Gene-specific methylation alterations in breast cancer have been suggested to occur early in tumorigenesis and have the potential to be used for early detection and prevention. The continuous increase in worldwide breast cancer incidences emphasizes the urgent need for identification of methylation biomarkers for early cancer detection and patient stratification. Using microfluidic PCR-based target enrichment and next-generation bisulfite sequencing technology, we analyzed methylation status of 48 candidate genes in paired tumor and normal tissues from 180 Chinese breast cancer patients. Analysis of the sequencing results showed 37 genes differentially methylated between tumor and matched normal tissues. Breast cancer samples with different clinicopathologic characteristics demonstrated distinct profiles of gene methylation. The methylation levels were significantly different between breast cancer subtypes, with basal-like and luminal B tumors having the lowest and the highest methylation levels, respectively. Six genes (ACADL, ADAMTSL1, CAV1, NPY, PTGS2, and RUNX3) showed significant differential methylation among the 4 breast cancer subtypes and also between the ER +/ER- tumors. Using unsupervised hierarchical clustering analysis, we identified a panel of 13 hypermethylated genes as candidate biomarkers that performed a high level of efficiency for cancer prediction. These 13 genes included CST6, DBC1, EGFR, GREM1, GSTP1, IGFBP3, PDGFRB, PPM1E, SFRP1, SFRP2, SOX17, TNFRSF10D, and WRN. Our results provide evidence that well-defined DNA methylation profiles enable breast cancer prediction and patient stratification. The novel gene panel might be a valuable biomarker for early detection of breast cancer.

Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

Circulating cell-free DNA (cfDNA) has been considered as a potential biomarker for non-invasive cancer detection. To evaluate the methylation levels of six candidate genes (EGFR, GREM1, PDGFRB, PPM1E, SOX17, and WRN) in plasma cfDNA as biomarkers for breast cancer early detection, quantitative analysis of the promoter methylation of these genes from 86 breast cancer patients and 67 healthy controls was performed by using microfluidic-PCR-based target enrichment and next-generation bisulfite sequencing technology. The predictive performance of different logistic models based on methylation status of candidate genes was investigated by means of the area under the ROC curve (AUC) and odds ratio (OR) analysis. Results revealed that EGFR, PPM1E, and 8 gene-specific CpG sites showed significantly hypermethylation in cancer patients' plasma and significantly associated with breast cancer (OR ranging from 2.51 to 9.88). The AUC values for these biomarkers were ranging from 0.66 to 0.75. Combinations of multiple hypermethylated genes or CpG sites substantially improved the predictive performance for breast cancer detection. Our study demonstrated the feasibility of quantitative measurement of candidate gene methylation in cfDNA by using microfluidic-PCR-based target enrichment and bisulfite next-generation sequencing, which is worthy of further validation and potentially benefits a broad range of applications in clinical oncology practice. Quantitative analysis of methylation pattern of plasma cfDNA by next-generation sequencing might be a valuable non-invasive tool for early detection of breast cancer.

Background: To evaluate the predictive value of serum HBV DNA, HBV RNA, HBcrAg, HBsAg, intrahepatic HBV DNA, and cccDNA for HBeAg clearance and seroconversion during long-term treatment of nucleos(t)ide analogues (NAs) in patients with chronic hepatitis B (CHB).Method: A single center, prospective cohort of CHB patients enrolled between June 2007 and July 2008 was used for this study. Serum HBV RNA levels were retrospectively measured at baseline, 6, 12, 24, 36, 48, 60, 72, and 84 months post-NAs treatment. Serum HBsAg and HBcrAg levels were quanti ed at baseline, month 6, 60, and 72. Histological sample from liver biopsy at baseline and month 60 were analyzed for intrahepatic HBV DNA and cccDNA.Results: Eighty-three HBeAg patients were enrolled with an median follow-up time of 108 months (range 18-138 months). Of them, 53 (63.86%) patients achieved HBeAg clearance, and 37 (44.58%) achieved HBeAg seroconversion. Only baseline HBV RNA was independently associated with HBeAg clearance (OR=0.50, 95%CI 0.309-0.809, P=0.005) and seroconversion (OR=0.689, 95% CI 0.513-0.925, P=0.013). The independent negative association with HBeAg clearance and seroconversion remained for HBV RNA levels at month 6 (OR=0.42, 95%CI 0.248-0.714, P=0.001; OR=0.44, 95%CI 0.260-0.744, P=0.002) and month 12 (OR=0.39, 95%CI 0.253-0.592, P<0.001; OR=0.58, 95%CI 0.427-0.798, P=0.001). The AUC of baseline HBV RNA for predicting the HBeAg clearance and seroconversion were 0.81 (95%CI: 0.70-0.89) and 0.68 (95%CI: 0.56-0.78), respectively, higher than that of HBV DNA, HBsAg and HBcrAg. Conclusion: Lower serum HBV RNA at baseline, month 6 and 12 post NAs treatment could predict HBeAg clearance and seroconversion during long-term NAs treatment.

Background & Aims: Correlations between serum viral markers and intrahepatic cccDNA in patients undergoing long-term nucleos(t)ide analogues (NAs) treatment haven't been fully explored. In this study, we evaluate the correlation between intrahepatic cccDNA and other serum viral markers and intrahepatic HBV DNA in HBeAg positive chronic hepatitis B (CHB) patients during 60-month treatment with NAs. Methods: Fifty-four HBeAg positive CHB patients received long-term NAs treatment were included in this study. Serial serum samples were regularly collected and quantitatively analyzed for HBsAg, HBV DNA, HBV RNA and HBcrAg. Histological samples from liver biopsy at baseline and month 60 were analyzed for intrahepatic HBV DNA and cccDNA. Results: At baseline, serum HBV DNA plus RNA was positively associated with intrahepatic cccDNA in multivariate regression analysis (β=0.205, P<0.001). In the correlation analysis between cccDNA and serum viral markers, HBV DNA plus RNA had the highest correlation coefficient (r=0.698, P<0.001), followed by serum HBV DNA (r=0.641, P<0.001), HBV RNA (r=0.590, P<0.001), and HBcrAg (r=0.564, P<0.001). At month 60, correlations between these serum viral markers and cccDNA were not observed (P>0.05). Multivariate regression analysis showed that only the decreased HBV DNA plus RNA was positively associated with cccDNA decline (β=0.172, P =0.006). Changes of HBV DNA plus RNA (r=0.525, P=0.001) was better correlated with cccDNA decline as compared to HBV RNA (r=0.384, P=0.008), HBV DNA (r=0.431, P=0.003), and HBsAg (r=0.342, P=0.029). Conclusions: Serum HBV DNA plus RNA better correlated with intrahepatic cccDNA than other viral makers before and during NAs treatment in HBeAg positive CHB patients.