Evidence map›Paper›PMID 31816603›Full record

ArticleAging2019

Identification of differentially expressed genes in non-small cell lung cancer.

Ke Wang, Ruo Chen, Zhuan Feng, Yu-Meng Zhu, Xiu-Xuan Sun, Wan Huang, Zhi-Nan Chen

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

22 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
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  5. ASPM promotes ATR-CHK1 activation and stabilizes stalled replication forks in response to replication stress.Proceedings of the National Academy of Sciences of the United States of America · 2022
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  14. Micro RNA-148a Targets Bcl-2 in Patients with Non-Small Cell Lung Cancer.Asian Pacific journal of cancer prevention : APJCP · 2021
    Article
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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

7 authors at 1 institution in 1 country.

Ke WangNational Translational Science Center for Molecular Medicine and Department of Cell Biology, Fourth Military Medical University, Shaanxi 710032, China.
Ruo ChenNational Translational Science Center for Molecular Medicine and Department of Cell Biology, Fourth Military Medical University, Shaanxi 710032, China.
Zhuan FengNational Translational Science Center for Molecular Medicine and Department of Cell Biology, Fourth Military Medical University, Shaanxi 710032, China.
Yu-Meng ZhuNational Translational Science Center for Molecular Medicine and Department of Cell Biology, Fourth Military Medical University, Shaanxi 710032, China.
Xiu-Xuan SunNational Translational Science Center for Molecular Medicine and Department of Cell Biology, Fourth Military Medical University, Shaanxi 710032, China.
Wan HuangNational Translational Science Center for Molecular Medicine and Department of Cell Biology, Fourth Military Medical University, Shaanxi 710032, China.
Zhi-Nan ChenNational Translational Science Center for Molecular Medicine and Department of Cell Biology, Fourth Military Medical University, Shaanxi 710032, China.
Air Force Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the most common malignant tumor and the leading cause of cancer-related deaths worldwide. Because current treatments for advanced non-small cell lung cancer (NSCLC), the most prevalent lung cancer histological subtype, show limited efficacy, screening for tumor-associated biomarkers using bioinformatics reflects the hope to improve early diagnosis and prognosis assessment. In our study, a Gene Expression Omnibus dataset was analyzed to identify genes with prognostic significance in NSCLC. Upon comparison with matched normal tissues, 118 differentially expressed genes (DEGs) were identified in NSCLC, and their functions were explored through bioinformatics analyses. The most significantly upregulated DEGs were TOP2A, SLC2A1, TPX2, and ASPM, all of which were significantly associated with poor overall survival (OS). Further analysis revealed that TOP2A had prognostic significance in early-stage lung cancer patients, and its expression correlated with levels of immune cell infiltration, especially dendritic cells (DCs). Our study provides a dataset of potentially prognostic NSCLC biomarkers, and highlights TOP2A as a valuable survival biomarker to improve prediction of prognosis in NSCLC.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungDatabases, FactualFemaleGene Expression Regulation, NeoplasticHumansMaleTranscriptomeUp-RegulationBiomarkers, TumorbioinformaticsbiomarkersNSCLCTOP2A

Identifiers

PMID31816603
PMCPMC6932904
OpenAlexW2995310639

What OpenQuestion holds

Textmetadata
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.