Genome-wide analysis of three-way interplay among gene expression, cancer cell invasion and anti-cancer compound sensitivity

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Title:	Genome-wide analysis of three-way interplay among gene expression, cancer cell invasion and anti-cancer compound sensitivity
Authors:	許藝瓊;Hsu, Yi-Chiung;Chen, Hsuan-Yu;Yuan, Shinsheng;Yu, Sung-Liang;Lin, Chia-Hung;Wu, Guani;Yang, Pan-Chyr;Li, Ker-Chau
Contributors:	生醫理工學院生醫科學與工程學系
Keywords:	Aged;Aged, 80 and over;Analysis;Antimitotic agents;Antineoplastic agents;Antineoplastic Agents - pharmacology;Antineoplastic Agents - therapeutic use;Biomarkers, Tumor - biosynthesis;Biomedicine;Breast cancer;Cancer;Cancer cells;Cancer invasiveness;Cell Proliferation;Chemotherapy;Female;Gene expression;Gene Expression Profiling;Genetic aspects;Humans;Male;Medical research;Medicine;Medicine & Public Health;Metastasis;Microarray Analysis;Middle Aged;Neoplasm Metastasis - genetics;Neoplasms - drug therapy;Neoplasms - genetics;Neoplasms - pathology;Prognosis;Proteins;Rankings;Research Article;Survival Analysis;Tumors
Date:	2013-04-16
Issue Date:	2026-04-23 11:16:10 (UTC+8)
Publisher:	BioMed Central Ltd.;London: BioMed Central
Abstract:	摘要： Background Chemosensitivity and tumor metastasis are two primary issues in cancer management. Cancer cells often exhibit a wide range of sensitivity to anti-cancer compounds. To gain insight on the genetic mechanism of drug sensitivity, one powerful approach is to employ the panel of 60 human cancer cell lines developed by the National Cancer Institute (NCI). Cancer cells also show a broad range of invasion ability. However, a genome-wide portrait on the contributing molecular factors to invasion heterogeneity is lacking. Methods Our lab performed an invasion assay on the NCI-60 panel. We identified invasion-associated (IA) genes by correlating our invasion profiling data with the Affymetrix gene expression data on NCI-60. We then employed the recently released chemosensitivity data of 99 anti-cancer drugs of known mechanism to investigate the gene-drug correlation, focusing on the IA genes. Afterwards, we collected data from four independent drug-testing experiments to validate our findings on compound response prediction. Finally, we obtained published clinical and molecular data from two recent adjuvant chemotherapy cohorts, one on lung cancer and one on breast cancer, to test the performance of our gene signature for patient outcome prediction. Results First, we found 633 IA genes from the invasion-gene expression correlation study. Then, for each of the 99 drugs, we obtained a subset of IA genes whose expression levels correlated with drug-sensitivity profiles. We identified a set of eight genes ( EGFR, ITGA3, MYLK, RAI14, AHNAK, GLS, IL32 and NNMT ) showing significant gene-drug correlation with paclitaxel, docetaxel, erlotinib, everolimus and dasatinib. This eight-gene signature (derived from NCI-60) for chemosensitivity prediction was validated by a total of 107 independent drug tests on 78 tumor cell lines, most of which were outside of the NCI-60 panel. The eight-gene signature predicted relapse-free survival for the lung and breast cancer patients (log-rank P = 0.0263; 0.00021). Multivariate Cox regression yielded a hazard ratio of our signature of 5.33 (95% CI = 1.76 to 16.1) and 1.81 (95% CI = 1.19 to 2.76) respectively. The eight-gene signature features the cancer hallmark epidermal growth factor receptor (EGFR) and genes involved in cell adhesion, migration, invasion, tumor growth and progression. Conclusions Our study sheds light on the intricate three-way interplay among gene expression, invasion and compound-sensitivity. We report the finding of a unique signature that predicts chemotherapy survival for both lung and breast cancer. Augmenting the NCI-60 model with in vitro characterization of important phenotype-like invasion potential is a cost-effective approach to power the genomic chemosensitivity analysis. 其他題名： BMC Med 出版者： London: BioMed Central 出版日期： 2013-04-16 出處： BMC medicine, 2013-04, Vol.11 (1), p.106-106, Article 106 資源來源： Publicly Available Content Database 版權： Hsu et al.; licensee BioMed Central Ltd. 2013 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 版權： COPYRIGHT 2013 BioMed Central Ltd. 版權： 2013 Hsu et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 版權： Copyright © 2013 Hsu et al.; licensee BioMed Central Ltd. 2013 Hsu et al.; licensee BioMed Central Ltd. 識別號： ISSN: 1741-7015 識別號： EISSN: 1741-7015 識別號： DOI: 10.1186/1741-7015-11-106 識別號： PMID: 23590835
Appears in Collections:	[Department of Biomedical Sciences and Engineering ] journal & Dissertation

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