ArticleMolecular oncology2019
Detection of mutational patterns in cell-free DNA of colorectal cancer by custom amplicon sequencing.
Article in Molecular oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Liquid Biopsy for Medical Imaging Analysis in Cancer Diagnosis.Current pharmaceutical design · 2025Review
- Liquid Biopsies: Emerging role and clinical applications in solid tumours.Translational oncology · 2023Article
- Liquid Biopsies, Novel Approaches and Future Directions.Cancers · 2023Review
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- Incidental discovery of acute myeloid leukemia during liquid biopsy of a lung cancer patient.Cold Spring Harbor molecular case studies · 2022Article
- Review
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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