Exploring effects of DNA methylation and gene expression on pan-cancer drug response by mathematical models.

Wenhua Lv, Xingda Zhang, Huili Dong, Qiong Wu, Baoqing Sun, Yan Zhang

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Article in Experimental biology and medicine (Maywood, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

0.1field-weighted citation impact, top 57% of its field

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed, 1 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Wenhua LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China.

Xingda ZhangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150081, China.

Huili DongSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.

Qiong WuSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.

Baoqing SunGuangzhou Institute of Respiratory health, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 51000, China.ORCID 0000-0002-1671-0723

Yan ZhangGuangzhou Institute of Respiratory health, State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 51000, China.ORCID 0000-0002-5307-2484

Harbin Institute of Technology · CNHarbin Medical University · CNState Key Laboratory of Respiratory Disease · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since genetic alteration only accounts for 20%-30% in the drug effect-related factors, the role of epigenetic regulation mechanisms in drug response is gradually being valued. However, how epigenetic changes and abnormal gene expression affect the chemotherapy response remains unclear. Therefore, we constructed a variety of mathematical models based on the integrated DNA methylation, gene expression, and anticancer drug response data of cancer cell lines from pan-cancer levels to identify genes whose DNA methylation is associated with drug response and then to assess the impact of epigenetic regulation of gene expression on the sensitivity of anticancer drugs. The innovation of the mathematical models lies in: Linear regression model is followed by logistic regression model, which greatly shortens the calculation time and ensures the reliability of results by considering the covariates. Second, reconstruction of prediction models based on multiple dataset partition methods not only evaluates the model stability but also optimizes the drug-gene pairs. For 368,520 drug-gene pairs with

Indexed as

DNA MethylationDrug Resistance, NeoplasmGene Expression Regulation, NeoplasticEpigenesis, GeneticHumansModels, TheoreticalNeoplasmsDNA methylationDrug responseepigeneticsgene expressionpan-cancerprediction models

Identifiers

PMID33910405

DOI10.1177/15353702211007766

PMCPMC8326438

OpenAlexW3158354657

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.