Evidence map›Paper›PMID 36852072›Full record

ArticleHeliyon2023

Identification of non-coding RNAs and their functional network associated with optic nerve invasion in retinoblastoma.

Jie Sun, Lu Gan, Jie Ding, Ruiqi Ma, Jiang Qian, Kang Xue

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 37% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Jie SunDepartment of Ophthalmology, Eye & ENT Hospital of Fudan University, Shanghai, 200031, China.
Lu GanDepartment of Ophthalmology, Eye & ENT Hospital of Fudan University, Shanghai, 200031, China.
Jie DingDepartment of Ophthalmology, Eye & ENT Hospital of Fudan University, Shanghai, 200031, China.
Ruiqi MaDepartment of Ophthalmology, Eye & ENT Hospital of Fudan University, Shanghai, 200031, China.
Jiang QianDepartment of Ophthalmology, Eye & ENT Hospital of Fudan University, Shanghai, 200031, China.
Kang XueDepartment of Ophthalmology, Eye & ENT Hospital of Fudan University, Shanghai, 200031, China.
Eye & ENT Hospital of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optic nerve invasion (ONI) is an important high-risk feature and prognostic indicator of retinoblastoma (RB). Emerging evidence has revealed that non-coding RNAs (ncRNAs) play important roles in tumor perineural invasion (PNI). Nevertheless, the regulatory role of ncRNAs in the ONI of RB is poorly understood. In the current study, whole-transcriptome sequencing was performed to assess the expression profiles of ncRNAs and mRNAs in RB tissues, with or without ONI. Based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we predicted the biological functions of differentially expressed (DE) mRNAs. We then constructed competing endogenous RNA (ceRNA) regulatory networks based on bioinformatics analysis. The hsa_circ_0015965/lncRNA MEG3-hsa-miR-378a-5p-NOTCH1 pathway was selected and validated by real-time qPCR, western blotting, and dual luciferase reporter assays. Moreover, we demonstrated that NOTCH1 promotes the malignant progression of RB. Taken together, our results provide novel insights into the mechanism underlying optic nerve invasion in RB.

Indexed as

ceRNAncRNAOptic nerve invasionPerineural invasionRetinoblastoma

Identifiers

PMID36852072
PMCPMC9958441
OpenAlexW4321054299

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.