Evidence map›Paper›PMID 34399788›Full record

ArticleWorld journal of surgical oncology2021

Effects of EFNA1 on cell phenotype and prognosis of esophageal carcinoma.

Yongqiang Zhang, Jinning Zhang, Guanlong Pan, Tianhao Guan, Changhao Zhang, An Hao, Yan Li, Hai Ren

Open access · goldAbstract read
In one paragraph

Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 57% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

8 authors at 1 institution in 1 country.

Yongqiang ZhangWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China.
Jinning ZhangWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China.
Guanlong PanWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China.
Tianhao GuanWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China.
Changhao ZhangWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China.
An HaoWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China.
Yan LiWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China.
Hai RenWard 2, Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Qiqihar Medical College, No. 27, Taishun Street, Tiefeng District, Qiqihar, 161000, Heilongjiang Province, China. renhai20210128@126.com.
Qiqihar Medical University · CN

Funding

Qiqihar City Science and Technology Plan Project SFGG-201642
6 · The paper itself

Abstract

backgroundTo investigate the expression and clinical significance of EFNA1 in broad-spectrum tumors, and to evaluate its relationship with prognosis and biological functions of esophageal carcinoma (ESCA).

methodsEFNA1 expression in various cancers was analyzed according to the data in the TCGA database. The clinical data were integrated, to analyze the relationship with ESCA clinical parameters and prognosis, and EFNA1 expression in ESCA tissue samples was detected by immunohistochemistry (IHC). Based on bioinformatics, the functional background of EFNA1 overexpression was analyzed. EFNA1 knockout cell model was established by EFNA1-shRNA transfecting ESCA cells, and the effect of knocking down EFNA1 on the proliferation of ESCA cells was detected by MTT.

resultsAmong 7563 samples from TCGA, the EFNA1 gene highly expressed in 15 samples with common cancers and endangered the prognosis of patients with tumors. Its overexpression in ESCA and its influence on the prognosis were most significant. EFNA1 expression in 80 samples with ESCA and their paired samples was tested by IHC to verify its high expression (paired t test, P < 0.001) in ESCA tissues. It was found that EFNA1 expression was related to clinical factors (TNM staging, P = 0.031; lymph node metastasis, P = 0.043; infiltration, P = 0.016). Meanwhile, EFNA1 was found to be an independent risk factor based on the COX multi-factor analysis. And to further explore the importance of EFNA1 in tumors, EC-9706 and ECA109 cells were screened from 8 ESCA-related cell lines to build EFNA1 knockdown cell models. The results showed that EFNA1 knockdown significantly inhibited the proliferation of tumor cells (P < 0.05). In terms of molecular mechanism, EFNA1 related genes were significantly enriched in the proliferative pathway according to the pathway enrichment analysis. It was found that knocking down EFNA1 did inhibit cell proliferation based on cell experiments.

conclusionsEFNA1 overexpression in ESCA tissue is related to the prognosis of patients. Knocking down EFNA1 can significantly inhibit the proliferation of ESCA cells.

Indexed as

CarcinomaEsophageal NeoplasmsComputational BiologyHumansPhenotypePrognosisCell proliferationEFNA1Esophageal carcinoma, Prognosis

Identifiers

PMID34399788
PMCPMC8369630
OpenAlexW3193679386

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Registered trials

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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.