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Published on: January 18, 2017
Risk Prediction of Colon Cancer Metastasis and Bioinformatics Analysis of Aspirin Treatment
Jing Li1, Xinyue Yu2, Jingjing Shao3
1Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China, ahnmc.com.
Background:
Metastasis is a major adverse prognostic factors of colon cancer. Aspirin chemoprophylaxis may improve outcomes for metastatic colon cancer patients. This study aimed to determine the impact of metastasis-related molecular subtypes on prognosis and aspirin chemoprophylaxis benefit.
Methods:
We obtained differentially expressed metastasis-related genes in cancer and normal tissues. A weighted gene co-expression network (WGCNA) was constructed by differentially expressed genes. Lasso-Cox regression identified key prognostic genes within relevant modules, establishing a risk score model. Transcription factors regulating module genes were explored. Aspirin-interacting genes were identified using the Comparative Toxicogenomics Database (CTD) and validated via cellular experiments.
Results:
WGCNA analysis of 2062 metastasis-related genes revealed significant correlations between blue/yellow modules and colon cancer. A risk score model based on blue module genes predicted overall survival and 1-, 3-, and 5-year survival rates. Transcription factor analysis implicated the E2F family in blue module regulation and NFκB1/STAT3 in yellow module regulation. CTD analysis showed persistent upregulation of NOX4, CXCL8, CXCL5, GDF15, and MMP13 post-aspirin treatment. Cellular experiments confirmed aspirin downregulated metastasis-related genes (E2F1, CCNE1, VEGFA, MMP3) in colon cancer.
Conclusion:
We developed a validated metastasis gene predictive model. Colon cancer patients with upregulated NOX4, CXCL8, CXCL5, GDF15, or MMP13 may not benefit from aspirin chemoprophylaxis. Conversely, patients showing aspirin-induced downregulation of E2F1, CCNE1, VEGFA, and MMP3 may derive chemoprophylactic benefit.
