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Use of a Combined Gene Expression Profile in Implementing a Drug Sensitivity Predictive Model for Breast Cancer

 Xianglan Zhang  ;  In-Ho Cha  ;  Ki-Yeol Kim 
 CANCER RESEARCH AND TREATMENT, Vol.49(1) : 116-128, 2017 
Journal Title
Issue Date
Analysis of Variance ; Antineoplastic Agents/pharmacology* ; Antineoplastic Agents/therapeutic use ; Breast Neoplasms/drug therapy ; Breast Neoplasms/genetics* ; Cell Line, Tumor ; Cluster Analysis ; Drug Resistance, Neoplasm/drug effects* ; Female ; Gene Expression Profiling* ; Gene Expression Regulation, Neoplastic/drug effects* ; Humans ; Models, Statistical ; Pharmacogenetics*/methods ; Transcriptome*
Combined predictor ; Drug sensitivity ; Gene expression
PURPOSE: Chemotherapy targets all rapidly growing cells, not only cancer cells, and thus is often associated with unpleasant side effects. Therefore, examination of the chemosensitivity based on genotypes is needed in order to reduce the side effects. MATERIALS AND METHODS: Various computational approaches have been proposed for predicting chemosensitivity based on gene expression profiles. A linear regression model can be used to predict the response of cancer cells to chemotherapeutic drugs, based on genomic features of the cells, and appropriate sample size for this method depends on the number of predictors. We used principal component analysis and identified a combined gene expression profile to reduce the number of predictors. RESULTS: The coefficients of determinanation (R2) of prediction models with combined gene expression and several independent gene expressions were similar. Corresponding F values, which represent model significances were improved by use of a combined gene expression profile, indicating that the use of a combined gene expression profile is helpful in predicting drug sensitivity. Even better, a prediction model can be used even with small samples because of the reduced number of predictors. CONCLUSION: Combined gene expression analysis is expected to contribute to more personalized management of breast cancer cases by enabling more effective targeting of existing therapies. This procedure for identifying a cell-type-specific gene expression profile can be extended to other chemotherapeutic treatments and many other heterogeneous cancer types.
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2. College of Dentistry (치과대학) > Dept. of Oral and Maxillofacial Surgery (구강악안면외과학교실) > 1. Journal Papers
5. Research Institutes (연구소) > Oral Cancer Research Institute (구강종양연구소) > 1. Journal Papers
Yonsei Authors
Kim, Ki Yeol(김기열) ORCID logo https://orcid.org/0000-0001-5357-1067
Zhang, Xiang Lan(장향란)
Cha, In Ho(차인호) ORCID logo https://orcid.org/0000-0001-8259-2190
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