Breast cancer is marked by specific, Public T-cell receptor CDR3 regions shared by mice and humans.
Miri GordinHagit PhilipAlona ZilberbergMoriah GidoniRaanan MargalitChristopher ClouserKristofor D AdamsFrancois VigneaultIrun R CohenGur YaariSol EfroniPublished in: PLoS computational biology (2021)
The partial success of tumor immunotherapy induced by checkpoint blockade, which is not antigen-specific, suggests that the immune system of some patients contain antigen receptors able to specifically identify tumor cells. Here we focused on T-cell receptor (TCR) repertoires associated with spontaneous breast cancer. We studied the alpha and beta chain CDR3 domains of TCR repertoires of CD4 T cells using deep sequencing of cell populations in mice and applied the results to published TCR sequence data obtained from human patients. We screened peripheral blood T cells obtained monthly from individual mice spontaneously developing breast tumors by 5 months. We then looked at identical TCR sequences in published human studies; we used TCGA data from tumors and healthy tissues of 1,256 breast cancer resections and from 4 focused studies including sequences from tumors, lymph nodes, blood and healthy tissues, and from single cell dataset of 3 breast cancer subjects. We now report that mice spontaneously developing breast cancer manifest shared, Public CDR3 regions in both their alpha and beta and that a significant number of women with early breast cancer manifest identical CDR3 sequences. These findings suggest that the development of breast cancer is associated, across species, with biomarker, exclusive TCR repertoires.
Keyphrases
- single cell
- regulatory t cells
- end stage renal disease
- newly diagnosed
- endothelial cells
- lymph node
- ejection fraction
- gene expression
- high fat diet induced
- healthcare
- chronic kidney disease
- prognostic factors
- mental health
- systematic review
- type diabetes
- electronic health record
- dna damage
- stem cells
- cell therapy
- emergency department
- early breast cancer
- big data
- early stage
- machine learning
- insulin resistance
- young adults
- metabolic syndrome
- oxidative stress
- adverse drug
- high throughput
- sentinel lymph node
- pluripotent stem cells