Computer-aided drug repurposing for cancer therapy: approaches and opportunities to challenge anticancer targets

Publication date: Available online 25 September 2019Source: Seminars in Cancer BiologyAuthor(s): Carla Mottini, Francesco Napolitano, Zhongxiao Li, Xin Gao, Luca CardoneABSTRACTDespite huge efforts made in academic and pharmaceutical worldwide research, current anticancer therapies achieve effective treatment in a limited number of neoplasia cases only. Oncology terms such as big killers - to identify tumours with yet a high mortality rate - or undruggable cancer targets, and chemoresistance, represent the current therapeutic debacle of cancer treatments. In addition, metastases, tumour microenvironments, tumour heterogeneity, metabolic adaptations, and immunotherapy resistance are essential features controlling tumour response to therapies, but still, lack effective therapeutics or modulators. In this scenario, where the pharmaceutical productivity and drug efficacy in oncology seem to have reached a plateau, the so-called drug repurposing - i.e. the use of old drugs, already in clinical use, for a different therapeutic indication - is an appealing strategy to improve cancer therapy. Opportunities for drug repurposing are often based on occasional observations or on time-consuming pre-clinical drug screenings that are often not hypothesis driven. In contrast, in-silico drug repurposing is an emerging, hypothesis-driven approach that takes advantage of the use of big-data. Indeed, the extensive use for -omics technologies, improved data storage, data meaning, machine learning...
Source: Seminars in Cancer Biology - Category: Cancer & Oncology Source Type: research