Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions

Author:

Hiatt Joseph B.123ORCID,Doebley Anna-Lisa456ORCID,Arnold Henry U.1ORCID,Adil Mohamed14ORCID,Sandborg Holly1,Persse Thomas W.4,Ko Minjeong4,Wu Feinan7,Quintanal Villalonga Alvaro8ORCID,Santana-Davila Rafael39ORCID,Eaton Keith39ORCID,Dive Caroline10ORCID,Rudin Charles M.1112ORCID,Thomas Anish13ORCID,Houghton A. McGarry9ORCID,Ha Gavin141415ORCID,MacPherson David1415ORCID

Affiliation:

1. Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA.

2. Veterans Affairs Puget Sound Healthcare System - Seattle Branch, Seattle, WA, USA.

3. Division of Medical Oncology, Department of Medicine, University of Washington, Seattle, WA, USA.

4. Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.

5. Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA, USA.

6. Medical Scientist Training Program, University of Washington, Seattle, WA, USA.

7. Genomics and Bioinformatics Shared Resource, Fred Hutchinson Cancer Center, Seattle, WA, USA.

8. Department of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

9. Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, WA, USA.

10. Cancer Research UK National Biomarker Centre, University of Manchester, Manchester, UK.

11. Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

12. Graduate Program in Pharmacology, Weill Cornell Medical College; New York, NY, USA.

13. Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

14. Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.

15. Department of Genome Sciences, University of Washington, Seattle, WA, USA.

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.

Publisher

American Association for the Advancement of Science (AAAS)

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