Evidence map›Paper›PMID 38847897›Full record

ReviewDiscover oncology2024

Exploring the enigma: history, present, and future of long non-coding RNAs in cancer.

Qais Ahmad Naseer, Abdul Malik, Fengyuan Zhang, Shengxia Chen

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

4 authors.

Qais Ahmad NaseerDepartment of Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, 212013, China.
Abdul MalikDepartment of Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, 212013, China.
Fengyuan ZhangDepartment of Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, 212013, China.
Shengxia ChenDepartment of Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, 212013, China. chensxia@ujs.edu.cn.

Funding

Basic Platform Project of the Ministry of Science and Technology of China No. TDRC-2019-194-30
6 · The paper itself

Abstract

Long noncoding RNAs (lncRNAs), which are more than 200 nucleotides in length and do not encode proteins, play crucial roles in governing gene expression at both the transcriptional and posttranscriptional levels. These molecules demonstrate specific expression patterns in various tissues and developmental stages, suggesting their involvement in numerous developmental processes and diseases, notably cancer. Despite their widespread acknowledgment and the growing enthusiasm surrounding their potential as diagnostic and prognostic biomarkers, the precise mechanisms through which lncRNAs function remain inadequately understood. A few lncRNAs have been studied in depth, providing valuable insights into their biological activities and suggesting emerging functional themes and mechanistic models. However, the extent to which the mammalian genome is transcribed into functional noncoding transcripts is still a matter of debate. This review synthesizes our current understanding of lncRNA biogenesis, their genomic contexts, and their multifaceted roles in tumorigenesis, highlighting their potential in cancer-targeted therapy. By exploring historical perspectives alongside recent breakthroughs, we aim to illuminate the diverse roles of lncRNA and reflect on the broader implications of their study for understanding genome evolution and function, as well as for advancing clinical applications.

Indexed as

BiogenesisGene expressionGenomic locationLncRNARegulatory mechanisms

Identifiers

PMID38847897
PMCPMC11161455

What OpenQuestion holds

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Registered trials

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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.