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Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer

基因签名 转录组 代谢组学 生物 腺癌 癌症研究 基因表达谱 肺癌 基因 代谢物 生物信息学 癌症 基因表达 计算生物学 肿瘤科 医学 遗传学 内分泌学
作者
Jose Thaiparambil,Jianfeng Dong,Sandra L. Grimm,Dimuthu Perera,Chandra Shekar R. Ambati,Vasanta Putluri,Matthew J. Robertson,Tajhal D. Patel,Brandon Mistretta,Preethi H. Gunaratne,Min P. Kim,Jason T. Yustein,Nagireddy Putluri,Cristian Coarfa,Randa El‐Zein
出处
期刊:Cancer Medicine [Wiley]
卷期号:12 (1): 584-596 被引量:7
标识
DOI:10.1002/cam4.4933
摘要

Non-small cell lung cancer (NSCLC) comprises the majority (~85%) of all lung tumors, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being the most frequently diagnosed histological subtypes. Multi-modal omics profiling has been carried out in NSCLC, but no studies have yet reported a unique metabolite-related gene signature and altered metabolic pathways associated with LUAD and LUSC.We integrated transcriptomics and metabolomics to analyze 30 human lung tumors and adjacent noncancerous tissues. Differential co-expression was used to identify modules of metabolites that were altered between normal and tumor.We identified unique metabolite-related gene signatures specific for LUAD and LUSC and key pathways aberrantly regulated at both transcriptional and metabolic levels. Differential co-expression analysis revealed that loss of coherence between metabolites in tumors is a major characteristic in both LUAD and LUSC. We identified one metabolic onco-module gained in LUAD, characterized by nine metabolites and 57 metabolic genes. Multi-omics integrative analysis revealed a 28 metabolic gene signature associated with poor survival in LUAD, with six metabolite-related genes as individual prognostic markers.We demonstrated the clinical utility of this integrated metabolic gene signature in LUAD by using it to guide repurposing of AZD-6482, a PI3Kβ inhibitor which significantly inhibited three genes from the 28-gene signature. Overall, we have integrated metabolomics and transcriptomics analyses to show that LUAD and LUSC have distinct profiles, inferred gene signatures with prognostic value for patient survival, and identified therapeutic targets and repurposed drugs for potential use in NSCLC treatment.

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