Litchfield, Kevin, Stanislaw, Stacey, Spain, Lavinia, Gallegos, Lisa L, Rowan, Andrew, Schnidrig, Desiree, Rosenbaum, Heidi, Harle, Alexandre, Au, Lewis, Hill, Samantha M et al (show 22 more authors)
(2020)
Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue.
CELL REPORTS, 31 (5).
107550-.
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Abstract
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | PEACE Consortium, Humans, Lung Neoplasms, Biopsy, Tumor Burden, Mutation, Urinary Bladder Neoplasms, High-Throughput Nucleotide Sequencing, Biomarkers, Tumor |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 21 May 2020 09:00 |
| Last Modified: | 18 Jan 2023 23:51 |
| DOI: | 10.1016/j.celrep.2020.107550 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3088187 |
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