Journal
JOURNAL OF CELLULAR PHYSIOLOGY
Volume 236, Issue 4, Pages 3143-3156Publisher
WILEY
DOI: 10.1002/jcp.30082
Keywords
cholangiocarcinoma; CpG island methylator phenotype; methylation; prognostic signature
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Funding
- National Nature Science Foundation of China [81401997, 81500565, 81572427, 81874065, 81874149]
- State Key Project on Infectious Diseases of China [2018ZX10723204-003]
- Hepato-Biliary-Pancreatic Malignant Tumor Investigation Fund of Chen Xiao-ping Foundation for the Development of Science and Technology of Hubei Province [CXPJJH11800001-2018356]
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The study identified a CIMP-related methylation signature specific for CCA (CMSC) that can classify patients into different risk groups and predict patient outcomes. Additionally, a subset of patients with an unfavorable prognosis correlated with CIMP-H was identified. Gene enrichment analysis suggested a potential mechanism of CIMP as a promoter of carcinogenesis by regulating proliferation.
Cholangiocarcinoma (CCA) still has a very unfavorable prognosis with a very high mortality, which is complicated by a lack of prognostic biomarkers. In this study, CCA patients in the Gene Expression Omnibus (GEO) cohort were categorized into two subtypes. Differentially expressed and methylated genes were identified, and the impact of DNA methylation in the trans-regulation of gene expression was investigated. Finally, a CIMP-related methylation signature specific for CCA (CMSC) was trained in GEO and validated in the Tongji cohort. A subset of patients with CIMP-H was identified, which was correlated with an unfavorable prognosis. Gene enrichment analysis implied the potential mechanism of CIMP as a promoter of carcinogenesis by regulating proliferation. The trans-regulation among differentially methylated CpG sites and genes with the same change trends was positively correlated, while the converse situation showed a negative correlation. Notably, CMSC based on four genes could significantly classify CCA patients into low- and high-risk groups in the GEO cohort, and the robustness of CMSC was validated in the Tongji cohort. The results of receiver operating characteristic analysis further indicated that CMSC was capable of highly sensitive and specific prediction of the patient outcomes in CCA. In conclusion, our work highlights the clinical significance of CMSC in the prognosis of CCA.
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