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DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy has proven to be a promising treatment for colorectal cancer (CRC). We aim to investigate the relationship between DNA methylation and tumor mutation burden (TMB) by integrating genomic and epigenetic profiles to precisely identify clinical benef...

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Autores principales: Huang, Hao, Cao, Weifan, Long, Zhiping, Kuang, Lei, Li, Xi, Feng, Yifei, Wu, Yuying, Zhao, Yang, Chen, Yinggang, Sun, Peng, Peng, Panxin, Zhang, Jinli, Yuan, Lijun, Li, Tianze, Hu, Huifang, Li, Gairui, Yang, Longkun, Zhang, Xing, Hu, Fulan, Sun, Xizhuo, Hu, Dongsheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9880489/
https://www.ncbi.nlm.nih.gov/pubmed/36713578
http://dx.doi.org/10.3389/fonc.2022.1030335
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author Huang, Hao
Cao, Weifan
Long, Zhiping
Kuang, Lei
Li, Xi
Feng, Yifei
Wu, Yuying
Zhao, Yang
Chen, Yinggang
Sun, Peng
Peng, Panxin
Zhang, Jinli
Yuan, Lijun
Li, Tianze
Hu, Huifang
Li, Gairui
Yang, Longkun
Zhang, Xing
Hu, Fulan
Sun, Xizhuo
Hu, Dongsheng
author_facet Huang, Hao
Cao, Weifan
Long, Zhiping
Kuang, Lei
Li, Xi
Feng, Yifei
Wu, Yuying
Zhao, Yang
Chen, Yinggang
Sun, Peng
Peng, Panxin
Zhang, Jinli
Yuan, Lijun
Li, Tianze
Hu, Huifang
Li, Gairui
Yang, Longkun
Zhang, Xing
Hu, Fulan
Sun, Xizhuo
Hu, Dongsheng
author_sort Huang, Hao
collection PubMed
description BACKGROUND: Immune checkpoint inhibitor (ICI) therapy has proven to be a promising treatment for colorectal cancer (CRC). We aim to investigate the relationship between DNA methylation and tumor mutation burden (TMB) by integrating genomic and epigenetic profiles to precisely identify clinical benefit populations and to evaluate the effect of ICI therapy. METHODS: A total of 536 CRC tissues from the Cancer Genome Atlas (TCGA) with mutation data were collected and subjected to calculate TMB. 80 CRC patients with high TMB and paired normal tissues were selected as training sets and developed the diagnostic and prognostic methylation models, respectively. In the validation set, the diagnostic model was validated in our in-house 47 CRC tissues and 122 CRC tissues from the Gene Expression Omnibus (GEO) datasets, respectively. And a total of 38 CRC tissues with high TMB from the COLONOMICS dataset verified the prognostic model. RESULTS: A positive correlation between differential methylation positions and TMB level was observed in TCGA CRC cohort (r=0.45). The diagnostic score that consisted of methylation levels of four genes (ADHFE1, DOK6, GPR75, and MAP3K14-AS1) showed high diagnostic performance in the discovery (AUC=1.000) and two independent validation (AUC=0.946, AUC=0.857) datasets. Additionally, these four genes showed significant positive correlations with NK cells. The prognostic score containing three genes (POU3F3, SYN2, and TMEM178A) had significantly poorer survival in the high-risk TMB samples than those in the low-risk TMB samples (P=0.016). CRC patients with low-risk scores combined with TMB levels represent a favorable survival. CONCLUSIONS: By integrating analyses of methylation and mutation data, it is suggested that DNA methylation patterns combined with TMB serve as a novel potential biomarker for early screening in more high-TMB populations and for evaluating the prognostic effect of CRC patients with ICI therapy.
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spelling pubmed-98804892023-01-28 DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden Huang, Hao Cao, Weifan Long, Zhiping Kuang, Lei Li, Xi Feng, Yifei Wu, Yuying Zhao, Yang Chen, Yinggang Sun, Peng Peng, Panxin Zhang, Jinli Yuan, Lijun Li, Tianze Hu, Huifang Li, Gairui Yang, Longkun Zhang, Xing Hu, Fulan Sun, Xizhuo Hu, Dongsheng Front Oncol Oncology BACKGROUND: Immune checkpoint inhibitor (ICI) therapy has proven to be a promising treatment for colorectal cancer (CRC). We aim to investigate the relationship between DNA methylation and tumor mutation burden (TMB) by integrating genomic and epigenetic profiles to precisely identify clinical benefit populations and to evaluate the effect of ICI therapy. METHODS: A total of 536 CRC tissues from the Cancer Genome Atlas (TCGA) with mutation data were collected and subjected to calculate TMB. 80 CRC patients with high TMB and paired normal tissues were selected as training sets and developed the diagnostic and prognostic methylation models, respectively. In the validation set, the diagnostic model was validated in our in-house 47 CRC tissues and 122 CRC tissues from the Gene Expression Omnibus (GEO) datasets, respectively. And a total of 38 CRC tissues with high TMB from the COLONOMICS dataset verified the prognostic model. RESULTS: A positive correlation between differential methylation positions and TMB level was observed in TCGA CRC cohort (r=0.45). The diagnostic score that consisted of methylation levels of four genes (ADHFE1, DOK6, GPR75, and MAP3K14-AS1) showed high diagnostic performance in the discovery (AUC=1.000) and two independent validation (AUC=0.946, AUC=0.857) datasets. Additionally, these four genes showed significant positive correlations with NK cells. The prognostic score containing three genes (POU3F3, SYN2, and TMEM178A) had significantly poorer survival in the high-risk TMB samples than those in the low-risk TMB samples (P=0.016). CRC patients with low-risk scores combined with TMB levels represent a favorable survival. CONCLUSIONS: By integrating analyses of methylation and mutation data, it is suggested that DNA methylation patterns combined with TMB serve as a novel potential biomarker for early screening in more high-TMB populations and for evaluating the prognostic effect of CRC patients with ICI therapy. Frontiers Media S.A. 2023-01-13 /pmc/articles/PMC9880489/ /pubmed/36713578 http://dx.doi.org/10.3389/fonc.2022.1030335 Text en Copyright © 2023 Huang, Cao, Long, Kuang, Li, Feng, Wu, Zhao, Chen, Sun, Peng, Zhang, Yuan, Li, Hu, Li, Yang, Zhang, Hu, Sun and Hu 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
Huang, Hao
Cao, Weifan
Long, Zhiping
Kuang, Lei
Li, Xi
Feng, Yifei
Wu, Yuying
Zhao, Yang
Chen, Yinggang
Sun, Peng
Peng, Panxin
Zhang, Jinli
Yuan, Lijun
Li, Tianze
Hu, Huifang
Li, Gairui
Yang, Longkun
Zhang, Xing
Hu, Fulan
Sun, Xizhuo
Hu, Dongsheng
DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden
title DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden
title_full DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden
title_fullStr DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden
title_full_unstemmed DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden
title_short DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden
title_sort dna methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9880489/
https://www.ncbi.nlm.nih.gov/pubmed/36713578
http://dx.doi.org/10.3389/fonc.2022.1030335
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