Evidence map›Paper›PMID 33536022›Full record

ArticleCancer cell international2021

circ-ANXA7 facilitates lung adenocarcinoma progression via miR-331/LAD1 axis.

Yu Wang

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

16 citing papers in PubMed, 29 citations in OpenAlex.

  1. Review
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  5. Role of circular RNAs in lung cancer.Frontiers in genetics · 2024
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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

1 author at 1 institution in 1 country.

Yu WangDepartment of Medical Laboratory, Zhumadian City Central Hospital, No. 747 Zhonghua Avenue, Yicheng District, Zhumadian, 463000, Henan, China. zmdzxyy0396@163.com.ORCID http://orcid.org/0000-0002-3294-5549
Zhumadian Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer, with a poor prognosis. The roles of circular RNAs (circRNAs) in tumors have been initially clarified. In this study, we probed into the functions and underlying molecular mechanisms of circ-ANXA7 in LUAD.

methodsAccording to circRNA microarray analysis based on 40 pairs of LUAD tissues and non-tumor tissues, a novel circ-ANXA7 was up-regulated in LUAD, which was verified in LUAD tissues and cells by RT-qPCR. Correlation between its expression and clinical features of LUAD was analyzed. When transfected with sh-circ-ANXA7, proliferation, invasion, and migration of LUAD cells were determined by a series of functional assays. Furthermore, tumor growth was investigated in nude mice injected with sh-circ-ANXA7. Dual luciferase report and gain and loss assays were used to confirm the relationships between circ-ANXA7 and miR-331, miR-331 and LAD1.

resultscirc-ANXA7 was up-regulated in LUAD tissues and cells. Its high expression promoted proliferation, migration, and invasion of LUAD cells as well as tumor growth. High circ-ANXA7 expression usually predicted a poorer prognosis for LUAD patients. Furthermore, circ-ANXA7 could accelerate proliferation and invasion of LUAD cells by targeting miR-331. miR-331 directly bound to the 3'-UTR of LAD1. LAD1 induced proliferation and invasion of LUAD cells, which was reversed after co-transfection with circ-ANXA7 knockdown. LAD1 expression could be an independent prognostic marker for LUAD by univariate and multivariate analysis.

conclusionsOur research identified a novel circ-ANXA7 for LUAD, which could facilitate proliferation, migration, and invasion of LUAD cells by miR-331/ LAD1 axis. circ-ANXA7 could become a promising prognosis and treatment target for LUAD.

Indexed as

circ-ANXA7InvasionLAD1Lung adenocarcinomamiR-331Proliferation

Identifiers

PMID33536022
PMCPMC7860208
OpenAlexW3127646397

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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.