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eaQTLdb:跨癌症类型的增强子活性数量性状基因座图谱。

eaQTLdb: An atlas of enhancer activity quantitative trait loci across cancer types.

作者信息

Yuan Jiapei, Tong Yang, Liu Xiaochuan, Li Mulin Jun, Zhang Qiang, Yang Yang

机构信息

Department of Geriatrics, Tianjin Medical University General Hospital, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Center for Reproductive Medicine of Tianjin Medical University Second Hospital, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.

State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.

出版信息

Int J Cancer. 2023 Jul 1;153(1):111-119. doi: 10.1002/ijc.34481. Epub 2023 Mar 3.

Abstract

Enhancers are key regulatory elements that exert crucial roles in diverse biological processes, including tumorigenesis and cancer development. Active enhancers could produce transcripts termed enhancer RNAs (eRNAs), which could be used as an index of enhancer activity. Here, we present a versatile data portal, enhancer activity quantitative trait loci database (eaQTLdb; http://www.bioailab.com:3838/eaQTLdb), for exploring the effects of genetic variants on enhancer activity and prioritizing candidate variants across different cancer types. By leveraging the accumulated multiomics data, we systematically identified genetic variants which influence enhancer activity in different cancer types, termed as eaQTLs. We have linked the eaQTLs to hallmarks of cancer and patients' overall survival to illustrate their potential biological roles in cancer development and progression. Notably, eaQTLs associated with the infiltration abundance of 24 different immune cell types were identified and incorporated into eaQTLdb. In addition, we applied colocalization analyses to examine 59 complex diseases and traits to identify eaQTLs colocalized with diseases/traits GWAS signals. Overall, eaQTLdb, incorporating a rich resource for exploration of eaQTLs in different cancer types, will not only benefit users in prioritizing candidate genetic variants and enhancers, but also help researchers decipher the roles of eaQTLs in the dysregulated pathways of cancer and tumor immune microenvironment, opening new diagnostic and therapeutic avenues in precise medicine.

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