{"entity": "publication", "iuid": "3587f5657b864707a25f9f208e43e3c1", "timestamp": "2026-10-11T13:54:18.744Z", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/3587f5657b864707a25f9f208e43e3c1.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/3587f5657b864707a25f9f208e43e3c1"}}, "title": "Illuminating Non-genetic Cellular Heterogeneity with Imaging-Based Spatial Proteomics.", "authors": [{"family": "Gnann", "given": "Christian", "initials": "C"}, {"family": "Cesnik", "given": "Anthony J", "initials": "AJ"}, {"family": "Lundberg", "given": "Emma", "initials": "E"}], "type": "journal article", "published": "2021-04-00", "journal": {"title": "Trends Cancer", "issn": "2405-8025", "volume": "7", "issue": "4", "pages": "278-282", "issn-l": null}, "abstract": "Cellular heterogeneity is an important biological phenomenon observed across space and time in human tissues. Imaging-based spatial proteomic technologies can provide fruitful new readouts of phenotypic states for individual cells at subcellular resolution, which may help unravel the roles of non-genetic cellular heterogeneity in tumorigenesis and drug resistance.", "doi": "10.1016/j.trecan.2020.12.006", "pmid": "33436349", "labels": [], "xrefs": [{"db": "pii", "key": "S2405-8033(20)30333-2"}], "notes": [], "created": "2026-09-23T10:16:50.532Z", "modified": "2026-09-23T10:55:24.941Z"}