ArticleScientific reports2017
Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype.Journal of neuro-oncology · 2023Article
- Immunotherapeutic Approaches in Ovarian Cancer.Current issues in molecular biology · 2023Review
- Currently favored sampling practices for tumor sequencing can produce optimal results in the clinical setting.Scientific reports · 2020Article
- Comprehensive Outline of Whole Exome Sequencing Data Analysis Tools Available in Clinical Oncology.Cancers · 2019Review
- Article
- Pathological Bases and Clinical Impact of Intratumor Heterogeneity in Clear Cell Renal Cell Carcinoma.Current urology reports · 2018Review
- Intratumor and Intertumor Heterogeneity in Melanoma.Translational oncology · 2017Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Short and long distance cell dispersal can have a marked effect on tumor structure, high cellular motility could lead to faster cell mixing and lower observable intratumor heterogeneity. Here we evaluated a model for cell mixing that investigates how short-range dispersal and cell turnover will account for mutational proportions. We show that cancer cells can penetrate neighboring and distinct areas in a matter of days. In next generation sequencing runs, higher proportions of a given cell line generated frequencies with higher precision, while mixtures with lower amounts of each cell line had lower precision manifesting in higher standard deviations. When multiple cell lines were co-cultured, cellular movement altered observed mutation frequency by up to 18.5%. We propose that some of the shared mutations detected at low allele frequencies represent highly motile clones that appear in multiple regions of a tumor owing to dispersion throughout the tumor. In brief, cell movement will lead to a significant technical (sampling) bias when using next generation sequencing to determine clonal composition. A possible solution to this drawback would be to radically decrease detection thresholds and increase coverage in NGS analyses.
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Registered trials
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