ArticleOncology letters2019
Integrated genomic and methylation profile analysis to identify candidate tumor marker genes in patients with colorectal cancer.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Obesity-Associated Differentially Methylated Regions in Colon Cancer.Journal of personalized medicine · 2022Article
- Aberrantly DNA Methylated-Differentially Expressed Genes in Pancreatic Cancer Through an Integrated Bioinformatics Approach.Frontiers in genetics · 2021Article
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Authors and funding
3 authors.
Funding
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Abstract
Aberrant genomic expression and methylation serve important roles in cancer development. Integrated analysis of genetic and methylation profiles may identify potential tumor marker genes for colorectal cancer (CRC) prediction. In the current study, DNA methylation and mRNA expression profiles associated with CRC were downloaded from The Cancer Genome Atlas database. Differentially expressed mRNAs and methylated genes between tumor samples and adjacent healthy tissues were identified. Candidate tumor marker genes and prognostic clinical factors were screened according to univariable and multivariable Cox regression analysis. A total of 218 DEGs with aberrant methylation levels were screened from tumor samples. A risk prediction model was constructed based on identified genes and clinical factors. Randomization tests were used to evaluate the performance of the prediction model, including area under the curve (AUC) calculation and cross-validation. Cox regression analysis revealed that eight genes and six prognostic clinical factors were significantly associated with survival outcomes. Functional and pathway enrichment analysis revealed that the eight genes were mainly involved in 'cell adhesion', 'fatty acid metabolism' and 'cytokine receptor interaction' pathways. After combining six clinical factors with eight genes, the accuracy of risk prediction model has been increased intensively. The P-values representing the association between risk grouping and prognosis decreased from 0.009 to 0.001 and the AUC increased from 0.992 to 0.999, indicating that the comprehensive risk prediction model exhibited a good performance for disease prognosis prediction. The current study integrated genomic and methylation profiles and identified eight tumor marker genes in CRC. These candidate genes may improve the prediction accuracy of CRC prognosis.
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Registered trials
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