ArticleScientific reports2023
Analyzing aberrant DNA methylation in colorectal cancer uncovered intangible heterogeneity of gene effects in the survival time of patients.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
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- A pseudouridine-related prognostic model of colorectal cancer based on single-cell sequencing analysis and transcriptome analysis.Scientific reports · 2026Article
- Multi-modal clustering reveals event-free patient subgroup in colorectal cancer survival.NPJ systems biology and applications · 2025Article
- Multiomics Signature Reveals Network Regulatory Mechanisms in a CRC Continuum.International journal of molecular sciences · 2025Article
- Data-Driven Identification of Early Cancer-Associated Genes via Penalized Trans-Dimensional Hidden Markov Models.Biomolecules · 2025Article
- Pan-cancer analysis of co-inhibitory molecules revealing their potential prognostic and clinical values in immunotherapy.Frontiers in immunology · 2025Article
- DNA methylation analysis of the SDC2, SEPT9 and VIM genes in fecal DNA for colorectal cancer diagnosis.BMC cancer · 2024Article
- Associations of SEMA7A, SEMA4D, ADAMTS10, and ADAM8 with KRAS, NRAS, BRAF, PIK3CA, and AKT Gene Mutations, Microsatellite Instability Status, and Cytokine Expression in Colorectal Cancer Tissue.Current issues in molecular biology · 2024Article
- Synergistic Enhancement of 5-Fluorouracil Chemotherapeutic Efficacy by Taurine in Colon Cancer Rat Model.Nutrients · 2024Article
- Developing survival prediction models in colorectal cancer using epigenome-wide DNA methylation data from whole blood.NPJ precision oncology · 2024Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Colorectal cancer (CRC) involves epigenetic alterations. Irregular gene-methylation alteration causes and advances CRC tumor growth. Detecting differentially methylated genes (DMGs) in CRC and patient survival time paves the way to early cancer detection and prognosis. However, CRC data including survival times are heterogeneous. Almost all studies tend to ignore the heterogeneity of DMG effects on survival. To this end, we utilized a sparse estimation method in the finite mixture of accelerated failure time (AFT) regression models to capture such heterogeneity. We analyzed a dataset of CRC and normal colon tissues and identified 3406 DMGs. Analysis of overlapped DMGs with several Gene Expression Omnibus datasets led to 917 hypo- and 654 hyper-methylated DMGs. CRC pathways were revealed via gene ontology enrichment. Hub genes were selected based on Protein-Protein-Interaction network including SEMA7A, GATA4, LHX2, SOST, and CTLA4, regulating the Wnt signaling pathway. The relationship between identified DMGs/hub genes and patient survival time uncovered a two-component mixture of AFT regression model. The genes NMNAT2, ZFP42, NPAS2, MYLK3, NUDT13, KIRREL3, and FKBP6 and hub genes SOST, NFATC1, and TLE4 were associated with survival time in the most aggressive form of the disease that can serve as potential diagnostic targets for early CRC detection.
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