Cell-free DNA from germline TP53 mutation carriers reflect cancer-like fragmentation patterns.
Derek WongMaha TageldeinPing LuoErik EnsmingerJeffrey BruceLeslie OldfieldHaifan GongNicholas William FischerBrianne LavertyVallijah SubasriScott DavidsonReem KhanAnita VillaniAdam ShlienRaymond H KimDavid MalkinTrevor J PughPublished in: Nature communications (2024)
Germline pathogenic TP53 variants predispose individuals to a high lifetime risk of developing multiple cancers and are the hallmark feature of Li-Fraumeni syndrome (LFS). Our group has previously shown that LFS patients harbor shorter plasma cell-free DNA fragmentation; independent of cancer status. To understand the functional underpinning of cfDNA fragmentation in LFS, we conducted a fragmentomic analysis of 199 cfDNA samples from 82 TP53 mutation carriers and 30 healthy TP53-wildtype controls. We find that LFS individuals exhibit an increased prevalence of A/T nucleotides at fragment ends, dysregulated nucleosome positioning at p53 binding sites, and loci-specific changes in chromatin accessibility at development-associated transcription factor binding sites and at cancer-associated open chromatin regions. Machine learning classification resulted in robust differentiation between TP53 mutant versus wildtype cfDNA samples (AUC-ROC = 0.710-1.000) and intra-patient longitudinal analysis of ctDNA fragmentation signal enabled early cancer detection. These results suggest that cfDNA fragmentation may be a useful diagnostic tool in LFS patients and provides an important baseline for cancer early detection.
Keyphrases
- papillary thyroid
- machine learning
- transcription factor
- end stage renal disease
- squamous cell
- newly diagnosed
- ejection fraction
- deep learning
- peritoneal dialysis
- dna damage
- prognostic factors
- case report
- squamous cell carcinoma
- minimally invasive
- lymph node metastasis
- patient reported outcomes
- risk factors
- dna methylation
- oxidative stress
- young adults
- copy number
- patient reported
- circulating tumor cells
- genome wide association study
- genome wide association