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Updated: Nov 30, 2025
Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Identification of potential target genes and crucial pathways in small cell lung cancer based on bioinformatic
Xiuwen Chen1, Li Wang1, Xiaomin Su2
1Department of Pathology, Taihe Hospital, Hubei University of Medicine, Hubei, China.
Abstract:
Small cell lung cancer (SCLC) is a carcinoma of the lungs with strong invasion, poor prognosis and resistant to multiple chemotherapeutic drugs. It has posed severe challenges for the effective treatment of lung cancer. Therefore, searching for genes related to the development and prognosis of SCLC and uncovering their underlying molecular mechanisms are urgent problems to be resolved. This study is aimed at exploring the potential pathogenic and prognostic crucial genes and key pathways of SCLC via bioinformatic analysis of public datasets. Firstly, 117 SCLC samples and 51 normal lung samples were collected and analyzed from three gene expression datasets. Then, 102 up-regulated and 106 down-regulated differentially expressed genes (DEGs) were observed. And then, functional annotation and pathway enrichment analyzes of DEGs was performed utilizing the FunRich. The protein-protein interaction (PPI) network of the DEGs was constructed through the STRING website, visualized by Cytoscape. Finally, the expression levels of eight hub genes were confirmed in Oncomine database and human samples from SCLC patients. It showed that CDC20, BUB1, TOP2A, RRM2, CCNA2, UBE2C, MAD2L1, and BUB1B were upregulated in SCLC tissues compared to paired adjacent non-cancerous tissues. These suggested that eight hub genes might be viewed as new biomarkers for prognosis of SCLC or to guide individualized medication for the therapy of SCLC.
Insights
Researchers identified eight key genes (CDC20, BUB1, TOP2A, RRM2, CCNA2, UBE2C, MAD2L1, BUB1B) that are highly expressed in small cell lung cancer (SCLC). These genes may serve as crucial biomarkers for SCLC prognosis and personalized treatment strategies.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Small cell lung cancer (SCLC) presents significant treatment challenges due to its aggressive nature and resistance to chemotherapy.
- Identifying novel molecular targets and prognostic markers is crucial for improving patient outcomes in SCLC.
Purpose of the Study:
- To identify critical genes and pathways involved in the pathogenesis and prognosis of SCLC using bioinformatics analysis.
- To explore potential novel biomarkers for SCLC diagnosis and individualized therapy.
Main Methods:
- Differential gene expression analysis of 117 SCLC and 51 normal lung samples from public datasets.
- Functional annotation and pathway enrichment analysis using FunRich.
- Protein-protein interaction network construction with STRING and visualization with Cytoscape.
Main Results:
- 102 upregulated and 106 downregulated differentially expressed genes (DEGs) were identified.
- Eight hub genes (CDC20, BUB1, TOP2A, RRM2, CCNA2, UBE2C, MAD2L1, BUB1B) were found to be significantly upregulated in SCLC tissues.
- These hub genes are implicated in key cellular processes relevant to cancer progression.
Conclusions:
- The identified eight hub genes represent potential novel biomarkers for predicting SCLC prognosis.
- These genes may guide the development of targeted therapies and personalized treatment approaches for SCLC patients.
