Abstract 3136: HYENA detects non-coding genes activated by distal enhancers in cancer
Authors: Yu Anqi , Yesilkanal Ali E. , Thakur Ashish , Wang Fan , Wu Xiaoyang , Muir Alexander , He Xin , Spitz Francois , Yang Lixing 
Published: April 2023

Genome instability is a hallmark of cancer, resulting in the accumulation of mutation. Among different types of mutations, structural variants (SVs) widely spread in cancer genomes and can be important cancer drivers, demonstrated in multiple cancer types. SVs can induce oncogene activation by redirecting enhancers to promoter regions or disrupting chromatin topology. These events are called “enhancer hijacking” and known to upregulate oncogenes in multiple cancers. Enhancers are among the best understood cis-regulatory elements and are essential regulators for precise gene expression in normal tissue. Since SV associated gene deregulation has been shown in multiple cancer types, it is a feasible way to infer putative oncogenes by detecting enhancer hijacking events. Taking advantage of next generation sequencing, bioinformatic tools were developed to study pan-histology protein-coding gene deregulation caused by SVs. However, algorithms that can unbiasedly detect enhancer hijacking in both coding and non-coding genes are yet to be developed. Here we present a computational algorithm “HYENA” to identify putative oncogenes activated by enhancer hijacking using whole-genome sequencing and RNA sequencing data. It deploys rank-based regression model to test whether an SV breakpoint located close to a gene significantly increases the gene expression. Permutation tests were used to generate a false discovery rate for each gene. By benchmarking with existing tools serving similar purposes, we confirmed that HYENA has superior capabilities to infer enhancer hijacking events. We detected 192 oncogene candidates in 1,148 tumor samples from 25 cancer types. While confirming the known cases of enhancer hijacking, we also identified numerous novel oncogene candidates, of which a substantial proportion was non-coding genes. Specifically, we found that a long non-coding RNA TOB1-AS1 was activated by rearranged enhancers in 10% of pancreatic cancer samples. Furthermore, experimental validation with pancreatic cancer cell lines and immunodeficient mice indicated that high expression of TOB1-AS1 is capable to promote cancer cell invasion and tumor metastasis, suggesting it is a novel cancer driver. As the existing treatments for pancreatic cancer are largely inefficacious and patients still have poor prognosis, new targets are urgently needed to improve pancreatic cancer treatments. Although the molecular mechanisms underlying TOB1-AS1 promoted metastasis remain to be unveiled, this non-coding gene can be a promising target in the patients carrying this enhancer hijacking event. In summary, our results demonstrated that HYENA is a sensitive and reliable tool to infer enhancer hijacking activated oncogenes and spot new potential targets to treat cancer.

Citation Format: Anqi Yu, Ali E. Yesilkanal, Ashish Thakur, Fan Wang, Xiaoyang Wu, Alexander Muir, Xin He, Francois Spitz, Lixing Yang. HYENA detects non-coding genes activated by distal enhancers in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3136.