Evidence map›Paper›PMID 34302635›Full record

ArticleGenes & genomics2021

LncRNA SNHG20 promotes cell proliferation and invasion by suppressing miR-217 in ovarian cancer.

Xuefeng Xing, Ming An, Tonghua Chen

Open access · hybridAbstract read
In one paragraph

Article in Genes & genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 34% 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

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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

8 citing papers in PubMed, 12 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.

Xuefeng XingSanya People's Hospital, Sanya, Hainan, China.
Ming AnSanya People's Hospital, Sanya, Hainan, China. anming526899@163.com.
Tonghua ChenSanya People's Hospital, Sanya, Hainan, China.
Sanya Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOvarian cancer is the most common female gynecological malignancy. SNHG20, as a long non-coding RNA, has been proven to be an important regulator in the occurrence and development of various tumors. However, the potential mechanism of SNHG20 in ovarian cancer is unclear.

objectiveThe present study was aimed to investigate the functions and mechanisms of SNHG20 in ovarian cancer.

methodsThe expression of SNHG20 and miR-217 in ovarian cancer tissues and cell lines was detected by qRT-PCR. CCK-8 assay was used to measure cell proliferation in transfected cells. The transwell assay was used to detect the relative invasion rate of transfected cells. The putative binding sites between SNHG20 and miR-217 were predicted by software LncBase v.2, and the interaction between SNHG20 and miR-217 was confirmed by dual-luciferase reporter assays and RIP assay. The rescue experiments were used to illustrate potential mechanisms.

resultsSNHG20 was upregulated in ovarian cancer tissues and cell lines. Overexpression of SNHG20 promoted ovarian cancer cell proliferation and invasion. MiR-217 was downregulated in ovarian cancer tissues and cells, and was negatively regulated by SNHG20. Moreover, miR-217 overexpression inhibited ovarian cancer cell proliferation and invasion. Furthermore, miR-217 mimic reversed the inhibitory effect of SNHG20 overexpression on the biological behavior of ovarian cancer cells.

conclusionsSNHG20 promoted cell proliferation and invasion by sponging miR-217 in ovarian cancer. These results suggested that SNHG20 and miR-217 might provide new targets for therapeutic application in ovarian cancer.

Indexed as

Cell Line, TumorCell MovementCell ProliferationFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsNeoplasm InvasivenessOvarian NeoplasmsProtein BindingRNA, Long Noncodinglong non-coding RNA SNHG20, humanMicroRNAsMIRN217 microRNA, humanRNA, Long NoncodingInvasionLncRNA SNHG20MiR-217Ovarian cancerProliferation

Identifiers

PMID34302635
PMCPMC8376724
OpenAlexW3186117731

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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.