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Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes

With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lac...

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Autores principales: Liu, Yang, Yin, Xiaoyao, Zhong, Jing, Guan, Naiyang, Luo, Zhigang, Min, Lishan, Yao, Xing, Bo, Xiaochen, Dai, Licheng, Bai, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5368690/
https://www.ncbi.nlm.nih.gov/pubmed/28245581
http://dx.doi.org/10.3390/genes8030086
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author Liu, Yang
Yin, Xiaoyao
Zhong, Jing
Guan, Naiyang
Luo, Zhigang
Min, Lishan
Yao, Xing
Bo, Xiaochen
Dai, Licheng
Bai, Hui
author_facet Liu, Yang
Yin, Xiaoyao
Zhong, Jing
Guan, Naiyang
Luo, Zhigang
Min, Lishan
Yao, Xing
Bo, Xiaochen
Dai, Licheng
Bai, Hui
author_sort Liu, Yang
collection PubMed
description With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi) of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA). Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.
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spelling pubmed-53686902017-04-05 Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes Liu, Yang Yin, Xiaoyao Zhong, Jing Guan, Naiyang Luo, Zhigang Min, Lishan Yao, Xing Bo, Xiaochen Dai, Licheng Bai, Hui Genes (Basel) Article With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi) of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA). Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation. MDPI 2017-02-24 /pmc/articles/PMC5368690/ /pubmed/28245581 http://dx.doi.org/10.3390/genes8030086 Text en © 2017 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
Liu, Yang
Yin, Xiaoyao
Zhong, Jing
Guan, Naiyang
Luo, Zhigang
Min, Lishan
Yao, Xing
Bo, Xiaochen
Dai, Licheng
Bai, Hui
Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes
title Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes
title_full Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes
title_fullStr Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes
title_full_unstemmed Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes
title_short Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes
title_sort systematic identification and assessment of therapeutic targets for breast cancer based on genome-wide rna interference transcriptomes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5368690/
https://www.ncbi.nlm.nih.gov/pubmed/28245581
http://dx.doi.org/10.3390/genes8030086
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