期刊论文详细信息
BMC Medicine
Genome-wide analysis of three-way interplay among gene expression, cancer cell invasion and anti-cancer compound sensitivity
Ker-Chau Li5  Pan-Chyr Yang1  Guani Wu3  Chia-Hung Lin3  Sung-Liang Yu2  Shinsheng Yuan3  Hsuan-Yu Chen3  Yi-Chiung Hsu4 
[1] Institute of Biomedical Sciences Academia Sinica, 128 Academia Road, Section 2, Taipei, 115, Taiwan;Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University College of Medicine, 1 Chang-Te Street, Taipei, 100, Taiwan;Institute of Statistical Science, Academia Sinica, 128 Academia Road, Section 2, Taipei, 115, Taiwan;NTU Research Center for Medical Excellence - Division of Genomic Medicine, 2 Syu-Jhou Road, Taipei, 100, Taiwan;Department of Statistics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
关键词: Chemotherapy;    Microarray;    Metastasis;    Invasion;    NCI-60;   
Others  :  857091
DOI  :  10.1186/1741-7015-11-106
 received in 2012-05-22, accepted in 2012-12-11,  发布年份 2013
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【 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.

【 授权许可】

   
2013 Hsu et al.; licensee BioMed Central Ltd.

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