Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue.
Date
2020-05-05Author
Litchfield, K
Stanislaw, S
Spain, L
Gallegos, LL
Rowan, A
Schnidrig, D
Rosenbaum, H
Harle, A
Au, L
Hill, SM
Tippu, Z
Thomas, J
Thompson, L
Xu, H
Horswell, S
Barhoumi, A
Jones, C
Leith, KF
Burgess, DL
Watkins, TBK
Lim, E
Birkbak, NJ
Lamy, P
Nordentoft, I
Dyrskjøt, L
Pickering, L
Hazell, S
Jamal-Hanjani, M
PEACE Consortium,
Larkin, J
Swanton, C
Alexander, NR
Turajlic, S
Type
Journal Article
Metadata
Show full item recordAbstract
Although thousands of solid tumors have been sequenced to date, a fundamental under-sampling bias is inherent in current methodologies. This is caused by a tissue sample input of fixed dimensions (e.g., 6 mm biopsy), which becomes grossly under-powered as tumor volume scales. Here, we demonstrate representative sequencing (Rep-Seq) as a new method to achieve unbiased tumor tissue sampling. Rep-Seq uses fixed residual tumor material, which is homogenized and subjected to next-generation sequencing. Analysis of intratumor tumor mutation burden (TMB) variability shows a high level of misclassification using current single-biopsy methods, with 20% of lung and 52% of bladder tumors having at least one biopsy with high TMB but low clonal TMB overall. Misclassification rates by contrast are reduced to 2% (lung) and 4% (bladder) when a more representative sampling methodology is used. Rep-Seq offers an improved sampling protocol for tumor profiling, with significant potential for improved clinical utility and more accurate deconvolution of clonal structure.
Collections
Subject
biomarkers
homogenization
molecular profiling
representative sampling
tumor hetereogeneity
tumor mutational burden
tumor sampling
tumor sequencing
Biomarkers, Tumor
Biopsy
High-Throughput Nucleotide Sequencing
Humans
Lung Neoplasms
Mutation
Tumor Burden
Urinary Bladder Neoplasms
Research team
Molec & Popul Genetics
Melanoma & Kidney Cancer
Language
eng
Date accepted
2020-04-01
License start date
2020-05-05
Citation
Cell Reports, 2020, 31 (5), pp. 107550 -
Publisher
CELL PRESS
Except where otherwise noted, this item's license is described
as
https://creativecommons.org/licenses/by-nc-nd/4.0/
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