title: Single-cell proteomics: potential implications for cancer diagnostics.
abstract: Single-cell proteomics in cancer is evolving and promises to provide more accurate diagnoses based on detailed molecular features of cells within tumors. This review focuses on technologies that allow for collection of complex data from single cells, but also highlights methods that are adaptable to routine cancer diagnostics. Current diagnostics rely on histopathological analysis, complemented by mutational detection and clinical imaging. Though crucial, the information gained is often not directly transferable to defined therapeutic strategies, and predicting therapy response in a patient is difficult. In cancer, cellular states revealed through perturbed intracellular signaling pathways can identify functional mutations recurrent in cancer subsets. Single-cell proteomics remains to be validated in clinical trials where serial samples before and during treatment can reveal excessive clonal evolution and therapy failure; its use in clinical trials is anticipated to ignite a diagnostic revolution that will better align diagnostics with the current biological understanding of cancer.
authors.affiliation: a Department of Neurology , Haukeland University Hospital , Bergen , Norway.
authors.forename: Sonia
authors.initials: S
authors.lastname: Gavasso
authors.affiliation: b Department of Clinical Science , University of Bergen , Bergen , Norway.
authors.forename: Stein-Erik
authors.initials: SE
authors.lastname: Gullaksen
authors.affiliation: b Department of Clinical Science , University of Bergen , Bergen , Norway.
authors.forename: Jørn
authors.initials: J
authors.lastname: Skavland
authors.affiliation: b Department of Clinical Science , University of Bergen , Bergen , Norway.|c Translational Hemato-Oncology Group , University of Bergen , Bergen , Norway.
authors.forename: Bjørn T
authors.initials: BT
authors.lastname: Gjertsen
mesh_terms: D021581:Active Transport, Cell Nucleus; D000970:Antineoplastic Agents / Q000627:therapeutic use; D060965:Clonal Evolution; D005434:Flow Cytometry; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000175:diagnosis* / Q000188:drug therapy / Q000235:genetics / Q000473:pathology; D044085:Microfluidics; D009154:Mutation; D009363:Neoplasm Proteins / Q000235:genetics* / Q000378:metabolism; D009360:Neoplastic Cells, Circulating / Q000378:metabolism / Q000473:pathology; D025941:Protein Interaction Mapping; D040901:Proteomics / Q000295:instrumentation / Q000379:methods*; D015398:Signal Transduction; D059010:Single-Cell Analysis / Q000295:instrumentation / Q000379:methods*; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
chemical_list: D000970:Antineoplastic Agents; D009363:Neoplasm Proteins; D014157:Transcription Factors
keywords: Signal transduction inhibitors; acute myeloid leukemia; nuclear transport blockers; protein-protein interactions; transcription factor inhibitors