bioRxivGenomicsPreprint
Integrated inference of cancer gene expression from cell-free plasma chromatin
Gunsagar Singh GulatiiD, Damien VasseuriD, Rashad NawfaliD, Shahabeddin SotudianiD, Karl SemaaniD, Marc EidiD, Ji-Heui SeoiD, Noa PhillipsiD, John CanniffiD, Hunter SavignanoiD, Surya B. ChhetriiD, Zhenjie JiniD, Yukun OuiD, Mohamed Amine BaniiD, Gwo‐Shu Mary LeeiD, Rachel Trowbridge, Ilana Bensussen EpsteiniD, Gabriella Rickards, Paulo Da Silva CordeiroiD, Ze Zhang, Razane El Hajj ChehadeiD, Brady James, Christophe MassardiD, Antoîne ItalianoiD, Antoine HollebecqueiD, , Matthew L. FreedmaniD
Abstract
Gene expression is a defining determinant of tumor identity, behavior, and therapeutic response, yet remains challenging to measure noninvasively. Here, we introduce APEX (Associating Plasma Epigenomic features with eXpression), a framework for inferring expression from circulating cell-free chromatin. Trained on [~]270,000 gene-sample pairs from matched tumor RNA-seq and plasma cfChIP-seq across multiple cancers and validated on >15 unseen cancer subtypes, APEX accurately infers cancer gene expression across a range of tumor fractions and outperforms existing plasma-based approaches by integrating positional histone mark and DNA fragmentation patterns across promoters and gene bodies. Using plasma alone, APEX enables classification of prognostically relevant basal and classical pancreatic cancer subtypes and identifies plasma-inferred NECTIN4 expression as a biomarker of response to enfortumab vedotin in metastatic bladder cancer. Together, these findings establish APEX as a biopsy-free approach for profiling tumor transcriptional states and extend liquid biopsy beyond genomic alterations to clinically relevant gene expression programs.
- organism: human
- assay: ChIP-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 2
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- cfOncoXpress: Tumor gene expression prediction from cell-free DNA whole-genome sequences
Weiling Li, Marjorie L. Roskes, … Ekta Khurana·bioRxiv·Oct 31, 2025
- ChIP-seq of plasma cell-free nucleosomes identifies cell-of-origin gene expression programs
Ronen Sadeh, Israa Sharkia, … Nir Friedman·Nature BiotechnologyPeer-reviewed·Jan 11, 2021
- Subtyping of Small Cell Lung Cancer using plasma cell-free nucleosomes
G. Fialkoff, N. Takahashi, … A. Thomas·bioRxiv·Jun 24, 2022
- Inferring expressed genes by whole-genome sequencing of plasma DNA
Peter Ulz, Gerhard G Thallinger, … Michael R Speicher·bioRxiv·Apr 22, 2016
- Inference of tumor cell-specific transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection of cancer
P. Ulz, S. Perakis, … M. R. Speicher·bioRxiv·Mar 31, 2019
- Multiplexed Single-Molecule Epigenetic Analysis of Plasma-Isolated Nucleosomes for Cancer Diagnostics