AUTHOR=Guan Qingzhou , Song Xuekun , Zhang Zhenzhen , Zhang Yizhi , Chen Yating , Li Jing TITLE=Identification of Tamoxifen-Resistant Breast Cancer Cell Lines and Drug Response Signature JOURNAL=Frontiers in Molecular Biosciences VOLUME=7 YEAR=2020 URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2020.564005 DOI=10.3389/fmolb.2020.564005 ISSN=2296-889X ABSTRACT=
Breast cancer cell lines are frequently used to elucidate the molecular mechanisms of the disease. However, a large proportion of cell lines are affected by problems such as mislabeling and cross-contamination. Therefore, it is of great clinical significance to select optimal breast cancer cell lines models. Using tamoxifen survival-related genes from breast cancer tissues as the gold standard, we selected the optimal cell line model to represent the characteristics of clinical tissue samples. Moreover, using relative expression orderings of gene pairs, we developed a gene pair signature that could predict tamoxifen therapy outcomes. Based on 235 consistently identified survival-related genes from datasets GSE17705 and GSE6532, we found that only the differentially expressed genes (DEGs) from the cell line dataset GSE26459 were significantly reproducible in tissue samples (binomial test,