Gene dysregulation analysis builds a mechanistic signature for prognosis and therapeutic benefit in colorectal cancer
作者机构：School of BiotechnologyEast China University of Science and TechnologyShanghai 200237China Shanghai Center for Bioinformation TechnologyShanghai 201203China Department of SurgeryShanghai Key Laboratory of Gastric NeoplasmsShanghai Institute of Digestive SurgeryRuijin HospitalShanghai jiao Tong University School of MedicineShanghai 200025China CAS Key Laboratory of Computational BiologyCAS-MPG Partner Institute for Computational BiologyShanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China Shanghai Engineering Research Center of Pharmaceutical Translation and Shanghai Industrial Technology InstituteShanghai 201203China
出 版 物：《Journal of Molecular Cell Biology》 (分子细胞生物学报（英文版）)
年 卷 期：2020年第12卷第11期
页 面：881-893页
核心收录：
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
基 金：This work was supported by the grants from the National Natural Science Foundation of China(81672736) the National Key R&D Program of China(2018YFC0910500) Shanghai Municipal Science and Technology(2017SHZDZX01 and 18DZ2294200) NIH CPTAC(Cancer Proteomic Tumor Analysis Consortium)program
主 题：gene dysregulation analysis mechanistic signature cancer precision medicine prognosis chemotherapy benefit colorectal cancer
摘 要：The implementation of cancer precision medicine requires biomarkers or signatures for predicting prognosis and therapeutic *** of current efforts in this field are paying much more attention to predictive accuracy than to molecular mechanistic ***-driven strategy has recently emerged,aiming to build signatures with both predictive power and explanatory *** by this strategy,we developed a robust gene dysregulation analysis framework with machine learning algorithms,which is capable of exploring gene dysregulations underlying carcinogenesis from high-dimensional data with cooperativity and synergy between regulators and several other transcriptional regulation rules taken into *** then applied the framework to a colorectal cancer(CRC)cohort from The Cancer Genome *** identified CRC-related dysregulations significantly covered known carcinogenic processes and exhibited good prognostic *** choosing dysregulations with greedy strategy,we built a four-dysregulation(4-DysReg)signature,which has the capability of predicting prognosis and adjuvant chemotherapy benefit.4-DysReg has the potential to explain carcinogenesis in terms of dysfunctional transcriptional *** results demonstrate that our gene dysregulation analysis framework could be used to develop predictive signature with mechanistic interpretability for cancer precision medicine,and furthermore,elucidate the mechanisms of carcinogenesis.
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