Pan-cancer methylome analysis for cancer diagnosis and classification of cancer cell of origin.
Dai ShimizuKenzui TaniueYusuke MatsuiHiroshi HaenoHiromitsu ArakiFumihito MiuraMitsuko FukunagaKenji ShiraishiYuji MiyamotoSeiichi TsukamotoAya KomineYuta KobayashiAkihiro KitagawaYukihiro YoshikawaKuniaki SatoTomoko SaitoShuhei ItoTakaaki MasudaAtsushi NiidaMakoto SuzukiHideo BabaTakashi ItoNobuyoshi AkimitsuYasuhiro KoderaKoshi MimoriPublished in: Cancer gene therapy (2021)
The accurate and early diagnosis and classification of cancer origin from either tissue or liquid biopsy is crucial for selecting the appropriate treatment and reducing cancer-related mortality. Here, we established the CAncer Cell-of-Origin (CACO) methylation panel using the methylation data of the 28 types of cancer in The Cancer Genome Atlas (7950 patients and 707 normal controls) as well as healthy whole blood samples (95 subjects). We showed that the CACO methylation panel had high diagnostic potential with high sensitivity and specificity in the discovery (maximum AUC = 0.998) and validation (maximum AUC = 1.000) cohorts. Moreover, we confirmed that the CACO methylation panel could identify the cancer cell type of origin using the methylation profile from liquid as well as tissue biopsy, including primary, metastatic, and multiregional cancer samples and cancer of unknown primary, independent of the methylation analysis platform and specimen preparation method. Together, the CACO methylation panel can be a powerful tool for the classification and diagnosis of cancer.
Keyphrases
- papillary thyroid
- squamous cell
- genome wide
- dna methylation
- machine learning
- cardiovascular disease
- end stage renal disease
- type diabetes
- small molecule
- childhood cancer
- mass spectrometry
- chronic kidney disease
- high throughput
- peritoneal dialysis
- ejection fraction
- artificial intelligence
- molecularly imprinted
- patient reported
- human health