Global identification and characterization of tRNA-derived RNA fragment landscapes across human cancers
Author(s) -
Xiwei Sun,
Juze Yang,
Mengqian Yu,
Dongxia Yao,
Liyuan Zhou,
Xufan Li,
Qiongzi Qiu,
Weiqiang Lin,
Bingjian Lü,
Enguo Chen,
Ping Wang,
Wantao Chen,
Sifeng Tao,
Haiming Xu,
Anna Marie Williams,
Yong Liu,
Xiaoqing Pan,
Allen W. Cowley,
Weiguo Lü,
Mingyu Liang,
Pengyuan Liu,
Yan Lü
Publication year - 2020
Publication title -
nar cancer
Language(s) - English
Resource type - Journals
ISSN - 2632-8674
DOI - 10.1093/narcan/zcaa031
Subject(s) - transfer rna , fragment (logic) , identification (biology) , computational biology , rna , biology , genetics , evolutionary biology , computer science , ecology , gene , algorithm
Transfer RNA-derived RNA fragments (tRFs) are a class of small non-coding RNAs that are abundant in many organisms, but their role in cancer has not been fully explored. Here, we report a functional genomic landscape of tRFs in 8118 specimens across 15 cancer types from The Cancer Genome Atlas. These tRFs exhibited characteristics of widespread expression, high sequence conservation, cytoplasmic localization, specific patterns of tRNA cleavage and conserved cleavage in tissues. A cross-tumor analysis revealed significant commonality among tRF expression subtypes from distinct tissues of origins, characterized by upregulation of a group of tRFs with similar size and activation of cancer-associated signaling. One of the largest superclusters was composed of 22 nt 3′-tRFs upregulated in 13 cancer types, all of which share the activation of Ras/MAPK, RTK and TSC/mTOR signaling. tRF-based subgrouping provided clinically relevant stratifications and significantly improved outcome prediction by incorporating clinical variables. Additionally, we discovered 11 cancer driver tRFs using an effective approach for accurately exploring cross-tumor and platform trends. As a proof of concept, we performed comprehensive functional assays on a non-microRNA driver tRF, 5′-IleAAT-8-1-L20, and validated its oncogenic roles in lung cancer in vitro and in vivo . Our study also provides a valuable tRF resource for identifying diagnostic and prognostic biomarkers, developing cancer therapy and studying cancer pathogenesis.
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