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Yuan T, Edelmann D, Kather JN, Fan Z, Tagscherer KE, Roth W, Bewerunge-Hudler M, Brobeil A, Kloor M, Bläker H, Burwinkel B, Brenner H, Hoffmeister M. CpG-biomarkers in tumor tissue and prediction models for the survival of colorectal cancer: A systematic review and external validation study. Crit Rev Oncol Hematol 2024; 193:104199. [PMID: 37952858 DOI: 10.1016/j.critrevonc.2023.104199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 11/14/2023] Open
Abstract
The research aimed to identify previously published CpG-methylation-based prognostic biomarkers and prediction models for colorectal cancer (CRC) prognosis and validate them in a large external cohort. A systematic search was conducted, analyzing 298 unique CpGs and 12 CpG-based prognostic models from 28 studies. After adjustment for clinical variables, 48 CpGs and five prognostic models were confirmed to be associated with survival. However, the discrimination ability of the models was insufficient, with area under the receiver operating characteristic curves ranging from 0.53 to 0.62. Calibration accuracy was mostly poor, and no significant added prognostic value beyond traditional clinical variables was observed. All prognostic models were rated at high risk of bias. While a fraction of CpGs showed potential clinical utility and generalizability, the CpG-based prognostic models performed poorly and lacked clinical relevance.
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Affiliation(s)
- Tanwei Yuan
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Dominic Edelmann
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jakob N Kather
- Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany; Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany
| | - Ziwen Fan
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Katrin E Tagscherer
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany; Institute of Pathology, University Medical Center Mainz, Mainz, Germany
| | - Wilfried Roth
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany; Institute of Pathology, University Medical Center Mainz, Mainz, Germany
| | | | - Alexander Brobeil
- Institute of Pathology, University of Heidelberg, Heidelberg, Germany
| | - Matthias Kloor
- Department of Applied Tumor Biology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Hendrik Bläker
- Institute of Pathology, University of Leipzig Medical Center, Leipzig, Germany
| | - Barbara Burwinkel
- Division of Molecular Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Gynecology and Obstetrics, Molecular Biology of Breast Cancer, University of Heidelberg, Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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2
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Zhan L, Sun C, Zhang Y, Zhang Y, Jia Y, Wang X, Li F, Li D, Wang S, Yu T, Zhang J, Li D. Four methylation-driven genes detected by linear discriminant analysis model from early-stage colorectal cancer and their methylation levels in cell-free DNA. Front Oncol 2022; 12:949244. [PMID: 36158666 PMCID: PMC9491101 DOI: 10.3389/fonc.2022.949244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 08/12/2022] [Indexed: 12/24/2022] Open
Abstract
The process of colorectal cancer (CRC) formation is considered a typical model of multistage carcinogenesis in which aberrant DNA methylation plays an important role. In this study, 752 methylation-driven genes (MDGs) were identified by the MethylMix package based on methylation and gene expression data of CRC in The Cancer Genome Atlas (TCGA). Iterative recursive feature elimination (iRFE) based on linear discriminant analysis (LDA) was used to determine the minimum MDGs (iRFE MDGs), which could distinguish between cancer and cancer-adjacent tissues. Further analysis indicated that the changes in methylation levels of the four iRFE MDGs, ADHFE1-Cluster1, CNRIP1-Cluster1, MAFB, and TNS4, occurred in adenoma tissues, while changes did not occur until stage IV in cell-free DNA. Furthermore, the methylation levels of iRFE MDGs were correlated with the genes involved in the reprogramming process of somatic cells to pluripotent stem cells, which is considered the common signature of cancer cells and embryonic stem cells. The above results indicated that the four iRFE MDGs may play roles in the early stage of colorectal carcinogenesis and highlighted the complicated relationship between tissue DNA and cell-free DNA (cfDNA).
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Affiliation(s)
- Lei Zhan
- Medical Oncology Department of Gastrointestinal Cancer, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, China
| | - Changjian Sun
- Clinical Laboratory, Air Force Hospital of Northern Theater, PLA, Shenyang, China
| | - Yu Zhang
- Clinical Laboratory, Air Force Hospital of Northern Theater, PLA, Shenyang, China
| | - Yue Zhang
- Clinical Laboratory, Air Force Hospital of Northern Theater, PLA, Shenyang, China
| | - Yuzhe Jia
- Clinical Laboratory, Air Force Hospital of Northern Theater, PLA, Shenyang, China
| | - Xiaoyan Wang
- Clinical Laboratory, Air Force Hospital of Northern Theater, PLA, Shenyang, China
| | - Feifei Li
- Medical Oncology Department of Gastrointestinal Cancer, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, China
| | - Donglin Li
- Orthopedics Department, Air Force Hospital of Northern Theater, PLA, Shenyang, China
| | - Shen Wang
- Department of Ultrasound and Special Diagnosis, Air Force Hospital of Northern Theater, PLA, Shenyang, China
| | - Tao Yu
- Nursing Department, Air Force Medical Center, PLA, Beijing, China
| | - Jingdong Zhang
- Medical Oncology Department of Gastrointestinal Cancer, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, China
| | - Deyang Li
- Clinical Laboratory, Air Force Hospital of Northern Theater, PLA, Shenyang, China
- *Correspondence: Deyang Li,
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3
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Cao L, Chen E, Zhang H, Ba Y, Yan B, Li T, Yang J. Construction of a novel methylation-related prognostic model for colorectal cancer based on microsatellite status. J Cell Biochem 2021; 122:1781-1790. [PMID: 34397105 DOI: 10.1002/jcb.30131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 07/30/2021] [Accepted: 08/03/2021] [Indexed: 12/15/2022]
Abstract
The present study aimed to construct a novel methylation-related prognostic model based on microsatellite status that may enhance the prognosis of colorectal cancer (CRC) from methylation and microsatellite status perspective. DNA methylation and mRNA expression data with clinical information were downloaded from The Cancer Genome Atlas (TCGA) data set. The samples were divided into microsatellite stability and microsatellite instability group, and CIBERSORT was used to assess the immune cell infiltration characteristics. After identifying the differentially methylated genes and differentially expression genes using R packages, the methylation-driven genes were further identified. Prognostic genes that were used to establish the methylation-related risk score model were generated by the univariate and multivariate Cox regression model. Finally, we established and evaluated the methylation-related prognostic model for CRC patients. A total of 69 MDGs were obtained and three of these genes (MIOX, TH, DKFZP434K028) were selected to construct the prognostic model. Patients in the low-risk score group had a conspicuously better overall survival than those in the high-risk score group (p < .0001). The area under the receiver operating characteristic curve for this model was 0.689 at 3 years, 0.674 at 4 years, and 0.658 at 5 years. The Wilcoxon test showed that higher risk score was associated with higher T stage (p = .01), N stages (p = .0028), metastasis (p = .013), and advanced pathological stage (p = .0013). However, the more instability of microsatellite status, the lower risk score of CRC patients (p = .0048). Our constructed methylation-related prognostic model based on microsatellite status presents potential significance in assessing recurrence risk stratification, tumor staging, and immunotherapy for CRC patients.
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Affiliation(s)
- Lichao Cao
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, China.,Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an, China
| | - Erfei Chen
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, China.,Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an, China
| | - Hezi Zhang
- Shenzhen Nuclear Gene Technology Co., Ltd., Shenzhen, China
| | - Ying Ba
- Shenzhen Nuclear Gene Technology Co., Ltd., Shenzhen, China
| | - Bianbian Yan
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, China.,Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an, China
| | - Tong Li
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, China.,Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an, China
| | - Jin Yang
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, China.,Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an, China
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Zhu L, Sun H, Tian G, Wang J, Zhou Q, Liu P, Tang X, Shi X, Yang L, Liu G. Development and validation of a risk prediction model and nomogram for colon adenocarcinoma based on methylation-driven genes. Aging (Albany NY) 2021; 13:16600-16619. [PMID: 34182539 PMCID: PMC8266312 DOI: 10.18632/aging.203179] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 05/13/2021] [Indexed: 12/13/2022]
Abstract
Evidence suggests that abnormal DNA methylation patterns play a crucial role in the etiology and pathogenesis of colon adenocarcinoma (COAD). In this study, we identified a total of 97 methylation-driven genes (MDGs) through a comprehensive analysis of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression analysis identified four MDGs (CBLN2, RBM47, SLCO4C1, and TMEM220) associated with overall survival (OS) in COAD patients. A risk prediction model was then developed based on these four MDGs to predict the prognosis of COAD patients. We also created a nomogram that incorporated risk scores, age, and TNM stage to promote a personalized prediction of OS in COAD patients. Compared with the traditional TNM staging system, our new nomogram was better at predicting the OS of COAD patients. In cell experiments, we confirmed that the mRNA expression levels of CLBN2 and TMEM220 were regulated by the methylation of their promoter regions. Moreover, immunohistochemistry showed that CBLN2 and TMEM220 were potential prognostic biomarkers for COAD patients. In summary, we have established a risk prediction model and nomogram that might be effectively utilized to promote the prediction of OS in COAD patients.
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Affiliation(s)
- Liangyu Zhu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, P.R. China
| | - Hongyu Sun
- Department of Epidemiology and Statistics, School of Public Health, Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, P.R. China
| | - Guo Tian
- Department of Medical Record, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, P.R. China
| | - Juan Wang
- Department of Pathology, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, P.R. China
| | - Qian Zhou
- Department of Clinical Pharmacology, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, P.R. China
| | - Pu Liu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, P.R. China
| | - Xuejiao Tang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, P.R. China
| | - Xinrui Shi
- Department of Epidemiology and Statistics, School of Public Health, Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, P.R. China
| | - Lei Yang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, P.R. China
| | - Guangjie Liu
- Department of Thoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, P.R. China
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5
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Huang H, Zhang L, Fu J, Tian T, Liu X, Liu Y, Sun H, Li D, Zhu L, Xu J, Zheng T, Jia C, Zhao Y. Development and validation of 3-CpG methylation prognostic signature based on different survival indicators for colorectal cancer. Mol Carcinog 2021; 60:403-412. [PMID: 33826760 DOI: 10.1002/mc.23300] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/16/2021] [Accepted: 03/24/2021] [Indexed: 12/24/2022]
Abstract
Abnormal DNA methylation is considered a vital hallmark to regulate gene expression and influence the development and progression of colorectal cancer (CRC). Although CRC-related methylation prognostic models have been developed, their clinical application is limited due to the lack of external validation and extension to other survival evaluation indicators. Therefore, this study aimed to develop and validate novel methylation prognostic models correlated with different survival indicators for individualized prognosis prediction for CRC patients. The prognostic-related CpG sites of methylation-driven genes screened by the MethylMix algorithm were identified and validated in The Cancer Genome Atlas (TCGA) CRC methylation data and our methylation data. The prognostic models correlated with different survival evaluation indicators (overall survival [OS] and disease-free survival [DFS]) were developed and validated in the TCGA CRC dataset (N = 376) and our independent CRC dataset (N = 227). We utilized the combination of selected 3-CpG methylation sites in three genes (DAPP1, FAM3D, and PIGR) to construct a prognostic risk-score model. In the training dataset, Kaplan-Meier survival analysis demonstrated that high-risk patients had significantly poorer survival than low-risk patients (pOS = .0014; pDFS < .001). Then, the 3-CpG methylation signature was successfully validated as an independent predictor in the testing data set (pOS = .016; pDFS = .016). A prognostic nomogram was constructed and validated. Additionally, mediation analysis revealed the direct effect of the methylation signature on CRC prognosis (pOS = 9.149e-06; pDFS = .001). In summary, our study revealed that the 3-CpG methylation signature might be a potential prognostic indicator to facilitate individualized survival prediction for CRC patients.
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Affiliation(s)
- Hao Huang
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Lei Zhang
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Jinming Fu
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Tian Tian
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Xinyan Liu
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Yupeng Liu
- Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Hongru Sun
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Dapeng Li
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Lin Zhu
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Jing Xu
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Ting Zheng
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Chenyang Jia
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
| | - Yashuang Zhao
- Department of Epidemiology, Public Health School of Harbin Medical University, Harbin, China
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Chen H, Luo J, Guo J. Identification of an alternative splicing signature as an independent factor in colon cancer. BMC Cancer 2020; 20:904. [PMID: 32962686 PMCID: PMC7510085 DOI: 10.1186/s12885-020-07419-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/15/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Colon cancer is a common malignant tumor with a poor prognosis. Abnormal alternative splicing (AS) events played a part in the occurrence and metastasis of the tumor. We aimed to develop a survival-associated AS signature in colon cancer. METHODS The Percent Spliced In values of AS events were available in The Cancer Genome Atlas (TCGA) SpliceSeq database. Univariate Cox analysis was carried out to detect the prognosis-related AS events. We created a predictive model on account of the survival-associated AS events, which was further validated with a training-testing group design. Kaplan-Meier analysis was applied to assess patient survival. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of this model. Meanwhile, the clinical relevance of the signature and its regulatory relationship with splicing factors (SFs) were also evaluated. RESULTS In total, 2132 survival-related AS events were identified from colon cancer samples. We developed an eleven-AS signature, in which the 5-year AUC value was 0.911. Meanwhile, the AUC values at five years were 0.782 and 0.855 in the testing and entire cohort, respectively. Multivariate Cox regression displayed that the T category and the risk score of the signature were independent risk factors of colon cancer survival. Also, we constructed an SFs-AS network based on 11 SFs and 48 AS events. CONCLUSIONS We identified an eleven-AS signature of colon cancer. This signature could be treated as an independent prognostic factor.
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Affiliation(s)
- Haitao Chen
- Department of Orthopedic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Jun Luo
- Department of Pathology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.,Wuhan University Center for Pathology and Molecular Diagnostics, Wuhan, 430071, China
| | - Jianchun Guo
- Department of Pathology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China. .,Wuhan University Center for Pathology and Molecular Diagnostics, Wuhan, 430071, China.
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