Detection of early stage pancreatic cancer using 5-hydroxymethylcytosine signatures in circulating cell free DNA.
Gulfem D GulerYuhong NingChin-Jen KuTierney PhillipsErin McCarthyChristopher K EllisonAnna BergamaschiFrancois CollinPaul LloydAaron ScottMichael AntoineWendy WangKim ChauAlan AshworthStephen R QuakeSamuel LevyPublished in: Nature communications (2020)
Pancreatic cancer is often detected late, when curative therapies are no longer possible. Here, we present non-invasive detection of pancreatic ductal adenocarcinoma (PDAC) by 5-hydroxymethylcytosine (5hmC) changes in circulating cell free DNA from a PDAC cohort (n = 64) in comparison with a non-cancer cohort (n = 243). Differential hydroxymethylation is found in thousands of genes, most significantly in genes related to pancreas development or function (GATA4, GATA6, PROX1, ONECUT1, MEIS2), and cancer pathogenesis (YAP1, TEAD1, PROX1, IGF1). cfDNA hydroxymethylome in PDAC cohort is differentially enriched for genes that are commonly de-regulated in PDAC tumors upon activation of KRAS and inactivation of TP53. Regularized regression models built using 5hmC densities in genes perform with AUC of 0.92 (discovery dataset, n = 79) and 0.92-0.94 (two independent test sets, n = 228). Furthermore, tissue-derived 5hmC features can be used to classify PDAC cfDNA (AUC = 0.88). These findings suggest that 5hmC changes enable classification of PDAC even during early stage disease.
Keyphrases
- early stage
- genome wide
- transcription factor
- genome wide identification
- papillary thyroid
- bioinformatics analysis
- machine learning
- dna methylation
- genome wide analysis
- small molecule
- squamous cell
- loop mediated isothermal amplification
- deep learning
- label free
- gene expression
- rectal cancer
- high throughput
- young adults
- single cell