Evidence map›Paper›PMID 31516585›Full record

ArticleOncology letters2019

Identification of candidate genes associated with the pathogenesis of small cell lung cancer via integrated bioinformatics analysis.

Yi Liao, Guofang Yin, Xue Wang, Ping Zhong, Xianming Fan, Chengliang Huang

Abstract 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 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
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

27 citing papers in PubMed.

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  3. Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.The Journal of clinical endocrinology and metabolism · 2024
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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

6 authors.

Yi LiaoDepartment of Respiratory and Critical Care Medicine II, The Affiliated Hospital of Southwest Medical University, Luzhuo, Sichuan 646000, P.R. China.
Guofang YinDepartment of Respiratory and Critical Care Medicine II, The Affiliated Hospital of Southwest Medical University, Luzhuo, Sichuan 646000, P.R. China.
Xue WangDepartment of Respiratory and Critical Care Medicine II, The Affiliated Hospital of Southwest Medical University, Luzhuo, Sichuan 646000, P.R. China.
Ping ZhongDepartment of Respiratory and Critical Care Medicine II, The Affiliated Hospital of Southwest Medical University, Luzhuo, Sichuan 646000, P.R. China.
Xianming FanDepartment of Respiratory and Critical Care Medicine II, The Affiliated Hospital of Southwest Medical University, Luzhuo, Sichuan 646000, P.R. China.
Chengliang HuangDepartment of Respiratory and Critical Care Medicine II, The Affiliated Hospital of Southwest Medical University, Luzhuo, Sichuan 646000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathogenesis of small cell lung cancer (SCLC), a highly metastatic malignant tumor, remains unclear. In the present study, important genes and pathways that are involved in the pathogenesis of SCLC were identified. The following four datasets were downloaded from the Gene Expression Omnibus: GSE60052, GSE43346, GSE15240 and GSE6044. The differentially expressed genes (DEGs) between the SCLC samples and the normal samples were analyzed using R software. The limma package was used for every dataset. The RobustRankAggreg package was used to integrate the DEGs from the four datasets. Functional and pathway enrichment analyses were conducted using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases with FunRich software and R software, respectively. In addition, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database and Cytoscape software. Hub genes and significant modules were identified using Molecular Complex Detection in Cytoscape software. Finally, the expression values of hub genes were determined using the Oncomine online database. In total, 412 DEGs were identified following the integration of the four datasets, with 146 upregulated genes and 266 downregulated genes. The upregulated DEGs were primarily enriched in the cell cycle, cell division and microtubule binding. The downregulated DEGs were primarily enriched in the complement and coagulation cascades, the cytokine-mediated signaling pathway and protein binding. Eight hub genes and 1 significant module correlated to the cell cycle pathway were identified based on a subset of the PPI network. Finally, five hub genes were identified as highly expressed in SCLC tissue compared with normal tissue. The cell cycle pathway may be the pathway most closely associated with the pathogenesis of SCLC. NDC80, BUB1B, PLK1, CDC20 and MAD2L1 should be the focus of follow-up studies regarding the diagnosis and treatment of SCLC.

Indexed as

bioinformatics analysishub genemicroarray analysisprotein-protein interactionsmall cell lung cancer

Identifiers

PMID31516585
PMCPMC6732946

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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.