ArticleJournal of oncology2021
Identifying Stage II Colorectal Cancer Recurrence Associated Genes by Microarray Meta-Analysis and Building Predictive Models with Machine Learning Algorithms.
Article in Journal of oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- SNHG5 enhances colorectal cancer metastasis through RNA-protein interaction with GNB2 and activation of canonical Wnt signaling.Non-coding RNA research · 2026Article
- Cost-effectiveness analysis of sequential two-step screening versus direct colonoscopy screening for colorectal cancer: a large-scale survey in Eastern China.Frontiers in oncology · 2025Article
- Genetic variations and recurrence in stage III Korean colorectal cancer: Insights from tumor-only mutation analysis.PloS one · 2025Article
- PROGNOSTIC VALUE OF TUMOR BUDDING IN SPORADIC COLORECTAL CANCER STAGE II PATIENTS WITH A LOW NUMBER OF LYMPH NODES EXAMINED.Acta clinica Croatica · 2024Article
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Authors and funding
12 authors.
Funding
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Abstract
backgroundStage II colorectal cancer patients had heterogeneous prognosis, and patients with recurrent events had poor survival. In this study, we aimed to identify stage II colorectal cancer recurrence associated genes by microarray meta-analysis and build predictive models to stratify patients' recurrence-free survival.
methodsWe searched the GEO database to retrieve eligible microarray datasets. The microarray meta-analysis was used to identify universal recurrence associated genes. Total samples were randomly divided into the training set and the test set. Two survival models (lasso Cox model and random survival forest model) were trained in the training set, and AUC values of the time-dependent receiver operating characteristic (ROC) curves were calculated. Survival analysis was performed to determine whether there was significant difference between the predicted high and low risk groups in the test set.
resultsSix datasets containing 651 stage II colorectal cancer patients were included in this study. The
conclusionsWe identified 479 stage II colorectal cancer recurrence associated genes by microarray meta-analysis. The random survival forest model which was based on the recurrence associated gene signature could strongly predict the recurrence risk of stage II colorectal cancer patients.
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