Evidence map›Paper›PMID 35117502›Full record

ArticleTranslational cancer research2020

The comprehensive investigation of transcription factor AP-2 alpha in lung adenocarcinoma.

Hongli Liao, Peng Lin

Open access · diamondAbstract read
In one paragraph

Article in Translational cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.2field-weighted citation impact, top 51% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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  3. Oncology research · 2025
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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

2 authors at 2 institutions in 1 country.

Hongli LiaoPathology Department, Wenzhou Central Hospital, Wenzhou 325000, China.
Peng LinPathology Department, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Wenzhou Central Hospital · CNWenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTranscription factor AP-2 alpha (TFAP2A) has been reported to participate in various tumors. However, the transcriptional levels and prognostic values of TFAP2A remain elusive in lung adenocarcinoma (LUAD). The purpose of the present study was to investigate the impact of the TFAP2A in LUAD.

methodsThe transcriptional levels and prognostic effects of TFAP2A were explored in patients with LUAD using various online databases, including the GEPIA, Oncomine, and Kaplan-Meier plotter databases. Meanwhile, meta-analyses were performed to verify the expression levels and prognostic effects of TFAP2A in LUAD using the Lung Cancer Explorer (LCE) database. In addition, target genes of TFAP2A were identified in the Animal TFDB3.0 dataset.

resultsOur comprehensively study indicated the mRNA expression levels of TFAP2A in LUAD were significantly higher than that of normal controls. In the survival analyses, higher TFAP2A levels were related to the shortened survival time of patients with LUAD. Meanwhile, the meta-analyses based on the LCE database also suggested the overexpressed TFAP2A led to worsen prognosis of patients with LUAD. Finally, the cell division cycle 6 (CDC6) and aurora kinase A (AURKA) were regarded as two target genes of TFAP2A.

conclusionsWe have performed comprehensive analyses for TFAP2A in patients with LUAD. Patients with higher TFAP2A levels demonstrated worsen prognosis than those with lower TFAP2A levels. The CDC6 and AURKA might be two target genes of TFAP2A. Further molecular biological experiments were required to study the mechanisms of TFAP2A in LUAD.

Indexed as

Lung adenocarcinomaprognosistranscription factor AP-2 alpha (TFAP2A)

Identifiers

PMID35117502
PMCPMC8799082
OpenAlexW3010158617

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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.