (TME) have not been much explored. Thus, the discovery of novel biomarkers potentially linked to ER and GATA3 functions and predicting aspects of the TME could significantly improve precision in the management of patient subgroups. We examined GATA3 protein and mRNA expression in a large in-house population-based BC series (n = 837), and in the METABRIC datasets (METABRIC Discovery, n = 997 and METABRIC Validation, n = 995). Associations with primary BC phenotypes, transcriptional programs, TME features, clinical outcomes, and potentially independent roles of GATA3 are reported. We find that low GATA3 expression associates with aggressive features like increased tumor diameter, higher histological grade, triple negative BC, and a basal-like (CK5/6 positive) phenotype. Low GATA3 mRNA expression associated with downregulation of ER-related genes, upregulation of transcriptional signatures reflecting hypoxia, and enrichment of gene sets reflecting tumor cell proliferation, epithelial-mesenchymal transition, and stemness. Low GATA3 protein and mRNA expression both associated with overall reduced BC-specific survival. Notably, low GATA3 expression strongly associated with upregulation of immune checkpoint markers, T-cell activation, and metabolic alterations not previously described in BC. Gene expression patterns underlying GATA3-low tumors, independent of ER status, reflected activation of immunological and metabolic processes. This study suggests that GATA3 might influence the TME independent of ER status. Our results point to metabolic and immunophenotypic alterations in GATA3-low BCs, in particular with T-cell activation and increased expression of immune checkpoints. These findings could be relevant for patient selection in the context of immunotherapies and potential targeting of metabolic pathways.