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Updated: Aug 29, 2025

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
The identification of hub biomarkers and pathways in lung cancer and prognostic evaluation
1Department of Medical Oncology, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China.
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 RRM2, CHEK1 and SERPINB5 enriched in the p53 signaling pathway, RRM2 and TYMS enriched in pyrimidine metabolism pathway maybe play a key role in SCLC&NSCLC and were significantly related to overall survival in patients with NSCLC.
Conclusions:
RRM2, CHEK1, TYMS and SERPINB5, which are mainly enriched in the p53 signaling pathway and pyrimidine metabolism pathway, were significantly associated with the overall survival of NSCLC patients. These genes could serve as potential prognostic markers in NSCLC and therapeutic target in lung cancer for personalized oncology.
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