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Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue

53 Pages Posted: 17 Jun 2019 Publication Status: Published

See all articles by Kevin Litchfield

Kevin Litchfield

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Stacey Stanislaw

Roche Tissue Diagnostics

Lavinia Spain

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Lisa Gallegos

Roche Tissue Diagnostics

Andrew Rowan

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Desiree Schnidrig

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Heidi Rosenbaum

Roche Sequencing Solutions

Alexandre Harle

Institut de Cancérologie de Lorraine - Biopathology Service; University of Lorraine

Lewis Au

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Samantha Hill

Roche Tissue Diagnostics

Zayd Tippu

Royal Marsden Hospital

Jennifer Thomas

Royal Marsden Hospital

Hang Xu

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Stuart Horswell

Francis Crick Institute

Aoune Barhoumi

Roche Tissue Diagnostics

Carol Jones

Roche Tissue Diagnostics

Katherine F. Leith

Roche Tissue Diagnostics

Daniel L. Burgess

Roche Sequencing Solutions

Thomas BK Watkins

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Emilia Lim

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Nicolai J. Birkbak

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Philippe Lamy

Aarhus University Hospital - Department of Molecular Medicine

Iver Nordentoft

Aarhus University Hospital - Department of Molecular Medicine

Lars Dyrskjøt

Aarhus University Hospital - Department of Molecular Medicine

Stephen Hazell

Royal Marsden NHS Foundation Trust

Mariam Jamal-Hanjani

University College London - Cancer Research UK Lung Cancer Centre of Excellence

James Larkin

Royal Marsden NHS Foundation Trust - Renal and Skin Units

Charles Swanton

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

Nelson R. Alexander

Roche Tissue Diagnostics

Samra Turajlic

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

More...

Abstract

While hundreds of 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. 6mm punch) from a single spatial location, which becomes grossly under-powered as tumor volume scales. Indeed our analysis of current clinical and research practice shows that existing protocols sample from only 0.0005% to 2.0% of the total tumor mass, raising the prospect of considerable sampling bias. Failure to address this bias risks undermining the clinical utility of genomic medicine in cancer; through lack of sensitivity to detect actionable mutations, miss-assignment of subclonal variants as clonal, and unreliable estimate of tumor mutational burden (TMB). 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 next generation sequencing. Rep-Seq was implemented on a proof of concept basis, and benchmarked against current methods across multiple solid tumor types including renal cell carcinoma, lung cancer, melanoma, breast and colorectal cancer. Analysis of intra-tumor TMB variability showed a high level of misclassification with current single biopsy methods, with 20% of lung tumors, and 52% of bladder tumors, having ≥1 biopsy with high-TMB, but low clonal TMB overall (based on 10.0 mutations/Mb threshold for immune checkpoint inhibitor therapy (CPI)). Misclassification rates by contrast were reduced to 2% (lung) and 4% (bladder) when a more representative sampling frame was used. Clonal clustering analysis revealed rapid convergence of cancer cell fraction estimates in Rep-Seq towards true values, as validated in >60 biopsies, and >5ctDNA samples, taken from a single tumor. As a consequence 100% of variants were correctly classified as clonal by Rep-Seq, compared to ~85% in single biopsy sequencing. In terms of subclonal mutation detection, Rep-Seq achieved a greater sensitivity to detect variants, as compared to single-biopsy sequencing at equivalent depth (p=6.6x10-11). Finally, in a rapid autopsy setting Rep-Seq was able to accurately reconstruct the clonal phylogeny of advanced stage disease, correctly identifying polyclonal metastases, whereas single biopsy sequencing predicted monoclonal disease. Clinically this case showed lack of response to three lines of immune CPI therapy, which was observed in the context of a heterogeneous subclonal neoantigen repertoire. In conclusion, 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, achieves greater accuracy in determining clonal from subclonal variants. Rep-Seq offers an improved sampling protocol for tumor profling, with the same equivalent sequencing costs as current methods (single biopsy sequencing), but with significant potential for improved clinical utility.

Keywords: Tumor Sequencing, Molecular Profiling, Next Generation Sequencing, Cancer Genetics, Cancer Biomarkers

Suggested Citation

Litchfield, Kevin and Stanislaw, Stacey and Spain, Lavinia and Gallegos, Lisa and Rowan, Andrew and Schnidrig, Desiree and Rosenbaum, Heidi and Harle, Alexandre and Au, Lewis and Hill, Samantha and Tippu, Zayd and Thomas, Jennifer and Xu, Hang and Horswell, Stuart and Barhoumi, Aoune and Jones, Carol and Leith, Katherine F. and Burgess, Daniel L. and Watkins, Thomas BK and Lim, Emilia and Birkbak, Nicolai J. and Lamy, Philippe and Nordentoft, Iver and Dyrskjøt, Lars and Hazell, Stephen and Jamal-Hanjani, Mariam and Larkin, James and Swanton, Charles and Alexander, Nelson R. and Turajlic, Samra, Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue (June 14, 2019). Available at SSRN: https://ssrn.com/abstract=3404257 or http://dx.doi.org/10.2139/ssrn.3404257
This version of the paper has not been formally peer reviewed.

Kevin Litchfield

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory ( email )

United Kingdom

Stacey Stanislaw

Roche Tissue Diagnostics

United States

Lavinia Spain

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Lisa Gallegos

Roche Tissue Diagnostics

United States

Andrew Rowan

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Desiree Schnidrig

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Heidi Rosenbaum

Roche Sequencing Solutions

500 S Rosa Road
Madison, WI
United States

Alexandre Harle

Institut de Cancérologie de Lorraine - Biopathology Service ( email )

France

University of Lorraine ( email )

Lorraine
France

Lewis Au

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Samantha Hill

Roche Tissue Diagnostics

United States

Zayd Tippu

Royal Marsden Hospital

Sutton
Surrey
London
United Kingdom

Jennifer Thomas

Royal Marsden Hospital

Sutton
Surrey
London
United Kingdom

Hang Xu

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Stuart Horswell

Francis Crick Institute

1 Midland Road
London, NW1 1AT
United Kingdom

Aoune Barhoumi

Roche Tissue Diagnostics

United States

Carol Jones

Roche Tissue Diagnostics

United States

Katherine F. Leith

Roche Tissue Diagnostics

United States

Daniel L. Burgess

Roche Sequencing Solutions

500 S Rosa Road
Madison, WI
United States

Thomas BK Watkins

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Emilia Lim

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Nicolai J. Birkbak

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Philippe Lamy

Aarhus University Hospital - Department of Molecular Medicine

Denmark

Iver Nordentoft

Aarhus University Hospital - Department of Molecular Medicine

Denmark

Lars Dyrskjøt

Aarhus University Hospital - Department of Molecular Medicine

Denmark

Stephen Hazell

Royal Marsden NHS Foundation Trust

London
United Kingdom

Mariam Jamal-Hanjani

University College London - Cancer Research UK Lung Cancer Centre of Excellence

United Kingdom

James Larkin

Royal Marsden NHS Foundation Trust - Renal and Skin Units

London
United Kingdom

Charles Swanton

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory

United Kingdom

Nelson R. Alexander

Roche Tissue Diagnostics

United States

Samra Turajlic (Contact Author)

Francis Crick Institute - Cancer Evolution and Genome Instability Laboratory ( email )

United Kingdom

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