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Cell-free DNA cues for gene expression

Authors :
Mohammad Shahrokh Esfahani
Emily G. Hamilton
Mahya Mehrmohamadi
Barzin Y. Nabet
Stefan K. Alig
Daniel A. King
ChloƩ B. Steen
Charles W. Macaulay
Andre Schultz
Monica C. Nesselbush
Joanne Soo
Joseph G. Schroers-Martin
Binbin Chen
Michael S. Binkley
Henning Stehr
Jacob J. Chabon
Brian J. Sworder
Angela B-Y Hui
Matthew J. Frank
Everett J. Moding
Chih Long Liu
Aaron M. Newman
James M. Isbell
Charles M. Rudin
Bob T. Li
David M. Kurtz
Maximilian Diehn
Ash A. Alizadeh
Source :
Nat Biotechnol
Publication Year :
2022

Abstract

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

Details

ISSN :
15487105
Volume :
19
Issue :
5
Database :
OpenAIRE
Journal :
Nature methodsResearch paper
Accession number :
edsair.doi.dedup.....8b7debb06a3da970ca2d0077dfbf5c07