Cutaneous T cell lymphoma (CTCL) is a non-Hodgkin lymphoma of skin-homing T lymphocytes.,We performed exome and whole genome DNA sequence and RNA sequencing on purified CTCL and matched normal cells.,The results implicate mutations in 17 genes in CTCL pathogenesis, including genes involved in T cell activation and apoptosis, NFκB signaling, chromatin remodeling, and DNA damage response.,CTCL is distinctive in that somatic copy number variants (SCNVs) comprise 92% of all driver mutations (mean of 11.8 pathogenic SCNVs vs.,1.0 somatic single nucleotide variants per CTCL).,These findings have implications for novel therapeutics.
Melanoma is currently divided on a genetic level according to mutational status.,However, this classification does not optimally predict prognosis.,In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology.,Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes.,We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group.,Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes.,We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response.,In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02).,In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.