Evidence map›Paper›PMID 31302496›Full record

ArticleMolecular therapy. Nucleic acids2019

Identifying Cancer Driver lncRNAs Bridged by Functional Effectors through Integrating Multi-omics Data in Human Cancers.

Yong Zhang, Gaoming Liao, Jing Bai, Xinxin Zhang, Liwen Xu, Chunyu Deng, Min Yan, Aimin Xie, Tao Luo, Zhilin Long and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular therapy. Nucleic acids, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 30 citations in OpenAlex.

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  15. Illuminating lncRNA Function Through Target Prediction.Methods in molecular biology (Clifton, N.J.) · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Yong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Gaoming LiaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Jing BaiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Xinxin ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Liwen XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Chunyu DengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Min YanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Aimin XieCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Tao LuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Zhilin LongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China.
Yun XiaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China; Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang 150086, China. Electronic address: xiaoyun@ems.hrbmu.edu.cn.
Xia LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150086, China; Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang 150086, China. Electronic address: lixia@hrbmu.edu.cn.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accumulation of somatic driver mutations in the human genome enables cells to gradually acquire a growth advantage and contributes to tumor development. Great efforts on protein-coding cancer drivers have yielded fruitful discoveries and clinical applications. However, investigations on cancer drivers in non-coding regions, especially long non-coding RNAs (lncRNAs), are extremely scarce due to the limitation of functional understanding. Thus, to identify driver lncRNAs integrating multi-omics data in human cancers, we proposed a computational framework, DriverLncNet, which dissected the functional impact of somatic copy number alteration (CNA) of lncRNAs on regulatory networks and captured key functional effectors in dys-regulatory networks. Applying it to 5 cancer types from The Cancer Genome Atlas (TCGA), we portrayed the landscape of 117 driver lncRNAs and revealed their associated cancer hallmarks through their functional effectors. Moreover, lncRNA RP11-571M6.8 was detected to be highly associated with immunotherapeutic targets (PD-1, PD-L1, and CTLA-4) and regulatory T cell infiltration level and their markers (IL2RA and FCGR2B) in glioblastoma multiforme, highlighting its immunosuppressive function. Meanwhile, a high expression of RP11-1020A11.1 in bladder carcinoma was predictive of poor survival independent of clinical characteristics, and CTD-2256P15.2 in lung adenocarcinoma responded to the sensitivity of methyl ethyl ketone (MEK) inhibitors. In summary, this study provided a framework to decipher the mechanisms of tumorigenesis from driver lncRNA level, established a new landscape of driver lncRNAs in human cancers, and offered potential clinical implications for precision oncology.

Indexed as

cancer driverscancer hallmarkscopy number alterationsimmunosuppressionlong non-coding RNAs

Identifiers

PMID31302496
PMCPMC6626872
OpenAlexW2949384887

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.