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BMC Med Genomics. 2018 Dec 31;11(Suppl 6):114. doi: 10.1186/s12920-018-0430-2.

CRlncRNA: a manually curated database of cancer-related long non-coding RNAs with experimental proof of functions on clinicopathological and molecular features.

Author information

1
CAS Key Laboratory of Tropical Plant Resources and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Yunnan, 666303, People's Republic of China.
2
Institute of Medical Sciences, Xiangya Hospital, Central South University, Changsha, 410008, People's Republic of China.
3
University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.
4
CAS Key Laboratory of Tropical Plant Resources and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Yunnan, 666303, People's Republic of China. lijing3@xtbg.ac.cn.
5
CAS Key Laboratory of Tropical Plant Resources and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Yunnan, 666303, People's Republic of China. liuchangning@xtbg.ac.cn.

Abstract

BACKGROUND:

Recent studies demonstrated that long non-coding RNAs (lncRNAs) could be intricately implicated in cancer-related molecular networks, and related to cancer occurrence, development and prognosis. However, clinicopathological and molecular features for these cancer-related lncRNAs, which are very important in bridging lncRNA basic research with clinical research, fail to well settle to integration.

RESULTS:

After manually reviewing more than 2500 published literature, we collected the cancer-related lncRNAs with the experimental proof of functions. By integrating from literature and public databases, we constructed CRlncRNA, a database of cancer-related lncRNAs. The current version of CRlncRNA embodied 355 entries of cancer-related lncRNAs, covering 1072 cancer-lncRNA associations regarding to 76 types of cancer, and 1238 interactions with different RNAs and proteins. We further annotated clinicopathological features of these lncRNAs, such as the clinical stages and the cancer hallmarks. We also provided tools for data browsing, searching and download, as well as online BLAST, genome browser and gene network visualization service.

CONCLUSIONS:

CRlncRNA is a manually curated database for retrieving clinicopathological and molecular features of cancer-related lncRNAs supported by highly reliable evidences. CRlncRNA aims to provide a bridge from lncRNA basic research to clinical research. The lncRNA dataset collected by CRlncRNA can be used as a golden standard dataset for the prospective experimental and in-silico studies of cancer-related lncRNAs. CRlncRNA is freely available for all users at http://crlnc.xtbg.ac.cn .

KEYWORDS:

Cancer; Clinicopathological feature; Database; Functional experiment; Long noncoding RNA

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