Exploration of drug-response mechanism by integrating genetics and epigenetics across cancers

Wenhua Lv; Mengying Zhang; Jiang Zhu; Min Zhang; Ce Ci; Shipeng Shang; Yanjun Wei; Hui Liu; Xin Li; Yan Zhang

doi:10.2217/epi-2017-0162

Exploration of drug-response mechanism by integrating genetics and epigenetics across cancers

Wenhua Lv
, Mengying Zhang
, Jiang Zhu
, Min Zhang
, Ce Ci
, Shipeng Shang
, Yanjun Wei
, Hui Liu
, Xin Li
, Yan Zhang^*

^*Corresponding author for this work

Harbin Medical University

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

Aim: To discover CpG island methylator phenotype (CIMP) as a predictor for cancer drug-response mechanism. Materials & methods: CIMP classification of 966 cancer cell lines was determined according to identified copy number alteration and differential methylation by DNA methylation profiles. CIMP-related drugs were analyzed by analysis of variance. Tissue-cell-drug networks were developed to predict drug response of individual samples. Results & conclusion: One hundred and thirty-six copy number gain and 142 copy number loss cell lines were classified into CIMP-high and CIMP-low groups, meanwhile 9 and 24 CIMP-associated drugs were identified, respectively. Specially, breast invasive carcinoma samples primarily composed by HCC1419 were predicted to be sensitive to GSK690693. The study provides guidance for drug response in cancer therapy through genome-wide DNA methylation.

Original language	English
Pages (from-to)	993-1010
Number of pages	18
Journal	Epigenomics
Volume	10
Issue number	7
DOIs	https://doi.org/10.2217/epi-2017-0162
State	Published - Jul 2018
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

ANOVA
CpG island methylator phenotype
TCGA
cancer
classification
copy number alteration
drug response
network
partial least squares
quadratic programing

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10.2217/epi-2017-0162

Cite this

@article{f1c81d2eb83c47408aaff6a107549884,

title = "Exploration of drug-response mechanism by integrating genetics and epigenetics across cancers",

abstract = "Aim: To discover CpG island methylator phenotype (CIMP) as a predictor for cancer drug-response mechanism. Materials \& methods: CIMP classification of 966 cancer cell lines was determined according to identified copy number alteration and differential methylation by DNA methylation profiles. CIMP-related drugs were analyzed by analysis of variance. Tissue-cell-drug networks were developed to predict drug response of individual samples. Results \& conclusion: One hundred and thirty-six copy number gain and 142 copy number loss cell lines were classified into CIMP-high and CIMP-low groups, meanwhile 9 and 24 CIMP-associated drugs were identified, respectively. Specially, breast invasive carcinoma samples primarily composed by HCC1419 were predicted to be sensitive to GSK690693. The study provides guidance for drug response in cancer therapy through genome-wide DNA methylation.",

keywords = "ANOVA, CpG island methylator phenotype, TCGA, cancer, classification, copy number alteration, drug response, network, partial least squares, quadratic programing",

author = "Wenhua Lv and Mengying Zhang and Jiang Zhu and Min Zhang and Ce Ci and Shipeng Shang and Yanjun Wei and Hui Liu and Xin Li and Yan Zhang",

note = "Publisher Copyright: {\textcopyright} 2018 Future Medicine Ltd.",

year = "2018",

month = jul,

doi = "10.2217/epi-2017-0162",

language = "英语",

volume = "10",

pages = "993--1010",

journal = "Epigenomics",

issn = "1750-1911",

publisher = "Taylor and Francis Ltd.",

number = "7",

}

TY - JOUR

T1 - Exploration of drug-response mechanism by integrating genetics and epigenetics across cancers

AU - Lv, Wenhua

AU - Zhang, Mengying

AU - Zhu, Jiang

AU - Zhang, Min

AU - Ci, Ce

AU - Shang, Shipeng

AU - Wei, Yanjun

AU - Liu, Hui

AU - Li, Xin

AU - Zhang, Yan

PY - 2018/7

Y1 - 2018/7

N2 - Aim: To discover CpG island methylator phenotype (CIMP) as a predictor for cancer drug-response mechanism. Materials & methods: CIMP classification of 966 cancer cell lines was determined according to identified copy number alteration and differential methylation by DNA methylation profiles. CIMP-related drugs were analyzed by analysis of variance. Tissue-cell-drug networks were developed to predict drug response of individual samples. Results & conclusion: One hundred and thirty-six copy number gain and 142 copy number loss cell lines were classified into CIMP-high and CIMP-low groups, meanwhile 9 and 24 CIMP-associated drugs were identified, respectively. Specially, breast invasive carcinoma samples primarily composed by HCC1419 were predicted to be sensitive to GSK690693. The study provides guidance for drug response in cancer therapy through genome-wide DNA methylation.

AB - Aim: To discover CpG island methylator phenotype (CIMP) as a predictor for cancer drug-response mechanism. Materials & methods: CIMP classification of 966 cancer cell lines was determined according to identified copy number alteration and differential methylation by DNA methylation profiles. CIMP-related drugs were analyzed by analysis of variance. Tissue-cell-drug networks were developed to predict drug response of individual samples. Results & conclusion: One hundred and thirty-six copy number gain and 142 copy number loss cell lines were classified into CIMP-high and CIMP-low groups, meanwhile 9 and 24 CIMP-associated drugs were identified, respectively. Specially, breast invasive carcinoma samples primarily composed by HCC1419 were predicted to be sensitive to GSK690693. The study provides guidance for drug response in cancer therapy through genome-wide DNA methylation.

KW - ANOVA

KW - CpG island methylator phenotype

KW - TCGA

KW - cancer

KW - classification

KW - copy number alteration

KW - drug response

KW - network

KW - partial least squares

KW - quadratic programing

UR - https://www.scopus.com/pages/publications/85049837015

U2 - 10.2217/epi-2017-0162

DO - 10.2217/epi-2017-0162

M3 - 文章

C2 - 29957027

AN - SCOPUS:85049837015

SN - 1750-1911

VL - 10

SP - 993

EP - 1010

JO - Epigenomics

JF - Epigenomics

IS - 7

ER -

Exploration of drug-response mechanism by integrating genetics and epigenetics across cancers

Abstract

UN SDGs

Keywords

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