Detection of mutational patterns in cell-free DNA of colorectal cancer by custom amplicon sequencing
Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell-free (cf) DNA offers a noninvasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance....
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
29 June 2019
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| In: |
Molecular oncology
Year: 2019, Volume: 13, Issue: 8, Pages: 1669-1683 |
| ISSN: | 1878-0261 |
| DOI: | 10.1002/1878-0261.12539 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/1878-0261.12539 Verlag, lizenzpflichtig, Volltext: https://febs.onlinelibrary.wiley.com/doi/abs/10.1002/1878-0261.12539 
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| Author Notes: | Simon Herrmann, Tianzuo Zhan, Johannes Betge, Benedikt Rauscher, Sebastian Belle, Tobias Gutting, Nadine Schulte, Ralf Jesenofsky, Nicolai Härtel, Timo Gaiser, Ralf-Dieter Hofheinz, Matthias P. Ebert and Michael Boutros |
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| 520 | |a Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell-free (cf) DNA offers a noninvasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatic workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open-software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our workflow to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from a pilot cohort of 34 patients with advanced colorectal cancer. Using our method, we could detect recurrent and patient-specific mutational patterns in the majority of patients. Furthermore, we show that dynamic changes of mutant allele frequencies in cfDNA correlate well with disease progression. Finally, we demonstrate that sequencing of cfDNA can reveal mechanisms of resistance to anti-Epidermal Growth Factor Receptor(EGFR) antibody treatment. Thus, our approach offers a simple and highly customizable method to explore genetic alterations in cfDNA. | ||
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