Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions
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Authors
Hiatt, J. B.Doebley, A. L.
Arnold, H. U.
Adil, M.
Sandborg, H.
Persse, T. W.
Ko, M.
Wu, F.
Quintanal Villalonga, A.
Santana-Davila, R.
Eaton, K.
Dive, Caroline
Rudin, C. M.
Thomas, A.
Houghton, A. M.
Ha, G.
MacPherson, D.
Affiliation
Cancer Research UK National Biomarker Centre, University of Manchester, Manchester, UK.Issue Date
2024
Metadata
Show full item recordAbstract
We 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.Citation
Hiatt 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.Journal
Science AdvancesDOI
10.1126/sciadv.adk2082PubMed ID
38598634Additional Links
https://dx.doi.org/10.1126/sciadv.adk2082Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1126/sciadv.adk2082