Evidence map›Paper›PMID 31186783›Full record

ArticleOncology letters2019

Gene set enrichment analysis and meta-analysis identified 12 key genes regulating and controlling the prognosis of lung adenocarcinoma.

Wenwu He, Liangmin Fu, Qunlun Yan, Qiuxi Zhou, Kun Yuan, Linxin Chen, Yongtao Han

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
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  4. Therapeutic targeting of STAT3 with small interference RNAs and antisense oligonucleotides embedded exosomes in liver fibrosis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2021
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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 3 institutions in 1 country.

Wenwu HeDepartment of Thoracic Surgery, Sichuan Cancer Hospital and Research Institute, Chengdu, Sichuan 610041, P.R. China.
Liangmin FuDepartment of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan 637000, P.R. China.
Qunlun YanDepartment of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan 637000, P.R. China.
Qiuxi ZhouDepartment of Respiratory Medicine, Nanchong Central Hospital, Nanchong, Sichuan 637000, P.R. China.
Kun YuanDepartment of Anesthesiology, North Sichuan Medical College, Nanchong, Sichuan 637000, P.R. China.
Linxin ChenDepartment of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan 637000, P.R. China.
Yongtao HanDepartment of Thoracic Surgery, Sichuan Cancer Hospital and Research Institute, Chengdu, Sichuan 610041, P.R. China.
North Sichuan Medical University · CNSichuan Cancer Hospital · CNNanchong Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the present study was to analyze lung adenocarcinoma-associated microarray data and identify potentially crucial genes. The gene expression profiles were downloaded from the Gene Expression Omnibus database and 6 datasets, of which 2 were discarded and 4 were retained, were preprocessed using packages in the R computing language. Subsequently, Gene Set Enrichment Analysis (GSEA) and meta-analysis was used to screen the common pathways and differentially expressed genes at the transcriptional level. The genes detected from GSEA through The Cancer Genome Atlas databases were subsequently examined, and the crucial genes by survival data were identified. Pathways of the crucial genes were obtained using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of the online website Database for Annotation, Visualization and Integrated Discovery (DAVID) tool, and the pathways of crucial genes that were upregulated or downregulated were matched using the Venn method to identify the common crucial pathways. Furthermore, on the basis of the common crucial pathways, key genes that are closely associated with the development and progression of lung adenocarcinoma were identified with the KEGG pathway of DAVID. Additional information was obtained through Gene Ontology annotation. A total of two key pathways, including cell cycle and DNA replication, as well as 12 key genes [DNA polymerase δ subunit 2, DNA replication licensing factor MCM4, MCM6, mitotic checkpoint serine/threonine-protein kinase BUB1, BUB1β, mitotic spindle assembly checkpoint protein MAD2A, dual specificity protein kinase TTK, M-phase inducer phosphatase 1, cell division control protein 45 homolog, cyclin-dependent kinase inhibitor 1C, pituitary tumor-transforming gene 1 protein and polo-like kinase 1] were identified. These key pathways and genes may be studied in future studies involving gene transfection/knockdown, which may provide insights into the prognosis of lung adenocarcinoma. Additional studies are required to confirm their biological function.

Indexed as

gene set enrichment analysiskey geneskey pathwayslung adenocarcinomameta-analysis

Identifiers

PMID31186783
PMCPMC6507356
OpenAlexW2938078272

What OpenQuestion holds

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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.