Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer

Abstract

Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In 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. Results In 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. Conclusions Methylation 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.

MicroRNA-638 inhibits the progression of breast cancer through targeting HOXA9 and suppressing Wnt/β-cadherin pathway

“…Among them, the incidence of postmenopausal women ranging from 40 to 60 years old is higher [ 3 ]. Similar to a few types of tumors, such as thyroid cancer, the natural development of breast cancer is usually long, and it takes 7 to 8 years for the tumor to reach a sphere with a diameter of 1 cm [ 4 ]. Moreover, surgical treatment is the main therapy for breast cancer, and radiotherapy is one of the local treatment methods [ 5 ].…”

PCDHB15 as a potential tumor suppressor and epigenetic biomarker for breast cancer

“…The fact that 22.4% (11 out of 49) of the benign tumor samples tested positive for PCDHB15 methylation supports these hypotheses; however, further clinical analysis using a larger sample size and different molecular subtypes will be required to demonstrate whether PCDHB15 methylation is involved in the field defect of breast cancer (36). The sensitivity of PCDHB15 methylation (40.8%) in breast cancer detection in serum would not allow its use as a sole biomarker; however it could potentially serve as one epigenetic biomarker in a 'methylation signature panel' for the diagnosis and/or prognosis of breast cancer (37)(38)(39). Previous studies have identified distinct methylation biomarkers indicating the signaling-mediated epigenetic silencing of tumor suppressors, regardless of different subtypes of breast (40)(41)(42).…”

“…The sensitivity of PCDHB15 methylation (40.8%) in breast cancer detection in serum would not allow its use as a sole biomarker; however it could potentially serve as one epigenetic biomarker in a ‘methylation signature panel’ for the diagnosis and/or prognosis of breast cancer ( 37 – 39 ). Previous studies have identified distinct methylation biomarkers indicating the signaling-mediated epigenetic silencing of tumor suppressors, regardless of different subtypes of breast ( 40 – 42 ).…”

Comprehensive analysis of the cancer driver genes in breast cancer demonstrates their roles in cancer prognosis and tumor microenvironment

“…For example, estrogen and progesterone receptor status can indicate whether a patient is suitable for endocrine therapy [ 26 ]. In contrast, traditional tumor markers are gradually showing their limitations, while novel markers at the molecular level, such as mRNA, miRNA, and DNA methylation, are being intensively investigated [ 27 – 30 ]. Tumor-infiltrating lymphocytes (TIL) are a heterogeneous population of lymphocytes [ 31 ].…”