Litchfield, K;
Stanislaw, S;
Spain, L;
Gallegos, LL;
Rowan, A;
Schnidrig, D;
Rosenbaum, H;
... Turajlic, S; + view all
(2020)
Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue.
Cell Reports
, 31
(5)
p. 107550.
10.1016/j.celrep.2020.107550.
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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.
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