Evidence map›Paper›PMID 39895777›Full record

ReviewJournal of Cancer2025

The regulatory role and therapeutic potential of long non-coding RNA in non-small cell lung cancer.

Sunming Xia, Xuean Lu, Weier Wang, Xinyi Pan, Jiaqi Cui, Shengjie Wang, Zhao Wang

Abstract readReview
In one paragraph

Review in Journal of Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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

7 authors.

Sunming XiaDonghai County People's Hospital affiliated to Kangda College of Nanjing Medical University, Lianyungang 222300, Jiangsu, China.
Xuean LuDonghai County People's Hospital affiliated to Kangda College of Nanjing Medical University, Lianyungang 222300, Jiangsu, China.
Weier WangSchool of Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu, China.
Xinyi PanDepartment of Basic Medicine, Kangda College of Nanjing Medical University, Lianyungang 222000, Jiangsu, China.
Jiaqi CuiDepartment of Basic Medicine, Kangda College of Nanjing Medical University, Lianyungang 222000, Jiangsu, China.
Shengjie WangDonghai County People's Hospital affiliated to Kangda College of Nanjing Medical University, Lianyungang 222300, Jiangsu, China.
Zhao WangDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) being the predominant subtype. Recent advances in transcriptome sequencing have highlighted the critical role of long non-coding RNAs (lncRNAs) in NSCLC, with lncRNAs influencing gene expression through epigenetic, transcriptional, and post-transcriptional mechanisms. Despite the growing understanding of lncRNAs, challenges such as delayed diagnosis and drug resistance continue to complicate NSCLC management. This review explores novel findings in the role of lncRNAs (e.g., MALAT1, HOTAIR, and GAS5) in NSCLC, with a particular focus on their encoded small peptides and N6-methyladenosine (m6A) modifications. We further discuss how the interplay between lncRNAs, their encoded peptides, and m6A modifications can provide new strategies for improving NSCLC diagnosis, treatment, and overcoming drug resistance. This review also highlights emerging research avenues that could lead to innovative clinical interventions in NSCLC.

Indexed as

LncRNAsmetastasisNSCLCproliferationtargeted therapies

Identifiers

PMID39895777
PMCPMC11786035

What OpenQuestion holds

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LicenceCC BY
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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.