Item Type: | Article |
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Title: | Using DNA sequencing data to quantify T cell fraction and therapy response |
Creators Name: | Bentham, R., Litchfield, K., Watkins, T.B.K., Lim, E.L., Rosenthal, R., Martínez-Ruiz, C., Hiley, C.T., Bakir, M.A., Salgado, R., Moore, D.A., Jamal-Hanjani, M., 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. |
Keywords: | Adenocarcinoma of Lung, alpha-beta T-Cell Antigen Receptors, Aspartic Acid Endopeptidases, Cohort Studies, Exome, Immunotherapy, Mutation, Neoplasms, Prognosis, T-Lymphocytes, Tumor-Infiltrating Lymphocytes, Whole Exome Sequencing |
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. - Copyright © The Author(s), under exclusive licence to Springer Nature Limited 2021 |
Official Publication: | https://doi.org/10.1038/s41586-021-03894-5 |
External Fulltext: | View full text on external repository or document server |
PubMed: | View item in PubMed |
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