ArticleTranslational cancer research2022
The identification of hub biomarkers and pathways in lung cancer and prognostic evaluation.
Article in Translational cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Integrative bioinformatics identifies NSCLC biomarkers associated with LPS metabolism and circadian disruption.Translational oncology · 2026Article
- In silico design of the multi-epitope vaccine for lung adenocarcinoma based on hub gene-derived neoantigens.BMC cancer · 2026Article
- Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches.PloS one · 2025Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung cancer is the most frequently diagnosed malignant tumor and the highest mortality worldwide, and can be divided into two differential histologic subtypes, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). However, there are significant differences in diagnosis and prognosis between NSCLC and SCLC. We aimed to identify hub differentially expressed genes (DEGs) and pathways for diagnostic and prognostic prediction in NSCLC and SCLC. Methods: Three expression profiles (GSE43346, GSE40275 and GSE18842) were obtained through GEO2R tools from Gene Expression Omnibus (GEO) database. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to investigate functional enrichment of the DEGs. The protein-protein interaction network was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. Kaplan-Meier analysis was performed using Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Results: We have identified 84 overlap DEGs that may play an important role in SCLC & NSCLC. However, we also found some genes were only significantly differential expressed in SCLC or NSCLC. There were 87 DEGs unique to SCLC tissues and 28 DEGs unique to NSCLC ones. Functional analysis results indicated that these DEGs had different biological functions and were significantly enriched in different pathways. Hub DEGs were identified via protein-protein interaction network and cross-validated using Kaplan-Meier plotter and GEPIA. The 14 hub DEGs were highly correlated with the overall survival of NSCLC. Kyoto Encyclopedia of Genes and Genome (KEGG) re-analysis of 14 hub DEGs showed that Conclusions:
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