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

Shamaine Wei Ting Ho(Agency for Science, Technology and Research), Taotao Sheng(Agency for Science, Technology and Research), Manjie Xing(Agency for Science, Technology and Research), Wen Fong Ooi(Agency for Science, Technology and Research), Chang Xu(Duke-NUS Medical School), Raghav Sundar(Yong In University), Kie Kyon Huang(Duke-NUS Medical School), Zhimei Li(National Cancer Centre Singapore), Vikrant Kumar(Duke-NUS Medical School), Kalpana Ramnarayanan(Duke-NUS Medical School), Feng Zhu(Yong In University), Supriya Srivastava(Yong In University), Zul Fazreen Bin Adam Isa(Agency for Science, Technology and Research), Chukwuemeka George Anene-Nzelu(Agency for Science, Technology and Research), Milad Razavi-Mohseni(Johns Hopkins University), Dustin Shigaki(Johns Hopkins University), Haoran Ma(Duke-NUS Medical School), Angie Lay Keng Tan(Duke-NUS Medical School), Xuewen Ong(Duke-NUS Medical School), Ming Hui Lee(Duke-NUS Medical School), Su Ting Tay(Duke-NUS Medical School), Yu Amanda Guo(Agency for Science, Technology and Research), Weitai Huang(Agency for Science, Technology and Research), Shang Li(National University of Singapore), M Beer(Johns Hopkins University), Roger Foo(Agency for Science, Technology and Research), Ming Teh(National University of Singapore), Anders J. Skanderup(Agency for Science, Technology and Research), Bin Tean Teh(Agency for Science, Technology and Research), Patrick Tan(Agency for Science, Technology and Research)
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Abstract

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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