Deciphering the genomic regulatory code of enhancers is a key challenge in biology as this code underlies cellular identity. A better understanding of how enhancers work will improve the interpretation of non-coding genome variation, and empower the generation of cell type specific drivers for gene therapy. Here we explore the combination of deep learning and cross-species chromatin accessibility profiling to build explainable enhancer models. We apply this strategy to decipher the enhancer code in melanoma, a relevant case study due to the presence of distinct melanoma cell states. We trained and validated a deep learning model, called DeepMEL, using chromatin accessibility data of 26 melanoma samples across six different species. We demonstrate the accuracy of DeepMEL predictions on the CAGI5 challenge, where it significantly outperforms existing models on the melanoma enhancer of IRF4. Next, we exploit DeepMEL to analyse enhancer architectures and identify accurate transcription factor binding sites for the core regulatory complexes in the two different melanoma states, with distinct roles for each transcription factor, in terms of nucleosome displacement
Background One-third of cancers activate endogenous synthesis of serine/glycine, and can become addicted to this pathway to sustain proliferation and survival. Mechanisms driving this metabolic rewiring remain largely unknown. Methods NKX2–1 overexpressing and NKX2–1 knockdown/knockout T-cell leukaemia and lung cancer cell line models were established to study metabolic rewiring using ChIP-qPCR, immunoblotting, mass spectrometry, and proliferation and invasion assays. Findings and therapeutic relevance were validated in mouse models and confirmed in patient datasets. Results Exploring T-cell leukaemia, lung cancer and neuroendocrine prostate cancer patient datasets highlighted the transcription factor NKX2–1 as putative driver of serine/glycine metabolism. We demonstrate that transcription factor NKX2–1 binds and transcriptionally upregulates serine/glycine synthesis enzyme genes, enabling NKX2–1 expressing cells to proliferate and invade in serine/glycine-depleted conditions. NKX2–1 driven serine/glycine synthesis generates nucleotides and redox molecules, and is associated with an altered cellular lipidome and methylome. Accordingly, NKX2–1 tumour-bearing mice display enhanced tumour aggressiveness associated with systemic metabolic rewiring. Therapeutically, NKX2–1-expressing cancer cells are more sensitive to serine/glycine conversion inhibition by repurposed anti-depressant sertraline, and to etoposide chemotherapy. Conclusion Collectively, we identify NKX2–1 as a novel transcriptional regulator of serine/glycine synthesis addiction across cancers, revealing a therapeutic vulnerability of NKX2–1-driven cancers.
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