癌症药物耐药潜在机制及预测方法

doi:10.11904/j.issn.1002-3070.2023.06.006

Abstract

Abstract: Cancer is a serious threat to human health and life,and its incidence and mortality are increasing year by year.Despite significant progress in the development of anticancer drugs,patients still inevitably develop drug resistance during treatment,leading to tumor recurrence.The mechanisms of cancer drug resistance are very complex,and how to accurately predict the response level of cancer patients to drug and intervene in advance has become a hot topic in the field of cancer research.With the continuous accumulation of high-throughput biomedical data,researchers have developed multiple large-scale data platforms related to cancer drug resistance,making the mining of biomedical big data more convenient.Moreover,with the development of artificial intelligence,various machine learning methods have also been applied to the prediction of cancer drug resistance.Thus,this paper summarizes the common resistance mechanisms of anticancer drugs,reviews the databases related to cancer drug resistance,and elaborates on the methods for predicting drug resistance,hoping to provides references and ideas for the treatment of drug-resistant tumors and the development of new drugs.

Key words: Drug resistance, Cancer, Drug response prediction, Machine learning, Deep learning

CLC Number:

R979.1

CAO Xinyu, ZHOU Xu, WANG Quan, JIANG Wei. Potential mechanisms and prediction methods of anticancer drug resistance[J]. Journal of Practical Oncology, 2023, 37(6): 491-495.

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URL: http://journal09.magtechjournal.com/Jwk3_syzlxzz/EN/10.11904/j.issn.1002-3070.2023.06.006

http://journal09.magtechjournal.com/Jwk3_syzlxzz/EN/Y2023/V37/I6/491

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Potential mechanisms and prediction methods of anticancer drug resistance

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