Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis
- Author(s)
- Savas, P; Virassamy, B; Ye, C; Salim, A; Mintoff, CP; Caramia, F; Salgado, R; Byrne, DJ; Teo, ZL; Dushyanthen, S; Byrne, A; Wein, L; Luen, SJ; Poliness, C; Nightingale, SS; Skandarajah, AS; Gyorki, DE; Thornton, CM; Beavis, PA; Fox, SB; Kathleen Cuningham Foundation Consortium for Research into Familial Breast, Cancer; Darcy, PK; Speed, TP; Mackay, LK; Neeson, PJ; Loi, S;
- Details
- Publication Year 2018-07,Volume 24,Issue #7,Page 986-993
- Journal Title
- Nature Medicine
- Publication Type
- Journal Article
- Abstract
- The quantity of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival, particularly in triple-negative and HER2-overexpressing BC subtypes (1) . Although T cells are the predominant TIL population (2) , the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6,311 T cells isolated from human BCs and show that significant heterogeneity exists in the infiltrating T cell population. We demonstrate that BCs with a high number of TILs contained CD8(+) T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8(+) TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8(+) TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple-negative breast cancer (TNBC) and provided better prognostication than CD8 expression alone. Our data suggest that CD8(+) TRM cells contribute to BC immunosurveillance and are the key targets of modulation by immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.
- Publisher
- Springer Nature
- Research Division(s)
- Bioinformatics
- PubMed ID
- 29942092
- Publisher's Version
- https://doi.org/10.1038/s41591-018-0078-7
- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2018-06-28 09:55:21
Last Modified: 2018-10-22 02:33:39