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Using DNA sequencing data to quantify T cell fraction and therapy response

Author

Listed:
  • Robert Bentham

    (University College London Cancer Institute
    University College London Cancer Institute)

  • Kevin Litchfield

    (University College London Cancer Institute
    University College London Cancer Institute)

  • Thomas B. K. Watkins

    (The Francis Crick Institute)

  • Emilia L. Lim

    (University College London Cancer Institute
    The Francis Crick Institute)

  • Rachel Rosenthal

    (The Francis Crick Institute)

  • Carlos Martínez-Ruiz

    (University College London Cancer Institute
    University College London Cancer Institute)

  • Crispin T. Hiley

    (University College London Cancer Institute
    The Francis Crick Institute)

  • Maise Al Bakir

    (The Francis Crick Institute)

  • Roberto Salgado

    (GZA-ZNA
    University of Melbourne)

  • David A. Moore

    (University College London Cancer Institute
    University College London Hospitals
    University College London Hospitals)

  • Mariam Jamal-Hanjani

    (University College London Cancer Institute
    University College London Hospitals
    University College London Cancer Institute)

  • Charles Swanton

    (University College London Cancer Institute
    The Francis Crick Institute
    University College London Hospitals)

  • Nicholas McGranahan

    (University College London Cancer Institute
    University College London Cancer Institute)

Abstract

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy1,2. However, measurements of tumour infiltrating lymphocytes (TILs) are limited by a shortage of appropriate data. Whole-exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations. Here we develop T cell exome TREC tool (T cell ExTRECT), a method for estimation of T cell fraction from WES samples using a signal from T cell receptor excision circle (TREC) loss during V(D)J recombination of the T cell receptor-α gene (TCRA (also known as TRA)). TCRA T cell fraction correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females than in males and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma. Using a meta-analysis of tumours treated with immunotherapy, we show that tumour TCRA T cell fraction predicts immunotherapy response, providing value beyond measuring tumour mutational burden. Applying T cell ExTRECT to a multi-sample pan-cancer cohort reveals a high diversity of the degree of immune infiltration within tumours. Subclonal loss of 12q24.31–32, encompassing SPPL3, is associated with reduced TCRA T cell fraction. T cell ExTRECT provides a cost-effective technique to characterize immune infiltrate alongside somatic changes.

Suggested Citation

  • Robert Bentham & Kevin Litchfield & Thomas B. K. Watkins & Emilia L. Lim & Rachel Rosenthal & Carlos Martínez-Ruiz & Crispin T. Hiley & Maise Al Bakir & Roberto Salgado & David A. Moore & Mariam Jamal, 2021. "Using DNA sequencing data to quantify T cell fraction and therapy response," Nature, Nature, vol. 597(7877), pages 555-560, September.
  • Handle: RePEc:nat:nature:v:597:y:2021:i:7877:d:10.1038_s41586-021-03894-5
    DOI: 10.1038/s41586-021-03894-5
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    Cited by:

    1. Alastair Magness & Emma Colliver & Katey S. S. Enfield & Claudia Lee & Masako Shimato & Emer Daly & David A. Moore & Monica Sivakumar & Karishma Valand & Dina Levi & Crispin T. Hiley & Philip S. Hobso, 2024. "Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    2. Hannah Poisner & Annika Faucon & Nancy Cox & Alexander G. Bick, 2024. "Genetic determinants and phenotypic consequences of blood T-cell proportions in 207,000 diverse individuals," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    3. Richard Culliford & Samuel E. D. Lawrence & Charlie Mills & Zayd Tippu & Daniel Chubb & Alex J. Cornish & Lisa Browning & Ben Kinnersley & Robert Bentham & Amit Sud & Husayn Pallikonda & Anna Frangou , 2024. "Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

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