Multi-omic characterization of genome-wide abnormal DNA methylation reveals diagnostic and prognostic markers for esophageal squamous-cell carcinoma.
Yiyi XiYuan LinWenjia GuoXinyu WangHengqiang ZhaoChuanwang MiaoWeiling LiuYachen LiuTianyuan LiuYingying LuoWenyi FanAi LinYamei ChenYanxia SunYulin MaXiangjie NiuCe ZhongWen TanMeng ZhouJianzhong SuChen WuDongxin LinPublished in: Signal transduction and targeted therapy (2022)
This study investigates aberrant DNA methylations as potential diagnosis and prognosis markers for esophageal squamous-cell carcinoma (ESCC), which if diagnosed at advanced stages has <30% five-year survival rate. Comparing genome-wide methylation sites of 91 ESCC and matched adjacent normal tissues, we identified 35,577 differentially methylated CpG sites (DMCs) and characterized their distribution patterns. Integrating whole-genome DNA and RNA-sequencing data of the same samples, we found multiple dysregulated transcription factors and ESCC-specific genomic correlates of identified DMCs. Using featured DMCs, we developed a 12-marker diagnostic panel with high accuracy in our dataset and the TCGA ESCC dataset, and a 4-marker prognostic panel distinguishing high-risk patients. In-vitro experiments validated the functions of 4 marker host genes. Together these results provide additional evidence for the important roles of aberrant DNA methylations in ESCC development and progression. Our DMC-based diagnostic and prognostic panels have potential values for clinical care of ESCC, laying foundations for developing targeted methylation assays for future non-invasive cancer detection methods.
Keyphrases
- genome wide
- dna methylation
- copy number
- circulating tumor
- gene expression
- cell free
- single molecule
- healthcare
- ejection fraction
- end stage renal disease
- transcription factor
- palliative care
- electronic health record
- nucleic acid
- single cell
- papillary thyroid
- machine learning
- risk assessment
- human health
- heat stress
- patient reported outcomes
- quality improvement
- artificial intelligence
- circulating tumor cells
- current status
- free survival
- sensitive detection
- label free
- bioinformatics analysis
- genome wide analysis