Detection of methylated septin 9 in tissue and plasma of colorectal patients with neoplasia and the relationship to the amount of circulating cell-free DNA

BACKGROUND: Determination of methylated Septin 9 (mSEPT9) in plasma has been shown to be a sensitive and specific biomarker for colorectal cancer (CRC). However, the relationship between methylated DNA in plasma and colon tissue of the same subjects has not been reported. METHODS: Plasma and matching biopsy samples were collected from 24 patients with no evidence of disease (NED), 26 patients with adenoma and 34 patients with CRC. Following bisulfite conversion of DNA a commercial RT-PCR assay was used to determine the total amount of DNA in each sample and the fraction of mSEPT9 DNA. The Septin-9 protein was assessed using immunohistochemistry. RESULTS: The percent of methylated reference (PMR) values for SEPT9 above a PMR threshold of 1% were detected in 4.2% (1/24) of NED, 100% (26/26) of adenoma and 97.1% (33/34) of CRC tissues. PMR differences between NED vs. adenoma and NED vs. CRC comparisons were significant (p<0.001). In matching plasma samples using a PMR cut-off level of 0.01%, SEPT9 methylation was 8.3% (2/24) of NED, 30.8% (8/26) of adenoma and 88.2% (30/34) of CRC. Significant PMR differences were observed between NED vs. CRC (p<0.01) and adenoma vs. CRC (p<0.01). Significant differences (p<0.01) were found in the amount of cfDNA (circulating cell-free DNA) between NED and CRC, and a modest correlation was observed between mSEPT9 concentration and cfDNA of cancer (R2 = 0.48). The level of Septin-9 protein in tissues was inversely correlated to mSEPT9 levels with abundant expression in normals, and diminished expression in adenomas and tumors. CONCLUSIONS: Methylated SEPT9 was detected in all tissue samples. In plasma samples, elevated mSEPT9 values were detected in CRC, but not in adenomas. Tissue levels of mSEPT9 alone are not sufficient to predict mSEPT9 levels in plasma. Additional parameters including the amount of cfDNA in plasma appear to also play a role

MethylExtract: High-Quality methylation maps and SNV calling from whole genome bisulfite sequencing data

[v2; ref status: indexed, http://f1000r.es/301]Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants. We developed MethylExtract, a user friendly tool to: i) generate high quality, whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. MethylExtract detects variation (SNVs – Single Nucleotide Variants) in a similar way to VarScan, a very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of MethylExtract is shown by means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called Bis-SNP. MethylExtract is able to detect SNVs within High-Throughput Sequencing experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of MethylExtract, in comparison with existing software, is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at http://bioinfo2.ugr.es/MethylExtract/ and http://sourceforge.net/projects/methylextract/, and also permanently accessible from 10.5281/zenodo.7144.This work was supported by the Spanish Government [BIO2008-01353 to JLO and BIO2010-20219 to MH], and Basque country 'AE' grant (GB)