Chromatin accessibility and gene expression profiling of primary and metastatic ER+ breast cancer [RNA-seq]

We established peak-to-gene correlations within a 0.5 Mbp window between chromatin accessibility and gene expression, assessing significance using a conservative null model. To investigate transcription factor (TF) activity, we applied TOBIAS footprinting, which infers TF occupancy by integrating chromatin accessibility with motif information. Leveraging footprinting scores together with RNA-seq expression, we computed a Total Functional Score of Enhancer Elements to identify the most relevant TFs per tissue.

Using this approach, we linked TF motif activity at each peak with gene expression correlations, revealing peaks with tissue-specific TF activity and contrasting motif patterns between Liver and Breast. By connecting ATAC-seq peaks to RNA-seq expression, we identified putative metastasis driver genes, including 99 genes in Liver and 9 in Lung, as well as 23 genes shared across both metastatic sites, such as CCNF, SPINT1, and SLC2A1, which may play critical roles in metastatic progression.

Notably, we discovered that the majority of these genes are correlated 3 or more enhancers in the metastatic tissue but not in the primary tissue.