Distinguishing Glioblastoma Subtypes by Methylation Signatures

Glioblastoma, also called glioblastoma multiform (GBM), is the most aggressive cancer that initiates within the brain. GBM is produced in the central nervous system. Cancer cells in GBM are similar to stem cells. Several different schemes for GBM stratification exist. These schemes are based on inte...

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Main Authors: Yu-Hang Zhang, Zhandong Li, Tao Zeng, Xiaoyong Pan, Lei Chen, Dejing Liu, Hao Li, Tao Huang, Yu-Dong Cai
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Genetics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2020.604336/full
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spelling doaj-abdc075de6bb404382845993dcfcf5cc2020-11-25T04:12:00ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-11-011110.3389/fgene.2020.604336604336Distinguishing Glioblastoma Subtypes by Methylation SignaturesYu-Hang Zhang0Yu-Hang Zhang1Zhandong Li2Tao Zeng3Xiaoyong Pan4Lei Chen5Dejing Liu6Hao Li7Tao Huang8Yu-Dong Cai9School of Life Sciences, Shanghai University, Shanghai, ChinaChanning Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United StatesCollege of Food Engineering, Jilin Engineering Normal University, Changchun, ChinaShanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai, ChinaInstitute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, ChinaCollege of Information Engineering, Shanghai Maritime University, Shanghai, ChinaShanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, ChinaCollege of Food Engineering, Jilin Engineering Normal University, Changchun, ChinaShanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, ChinaSchool of Life Sciences, Shanghai University, Shanghai, ChinaGlioblastoma, also called glioblastoma multiform (GBM), is the most aggressive cancer that initiates within the brain. GBM is produced in the central nervous system. Cancer cells in GBM are similar to stem cells. Several different schemes for GBM stratification exist. These schemes are based on intertumoral molecular heterogeneity, preoperative images, and integrated tumor characteristics. Although the formation of glioblastoma is remarkably related to gene methylation, GBM has been poorly classified by epigenetics. To classify glioblastoma subtypes on the basis of different degrees of genes’ methylation, we adopted several powerful machine learning algorithms to identify numerous methylation features (sites) associated with the classification of GBM. The features were first analyzed by an excellent feature selection method, Monte Carlo feature selection (MCFS), resulting in a feature list. Then, such list was fed into the incremental feature selection (IFS), incorporating one classification algorithm, to extract essential sites. These sites can be annotated onto coding genes, such as CXCR4, TBX18, SP5, and TMEM22, and enriched in relevant biological functions related to GBM classification (e.g., subtype-specific functions). Representative functions, such as nervous system development, intrinsic plasma membrane component, calcium ion binding, systemic lupus erythematosus, and alcoholism, are potential pathogenic functions that participate in the initiation and progression of glioblastoma and its subtypes. With these sites, an efficient model can be built to classify the subtypes of glioblastoma.https://www.frontiersin.org/articles/10.3389/fgene.2020.604336/fullglioblastomamethylationsignaturesubtypeclassification
collection DOAJ
language English
format Article
sources DOAJ
author Yu-Hang Zhang
Yu-Hang Zhang
Zhandong Li
Tao Zeng
Xiaoyong Pan
Lei Chen
Dejing Liu
Hao Li
Tao Huang
Yu-Dong Cai
spellingShingle Yu-Hang Zhang
Yu-Hang Zhang
Zhandong Li
Tao Zeng
Xiaoyong Pan
Lei Chen
Dejing Liu
Hao Li
Tao Huang
Yu-Dong Cai
Distinguishing Glioblastoma Subtypes by Methylation Signatures
Frontiers in Genetics
glioblastoma
methylation
signature
subtype
classification
author_facet Yu-Hang Zhang
Yu-Hang Zhang
Zhandong Li
Tao Zeng
Xiaoyong Pan
Lei Chen
Dejing Liu
Hao Li
Tao Huang
Yu-Dong Cai
author_sort Yu-Hang Zhang
title Distinguishing Glioblastoma Subtypes by Methylation Signatures
title_short Distinguishing Glioblastoma Subtypes by Methylation Signatures
title_full Distinguishing Glioblastoma Subtypes by Methylation Signatures
title_fullStr Distinguishing Glioblastoma Subtypes by Methylation Signatures
title_full_unstemmed Distinguishing Glioblastoma Subtypes by Methylation Signatures
title_sort distinguishing glioblastoma subtypes by methylation signatures
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2020-11-01
description Glioblastoma, also called glioblastoma multiform (GBM), is the most aggressive cancer that initiates within the brain. GBM is produced in the central nervous system. Cancer cells in GBM are similar to stem cells. Several different schemes for GBM stratification exist. These schemes are based on intertumoral molecular heterogeneity, preoperative images, and integrated tumor characteristics. Although the formation of glioblastoma is remarkably related to gene methylation, GBM has been poorly classified by epigenetics. To classify glioblastoma subtypes on the basis of different degrees of genes’ methylation, we adopted several powerful machine learning algorithms to identify numerous methylation features (sites) associated with the classification of GBM. The features were first analyzed by an excellent feature selection method, Monte Carlo feature selection (MCFS), resulting in a feature list. Then, such list was fed into the incremental feature selection (IFS), incorporating one classification algorithm, to extract essential sites. These sites can be annotated onto coding genes, such as CXCR4, TBX18, SP5, and TMEM22, and enriched in relevant biological functions related to GBM classification (e.g., subtype-specific functions). Representative functions, such as nervous system development, intrinsic plasma membrane component, calcium ion binding, systemic lupus erythematosus, and alcoholism, are potential pathogenic functions that participate in the initiation and progression of glioblastoma and its subtypes. With these sites, an efficient model can be built to classify the subtypes of glioblastoma.
topic glioblastoma
methylation
signature
subtype
classification
url https://www.frontiersin.org/articles/10.3389/fgene.2020.604336/full
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