AI Article Synopsis

  • This study presents a cancer phenotyping method using targeted sequencing of cell-free DNA (cfDNA) specifically for small cell lung cancer (SCLC).
  • The researchers developed a targeted capture panel that analyzes transcription factor (TF) binding sites and gene transcription start sites, successfully detecting mutations and TF activity in SCLC samples.
  • The prediction models for specific TF activities demonstrated high accuracy, with potential for distinguishing different lung cancer types and monitoring tumor transformations, indicating broader applications for other cancer types.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11006233PMC
http://dx.doi.org/10.1126/sciadv.adk2082DOI Listing

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