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Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

5741 - Development and analytical validation of a plasma-based tumor mutational burden (TMB) score from next-generation sequencing panels

Date

20 Oct 2018

Session

Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

Presenters

Katie Quinn

Citation

Annals of Oncology (2018) 29 (suppl_8): viii14-viii57. 10.1093/annonc/mdy269

Authors

K. Quinn1, E. Helman1, T. Nance1, C. Artieri1, J. Yen1, J. Zhao1, S. Fairclough1, M. Sikora2, D. Chudova2, R.B. Lanman3, A. Talasaz4

Author affiliations

  • 1 Bioinformatics, Guardant Health, 94063 - Redwood City/US
  • 2 Bioinformatics, Guardant Health, 94536 - Redwood City/US
  • 3 Medical Affairs, Guardant Health, 94063 - Redwood City/US
  • 4 Guardant Health, 94536 - Redwood City/US
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Resources

Abstract 5741

Background

The advantages of plasma-based tumor mutational burden (TMB) include non-invasive, real-time assessment of mutational load, without the limitations of insufficient tissue. However, at low levels of tumor DNA shedding, TMB may be underestimated if a fraction of the genomic alterations is below assay limit of detection. Currently available blood TMB panels report a 1% tumor content limit of detection, which would result in about half of all clinical plasma samples (based on > 30,000 patients) with unevaluable TMB. Hence, clinically effective blood-based diagnostics must be highly sensitive and account for tumor shedding. Here, we present a comprehensive cfDNA-based TMB using a 500-gene (GuardantOMNI) and a 73-gene (Guardant360) panel.

Methods

We developed a statistical model to calculate TMB on plasma samples with low cell-free circulating tumor DNA (ctDNA) content. Theoretical panel performance was assessed in silico by subsetting mutations from whole exome sequencing (WES) to the Guardant panel space (2Mb for GuardantOMNI and 200Kb for Guardant360) from 9,104 TCGA samples and 30 lung cancer samples with published immunotherapy outcomes. Sensitivity was evaluated using 50 serially diluted cfDNA specimens. Analytical validation was performed against tissue-based WES TMB using matched plasma and tissue samples across multiple tumor types.

Results

High correlation was observed between TMB called on the Guardant panel and WES mutations from the TCGA dataset (r = 0.99 with GuardantOMNI; r = 0.92 with Guardant360). Subsetting WES from clinical outcome cohorts to each panel recapitulated the association with PFS on immunotherapy (HR = 0.41 with GuardantOMNI; HR = 0.27 with Guardant360). The sensitivity of detection was assessed down to 0.3% tumor content and 5ng cfDNA input. Lastly, we show high quantitative concordance between matched plasma and tissue WES samples for both GuardantOMNI and Guardant360.

Conclusions

We describe a plasma-based TMB score that correlates with tissue-derived TMB at tumor fractions down to 0.3%, enabling TMB calculation on > 70% of all clinical samples. Accurate reporting of TMB from a plasma sample has the potential to accelerate clinical trial enrollment and improve outcomes.

Clinical trial identification

Legal entity responsible for the study

Guardant Health, Inc.

Funding

Guardant Health, Inc.

Editorial Acknowledgement

Disclosure

K. Quinn, E. Helman, T. Nance, C. Artieri, J. Yen, J. Zhao, S. Fairclough, M. Sikora, D. Chudova, R.B. Lanman, A. Talasaz: Employee and ownership (stock): Guardant Health, Inc.

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