Whole-genome sequencing of CTCLs identifies novel putative driver genes and stage-specific genetic alterations.
PD1 deletions lead to reversal of T-cell exhaustion signatures in humans and mice and are associated with a worse prognosis.
Cutaneous T-cell lymphomas (CTCLs) are a clinically heterogeneous collection of lymphomas of the skin-homing T cell. To identify molecular drivers of disease phenotypes, we assembled representative samples of CTCLs from patients with diverse disease subtypes and stages. Via DNA/RNA-sequencing, immunophenotyping, and ex vivo functional assays, we identified the landscape of putative driver genes, elucidated genetic relationships between CTCLs across disease stages, and inferred molecular subtypes in patients with stage-matched leukemic disease. Collectively, our analysis identified 86 putative driver genes, including 19 genes not previously implicated in this disease. Two mutations have never been described in any cancer. Functionally, multiple mutations augment T-cell receptor–dependent proliferation, highlighting the importance of this pathway in lymphomagenesis. To identify putative genetic causes of disease heterogeneity, we examined the distribution of driver genes across clinical cohorts. There are broad similarities across disease stages. Many driver genes are shared by mycosis fungoides (MF) and Sezary syndrome (SS). However, there are significantly more structural variants in leukemic disease, leading to highly recurrent deletions of putative tumor suppressors that are uncommon in early-stage skin-centered MF. For example, TP53 is deleted in 7% and 87% of MF and SS, respectively. In both human and mouse samples, PD1 mutations drive aggressive behavior. PD1 wild-type lymphomas show features of T-cell exhaustion. PD1 deletions are sufficient to reverse the exhaustion phenotype, promote a FOXM1-driven transcriptional signature, and predict significantly worse survival. Collectively, our findings clarify CTCL genetics and provide novel insights into pathways that drive diverse disease phenotypes.