ArticleMolecular oncology2018
A robust gene signature for the prediction of early relapse in stage I-III colon cancer.
Article in Molecular oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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40 citing papers in PubMed, 76 citations in OpenAlex.
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- Comprehensive analysis of novel cancer prediction genes and tumor microenvironment infiltration in colon cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Article
- Polyamine metabolism patterns characterized tumor microenvironment, prognosis, and response to immunotherapy in colorectal cancer.Cancer cell international · 2023Article
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- Based on Molecular Subtypes, Immune Characteristics and Genomic Variation to Constructing and Verifying Multi-Gene Prognostic Characteristics of Colorectal Cancer.Frontiers in cell and developmental biology · 2022Article
- Comprehensive Analysis of the Tumor Immune Microenvironment Landscape in Glioblastoma Reveals Tumor Heterogeneity and Implications for Prognosis and Immunotherapy.Frontiers in immunology · 2022Article
- Identification of genes modified by N6-methyladenosine in patients with colorectal cancer recurrence.Frontiers in genetics · 2022Article
- An 11-gene signature for the prediction of systemic recurrences in colon adenocarcinoma.Gastroenterology report · 2021Article
- Regulation of ARL2 in colorectal cancer cell proliferation and tumorigenicity, and its negative association with AXL.Oncology letters · 2021Article
- Increased Expression ofJournal of personalized medicine · 2021Article
- Identification and development of a novel invasion-related gene signature for prognosis prediction in colon adenocarcinoma.Cancer cell international · 2021Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colon cancer patients experiencing early relapse consistently exhibited poor survival. The aim of our study was to develop an mRNA signature that can help to detect early relapse cases in stage I-III colon cancer. Public microarray datasets of stage I-III colon cancer samples were extracted from the Gene Expression Omnibus database. Propensity score matching analysis was performed between patients in the early relapse group and the long-term survival group from GSE39582 discovery series (N = 386), and patients were 1 : 1 matched. Global mRNA expression changes were then analyzed between the paired groups to identify the differentially expressed genes. Lasso Cox regression modeling analysis was conducted for the selection of prognostic mRNA. Fifteen mRNA were finally identified to build an early relapse classifier. With specific risk score formula, patients were classified into a high-risk group and a low-risk group. Relapse-free survival was significantly different between the two groups in every series, including discovery [hazard ratio (HR): 2.547, 95% confidence interval (CI): 1.708-3.797, P < 0.001)], internal validation (HR: 5.146, 95% CI: 1.968-13.457, P < 0.001), and external validation (HR: 1.977, 95% CI: 1.295-3.021, P < 0.001) sets of patients. Time-dependent receiver-operating characteristic at 1 year suggested more prognostic accuracy of the classifier [area under curve (AUC = 0.703)] than the American Joint Commission on Cancer tumor-node-metastasis staging system (AUC = 0.659) in all 951 patients. In conclusion, we developed a robust mRNA signature that can effectively classify colon cancer patients into groups with low and high risks of early relapse. This mRNA signature may help select high-risk colon cancer patients who require more aggressive therapeutic intervention.
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