Science AdvancesImmunologyPeer-reviewed journal article
CD4+Foxp3E2+ regulatory T cell frequency predicts breast cancer prognosis and recurrence
Clorinda FuscoiD, Francesca Di RellaiD, Antonietta LiottiiD, Alessandra ColamatteoiD, Anne Lise FerraraiD, Vincenzo GigantinoiD, Francesca CollinaiD, Emanuela EspositoiD, Ivana DonzelliiD, Antonio PorcelliniiD, Antonia FeolaiD, Teresa MicilloiD, Francesco PernaiD, Federica GarzianoiD, Giorgia Teresa ManiscalcoiD, Gilda VarricchiiD, Maria MottolaiD, Bruno ZuccarelliiD, Bruna De SimoneiD, Maurizio Di Bonito, Giuseppe MatareseiD, Antonello AccursoiD, Martina PontilloiD, Daniela RussoiD, Luigi InsabatoiD, , Veronica De RosaiD
Abstract
CD4+Foxp3+ regulatory T cells (Tregs) are key to maintain peripheral self-tolerance and suppress immune responses to tumors. Their accumulation in the tumor microenvironment (TME) correlates with poor clinical outcome in several human cancers, including breast cancer (BC). However, the properties of intratumoral Tregs remain largely unknown. Here, we found that a functionally distinct subpopulation of tumor-infiltrating Tregs, which express the Foxp3 splicing variant retaining exon 2 (Foxp3E2), is prominent in the TME and peripheral blood of hormone receptor- positive (HR+) BC subjects with poor prognosis. Notably, a comprehensive examination of the Tumor Cell Genome Atlas (TCGA) validated Foxp3E2 as an independent prognostic marker in all other BC subtypes. We found that FOXP3E2 expression underlies BCs with highly immune suppressive landscape, defective mismatch repair and a stem-like signature thus highlighting pathways involved in tumor immune evasion. Finally, we confirmed the higher immunosuppressive capacity of BC patients-derived Foxp3E2+ Tregs by functional assays. Our study suggests Foxp3E2+ Tregs might be used as an independent biomarker to predict BC prognosis and recurrence, and to develop super-targeted depletion-based immunotherapies. One-sentence summariesFoxp3E2+ Treg enrichment reflects an increased tumor-immune suppression and predicts prognosis and recurrence in breast cancer.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: protein folding & dynamics
- research focus: cell type annotation
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 13
- FWCI
- 4.24
- Field percentile
- top 5%
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