Abstract
Abstract(1)BackgroundCompared with monotherapy, efficacious drug combinations can increase the therapeutic effect, decrease drug resistance of experimental subjects and the side effects of drugs. Therefore, efficacious drug combinations are widely used in the treatment of complex diseases, such as various cancers. However, compared with the mathematical model and computational method, experimental screening efficacious drug combinations is time-consuming, costly, laborious, and inefficient;(2)Methodswe predicted efficacious drug combinations in cancer based on random walk with restart (RWRDC). An efficacious score can be obtained between any two individual drugs by RWRDC;(3)ResultsAs a result, we analyzed the rationality of the efficacious score first. Besides, compared with the other methods by leave-one-out cross-validation, all the Area Under Receiver Operating Characteristic Curves (AUROCs) of RWRDC were higher for data sets of breast cancer, colorectal cancer, and lung cancer. Moreover, the case study of breast cancer showed that RWRDC could discover potential efficacious drug combinations;(4)ConclusionsThese results suggest that RWRDC is a novel way to discover efficacious drug combinations in cancer, which provides new prospects for cancer treatment. Furthermore, RWRDC is a semi-supervised learning framework that can be used to predict combinations of drugs for other complex diseases.
Publisher
Cold Spring Harbor Laboratory
Reference48 articles.
1. Randomized phase II trial of everolimus in combination with tamoxifen in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative metastatic breast cancer with prior exposure to aromatase inhibitors: a GINECO study;Journal of clinical oncology: official journal of the American Society of Clinical Oncology,2012
2. Backstrom, L. and Leskovec, J. (2011) supervised random walks. In King, I. , Nejdl, W. and Li, H. (eds), Proceedings of the fourth ACM international conference on Web search and data mining - WsDM‘11. New York, New York, UsA, ACM Press, 635.
3. Prediction of Effective Drug Combinations by an Improved Naïve Bayesian Algorithm
4. Barr, J.A. et al. (02152016) Abstract OT3-01-12: Phase II trial of lapatinib and everolimus for HER2 positive metastatic breast cancer. In, Ongoing Clinical Trials. American Association for Cancer Research, OT3-01-12-OT3-01-12.
5. Capecitabine and trastuzumab in heavily pretreated metastatic breast cancer;Journal of clinical oncology: official journal of the American Society of Clinical Oncology,2007
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