Evidence map›Paper›PMID 33217893›Full record

ArticleJournal of clinical medicine2020

Co-Expression of Coxsackievirus/Adenovirus Receptors and Desmoglein 2 in Lung Adenocarcinoma: A Comprehensive Analysis of Bioinformatics and Tissue Microarrays.

Ching-Fu Weng, Chi-Jung Huang, Mei-Hsuan Wu, Henry Hsin-Chung Lee, Thai-Yen Ling

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 49% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
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  4. Review
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

5 authors at 3 institutions in 1 country.

Ching-Fu WengDivision of Pulmonary Medicine, Department of Internal Medicine, Hsinchu Cathay General Hospital, Hsinchu 300, Taiwan.ORCID 0000-0002-1240-3793
Chi-Jung HuangMedical Research Center, Cathay General Hospital, Taipei 106, Taiwan.
Mei-Hsuan WuTeaching and Research Center, Hsinchu Cathay General Hospital, Hsinchu 300, Taiwan.ORCID 0000-0002-0090-323X
Henry Hsin-Chung LeeSchool of Medicine, Fu Jen Catholic University, New Taipei 242, Taiwan.
Thai-Yen LingDepartment and Graduate Institute of Pharmacology, National Taiwan University, Taipei 100, Taiwan.
Fu Jen Catholic University · TWNational Taiwan University · TWCathay General Hospital · TW

Funding

National Health Research Institutes NHRI-109BCCO-MF-202021-21
6 · The paper itself

Abstract

introductionCoxsackievirus/adenovirus receptors (CARs) and desmoglein-2 (DSG2) are similar molecules to adenovirus-based vectors in the cell membrane. They have been found to be associated with lung epithelial cell tumorigenesis and can be useful markers in predicting survival outcome in lung adenocarcinoma (LUAD).

methodsA gene ontology enrichment analysis disclosed that DSG2 was highly correlated with CAR. Survival analysis was then performed on 262 samples from the Cancer Genome Atlas, forming "Stage 1A" or "Stage 1B". We therefore analyzed a tissue microarray (TMA) comprised of 108 lung samples and an immunohistochemical assay. Computer counting software was used to calculate the H-score of the immune intensity. Cox regression and Kaplan-Meier analyses were used to determine the prognostic value.

results

conclusionsThe co-expression of CAR/DSG2 predicted a worse overall survival in LUAD. CAR combined with DSG2 expression can predict prognosis.

Indexed as

coxsackievirus and adenovirus receptordesmoglein-2immunohistochemistrylung adenocarcinomaprognosis prediction

Identifiers

PMID33217893
PMCPMC7698609
OpenAlexW3098248082

What OpenQuestion holds

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LicenceCC BY
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.