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

Item Type:Article
Title:Using DNA sequencing data to quantify T cell fraction and therapy response
Creators Name:Bentham, R. and Litchfield, K. and Watkins, T.B.K. and Lim, E.L. and Rosenthal, R. and Martínez-Ruiz, C. and Hiley, C.T. and Bakir, M.A. and Salgado, R. and Moore, D.A. and Jamal-Hanjani, M. and Swanton, C. and McGranahan, N.
Abstract:The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy. 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.
Source:Nature
ISSN:0028-0836
Publisher:Nature Publishing Group
Volume:597
Number:7877
Page Range:555-560
Date:23 September 2021
Additional Information:Roland Schwarz, Tom L. Kaufmann and Matthew Huska are members of the TRACERx Consortium.
Official Publication:https://doi.org/10.1038/s41586-021-03894-5
PubMed:View item in PubMed

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