Melanoma is the most aggressive type of skin cancer, with increasing incidence worldwide. Advances in targeted therapy and immunotherapy have improved the survival of melanoma patients experiencing recurrent disease, but unfortunately treatment resistance frequently reduces patient survival. Resistance to targeted therapy is associated with transcriptomic changes and has also been shown to be accompanied by increased expression of programmed death ligand 1 (PD-L1), a potent inhibitor of immune response. Intrinsic upregulation of PD-L1 is associated with genome-wide DNA hypomethylation and widespread alterations in gene expression in melanoma cell lines. However, an in-depth analysis of the transcriptomic landscape of melanoma cells with intrinsically upregulated PD-L1 expression is lacking. To determine the transcriptomic landscape of intrinsically upregulated PD-L1 expression in melanoma, we investigated transcriptomes in melanomas with constitutive versus inducible PD-L1 expression (referred to as PD-L1CON and PD-L1IND). RNA-Seq analysis was performed on seven PD-L1CON melanoma cell lines and ten melanoma cell lines with low inducible PD-L1IND expression. We observed that PD-L1CON melanoma cells had a reprogrammed transcriptome with a characteristic pattern of dedifferentiated gene expression, together with active interferon (IFN) and tumour necrosis factor (TNF) signalling pathways. Furthermore, we identified key transcription factors that were also differentially expressed in PD-L1CON versus PD-L1IND melanoma cell lines. Overall, our studies describe transcriptomic reprogramming of melanomas with PD-L1CON expression.
Sequencing-based genome-wide DNA methylation, gene expression studies and associated data on paired colorectal cancer (CRC) primary and liver metastasis are very limited. We have profiled the DNA methylome and transcriptome of matched primary CRC and liver metastasis samples from the same patients. Genome-scale methylation and expression levels were examined using Reduced Representation Bisulfite Sequencing (RRBS) and RNA-Seq, respectively. To investigate DNA methylation and expression patterns, we generated a total of 1.01 × 109 RRBS reads and 4.38 × 108 RNA-Seq reads from the matched cancer tissues. Here, we describe in detail the sample features, experimental design, methods and bioinformatic pipeline for these epigenetic data. We demonstrate the quality of both the samples and sequence data obtained from the paired samples. The sequencing data obtained from this study will serve as a valuable resource for studying underlying mechanisms of distant metastasis and the utility of epigenetic profiles in cancer metastasis.