Evidence map›Paper›PMID 34712733›Full record

ArticleBioMed research international2021

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis.

Huanqing Liu, Tingting Li, Xunda Ye, Jun Lyu

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. 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

4 authors at 2 institutions in 1 country.

Huanqing LiuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Tingting LiDepartment of Pharmacy, Xi'an Chest Hospital, Xi'an, Shaanxi, China.
Xunda YeClinical Medicine Research Institute, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Jun LyuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0002-2237-8771
First Affiliated Hospital of Jinan University · CNXi'an Chest Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSmall-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

methodsKey genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

resultsA total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

conclusionIdentification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.

Indexed as

Biomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansKaplan-Meier EstimateLung NeoplasmsMolecular Sequence AnnotationPrognosisProtein Interaction MapsSignal TransductionSmall Cell Lung CarcinomaBiomarkers, Tumor

Identifiers

PMID34712733
PMCPMC8548101
OpenAlexW3206738088

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.