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Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer

Advanced adenoma (AA) holds a significantly increased risk for progression to colorectal cancer (CRC), and we developed a noninvasive DNA methylation prediction model to monitor the risk of AA progression to CRC. We analyzed the differential methylation markers between 53 normal mucosa and 138 CRC t...

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Autores principales: Wang, Wei, Zhang, Xuecong, Zhu, Xiaohui, Cui, Wenzhi, Ye, Danli, Tong, Guihui, Huang, Dingpeng, Zhou, Juan, Lai, Xuwen, Yan, Guangning, Li, Xia, Fan, Jianbing, Zhu, Hongwu, Lei, Chengyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133334/
https://www.ncbi.nlm.nih.gov/pubmed/35646690
http://dx.doi.org/10.3389/fonc.2022.827811
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author Wang, Wei
Zhang, Xuecong
Zhu, Xiaohui
Cui, Wenzhi
Ye, Danli
Tong, Guihui
Huang, Dingpeng
Zhou, Juan
Lai, Xuwen
Yan, Guangning
Li, Xia
Fan, Jianbing
Zhu, Hongwu
Lei, Chengyong
author_facet Wang, Wei
Zhang, Xuecong
Zhu, Xiaohui
Cui, Wenzhi
Ye, Danli
Tong, Guihui
Huang, Dingpeng
Zhou, Juan
Lai, Xuwen
Yan, Guangning
Li, Xia
Fan, Jianbing
Zhu, Hongwu
Lei, Chengyong
author_sort Wang, Wei
collection PubMed
description Advanced adenoma (AA) holds a significantly increased risk for progression to colorectal cancer (CRC), and we developed a noninvasive DNA methylation prediction model to monitor the risk of AA progression to CRC. We analyzed the differential methylation markers between 53 normal mucosa and 138 CRC tissues, as well as those in cfDNA (cell-free DNA) between 59 AA and 68 early-stage CRC patients. We screened the overlapping markers between tissue DNA and cfDNA for model variables and optimized the selected variables. Then, we established a cfDNA methylation prediction model (SDMBP model) containing seven methylation markers that can effectively discriminate early-stage CRC and AA in the training and validation cohorts, and the AUC (area under the curve) reached 0.979 and 0.918, respectively. Our model also reached high precision (AUC=0.938) in detecting advanced CRC (stage III/IV) and presented better performance than serum CEA and CA199 in screening CRC. The cd-score of the SDMBP model could also robustly predict the TNM stage of CRC. Overall, our SDMBP model can monitor the malignant progression from AA to CRC, and may provide a noninvasive monitoring method for high-risk populations with AA.
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spelling pubmed-91333342022-05-27 Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer Wang, Wei Zhang, Xuecong Zhu, Xiaohui Cui, Wenzhi Ye, Danli Tong, Guihui Huang, Dingpeng Zhou, Juan Lai, Xuwen Yan, Guangning Li, Xia Fan, Jianbing Zhu, Hongwu Lei, Chengyong Front Oncol Oncology Advanced adenoma (AA) holds a significantly increased risk for progression to colorectal cancer (CRC), and we developed a noninvasive DNA methylation prediction model to monitor the risk of AA progression to CRC. We analyzed the differential methylation markers between 53 normal mucosa and 138 CRC tissues, as well as those in cfDNA (cell-free DNA) between 59 AA and 68 early-stage CRC patients. We screened the overlapping markers between tissue DNA and cfDNA for model variables and optimized the selected variables. Then, we established a cfDNA methylation prediction model (SDMBP model) containing seven methylation markers that can effectively discriminate early-stage CRC and AA in the training and validation cohorts, and the AUC (area under the curve) reached 0.979 and 0.918, respectively. Our model also reached high precision (AUC=0.938) in detecting advanced CRC (stage III/IV) and presented better performance than serum CEA and CA199 in screening CRC. The cd-score of the SDMBP model could also robustly predict the TNM stage of CRC. Overall, our SDMBP model can monitor the malignant progression from AA to CRC, and may provide a noninvasive monitoring method for high-risk populations with AA. Frontiers Media S.A. 2022-05-12 /pmc/articles/PMC9133334/ /pubmed/35646690 http://dx.doi.org/10.3389/fonc.2022.827811 Text en Copyright © 2022 Wang, Zhang, Zhu, Cui, Ye, Tong, Huang, Zhou, Lai, Yan, Li, Fan, Zhu and Lei https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Wang, Wei
Zhang, Xuecong
Zhu, Xiaohui
Cui, Wenzhi
Ye, Danli
Tong, Guihui
Huang, Dingpeng
Zhou, Juan
Lai, Xuwen
Yan, Guangning
Li, Xia
Fan, Jianbing
Zhu, Hongwu
Lei, Chengyong
Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer
title Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer
title_full Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer
title_fullStr Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer
title_full_unstemmed Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer
title_short Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer
title_sort seven dna methylation biomarker prediction models for monitoring the malignant progression from advanced adenoma to colorectal cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133334/
https://www.ncbi.nlm.nih.gov/pubmed/35646690
http://dx.doi.org/10.3389/fonc.2022.827811
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