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dc.contributor.authorHiatt, J. B.en
dc.contributor.authorDoebley, A. L.en
dc.contributor.authorArnold, H. U.en
dc.contributor.authorAdil, M.en
dc.contributor.authorSandborg, H.en
dc.contributor.authorPersse, T. W.en
dc.contributor.authorKo, M.en
dc.contributor.authorWu, F.en
dc.contributor.authorQuintanal Villalonga, A.en
dc.contributor.authorSantana-Davila, R.en
dc.contributor.authorEaton, K.en
dc.contributor.authorDive, Carolineen
dc.contributor.authorRudin, C. M.en
dc.contributor.authorThomas, A.en
dc.contributor.authorHoughton, A. M.en
dc.contributor.authorHa, G.en
dc.contributor.authorMacPherson, D.en
dc.date.accessioned2024-07-08T15:12:51Z
dc.date.available2024-07-08T15:12:51Z
dc.date.issued2024en
dc.identifier.citationHiatt JB, Doebley AL, Arnold HU, Adil M, Sandborg H, Persse TW, et al. Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions. Science advances. 2024 Apr 12;10(15):eadk2082. PubMed PMID: 38598634. Pubmed Central PMCID: PMC11006233. Epub 2024/04/10. eng.en
dc.identifier.pmid38598634en
dc.identifier.doi10.1126/sciadv.adk2082en
dc.identifier.urihttp://hdl.handle.net/10541/627027
dc.description.abstractWe report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.en
dc.language.isoenen
dc.relation.urlhttps://dx.doi.org/10.1126/sciadv.adk2082en
dc.titleMolecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regionsen
dc.typeArticleen
dc.contributor.departmentCancer Research UK National Biomarker Centre, University of Manchester, Manchester, UK.en
dc.identifier.journalScience Advancesen
dc.description.noteen]
refterms.dateFOA2024-07-10T09:45:17Z


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