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Published on: October 11, 2018
Shared Biomarkers LCN2 and CXCL11 for Ulcerative Colitis and Colon Cancer: Bioinformatics Analysis and Diagnostic
Zhihao Wu1, Xiaofen Sun1, Binglong Li1
1Department of Radiology, The First Clinical College, The First Affiliated Hospital, Hainan Medical University, Haikou, 570100, People's Republic of China.
Ulcerative colitis and colon cancer share common diagnostic markers and inflammatory pathways. A multi-gene diagnostic model shows superior accuracy compared to single-gene detection for these conditions.
Area of Science:
- Oncology
- Gastroenterology
- Immunology
Background:
- Chronic inflammation, particularly ulcerative colitis, significantly elevates colon cancer risk (2-3x general population).
- Ulcerative colitis is a complex chronic inflammatory condition.
- Understanding shared molecular mechanisms between ulcerative colitis and colon cancer is crucial for early detection and treatment.
Purpose of the Study:
- To identify common diagnostic markers between ulcerative colitis and colon cancer.
- To investigate shared pathogenic pathways and immune microenvironment similarities.
- To develop and evaluate a multi-gene diagnostic model for these diseases.
Main Methods:
- Transcriptome data analysis from GEO and TCGA databases.
- Gene identification using Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis.
- Machine learning algorithms (MCC, LASSO, RF) and pathway analyses (GO, KEGG, GSEA) for core gene and pathway identification.
Main Results:
- Eighty-seven common differentially expressed genes were identified between ulcerative colitis and colon cancer.
- LCN2 and CXCL11 were identified as key diagnostic genes with high expression and AUC > 0.7.
- Pathway analyses revealed enrichment in immune response and cell proliferation, highlighting shared inflammatory mechanisms.
Conclusions:
- Ulcerative colitis and colon cancer share common diagnostic markers and pathogenic pathways.
- Similarities exist in the immune cell infiltration microenvironment.
- A multi-gene diagnostic model demonstrates superior diagnostic performance over single genes.
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