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Updated: Feb 16, 2026
Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
Published on: August 10, 2009
Gene function analysis and underlying mechanism of esophagus cancer based on microarray gene expression profiling
Ying Yue1,2,3, Mengjia Song1,2, Yamin Qiao1,2
1Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
Abstract:
Esophageal cancer (EC) is one of the most common digestive malignant tumors worldwide. Over the past decades, there have been minimal improvements in outcomes for patients with EC. New targets and novel therapies are needed to improve outcomes for these patients. This study aimed to explore the molecular mechanisms of EC by integrated bioinformatic analyses of the feature genes associated with EC and correlative gene functions which can distinguish cancerous tissues from non-cancerous tissues. Gene expression profile GSE20347 was downloaded from Gene Expression Omnibus (GEO) database, including 17 EC samples and their paired adjacent non-cancerous samples. The differentially expressed genes (DEGs) between EC and normal specimens were identified and then applied to analyze the GO enrichment on gene functions and KEGG pathways. Corresponding Pathway Relation Network (Pathway-net) and Gene Signal Network (signal-net) of DEGs were established based on the data collected from GCBI datasets. The results showed that DEGs mainly participated in the process of cell adhesion, cell proliferation, survival, invasion, metastasis and angiogenesis. Aberrant expression of PTK2, MAPK signaling pathway, PI3K-Akt signaling pathway, p53 signaling pathway and MET were closely associated with EC carcinogenesis. Importantly, Interleukin 8 (IL8) and C-X-C chemokine receptor type 7 (CXCR-7) were predicted to be significantly related to EC. These findings were further validated by analyzing both TCGA database and our clinical samples of EC. Our discovery provides a registry of genes and pathways that are disrupted in EC, which has the potential to be used in clinic for diagnosis and target therapy of EC in future.
Insights
This study identifies key genes and pathways involved in esophageal cancer (EC) development. Findings highlight potential new targets for diagnosis and therapy to improve patient outcomes.
Area of Science:
- Oncology
- Bioinformatics
- Molecular Biology
Background:
- Esophageal cancer (EC) remains a significant global health challenge with limited therapeutic advancements.
- Novel molecular targets are crucial for improving patient survival rates in EC.
Purpose of the Study:
- To elucidate the molecular mechanisms underlying EC through integrated bioinformatic analysis.
- To identify feature genes and pathways distinguishing cancerous from non-cancerous esophageal tissues.
Main Methods:
- Utilized Gene Expression Omnibus (GEO) dataset GSE20347 for differential gene expression analysis.
- Performed Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.
- Constructed Pathway Relation Networks (Pathway-net) and Gene Signal Networks (signal-net).
- Validated findings using The Cancer Genome Atlas (TCGA) database and clinical EC samples.
Main Results:
- Differentially expressed genes (DEGs) are implicated in cell adhesion, proliferation, invasion, metastasis, and angiogenesis.
- Aberrant expression of PTK2, MAPK, PI3K-Akt, p53 signaling pathways, and MET are linked to EC carcinogenesis.
- Interleukin 8 (IL8) and C-X-C chemokine receptor type 7 (CXCR-7) show significant association with EC.
Conclusions:
- Identified a set of disrupted genes and pathways crucial for EC development.
- These findings offer potential biomarkers for EC diagnosis and therapeutic targets.
- The study provides a foundation for developing novel treatment strategies for esophageal cancer.
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