Acquired drug resistance is the major reason why patients fail to respond to cancer therapies.It is a challenging task to deter.mine the tipping point of endocrine resistance and detect the associated molecules.Derive...Acquired drug resistance is the major reason why patients fail to respond to cancer therapies.It is a challenging task to deter.mine the tipping point of endocrine resistance and detect the associated molecules.Derived from new systems biology theory, the dynamic network biomarker (DNB) method is designed to quantitatively identify the tipping point of a drastic system transition and can theoretically identify DNB genes that play key roles in acquiring drug resistance.We analyzed time-course mRNA sequence data generated from the tamoxifen-treated estrogen receptor (ER)-positive MCF-7 cell line, and identified the tipping point of endocrine resistance with its leading molecules.The results show that there is interplay between gene mutations and DNB genes, in which the accumulated mutations eventually affect the DNB genes that subsequently cause the change of transcriptional landscape, enabling full-blown drug resistance. Survival analyses based on clinical datasets validated that the DNB genes were associated with the poor survival of breast cancer patients.The results provided the detection for the pre-resistance state or early signs of endocrine resistance.Our predictive method may greatly benefit the scheduling of treatments for complex diseases in which patients are exposed to considerably different drugs and may become drug resistant.展开更多
基金This work was supported by grants from the National Key R&D Program of China (2017YFA0505500)Strategic Priority Research Program of the Chinese Academy of Sciences (XDBl3040700)+6 种基金the National Natural Science Foundation of China (11771152,91529303,31771476,31571363,31771469,91530320,61134013,81573023,81501203,and 11326035)Pearl River Science and Technology Nova Program of Guangzhou (201610010029)FISRT,Aihara Innovative Mathematical Modeling Project from Cabinet Office,JapanFundamental Research Funds for the Central Universities (2017ZD095)JSPS KAKENHI (15H05707)Grant-in-Aid for Scientific Research on Innovative Areas (3901) and SPS KAKENHI (15KT0084,17H06299,17H06302,and 18H04031)RIKEN Epigenome and Single Cell Project Grants to M.O.-H.This work was performed in part under the International Cooperative Research Program of Institute for Protein Research,Osaka University (ICRa-17-01 to L.C.and M.O.-H.).
文摘Acquired drug resistance is the major reason why patients fail to respond to cancer therapies.It is a challenging task to deter.mine the tipping point of endocrine resistance and detect the associated molecules.Derived from new systems biology theory, the dynamic network biomarker (DNB) method is designed to quantitatively identify the tipping point of a drastic system transition and can theoretically identify DNB genes that play key roles in acquiring drug resistance.We analyzed time-course mRNA sequence data generated from the tamoxifen-treated estrogen receptor (ER)-positive MCF-7 cell line, and identified the tipping point of endocrine resistance with its leading molecules.The results show that there is interplay between gene mutations and DNB genes, in which the accumulated mutations eventually affect the DNB genes that subsequently cause the change of transcriptional landscape, enabling full-blown drug resistance. Survival analyses based on clinical datasets validated that the DNB genes were associated with the poor survival of breast cancer patients.The results provided the detection for the pre-resistance state or early signs of endocrine resistance.Our predictive method may greatly benefit the scheduling of treatments for complex diseases in which patients are exposed to considerably different drugs and may become drug resistant.
