ArticleWorld journal of surgical oncology2021
Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer.
Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed, 34 citations in OpenAlex.
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- Comprehensive in silico CpG methylation analysis in hepatocellular carcinoma identifies tissue- and tumor-type specific marks disconnected from gene expression.Journal of physiology and biochemistry · 2024Article
- ADCY4 promotes brain metastasis in small cell lung cancer and is associated with energy metabolism.Heliyon · 2024Article
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- Methylation Profile of Small Breast Cancer Tumors Evaluated by Modified MS-HRM.International journal of molecular sciences · 2023Article
- Microtubule-Associated Serine/Threonine (MAST) Kinases in Development and Disease.International journal of molecular sciences · 2023Review
- DNA methylation biomarkers accurately detect esophageal cancer prior and post neoadjuvant chemoradiation.Cancer medicine · 2023Article
- Promoter Methylation-Regulated Differentially Expressed Genes in Breast Cancer.Breast cancer (Dove Medical Press) · 2023Article
- LINE-1 hypomethylation is associated with poor outcomes in locoregionally advanced oropharyngeal cancer.Clinical epigenetics · 2022Article
- Screening for aberrantly methylated and differentially expressed genes in nonalcoholic fatty liver disease of hepatocellular carcinoma patients with cirrhosis.World journal of surgical oncology · 2022Article
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9 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAberrant DNA methylation is significantly associated with breast cancer.
methodsIn this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis.
resultsIn this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival.
conclusionsMethylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer.
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