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Meta-Analysis
. 2021 Feb 17;11(1):3962.
doi: 10.1038/s41598-021-83352-4.

Spectrum of mutational signatures in T-cell lymphoma reveals a key role for UV radiation in cutaneous T-cell lymphoma

Collaborators, Affiliations
Meta-Analysis

Spectrum of mutational signatures in T-cell lymphoma reveals a key role for UV radiation in cutaneous T-cell lymphoma

Christine L Jones et al. Sci Rep. .

Abstract

T-cell non-Hodgkin's lymphomas develop following transformation of tissue resident T-cells. We performed a meta-analysis of whole exome sequencing data from 403 patients with eight subtypes of T-cell non-Hodgkin's lymphoma to identify mutational signatures and associated recurrent gene mutations. Signature 1, indicative of age-related deamination, was prevalent across all T-cell lymphomas, reflecting the derivation of these malignancies from memory T-cells. Adult T-cell leukemia-lymphoma was specifically associated with signature 17, which was found to correlate with the IRF4 K59R mutation that is exclusive to Adult T-cell leukemia-lymphoma. Signature 7, implicating UV exposure was uniquely identified in cutaneous T-cell lymphoma (CTCL), contributing 52% of the mutational burden in mycosis fungoides and 23% in Sezary syndrome. Importantly this UV signature was observed in CD4 + T-cells isolated from the blood of Sezary syndrome patients suggesting extensive re-circulation of these T-cells through skin and blood. Analysis of non-Hodgkin's T-cell lymphoma cases submitted to the national 100,000 WGS project confirmed that signature 7 was only identified in CTCL strongly implicating UV radiation in the pathogenesis of cutaneous T-cell lymphoma.

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Conflict of interest statement

Research support was provided by Galderma. The funder had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.

Figures

Figure 1
Figure 1
Comparison of the distribution of number of exomes sequenced with the US incidence rate of each subtype. Literature analysis identified 631 whole exome sequences performed on mature T-cell NHL samples. US Incidence rates are derived from the 2016 US lymphoid malignancy statistics which estimated 8,380 new cases of mature T-cell NHL in 2016.
Figure 2
Figure 2
Number of coding SNVs per sample across disease subtypes. Data were collated for those studies where full mutation lists were published and for subtypes where sequencing had been performed on at least 10 patients.
Figure 3
Figure 3
Recurrent driver gene mutations in mature T-cell NHL. Heatmap showing the number of patients with a given driver gene mutation for each subtype where a given variant occurred in three or more patients.
Figure 4
Figure 4
Mutational signatures identified in T-cell lymphoma. (a) matrix showing the percentage of mutations in each disease subtype assigned to the 30 COSMIC signatures. (b) plots showing the likelihood of each mutation in each trinucleotide context for Signatures 1 and 7 as per COSMIC mutational signatures v2 and the observed SNV catalogues for Sezary syndrome and mycosis fungoides.
Figure 5
Figure 5
Characteristic features of UV induced mutation are observed only in patients with cutaneous T-cell lymphoma. Whole genome sequencing data from the UK 100,000 genomes project comparing representative cutaneous and nodal T-cell lymphoma patients. The highlighted track on the circos plots is a rainfall diagram of SNVs where distance from the centre is proportional to the logarithm of the distance between adjacent SNVs. Cutaneous T-cell lymphoma patients have a characteristic inner ring of C>T variants due to CC>TT substitutions, which are also clear in the light green bar on the dinucleotide variants plot. Single nucleotide variants occurring within gene bodies were assessed to determine whether they affect the transcriptional or non-transcriptional strand. Significant transcriptional strand bias was observed for C>T mutations in cutaneous T-cell lymphoma but not nodal T-cell lymphoma indicating transcription-coupled nucleotide excision repair, a feature of UV induced mutation.
Figure 6
Figure 6
Patients with the STAT3 Y640F mutation showed significantly greater contribution of signature 5 to their mutational catalogue. Wilcoxon rank sum test was used to compare the contribution of each signature between the groups mutant or WT for a given mutation.
Figure 7
Figure 7
Patients with the IRF4 K59R mutation showed significantly greater contribution of signature 17 to their mutational catalogue. Wilcoxon rank sum test was used to compare the contribution of each signature between the groups mutant or WT for a given mutation.

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