P. Reference scripts are available on GitHub (https://github.com/cclab-brca/BCMC, 10.5281/zenodo.4445719). Abstract 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 Kv3 modulator 3 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. and or PDTX tissue of origin (primary versus metastatic). Similarly, we found no clear association between phenotypic heterogeneity and the relative amount of mouse stroma or genomic heterogeneity (quantified by mutant-allele tumour heterogeneity, MATH, score56) (Supplementary Fig.?4c). Remarkably, tSNE plots revealed that inter-tumour (between models) phenotypic heterogeneity is mostly driven by human tumour compartment markers, whereas intra-tumour (within the model) phenotypic heterogeneity is mostly driven by oncogenic signalling activation markers (Fig.?3e and Supplementary Fig.?4dCf). The average coefficient of variation (CV) per model and marker subpanel revealed cell cycle and apoptosis had the highest variability, oncogenic signalling activation intermediate levels and human tumour compartment the lowest (Fig.?3f). These results taken together indicate a wide-range of inter- and intra-tumour cellular phenotypic heterogeneity across PDTXs, and this novel feature showed preferential associations with known breast cancer molecular subtypes. Interestingly, inter- and intra-tumour cellular phenotypic heterogeneities appear to be driven by different mechanisms, with oncogenic signalling being the main driver of the intra-tumour phenotypic heterogeneity in breast cancer. Imaging mass cytometry reveals the spatial distribution of cell phenotypes in xenografts The spatial distribution of both tumour cells and the microenvironment is structured and has clinical implications29,32. To characterise the spatial architecture of CCs, we performed imaging Kv3 modulator 3 mass cytometry (IMC) in a subset of PDTXs (8 models), with a panel of 10 antibodies that overlapped with the BCMC panel (Fig.?4a, Supplementary Table?1 and Methods section). Clustering using the IMC-based expression of the 10 markers across the 8 PDTX tissue samples analysed showed the low phenotypic distance Kv3 modulator 3 between replicates (Supplementary Fig.?5a). A novel machine learning approach, cross-mass cytometry (MC) cell-classifier, was developed to map CCs identified by mass cytometry to their tissue-based IMC counterparts (Fig.?4a and Methods section). Centroids of each CC computed per-model on the mass cytometry training data showed a high correlation (median 22). A two-sided mutant models, while luminal CCs L2, L4, L5 were enriched in mutations were highly prevalent in L5 luminal-like cells, which are characterised by activation of Akt-mTOR signalling (see above, Fig.?3a). Inactivating mutations were mainly associated with L3 (Fig.?5b), a luminal-like cell phenotype Rabbit polyclonal to Cytokeratin5 with decreased levels of MAPK effectors (p-c-JUN and p-p38) (Fig.?3a). L3 is also enriched in models with mutations in a range of ER-related epigenetic regulators (and DDR-related genes (for 3?min, supernatants were discarded, and the cell pellets were washed twice before suspension in CSB and stored short-term at 4?C until the next step. Antibodies for mass cytometry and IMC Metal-labelled antibodies were as commercially available or purchased in carrier-free PBS to be conjugated to metal isotopes. Antibody conjugation used the Maxpar Antibody Labelling kit (Fluidigm) as per manufacturers instructions (herein referred as custom) (Supplementary Table?1). Details on the antibody identifiers, validation process and dilution used for each antibody are reported in Supplementary Table?1. Mass cytometry measured 41 parameters/channels: 33 antibody markers (32 channels), 7 heavy metal barcodes, 1 intercalator as intact single-cell inclusion marker.