ArticleExperimental and therapeutic medicine2018
Comprehensive analysis of differential expression profiles reveals potential biomarkers associated with the cell cycle and regulated by p53 in human small cell lung cancer.
Article in Experimental and therapeutic medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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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.
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Who cites it
14 citing papers in PubMed, 19 citations in OpenAlex.
- Significant prognostic value of cell-cycle proteins in early-stage small cell carcinoma of cervix.Scientific reports · 2025Article
- Unlocking the potential of non-coding RNAs in cancer research and therapy.Translational oncology · 2023Article
- Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis.Biology · 2022Article
- Article
- Identification ofCell journal · 2021Article
- Computational identification of biomarker genes for lung cancer considering treatment and non-treatment studies.BMC bioinformatics · 2020Article
- An in-silico method leads to recognition of hub genes and crucial pathways in survival of patients with breast cancer.Scientific reports · 2020Article
- Identification ofWorld journal of clinical cases · 2020Article
- Article
- Characterization of lncRNA-Associated ceRNA Network to Reveal Potential Prognostic Biomarkers in Lung Adenocarcinoma.Frontiers in bioengineering and biotechnology · 2020Article
- Article
- Identification of candidate genes associated with the pathogenesis of small cell lung cancer via integrated bioinformatics analysis.Oncology letters · 2019Article
- Identification of potential agents for thymoma by integrated analyses of differentially expressed tumour-associated genes and molecular docking experiments.Experimental and therapeutic medicine · 2019Article
- Lung Cancer: One Disease or Many.Human heredity · 2018Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Small cell lung cancer (SCLC) is the subtype of lung cancer with the highest degree of malignancy and the lowest degree of differentiation. The purpose of this study was to investigate the molecular mechanisms of SCLC using bioinformatics analysis, and to provide new ideas for the early diagnosis and targeted therapy of SCLC. Microarray data were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) in SCLC were compared with the normal lung samples and identified. Gene Ontology (GO) function and pathway analysis of DEGs was performed through the DAVID database. Furthermore, microarray data was analyzed by using the clustering analysis tool GoMiner. Protein-protein interaction (PPI) networks of DEGs were constructed using the STRING online database. Protein expression was determined from the Human Protein Atlas, and SCLC gene expression was determined using Oncomine. In total, 153 DEGs were obtained. Functional enrichment analysis suggested that the majority of DEGs were associated with the cell cycle.
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