Enhanced detection of circulating tumor DNA by fragment size analysis.
Ahlborn, Lise Barlebo
van der Heijden, Michiel S
Parkinson, Christine A
Sci Transl Med
American Association for the Advancement of Science (AAAS)
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Mouliere, F., Chandrananda, S., Piskorz, A. M., Moore, E. K., Morris, J., Ahlborn, L. B., Mair, R., et al. (2018). Enhanced detection of circulating tumor DNA by fragment size analysis.. Sci Transl Med, 10 (466) https://doi.org/10.1126/scitranslmed.aat4921
Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for noninvasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 patients with cancer using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90 and 150 bp and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90 and 150 bp improved detection of tumor DNA, with more than twofold median enrichment in >95% of cases and more than fourfold enrichment in >10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with area under the curve (AUC) >0.99 compared to AUC <0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC > 0.91 compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection and could complement or provide an alternative to deeper sequencing of cfDNA.
Animals, Humans, Mice, Mutation, Genome, Human, DNA Copy Number Variations, Machine Learning, Whole Genome Sequencing, Circulating Tumor DNA
We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and the EPSRC (CRUK grant numbers A11906 (NR), A20240 (NR), A22905 (JDB), A15601 (JDB), A25177 (CRUK Cancer Centre Cambridge), A17242 (KMB), A16465 (CRUK-EPSRC Imaging Centre in Cambridge and Manchester)). The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 337905. The research was supported by the National Institute for Health Research Cambridge, National Cancer Research Network, Cambridge Experimental Cancer Medicine Centre and Hutchison Whampoa Limited. This research is also supported by Target Ovarian Cancer and the Medical Research Council through their Joint Clinical Research Training Fellowship for Dr Moore. The CALIBRATE study was supported by funding from AstraZeneca.
Medical Research Council (MR/L017415/1)
Cancer Research UK (CB4150)
Cancer Research UK (C14303/A17197)
European Research Council (337905)
Cancer Research UK (unknown)
Cancer Research UK (CRUK-A22905)
Cancer Research UK (CRUK-A15601)
Cancer Research UK (C96/A25177)
External DOI: https://doi.org/10.1126/scitranslmed.aat4921
This record's URL: https://www.repository.cam.ac.uk/handle/1810/286423