Landscapes of cellular phenotypic diversity in breast cancer xenografts and their impact on drug response
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s41467-021-22303-z.pdf
Description
Published version
Size
8.44 MB
Format
Unknown
Checksum (MD5)
039ccca2a0fd6994df01fdab8ff407c5
Author(s)
Georgopoulou, Dimitra
Callari, Maurizio
Rueda, Oscar M.
Shea, Abigail
Martin, Alistair
Giovannetti, Agnese
Qosaj, Fatime
Dariush, Ali
Chin, Suet-Feung
Carnevalli, Larissa S.
Date Issued
March 2021
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Georgopoulou, Dimitra, Callari, Maurizio, Rueda, Oscar M, Shea, Abigail, Martin, Alistair et al. 2021. "Landscapes of cellular phenotypic diversity in breast cancer xenografts and their impact on drug response." Nature Communications, 12 (1).
Version
Final published version
Abstract
AbstractThe heterogeneity of breast cancer plays a major role in drug response and resistance and has been extensively characterized at the genomic level. Here, a single-cell breast cancer mass cytometry (BCMC) panel is optimized to identify cell phenotypes and their oncogenic signalling states in a biobank of patient-derived tumour xenograft (PDTX) models representing the diversity of human breast cancer. The BCMC panel identifies 13 cellular phenotypes (11 human and 2 murine), associated with both breast cancer subtypes and specific genomic features. Pre-treatment cellular phenotypic composition is a determinant of response to anticancer therapies. Single-cell profiling also reveals drug-induced cellular phenotypic dynamics, unravelling previously unnoticed intra-tumour response diversity. The comprehensive view of the landscapes of cellular phenotypic heterogeneity in PDTXs uncovered by the BCMC panel, which is mirrored in primary human tumours, has profound implications for understanding and predicting therapy response and resistance.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/s41467-021-22303-z
