Cargando…

Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models

The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for buildin...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Yitan, Brettin, Thomas, Evrard, Yvonne A., Xia, Fangfang, Partin, Alexander, Shukla, Maulik, Yoo, Hyunseung, Doroshow, James H., Stevens, Rick L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565427/
https://www.ncbi.nlm.nih.gov/pubmed/32933072
http://dx.doi.org/10.3390/genes11091070
_version_ 1783595930346323968
author Zhu, Yitan
Brettin, Thomas
Evrard, Yvonne A.
Xia, Fangfang
Partin, Alexander
Shukla, Maulik
Yoo, Hyunseung
Doroshow, James H.
Stevens, Rick L.
author_facet Zhu, Yitan
Brettin, Thomas
Evrard, Yvonne A.
Xia, Fangfang
Partin, Alexander
Shukla, Maulik
Yoo, Hyunseung
Doroshow, James H.
Stevens, Rick L.
author_sort Zhu, Yitan
collection PubMed
description The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.
format Online
Article
Text
id pubmed-7565427
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75654272020-10-26 Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models Zhu, Yitan Brettin, Thomas Evrard, Yvonne A. Xia, Fangfang Partin, Alexander Shukla, Maulik Yoo, Hyunseung Doroshow, James H. Stevens, Rick L. Genes (Basel) Article The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response. MDPI 2020-09-11 /pmc/articles/PMC7565427/ /pubmed/32933072 http://dx.doi.org/10.3390/genes11091070 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhu, Yitan
Brettin, Thomas
Evrard, Yvonne A.
Xia, Fangfang
Partin, Alexander
Shukla, Maulik
Yoo, Hyunseung
Doroshow, James H.
Stevens, Rick L.
Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
title Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
title_full Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
title_fullStr Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
title_full_unstemmed Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
title_short Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
title_sort enhanced co-expression extrapolation (coxen) gene selection method for building anti-cancer drug response prediction models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565427/
https://www.ncbi.nlm.nih.gov/pubmed/32933072
http://dx.doi.org/10.3390/genes11091070
work_keys_str_mv AT zhuyitan enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT brettinthomas enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT evrardyvonnea enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT xiafangfang enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT partinalexander enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT shuklamaulik enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT yoohyunseung enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT doroshowjamesh enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels
AT stevensrickl enhancedcoexpressionextrapolationcoxengeneselectionmethodforbuildinganticancerdrugresponsepredictionmodels