Evidence map›Paper›PMID 29593420›Full record

ArticleOncoTargets and therapy2018

Novel long noncoding RNA GACAT3 promotes colorectal cancer cell proliferation, invasion, and migration through miR-149.

Weiwei Zhou, Lei Wang, Yu Miao, Rongge Xing

Abstract read
In one paragraph

Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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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

21 citing papers in PubMed.

  1. Review
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  5. Tumor-derived exosomal non-coding RNAs as diagnostic biomarkers in cancer.Cellular and molecular life sciences : CMLS · 2022
    Review
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  8. LncRNAFrontiers in cell and developmental biology · 2022
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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.

Weiwei ZhouDepartment of Pathology, Central Hospital of Cangzhou, Hebei.
Lei WangDepartment of Pharmacy, Cangzhou Medical College, Hebei, China.
Yu MiaoDepartment of Pathology, Central Hospital of Cangzhou, Hebei.
Rongge XingDepartment of Pathology, Central Hospital of Cangzhou, Hebei.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo explore the expression and clinical significance of long noncoding RNA (lncRNA) gastric cancer-associated transcript 3 (GACAT3) in human colorectal cancer (CRC).

methodsExpression of GACAT3 in CRC tissues and cell lines was measured using quantitative real-time PCR. CCK-8 and colony formation assays were used to assess the effect of GACAT3 on CRC cell line proliferation. Transwell invasion and migration assays were performed to detect the effect of GACAT3 on CRC cell line invasion and migration. Bioinformatics prediction, luciferase reporter assay, and pull-down assay were used to determine if miR-149 was a target of GACAT3. In addition, we also conducted colony formation assays and invasion assays to verify that GACAT3 promotes tumor progression through miR-149. Finally, in vivo tumorigenesis studies were used to demonstrate subcutaneous tumor growth.

resultsIn the present study, we found that GACAT3 was highly expressed in CRC tissues and cell lines. Si-GACAT3 significantly decreased cell proliferation, motility, and invasiveness both in vitro and in vivo. We confirmed that downregulated GACAT3 significantly increased the expression of miR-149, and miR-149 binds to GACAT3 in a sequence-specific manner using luciferase reporter assays and pull-down assay. Further functional experiments indicated that GACAT3 could directly upregulate SP1 and STAT3 expressions by functioning as a competing endogenous RNA for miR-149, and consequentially, promoting CRC cell proliferation and invasion in vitro.

conclusionThis study demonstrated that GACAT3 promotes tumor progression through competitive binding to miR-149 and suggests a promising new strategy for anti-CRC therapy.

Indexed as

colorectal cancerGACAT3growthmetastasismiR-149SP1STAT3

Identifiers

PMID29593420
PMCPMC5865577

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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.