System level network data and models attack cancer drug resistance.

IF 6.8 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Márk Kerestély, Dávid Keresztes, Levente Szarka, Borbála M Kovács, Klára Schulc, Dániel V Veres, Peter Csermely
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引用次数: 0

Abstract

Drug resistance is responsible for >90% of cancer related deaths. Cancer drug resistance is a system level network phenomenon covering the entire cell. Small-scale interactomes and signalling network models of drug resistance guide directed drug development. Recently, proteome-wide human interactome and signalling network data have become available, which have been extended by drug-target interactions, drug resistance-inducing mutations, as well as by several cancer and drug resistance-related multi-omics datasets. System level signalling network models have become available examining therapy resistance, performing in silico clinical trials, and conducting large, in silico drug combination screens. Drug resistance network data and models have become interoperable and reliable. These advances paved the road for building proteome-wide drug resistance models.

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来源期刊
CiteScore
15.40
自引率
12.30%
发文量
270
审稿时长
2.0 months
期刊介绍: The British Journal of Pharmacology (BJP) is a biomedical science journal offering comprehensive international coverage of experimental and translational pharmacology. It publishes original research, authoritative reviews, mini reviews, systematic reviews, meta-analyses, databases, letters to the Editor, and commentaries. Review articles, databases, systematic reviews, and meta-analyses are typically commissioned, but unsolicited contributions are also considered, either as standalone papers or part of themed issues. In addition to basic science research, BJP features translational pharmacology research, including proof-of-concept and early mechanistic studies in humans. While it generally does not publish first-in-man phase I studies or phase IIb, III, or IV studies, exceptions may be made under certain circumstances, particularly if results are combined with preclinical studies.
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