Computational Reconstruction of Enhancer-Gene Regulatory Networks Altered in Cancer

Hariprakash, Judith Mary (2022). Computational Reconstruction of Enhancer-Gene Regulatory Networks Altered in Cancer. PhD thesis The Open University.



Enhancers are cis-acting non-coding regulatory elements that regulate the transcriptional output of target genes. Their dysregulation has been associated with various diseases including cancer. However, identification and characterisation of non-coding mutations that are relevant for tumorigenesis and prognosis remains a major challenge. We hypothesised that non-coding mutations in enhancers could significantly influence cancer prognosis and patient survival and thus can be exploited as novel prognostic biomarkers for better patient stratification and targeted therapy in lung cancer. Here we present the detection and characterisation of enhancer mutations in a genome-wide analysis of 159 lung cancer samples. To define enhancers across the genome we leverage the epigenomic signatures incorporating histone marks (H3K27ac) and chromatin accessibility (DNase I sensitivity or ATAC-seq) from 8 lung cell lines and primary tissue. We observe that the mutation burden at enhancers, promoters and exons is similar, whereas the mutation signature at these genomic locations varies significantly. We observe recurrent mutations in enhancers at base pair level and show their impact on target genes. We also demonstrate that genes have more than one enhancer and when they are mutated, the gene expression is altered. We also observe pathway-level aggregated enhancer mutations in cancer patients. These results contribute to a new approach towards the functional validation of non-coding mutations in cancer.

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