Regulatory enhancer profiling of mesenchymal-type gastric cancer reveals subtype-specific epigenomic landscapes and targetable vulnerabilities

表观遗传学 增强子 生物 转录组 癌症研究 染色质免疫沉淀 计算生物学 DNA甲基化 基因表达 遗传学 基因 发起人
作者
Shamaine Wei Ting Ho,Taotao Sheng,Manjie Xing,Wen Fong Ooi,Chang Xu,Raghav Sundar,Kie Kyon Huang,Zhimei Li,Vikrant Kumar,Kalpana Ramnarayanan,Feng Zhu,Supriya Srivastava,Zul Fazreen Bin Adam Isa,Chukwuemeka George Anene-Nzelu,Milad Razavi-Mohseni,Dustin Shigaki,Haoran Ma,Angie Lay Keng Tan,Xuewen Ong,Ming Hui Lee
出处
期刊:Gut [BMJ]
卷期号:72 (2): 226-241 被引量:33
标识
DOI:10.1136/gutjnl-2021-326483
摘要

Objective Gastric cancer (GC) comprises multiple molecular subtypes. Recent studies have highlighted mesenchymal-subtype GC (Mes-GC) as a clinically aggressive subtype with few treatment options. Combining multiple studies, we derived and applied a consensus Mes-GC classifier to define the Mes-GC enhancer landscape revealing disease vulnerabilities. Design Transcriptomic profiles of ~1000 primary GCs and cell lines were analysed to derive a consensus Mes-GC classifier. Clinical and genomic associations were performed across >1200 patients with GC. Genome-wide epigenomic profiles (H3K27ac, H3K4me1 and assay for transposase-accessible chromatin with sequencing (ATAC-seq)) of 49 primary GCs and GC cell lines were generated to identify Mes-GC-specific enhancer landscapes. Upstream regulators and downstream targets of Mes-GC enhancers were interrogated using chromatin immunoprecipitation followed by sequencing (ChIP-seq), RNA sequencing, CRISPR/Cas9 editing, functional assays and pharmacological inhibition. Results We identified and validated a 993-gene cancer-cell intrinsic Mes-GC classifier applicable to retrospective cohorts or prospective single samples. Multicohort analysis of Mes-GCs confirmed associations with poor patient survival, therapy resistance and few targetable genomic alterations. Analysis of enhancer profiles revealed a distinctive Mes-GC epigenomic landscape, with TEAD1 as a master regulator of Mes-GC enhancers and Mes-GCs exhibiting preferential sensitivity to TEAD1 pharmacological inhibition. Analysis of Mes-GC super-enhancers also highlighted NUAK1 kinase as a downstream target, with synergistic effects observed between NUAK1 inhibition and cisplatin treatment. Conclusion Our results establish a consensus Mes-GC classifier applicable to multiple transcriptomic scenarios. Mes-GCs exhibit a distinct epigenomic landscape, and TEAD1 inhibition and combinatorial NUAK1 inhibition/cisplatin may represent potential targetable options.
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