Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue.

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.

Authors:: K Litchfield, S Stanislaw, L Spain, LL Gallegos, A Rowan, D Schnidrig, H Rosenbaum, A Harle, L Au, SM Hill, Z Tippu, J Thomas, L Thompson, H Xu, S Horswell, A Barhoumi, C Jones, KF Leith, DL Burgess, TBK Watkins, E Lim, NJ Birkbak, P Lamy, I Nordentoft, L Dyrskjøt, L Pickering, S Hazell, M Jamal-Hanjani, PEACE Consortium, J Larkin, C Swanton, NR Alexander, S Turajlic

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