biostudies-literatureGerdes MJCancer Research UKMedical Research CouncilNational Institute for Health Research (NIHR)NCI NIH HHS406-417https://www.ebi.ac.uk/biostudies/studies/S-EPMC6192037biostudies-literatureUnknown31(3)Heterogeneous patterns of mutations and RNA expression have been well documented in invasive cancers. However, technological challenges have limited the ability to study heterogeneity of protein expression. This is particularly true for pre-invasive lesions such as ductal carcinoma in situ of the breast. Cell-level heterogeneity in ductal carcinoma in situ was analyzed in a single 5 μm tissue section using a multiplexed immunofluorescence analysis of 11 disease-related markers (EGFR, HER2, HER4, S6, pmTOR, CD44v6, SLC7A5 and CD10, CD4, CD8 and CD20, plus pan-cytokeratin, pan-cadherin, DAPI, and Na+K+ATPase for cell segmentation). Expression was quantified at cell level using a single-cell segmentation algorithm. K-means clustering was used to determine co-expression patterns of epithelial Modern pathology : an official journal of the United States and Canadian Academy of Pathology, IncSingle-cell heterogeneity in ductal carcinoma in situ of breast.PMC6192037G03006481897416466R01 CA194600NF-SI-0611-1016311359Harris ALTan PHBadve SSGokmen-Polar YSui YLaPlante NGinty FPang ASGerdes MJfalseSingle-cell heterogeneity in ductal carcinoma in situ of breast.Heterogeneous patterns of mutations and RNA expression have been well documented in invasive cancers. However, technological challenges have limited the ability to study heterogeneity of protein expression. This is particularly true for pre-invasive lesions such as ductal carcinoma in situ of the breast. Cell-level heterogeneity in ductal carcinoma in situ was analyzed in a single 5 μm tissue section using a multiplexed immunofluorescence analysis of 11 disease-related markers (EGFR, HER2, HER4, S6, pmTOR, CD44v6, SLC7A5 and CD10, CD4, CD8 and CD20, plus pan-cytokeratin, pan-cadherin, DAPI, and Na+K+ATPase for cell segmentation). Expression was quantified at cell level using a single-cell segmentation algorithm. K-means clustering was used to determine co-expression patterns of epithelial 2018-01-01T00:00:00Z2018 Mar2025-04-04T10:58:20.452Z2019-03-27T00:02:47ZS-EPMC61920372914854010.1038/modpathol.2017.143