Background: Abnormal DNA methylation is a hallmark of human cancers and may be a promising biomarker for early diagnosis of human cancers. However, the majority of DNA methylation biomarkers that have been identified are based on the hypothesis that early differential methylation regions (DMRs) are maintained throughout carcinogenesis and could be detected at all stages of cancer. Methods: In this study, we identified potential early biomarkers of colorectal cancer (CRC) development by genomewide DNA methylation assay (Illumina infinium450, 450 K) of normal (N = 20) and pre-colorectal cancer samples including 18 low-grade adenoma (LGA) and 22 high-grade adenoma (HGA), integrated with GEO and ArrayExpress datasets (N = 833). Results:We identified 209 and 8692 CpG sites that were significantly hyper-methylated in LGA and HGA, respectively. Pathway analysis identified nervous system-related methylation changes that are significantly associated with early adenoma development. Integration analysis revealed that DNA methylation in the promoter region of ADHFE1 has the most potential for being an early diagnostic biomarker for colorectal adenoma and cancer (sensitivity = 0.96, specificity = 0.95, area under the curve = 0.97).Conclusions: Overall, we demonstrated that DNA methylation have been shown significant changes in the stage of LGA and HGA in the development of colon cancer. Genome-wide DNA methylation to LGA and HGA provided an important proxy to identify promising early diagnosis biomarkers for colorectal cancer.

In this manuscript, spherical fuzzy set (SFS) and T-spherical fuzzy set (TSFS) are discussed, which are two generalizations of fuzzy set (FS), intuitionistic fuzzy set (IFS), Pythagorean fuzzy set (PFS) and picture fuzzy set (PFS). As TSFS is more capable of processing and expressing unknown information in unknown environment, it is widely used in various areas. However, how to accurately measure the distance between TSFSs is still an unsolved problem. This manuscript discusses some limitations of the existing divergence measures and the problems that the existing divergence measures cannot be applied to the information provided in the TSFSs environment by some numerical examples. Therefore, a new divergence measure under TSFSs structure is proposed by utilizing the advantages of Jensen-Shannon divergence, which is called TSFSJS distance. This TSFSJS distance not only satisfies the distance measurement axiom, but also can better distinguish the difference between TSFSs than other distance measures. More importantly, this TSFSJS distance can avoid counter-intuitive results through the argument of some numerical results in the paper. The proposed approach can deal with more types of uncertain information as demonstrated by establishing a comparative study. INDEX TERMST-spherical fuzzy set (TSFS), divergence measures, Jensen-Shannon divergence, pattern recognition.

Background: Circulating cell-free DNA (cfDNA) methylation has been demonstrated to be a promising approach for non-invasive cancer diagnosis. However, the high cost of whole genome bisulfite sequencing (WGBS) hinders the clinical implementation of a methylation-based cfDNA early detection biomarker. We proposed a novel strategy in low-pass WGBS (~5 million reads) to detect methylation changes in circulating cell-free DNA (cfDNA) from patients with liver diseases and hepatocellular carcinoma (HCC). Methods: The effective small sequencing depth were determined by 5 pilot cfDNA samples with relative highdepth WGBS. CfDNA of 51 patients with hepatitis, cirrhosis, and HCC were conducted using low-pass WGBS. The strategy was validated in an independent WGBS cohort of 32 healthy individuals and 26 early-stage HCC patients. Fifteen paired tumor tissue and buffy coat samples were used to characterize the methylation of hepatitis B virus (HBV) integration regions and genome distribution of cfDNA.