Currently favored sampling practices for tumor sequencing can produce optimal results in the clinical setting

Tumor heterogeneity is a consequence of clonal evolution, resulting in a fractal-like architecture with spatially separated main clones, sub-clones and single-cells. As sequencing an entire tumor is not feasible, we ask the question whether there is an optimal clinical sampling strategy that can han...

Full description

Saved in:
Bibliographic Details
Published in:Scientific reports Vol. 10; no. 1; p. 14403
Main Authors: Pongor, Lőrinc S., Munkácsy, Gyöngyi, Vereczkey, Ildikó, Pete, Imre, Győrffy, Balázs
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 01.09.2020
Nature Publishing Group
Subjects:
631/114
631/208
631/67
631/67/68
692/4028
692/4028/67/68
Anaplastic large-cell lymphoma
Biopsy
Cancer
Clonal Evolution - genetics
DNA microarrays
Exome
Female
Fibronectin
Gene Frequency
Genetic Heterogeneity
Germ-Line Mutation
Heterogeneity
High-Throughput Nucleotide Sequencing - methods
Humanities and Social Sciences
Humans
Lymphoma
Mesenchyme
Metastases
multidisciplinary
Mutation
Mutation Rate
Non-coding RNA
Ovarian cancer
Ovarian Neoplasms - genetics
Ovarian Neoplasms - pathology
Pathogens
Science
Science (multidisciplinary)
Sequence Analysis, DNA - methods
Tumors
Whole Exome Sequencing - methods
ISSN:2045-2322, 2045-2322
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Tumor heterogeneity is a consequence of clonal evolution, resulting in a fractal-like architecture with spatially separated main clones, sub-clones and single-cells. As sequencing an entire tumor is not feasible, we ask the question whether there is an optimal clinical sampling strategy that can handle heterogeneity and hypermutations? Here, we tested the effect of sample size, pooling strategy as well as sequencing depth using whole-exome sequencing of ovarian tumor specimens paired with normal blood samples. Our study has an emphasis on clinical application—hence we compared single biopsy, combined local biopsies and combined multi-regional biopsies. Our results show that sequencing from spatially neighboring regions show similar genetic compositions, with few private mutations. Pooling samples from multiple distinct regions of the primary tumor did not increase the overall number of identified mutations but may increase the robustness of detecting clonal mutations. Hypermutating tumors are a special case, since increasing sample size can easily dilute sub-clonal private mutations below detection thresholds. In summary, we compared the effects of sampling strategies (single biopsy, multiple local samples, pooled global sample) on mutation detection by next generation sequencing. In view of the limitations of present tools and technologies, only one sequencing run per sample combined with high coverage (100–300 ×) sequencing is affordable and practical, regardless of the number of samples taken from the same patient.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-71382-3