Contributors: IMAXT Consortium; Ali, H.R.; Al Sa'd, M.; Alon, S.; Aparicio, S.; Battistoni, G.; Balasubramanian, S.; Becker, R.; Bodenmiller, B.; Boyden, E.S.; Bressan, D.; Bruna, A.; Burger, M.; Caldas, C.; Callari, M.; Cannell, I.G.; Casbolt, H.; Chornay, N.; Cui, Y.; Dariush, A.; Dinh, K.; Emenari, A.; Eyal-Lubling, Y.; Fan, J.; Fatemi, A.; Fisher, E.; González-Solares, E.A.; González-Fernández, C.; Goodwin, D.; Greenwood, W.; Grimaldi, F.; Hannon, G.J.; Harris, O.; Harris, S.; Jauset, C.; Joyce, J.A.; Karagiannis, E.D.; Kovačević, T.; Kuett, L.; Kunes, R.; Küpcü, Y.A.; Lai, D.; Laks, E.; Lee, H.; Lee, M.; Lerda, G.; Li, Y.; McPherson, A.; Millar, N.; Mulvey, C.M.; Nugent, F.; O'Flanagan, C.H.; Paez-Ribes, M.; Pearsall, I.; Qosaj, F.; Roth, A.J.; Rueda, O.M.; Ruiz, T.; Sawicka, K.; Sepúlveda, L.A.; Shah, S.P.; Shea, A.; Sinha, A.; Smith, A.; Tavaré, S.; Tietscher, S.; Vázquez-García, I.; Vogl, S.L.; Walton, N.A.; Wassie, A.T.; Watson, S.S.; Weselak, J.; Wild, S.A.; Williams, E.; Windhager, J.; Whitmarsh, T.; Xia, C.; Zheng, P.; Zhuang, X.
نبذة مختصرة : The 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.
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