Reduced representative methylome profiling of cell-free DNA for breast cancer detection.

BACKGROUND: Whole-genome methylation sequencing of cfDNA is not cost-effective for tumor detection. Here, we introduce reduced representative methylome profiling (RRMP), which employs restriction enzyme for depletion of AT-rich sequence to achieve enrichment and deep sequencing of CG-rich sequences. METHODS: We first verified the ability of RRMP to enrich CG-rich sequences using tumor cell genomic DNA and analyzed differential methylation regions between tumor cells and normal whole blood cells. We then analyzed cfDNA from 29 breast cancer patients and 27 non-breast cancer individuals to detect breast cancer by building machine learning models. RESULTS: RRMP captured 81.9% CpG islands and 75.2% gene promoters when sequenced to 10 billion base pairs, with an enrichment efficiency being comparable to RRBS. RRMP allowed us to assess DNA methylation changes between tumor cells and whole blood cells. Applying our approach to cfDNA from 29 breast cancer patients and 27 non-breast cancer individuals, we developed machine learning models that could discriminate between breast cancer and non-breast cancer controls (AUC = 0.85), suggesting possibilities for truly non-invasive cancer detection. CONCLUSIONS: We developed a new method to achieve reduced representative methylome profiling of cell-free DNA for tumor detection.

Hepatocellular carcinoma detection via targeted enzymatic methyl sequencing of plasma cell-free DNA.

BACKGROUND: Epigenetic variants carried by circulating tumor DNA can be used as biomarkers for early detection of hepatocellular carcinoma (HCC) by noninvasive liquid biopsy. However, traditional methylation analysis method, bisulfite sequencing, with disadvantages of severe DNA damage, is limited in application of low-amount cfDNA analysis. RESULTS: Through mild enzyme-mediated conversion, enzymatic methyl sequencing (EM-seq) is ideal for precise determination of cell-free DNA methylation and provides an opportunity for HCC early detection. EM-seq of methylation control DNA showed that enzymatic conversion of unmethylated C to U was more efficient than bisulfite conversion. Moreover, a relatively large proportion of incomplete converted EM-seq reads contains more than 3 unconverted CH site (CH = CC, CT or CA), which can be removed by filtering to improve accuracy of methylation detection by EM-seq. A cohort of 241 HCC, 76 liver disease, and 279 normal plasma samples were analyzed for methylation value on 1595 CpGs using EM-seq and targeted capture. Model training identified 283 CpGs with significant differences in methylation levels between HCC and non-HCC samples. A HCC screening model based on these markers can efficiently distinguish HCC sample from non-HCC samples, with area under the curve of 0.957 (sensitivity = 90%, specificity = 97%) in the test set, performing well in different stages as well as in serum α-fetoprotein/protein induced by vitamin K absence-II negative samples. CONCLUSION: Filtering of reads with ≥ 3 CHs derived from incomplete conversion can significantly reduce the noise of EM-seq detection. Based on targeted EM-seq analysis of plasma cell-free DNA, our HCC screening model can efficiently distinguish HCC patients from non-HCC individuals with high sensitivity and specificity.

The feasibility study of non-invasive fetal trisomy 18 and 21 detection with semiconductor sequencing platform.

OBJECTIVE: Recent non-invasive prenatal testing (NIPT) technologies are based on next-generation sequencing (NGS). NGS allows rapid and effective clinical diagnoses to be determined with two common sequencing systems: Illumina and Ion Torrent platforms. The majority of NIPT technology is associated with Illumina platform. We investigated whether fetal trisomy 18 and 21 were sensitively and specifically detectable by semiconductor sequencer: Ion Proton. METHODS: From March 2012 to October 2013, we enrolled 155 pregnant women with fetuses who were diagnosed as high risk of fetal defects at Xiamen Maternal & Child Health Care Hospital (Xiamen, Fujian, China). Adapter-ligated DNA libraries were analyzed by the Ion Proton™ System (Life Technologies, Grand Island, NY, USA) with an average 0.3× sequencing coverage per nucleotide. Average total raw reads per sample was 6.5 million and mean rate of uniquely mapped reads was 59.0%. The results of this study were derived from BWA mapping. Z-score was used for fetal trisomy 18 and 21 detection. RESULTS: Interactive dot diagrams showed the minimal z-score values to discriminate negative versus positive cases of fetal trisomy 18 and 21. For fetal trisomy 18, the minimal z-score value of 2.459 showed 100% positive predictive and negative predictive values. The minimal z-score of 2.566 was used to classify negative versus positive cases of fetal trisomy 21. CONCLUSION: These results provide the evidence that fetal trisomy 18 and 21 detection can be performed with semiconductor sequencer. Our data also suggest that a prospective study should be performed with a larger cohort of clinically diverse obstetrics patients.