Evidence map›Paper›PMID 33269005›Full record

ArticleCancer management and research2020

Expression and Bioinformatics-Based Functional Analysis of UAP1 in Lung Adenocarcinoma.

Xianghai Wang, Xingwu Chen, Hongbing Liu

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 22 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 2 institutions in 1 country.

Xianghai WangDepartment of Respiratory Medicine, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui 241001, People's Republic of China.ORCID 0000-0002-4955-6531
Xingwu ChenDepartment of Respiratory Medicine, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui 241001, People's Republic of China.
Hongbing LiuDepartment of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu 210002, People's Republic of China.
Wannan Medical College · CNNanjing General Hospital of Nanjing Military Command · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LAD) is the most prevalent type of lung cancer. The abnormal expression of UDP-N-acetylglucosamine pyrophosphorylase 1 (UAP1) has been reported to be involved in many biological processes of cancer cells, but the expression of UAP1 in LAD is unclear.

methodsBioinformatics was used to analyse the LAD gene expression data and related clinical data in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. DAVID6.8 was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) signal pathway enrichment analyses of UAP1 expression-related genes. The STRING database was used to analyse protein-protein interaction (PPI) networks. RNA isolation and reverse transcription-quantitative polymerase chain reaction (RT‑qPCR) assay were used to detect the expression of UAP1 in tissues and blood samples.

resultsWe found that UAP1 was upregulated in LAD tissues and correlated with poor clinical outcome. GO analysis showed that these genes were enriched in biological processes and functions including intracellular transport, cellular protein catabolic process, and mitochondria (

conclusionUAP1 could be a novel diagnostic biomarker and a promising therapeutic target for LAD.

Indexed as

bioinformaticsexpressionlung adenocarcinomaprognosisUAP1

Identifiers

PMID33269005
PMCPMC7701148
OpenAlexW3109226163

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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.