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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
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Screening for candidate genes related to breast cancer with cDNA microarray analysis
Yu-Juan Xiang1, Qin-Ye Fu1, Zhong-Bing Ma1
1Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China.
Chronic Diseases and Translational Medicine
|October 25, 2017
Summary
This study identified 427 differentially expressed genes in breast cancer, revealing key changes in cell proliferation and adhesion. These findings offer promising new candidate genes for understanding breast cancer development and discovering novel biomarkers.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Breast cancer is a complex disease with numerous contributing genetic factors.
- Understanding gene expression changes is crucial for identifying novel therapeutic targets and diagnostic markers.
Purpose of the Study:
- To identify differentially expressed genes in breast cancer tissues compared to normal tissues.
- To explore potential new genes and factors involved in breast cancer pathogenesis.
Main Methods:
- Gene expression profiling using cDNA microarray analysis in seven breast cancer patients.
- Quantitative analysis of IFI30 gene expression via real-time PCR for validation.
Main Results:
- Identified 427 significantly differentially expressed genes (221 up-regulated, 206 down-regulated).
- Gene Ontology analysis revealed enrichment of cell proliferation, cell cycle, and apoptosis genes among up-regulated genes.
- Down-regulated genes were enriched in cell adhesion, proteolysis, and transport pathways.
Conclusions:
- The study identified a comprehensive set of differentially expressed genes in breast cancer.
- These genes represent potential candidates for further research into breast cancer pathogenesis and biomarker discovery.
