Evidence map›Paper›PMID 34676873›Full record

ReviewOncology reports2021

Interactions between long non‑coding RNAs and RNA‑binding proteins in cancer (Review).

Handong Huang, Lu Li, Kunming Wen

Open access · hybridAbstract readReview
In one paragraph

Review in Oncology reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

24 citing papers in PubMed, 43 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Handong HuangDepartment of Gastrointestinal Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Lu LiDepartment of Ophthalmology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Kunming WenDepartment of Gastrointestinal Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Zunyi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non‑coding RNAs (lncRNAs) fulfill important roles in the majority of cellular processes. Previous studies have demonstrated that lncRNAs are involved in the pathogenesis of various diseases, including cancer. However, to date, the functions of only a small number of the known lncRNAs have been well‑documented. lncRNAs comprise a class of multifunctional non‑coding transcripts that are able to interact with different types of biomolecules. Interactions between lncRNAs and RNA‑binding proteins (RBPs) provide an important mechanism through which lncRNAs exert their regulatory functions, mainly through findings on 'generalized RBPs'. Regulatory effects on lncRNAs mediated by RBPs have also been explored. Taking account of the research that has been completed to date, the continued and in‑depth study of the bidirectional interactions between lncRNAs and RBPs will prove to be of major importance for understanding the pathogenesis of cancer and for developing effective therapies. The present review aims to explore the interactions between lncRNAs and RBPs that have been investigated in cancer, taking into consideration several different aspects, including the regulation of expression, subcellular localization and the mediation of diverse functions.

Indexed as

HumansNeoplasmsRNA-Binding ProteinsRNA, Long NoncodingRNA-Binding ProteinsRNA, Long Noncodingcancerinteraction networklong non‑coding RNAsRNA‑binding proteinsRNA‑protein interaction

Identifiers

PMID34676873
PMCPMC8548813
OpenAlexW3206713747

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.