ArticleMedical science monitor : international medical journal of experimental and clinical research2018
Identification of Critical Genes and Five Prognostic Biomarkers Associated with Colorectal Cancer.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Prognostic model construction and drug prediction in colorectal cancer using mitochondrial programmed cell death-related genes.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- The multifaceted roles of the ACSL family in cancer: Metabolic reprogramming, ferroptosis regulation and tumour immune microenvironment remodelling.Clinical and translational medicine · 2026Review
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- 3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity.medRxiv : the preprint server for health sciences · 2024Article
- Ferroptosis-related gene signature and clinical prognostic factors as prognostic marker for colon adenocarcinoma.Heliyon · 2024Article
- Novel methylation-related long non-coding RNA clinical outcome prediction method: the clinical phenotype and immune infiltration research in low-grade gliomas.Frontiers in oncology · 2023Article
- Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction.BMC gastroenterology · 2022Article
- Identification and validation of a novel signature as a diagnostic and prognostic biomarker in colorectal cancer.Biology direct · 2022Article
- mFrontiers in genetics · 2022Article
- Identification of Key Genes Associated With the Process of Hepatitis B Inflammation and Cancer Transformation by Integrated Bioinformatics Analysis.Frontiers in genetics · 2021Article
- Metabolic reprogramming-associated genes predict overall survival for rectal cancer.Journal of cellular and molecular medicine · 2020Article
- Circulating lncRNA DANCR as a potential auxillary biomarker for the diagnosis and prognostic prediction of colorectal cancer.Bioscience reports · 2020Article
- Identification of 6 Hub Proteins and Protein Risk Signature of Colorectal Cancer.BioMed research international · 2020Article
- Identification of Potential Key Genes for Pathogenesis and Prognosis in Prostate Cancer by Integrated Analysis of Gene Expression Profiles and the Cancer Genome Atlas.Frontiers in oncology · 2020Article
- Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics.Mediators of inflammation · 2020Article
- Identification of novel biomarkers and small molecule drugs in human colorectal cancer by microarray and bioinformatics analysis.Molecular genetics & genomic medicine · 2019Article
- Emerging roles for multifunctional ion channel auxiliary subunits in cancer.Cell calcium · 2019Review
- Systemic Inflammation and the Increased Risk of Inflamm-Aging and Age-Associated Diseases in People Living With HIV on Long Term Suppressive Antiretroviral Therapy.Frontiers in immunology · 2019Article
- Contribution ofCancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Colorectal cancer (CRC) is a common malignant tumor with high incidence and mortality worldwide. The aim of this study was to evaluate the association between differentially expressed genes (DEGs), which may function as biomarkers for CRC prognosis and therapies, and the clinical outcome in patients with CRC. MATERIAL AND METHODS A total of 116 normal mucous tissue and 930 CRC tissue datasets were downloaded from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA). After screening DEGs based on limma package in R. Gene Ontology (GO) and KEGG enrichment analysis as well as the protein-protein interaction (PPI) networks were performed to predict the function of these DEGs. Meanwhile, Cox proportional hazards regression was used to build a prognostic model of these DEGs. Then, Kaplan-Meier risk analysis was used to test the model in TCGA datasets and validation datasets. RESULTS In the present study, 300 DEGs with 100 upregulated genes and 200 downregulated genes were identified. The PPI networks including 162 DEGs and 256 nodes were constructed and 2 modules with high degree were selected. Moreover, 5 genes (MMP1, ACSL6, SMPD1, PPARGC1A, and HEPACAM2) were identified using the Cox proportional hazards stepwise regression. Kaplan-Meier risk curve in the TCGA and validation cohorts showed that high-risk group had significantly poor overall survival than the low-risk group. CONCLUSIONS Our study provided insights into the mechanisms of CRC formation and found 5 prognostic genes, which could potentially inform further studies and clinical therapies.
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