ArticleWorld journal of surgical oncology2021
Identification of a prognostic gene signature of colon cancer using integrated bioinformatics analysis.
Article in World journal of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- A Ferroptosis-Related LncRNA Signature Associated with Prognosis, Tumor Immune Environment, and Genome Instability in Hepatocellular Carcinoma.Computational and mathematical methods in medicine · 2022Trial
- The metabolic crossroads: glycolysis in cancer and neurodegeneration.BMC neurology · 2025Article
- Machine learning-driven multi-targeted drug discovery in colon cancer using biomarker signatures.NPJ precision oncology · 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
- Evaluating Ovarian Cancer Chemotherapy Response Using Gene Expression Data and Machine Learning.BioMedInformatics · 2024Article
- Integrated single-cell and bulk RNA sequencing analysis identifies a prognostic signature related to ferroptosis dependence in colorectal cancer.Scientific reports · 2023Article
- Identification of key immune cell-related genes involved in tumorigenesis and prognosis of cervical squamous cell carcinoma.Human vaccines & immunotherapeutics · 2023Article
- Comprehensive genomics analysis of aging related gene signature to predict the prognosis and drug resistance of colon adenocarcinoma.Frontiers in pharmacology · 2023Article
- Identification of novel gene signature for lung adenocarcinoma by machine learning to predict immunotherapy and prognosis.Frontiers in immunology · 2023Article
- Molecular Biomarker of Drug Resistance Developed From Patient-Derived Organoids Predicts Survival of Colorectal Cancer Patients.Frontiers in oncology · 2022Article
- Identification and validation of an immune-associated RNA-binding proteins signature to predict clinical outcomes and therapeutic responses in colon cancer patients.World journal of surgical oncology · 2021Article
- Circ_0026416 downregulation blocks the development of colorectal cancer through depleting MYO6 expression by enriching miR-545-3p.World journal of surgical oncology · 2021Article
- LINC01224 promotes colorectal cancer progression through targeting miR-485-5p/MYO6 axis.World journal of surgical oncology · 2021Article
- Determination of a six-gene prognostic model for cervical cancer based on WGCNA combined with LASSO and Cox-PH analysis.World journal of surgical oncology · 2021Article
- Importance of Circ0009910 in colorectal cancer pathogenesis as a possible regulator of miR-145 and PEAK1.World journal of surgical oncology · 2021Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundColon cancer is a worldwide leading cause of cancer-related mortality, and the prognosis of colon cancer is still needed to be improved. This study aimed to construct a prognostic model for predicting the prognosis of colon cancer.
methodsThe gene expression profile data of colon cancer were obtained from the TCGA, GSE44861, and GSE44076 datasets. The WGCNA module genes and common differentially expressed genes (DEGs) were used to screen out the prognosis-associated DEGs, which were used to construct a prognostic model. The performance of the prognostic model was assessed and validated in the TCGA training and microarray validation sets (GSE38832 and GSE17538). At last, the model and prognosis-associated clinical factors were used for the construction of the nomogram.
resultsFive colon cancer-related WGCNA modules (including 1160 genes) and 1153 DEGs between tumor and normal tissues were identified, inclusive of 556 overlapping DEGs. Stepwise Cox regression analyses identified there were 14 prognosis-associated DEGs, of which 12 DEGs were included in the optimized prognostic gene signature. This prognostic model presented a high forecast ability for the prognosis of colon cancer both in the TCGA training dataset and the validation datasets (GSE38832 and GSE17538; AUC > 0.8). In addition, patients' age, T classification, recurrence status, and prognostic risk score were associated with the prognosis of TCGA patients with colon cancer. The nomogram was constructed using the above factors, and the predictive 3- and 5-year survival probabilities had high compliance with the actual survival proportions.
conclusionsThe 12-gene signature prognostic model had a high predictive ability for the prognosis of colon cancer.
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