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Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer
BACKGROUND: The prognosis of patients with colorectal cancer is related to early detection. However, commonly used screening markers lack sensitivity and specificity. In this study, we identified diagnostic methylation sites for colorectal cancer. METHODS: After screening the colorectal cancer methy...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318760/ https://www.ncbi.nlm.nih.gov/pubmed/37400791 http://dx.doi.org/10.1186/s12885-023-10922-2 |
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author | Ye, Zhen Song, Guangle Liang, Jianwei Yi, Shuying Gao, Yuqi Jiang, Hanming |
author_facet | Ye, Zhen Song, Guangle Liang, Jianwei Yi, Shuying Gao, Yuqi Jiang, Hanming |
author_sort | Ye, Zhen |
collection | PubMed |
description | BACKGROUND: The prognosis of patients with colorectal cancer is related to early detection. However, commonly used screening markers lack sensitivity and specificity. In this study, we identified diagnostic methylation sites for colorectal cancer. METHODS: After screening the colorectal cancer methylation dataset, diagnostic sites were identified via survival analysis, difference analysis, and ridge regression dimensionality reduction. The correlation between the selected methylation sites and the estimation of immune cell infiltration was analyzed. The accuracy of the diagnosis was verified using different datasets and the 10-fold crossover method. RESULTS: According to Gene Ontology, the main enrichment pathways of genes with hypermethylation sites are axon development, axonogenesis, and pattern specification processes. However, the Kyoto Encyclopedia of Genes and Genomes (KEGG) suggests the following main enrichment pathways: neuroactive ligand–receptor interaction, calcium signaling, and cAMP signaling. In The Cancer Genome Atlas (TCGA) and GSE131013 datasets, the area under the curve of cg07628404 was > 0.95. For the NaiveBayes machine model of cg02604524, cg07628404, and cg27364741, the accuracies of 10-fold cross-validation in the GSE131013 and TCGA datasets were 95% and 99.4%, respectively. The survival prognosis of the hypomethylated group (cg02604524, cg07628404, and cg27364741) was better than that of the hypermethylated group. The mutation risk did not differ between the hypermethylated and hypomethylated groups. The correlation coefficient between the three loci and CD4 central memory T cells, hematological stem cells, and other immune cells was not high (p < 0.05). CONCLUSION: In cases of colorectal cancer, the main enrichment pathway of genes with hypermethylated sites was axon and nerve development. In the biopsy tissues, the hypermethylation sites were diagnostic for colorectal cancer, and the NaiveBayes machine model of the three loci showed good diagnostic performance. Site (cg02604524, cg07628404, and cg27364741) hypermethylation predicts poor survival for colorectal cancer. Three methylation sites were weakly correlated with individual immune cell infiltration. Hypermethylation sites may be a useful repository for diagnosing colorectal cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10922-2. |
format | Online Article Text |
id | pubmed-10318760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103187602023-07-05 Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer Ye, Zhen Song, Guangle Liang, Jianwei Yi, Shuying Gao, Yuqi Jiang, Hanming BMC Cancer Research BACKGROUND: The prognosis of patients with colorectal cancer is related to early detection. However, commonly used screening markers lack sensitivity and specificity. In this study, we identified diagnostic methylation sites for colorectal cancer. METHODS: After screening the colorectal cancer methylation dataset, diagnostic sites were identified via survival analysis, difference analysis, and ridge regression dimensionality reduction. The correlation between the selected methylation sites and the estimation of immune cell infiltration was analyzed. The accuracy of the diagnosis was verified using different datasets and the 10-fold crossover method. RESULTS: According to Gene Ontology, the main enrichment pathways of genes with hypermethylation sites are axon development, axonogenesis, and pattern specification processes. However, the Kyoto Encyclopedia of Genes and Genomes (KEGG) suggests the following main enrichment pathways: neuroactive ligand–receptor interaction, calcium signaling, and cAMP signaling. In The Cancer Genome Atlas (TCGA) and GSE131013 datasets, the area under the curve of cg07628404 was > 0.95. For the NaiveBayes machine model of cg02604524, cg07628404, and cg27364741, the accuracies of 10-fold cross-validation in the GSE131013 and TCGA datasets were 95% and 99.4%, respectively. The survival prognosis of the hypomethylated group (cg02604524, cg07628404, and cg27364741) was better than that of the hypermethylated group. The mutation risk did not differ between the hypermethylated and hypomethylated groups. The correlation coefficient between the three loci and CD4 central memory T cells, hematological stem cells, and other immune cells was not high (p < 0.05). CONCLUSION: In cases of colorectal cancer, the main enrichment pathway of genes with hypermethylated sites was axon and nerve development. In the biopsy tissues, the hypermethylation sites were diagnostic for colorectal cancer, and the NaiveBayes machine model of the three loci showed good diagnostic performance. Site (cg02604524, cg07628404, and cg27364741) hypermethylation predicts poor survival for colorectal cancer. Three methylation sites were weakly correlated with individual immune cell infiltration. Hypermethylation sites may be a useful repository for diagnosing colorectal cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10922-2. BioMed Central 2023-07-03 /pmc/articles/PMC10318760/ /pubmed/37400791 http://dx.doi.org/10.1186/s12885-023-10922-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Ye, Zhen Song, Guangle Liang, Jianwei Yi, Shuying Gao, Yuqi Jiang, Hanming Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer |
title | Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer |
title_full | Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer |
title_fullStr | Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer |
title_full_unstemmed | Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer |
title_short | Optimized screening of DNA methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer |
title_sort | optimized screening of dna methylation sites combined with gene expression analysis to identify diagnostic markers of colorectal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318760/ https://www.ncbi.nlm.nih.gov/pubmed/37400791 http://dx.doi.org/10.1186/s12885-023-10922-2 |
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