ArticleMolecular oncology2017
Recurrence-associated gene signature optimizes recurrence-free survival prediction of colorectal cancer.
Article in Molecular oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
- Pooled it
- COX-2/C-MET/KRAS status-based prognostic nomogram for colorectal cancer: A multicenter cohort study.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology AssociationTrial
- OmixLitMiner 2: Guided Literature Mining for Automated Categorization of Marker Candidates in Omics Studies.Proteomics · 2025Article
- Investigating stage-specific metabolic alterations in colorectal cancer through urine metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Discovery and validation of a 10-gene predictive signature for response to adjuvant chemotherapy in stage II and III colon cancer.Cell reports. Medicine · 2024Article
- A recurrence-predictive model based on eight genes and tumor mutational burden/microsatellite instability status in Stage II/III colorectal cancer.Cancer medicine · 2024Article
- Transcriptomic Profiling Reveals an Enhancer RNA Signature for Recurrence Prediction in Colorectal Cancer.Genes · 2023Article
- Deconvolution of bulk tumors into distinct immune cell states predicts colorectal cancer recurrence.iScience · 2022Article
- Polarimetric biomarkers of peri-tumoral stroma can correlate with 5-year survival in patients with left-sided colorectal cancer.Scientific reports · 2022Article
- A Prediction Model for Tumor Recurrence in Stage II-III Colorectal Cancer Patients: From a Machine Learning Model to Genomic Profiling.Biomedicines · 2022Article
- A Three-Genes Signature Predicting Colorectal Cancer Relapse Reveals LEMD1 Promoting CRC Cells Migration by RhoA/ROCK1 Signaling Pathway.Frontiers in oncology · 2022Article
- 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
- Clinical Significance of a Novel Tumor Progression-Associated Immune Signature in Colorectal Adenocarcinoma.Frontiers in cell and developmental biology · 2021Article
- Identification of Distinct Molecular Patterns and a Four-Gene Signature in Colon Cancer Based on Invasion-Related Genes.Frontiers in genetics · 2021Article
- UBE2T Contributes to the Prognosis of Esophageal Squamous Cell Carcinoma.Pathology oncology research : POR · 2021Article
- Identification of a 5-Gene-Based Scoring System by WGCNA and LASSO to Predict Prognosis for Rectal Cancer Patients.Analytical cellular pathology (Amsterdam) · 2021Article
- Multiple microarray analyses identify key genes associated with the development of Non-Small Cell Lung Cancer from Chronic Obstructive Pulmonary Disease.Journal of Cancer · 2021Article
- MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer.Nature communications · 2020Article
- OmixLitMiner: A Bioinformatics Tool for Prioritizing Biological Leads from 'Omics Data Using Literature Retrieval and Data Mining.International journal of molecular sciences · 2020Article
- Prediction of hepatocellular carcinoma prognosis based on expression of an immune-related gene set.Aging · 2020Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High throughput gene expression profiling has showed great promise in providing insight into molecular mechanisms. Metastasis-related mRNAs may potentially enrich genes with the ability to predict cancer recurrence, therefore we attempted to build a recurrence-associated gene signature to improve prognostic prediction of colorectal cancer (CRC). We identified 2848 differentially expressed mRNAs by analyzing CRC tissues with or without metastasis. For the selection of prognostic genes, a LASSO Cox regression model (least absolute shrinkage and selection operator method) was employed. Using this method, a 13-mRNA signature was identified and then validated in two independent Gene Expression Omnibus cohorts. This classifier could successfully discriminate the high-risk patients in discovery cohort [hazard ratio (HR) = 5.27, 95% confidence interval (CI) 2.30-12.08, P < 0.0001). Analysis in two independent cohorts yielded consistent results (GSE14333: HR = 4.55, 95% CI 2.18-9.508, P < 0.0001; GSE33113: HR = 3.26, 95% CI 2.16-9.16, P = 0.0176). Further analysis revealed that the prognostic value of this signature was independent of tumor stage, postoperative chemotherapy and somatic mutation. Receiver operating characteristic (ROC) analysis showed that the area under ROC curve of this signature was 0.8861 and 0.8157 in the discovery and validation cohort, respectively. A nomogram was constructed for clinicians, and did well in the calibration plots. Furthermore, this 13-mRNA signature outperformed other known gene signatures, including oncotypeDX colon cancer assay. Single-sample gene-set enrichment analysis revealed that a group of pathways related to drug resistance, cancer metastasis and stemness were significantly enriched in the high-risk patients. In conclusion, this 13-mRNA signature may be a useful tool for prognostic evaluation and will facilitate personalized management of CRC patients.
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