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

Bentham, R; Litchfield, K; Watkins, TBK; Lim, EL; Rosenthal, R; Martinez-Ruiz, C; Hiley, CT; ... McGranahan, N; + view all (2021) Using DNA sequencing data to quantify T cell fraction and therapy response. Nature , 597 pp. 555-560. 10.1038/s41586-021-03894-5. Green open access

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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.

Type: Article
Title: Using DNA sequencing data to quantify T cell fraction and therapy response
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41586-021-03894-5
Publisher version: https://doi.org/10.1038/s41586-021-03894-5
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Biomarkers, Immunology, Software, Tumour immunology
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > CRUK Cancer Trials Centre
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Cancer Bio
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Haematology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Oncology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Pathology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Respiratory Medicine
URI: https://discovery.ucl.ac.uk/id/eprint/10134831
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