Evidence map›Paper›PMID 40425316›Full record

ArticleGenome research2025

Cancer driver topologically associated domains identify oncogenic and tumor-suppressive lncRNAs.

Ziyan Rao, Min Zhang, Shaodong Huang, Chenyang Wu, Yuheng Zhou, Weijie Zhang, Xia Lin, Dongyu Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

8 authors.

Ziyan RaoDepartment of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China.ORCID 0000-0002-9961-2036
Min ZhangZhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; zhaodongyu@bjmu.edu.cn minzh@zju.edu.cn.
Shaodong HuangDepartment of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Chenyang WuDepartment of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Yuheng ZhouDepartment of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Weijie ZhangZhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China.
Xia LinZhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Dongyu ZhaoDepartment of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China; zhaodongyu@bjmu.edu.cn minzh@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer long noncoding RNAs (lncRNAs) have been identified by experimental and in silico methods. However, current approaches for identifying cancer lncRNAs are not sufficient and effective. To uncover them, we focus on the core cancer driver lncRNAs, which directly interact with cancer driver protein-coding genes (PCGs). We investigate various aspects of cancer lncRNAs, including their expression patterns, genomic locations, and direct interactions with cancer driver PCGs, and developed a pipeline to identify candidate cancer driver lncRNAs. Finally, we validate the reliability of potential cancer driver lncRNAs through functional analysis of bioinformatics data and CRISPR-Cas9 knockout experiments. We find that cancer lncRNAs are more concentrated in cancer driver topologically associated domains (CDTs), and CDT is an important feature in identifying cancer lncRNAs. Moreover, cancer lncRNAs show a high tendency to be coexpressed with and bind to cancer driver PCGs. Utilizing these distinctive characteristics, we develop a pipeline

Indexed as

Genes, Tumor SuppressorNeoplasmsOncogenesRNA, Long NoncodingComputational BiologyCRISPR-Cas SystemsGene Expression Regulation, NeoplasticHumansRNA, Long Noncoding

Identifiers

PMID40425316
PMCPMC12315868

What OpenQuestion holds

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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.