Distinct RNA-RNA spatial interaction sub-networks of tran-scription factors in human hepatoma cells

We applied the latest RIC-seq technology to study the RNA-RNA interactions in human liver HepG2 cells. Integrating ChIP-seq data with the RIC-seq data, we clas-sified various transcription factors (TFs) into three distinct clusters based on the spatial interaction levels of the uaRNA (RNA transcribed in promoter regions) and eRNA (RNA transcribed in enhancer regions) potentially transcribed by the TF binding sites. Using RIC-seq technology, we performed high-throughput sequencing of HepG2 cells and integrated publicly available HepG2 datasets to systematically an-alyze eRNA-uaRNA interactions. By combining this analysis with ChIP-seq, we classified 115 transcription factors (TFs) into three distinct clusters. Integrating Hi-C data, and clinical data from liver cancer patients, we further explored the ge-nomic characteristics of these TF clusters and examined their correlation with tumor patient prognosis, shedding light on their potential role in tumor initiation and pro-gression.