A high-throughput test enables specific detection of hepatocellular carcinoma.
David CheishviliChifat WongMohammad Mahbubul KarimMohammad Golam KibriaNusrat JahanPappu Chandra DasMd Abul Khair YousufMd Atikul IslamDulal Chandra DasSheikh Mohammad Noor-E-AlamMoshe SzyfSarwar AlamWasif Ali KhanMamun A MahtabPublished in: Nature communications (2023)
High-throughput tests for early cancer detection can revolutionize public health and reduce cancer morbidity and mortality. Here we show a DNA methylation signature for hepatocellular carcinoma (HCC) detection in liquid biopsies, distinct from normal tissues and blood profiles. We developed a classifier using four CpG sites, validated in TCGA HCC data. A single F12 gene CpG site effectively differentiates HCC samples from other blood samples, normal tissues, and non-HCC tumors in TCGA and GEO data repositories. The markers were validated in a separate plasma sample dataset from HCC patients and controls. We designed a high-throughput assay using next-generation sequencing and multiplexing techniques, analyzing plasma samples from 554 clinical study participants, including HCC patients, non-HCC cancers, chronic hepatitis B, and healthy controls. HCC detection sensitivity was 84.5% at 95% specificity and 0.94 AUC. Implementing this assay for high-risk individuals could significantly decrease HCC morbidity and mortality.
Keyphrases
- high throughput
- dna methylation
- end stage renal disease
- public health
- gene expression
- ejection fraction
- chronic kidney disease
- newly diagnosed
- loop mediated isothermal amplification
- real time pcr
- peritoneal dialysis
- single cell
- papillary thyroid
- squamous cell carcinoma
- copy number
- genome wide
- big data
- prognostic factors
- lymph node metastasis
- quantum dots
- deep learning
- patient reported
- ionic liquid