bioRxivBioinformaticsPreprint
Xenograft supervision and joint methylation-fragment-end encoding define a reusable molecular scoring layer for cell-free tumor DNA
Xuchao Zhang, Xiaojun SuniD, Rui WangiD, Ningning Zhao, Fang Liu, Xuhua Li, Jian Huang, Jiamin SuniD, Han Li, Shang Lou, Haoyi WangiD, Hailong ZhaoiD, Han ShuiD, Peimeng ZheniD, Hongcang GuiD, Jiantao ShiiD, Tao Wang, Fan ZhangiD
Abstract
Circulating tumor DNA is often scarce in plasma, and regional methylation summaries can obscure informative differences between individual molecules. Here we present ctDNA-BERT, a Transformer that scores individual bisulfite reads without predefined differentially methylated regions by jointly encoding CpG methylation state, nucleotide context and the fragment 3' end. Xenografts provide molecule-level tumor supervision. The resulting frozen scorer supported tumor-fraction estimation in synthetic and patient-derived xenograft mixtures and enriched tumor-concordant methylation and chromatin-accessibility signals in independent hepatocellular carcinoma and stage III pan-cancer plasma without cohort-specific retraining. Features derived from selected reads discriminated stage I cancers from healthy controls in a retrospective cohort of 1,477 specimens, achieving an out-of-fold area under the receiver operating characteristic curve of 0.884. By separating molecular scoring from sample-level inference, ctDNA-BERT provides a reusable read-level scoring layer for cell-free DNA methylation analysis.
- organism: human
- assay: DNA methylation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- research focus: database / resource
- approach: deep learning
- approach: transformer / foundation model
- Citations
- 0
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