Somatic copy number profiling from hepatocellular carcinoma circulating tumor cells.
Colin M CourtShuang HouLian LiuPaul WinogradBenjamin J DiPardoSean X LiuPin-Jung ChenYazhen ZhuMatthew SmalleyRyan ZhangSaeed SadeghiRichard S FinnFady M KaldasRonald W BusuttilXianghong J ZhouHsian-Rong TsengJames S TomlinsonThomas Glen GraeberVatche G AgopianPublished in: NPJ precision oncology (2020)
Somatic copy number alterations (SCNAs) are important genetic drivers of many cancers. We investigated the feasibility of obtaining SCNA profiles from circulating tumor cells (CTCs) as a molecular liquid biopsy for hepatocellular carcinoma (HCC). CTCs from ten HCC patients underwent SCNA profiling. The Cancer Genome Atlas (TCGA) SCNA data were used to develop a cancer origin classification model, which was then evaluated for classifying 44 CTCs from multiple cancer types. Sequencing of 18 CTC samples (median: 4 CTCs/sample) from 10 HCC patients using a low-resolution whole-genome sequencing strategy (median: 0.88 million reads/sample) revealed frequent SCNAs in previously reported HCC regions such as 8q amplifications and 17p deletions. SCNA profiling revealed that CTCs share a median of 80% concordance with the primary tumor. CTCs had SCNAs not seen in the primary tumor, some with prognostic implications. Using a SCNA profiling model, the tissue of origin was correctly identified for 32/44 (73%) CTCs from 12/16 (75%) patients with different cancer types.
Keyphrases
- circulating tumor cells
- copy number
- single cell
- papillary thyroid
- mitochondrial dna
- circulating tumor
- genome wide
- end stage renal disease
- squamous cell
- ejection fraction
- newly diagnosed
- chronic kidney disease
- dna methylation
- childhood cancer
- machine learning
- lymph node metastasis
- peritoneal dialysis
- single molecule
- patient reported outcomes
- artificial intelligence