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Poster Discussion session - Translational research 2

1969 - Representative Sequencing: profiling extreme tumor diversity


21 Oct 2018


Poster Discussion session - Translational research 2


Translational Research

Tumour Site


Kevin Litchfield


Annals of Oncology (2018) 29 (suppl_8): viii649-viii669. 10.1093/annonc/mdy303


K. Litchfield1, L. Au2, C. Swanton3, S. Turajlic3

Author affiliations

  • 1 Swanton Lab, The Francis Crick Institute, NW1 1AT - London/GB
  • 2 Translational Cancer Therapeutics, The Francis Crick Institute, London/GB
  • 3 Translational Cancer Therapeutics, The Francis Crick Institute, NW1 1AT - London/GB

Abstract 1969


While next-generation sequencing (NGS) has been applied to thousands of solid tumors to date, there exists a fundamental undersampling bias inherent in current methodologies. This is caused by a biopsy input sample of fixed dimensions, which becomes grossly under-powered as tumor volume scales. Indeed pan-cancer analysis reveals that current protocols sample on average only 1.5% of cancer cells, decreasing to 0.3% for stage IV tumors. Failure to address this bias risks undermining the clinical utility of genomic medicine in cancer.


Here we demonstrate Representative Sequencing (Rep-Seq), as a novel method to achieve unbiased sampling of solid tumor tissue. The Rep-Seq protocol comprises homogenization of all residual tumor material not taken for pathology into a well-mixed solution, coupled with NGS. Rep-Seq was implemented on a proof of concept basis in 13 tumors, and benchmarked against single and multiregion sequencing approaches.


Rep-Seq achieved a linear rate of novel variant discovery in whole-exome sequencing across 0 to 5,000x coverage, detecting four-fold more mutations as compared to multi-region sequencing at equivalent total read depth. All variants were validated using custom panel and Ion Torrent platforms. Targeted panel Rep-Seq at 50,000x showed sensitivity to detect extreme parallel evolution, with 16 independent mutations in the gene SETD2 observed in a single tumor. Clonal clustering analysis revealed rapid convergence of cancer cell fraction estimates in Rep-Seq towards true values, as validated in > 70 biopsies taken from a single tumor. As a consequence, 97% of variants were correctly classified as clonal by Rep-Seq, compared to > 85% in single biopsy sequencing. Finally, in a rapid autopsy setting Rep-Seq was able to accurately reconstruct the clonal phylogency of advanced stage disease, recovering a high proportion of all primary and metastatic variants, from deep sequencing of primary tissue alone.


Rep-Seq effectively implements an unbiased tumor sampling approach, drawing DNA molecules from a well-mixed solution of the entire tumor mass, hence removing spatial bias inherent in current approaches. As a result Rep-Seq detects more mutations, and achieves greater accuracy in determining clonal from subclonal variants.

Clinical trial identification

Legal entity responsible for the study

The Francis Crick Institute.



Editorial Acknowledgement


C. Swanton: Consulting and speaker: Boehringer Ingelheim, Eli Lilly, Novartis, Roche; Grant support: Cancer Research UK, UCLH Biomedical Research Council, Rosetrees Trust, Roche. S. Turajlic: Grant support: Roche. All other authors have declared no conflicts of interest.

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