Computational optimisation of targeted DNA sequencing for cancer detection.
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ABSTRACT:
SUBMITTER: Martinez P
PROVIDER: S-EPMC6506443 | biostudies-literature | 2013 Dec
REPOSITORIES: biostudies-literature
Publications
Computational optimisation of targeted DNA sequencing for cancer detection.
Martinez Pierre P McGranahan Nicholas N Birkbak Nicolai Juul NJ Gerlinger Marco M Swanton Charles C
Scientific reports 20131203
Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing circulating tumour DNA (ctDNA) might represent a non-invasive method to detect mutations in patients, facilitating early detection. In this article, we define reduced gene panels from publicly available da ...[more]
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Project description:BackgroundEpigenetic 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.ResultsThrough 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.ConclusionFiltering 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.
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Project description:PurposePrecision medicine in pancreatic ductal adenocarcinoma (PDAC) could be substantially supported by tools that allow to establish and monitor the molecular setup of the tumor. In particular, noninvasive approaches are desirable, but not validated. Characterization of circulating tumor DNA (ctDNA) may help to achieve this goal.Experimental designBlood samples from patients with metastatic PDAC prior to and during palliative treatment were collected. ctDNA and corresponding tumor tissue were analyzed by targeted next generation sequencing and droplet digital PCR for the 7 most frequently mutated genes in PDAC (TP53, SMAD4, CDKN2A, KRAS, APC, ATM, and FBXW7). Findings were correlated with clinical and imaging data.ResultsA total of 20 patients (therapy naïve n = 11; pretreated n = 9) were included. All therapy naïve patients (n = 11/11) presented with detectable ctDNA at baseline. In pretreated patients, 3/7 (prior to 2nd line treatment) and 2/2 (prior to 3rd line chemotherapy) had detectable ctDNA. The combined mutational allele frequency (CMAF) of KRAS and TP53 was chosen to reflect the amount of ctDNA. The median CMAF level significantly decreased during treatment (P = 0.0027) and increased at progression (P = 0.0104). CA19-9 analyses did not show significant differences. In treatment naïve patients, the CMAF levels during therapy significantly correlated with progression-free survival (Spearman, r = -0.8609, P = 0.0013).ConclusionsMonitoring of ctDNA and its changes during treatment may enable to adapt therapeutic strategies to the specific molecular changes present at a certain time during treatment of mPDAC.
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