Molecular chess? Hallmarks of anti-cancer drug resistance!

被引:218
作者
Cree, Ian A. [1 ,2 ]
Charlton, Peter [3 ]
机构
[1] Univ Hosp Coventry & Warwickshire, Dept Pathol, Coventry CV2 2DX, W Midlands, England
[2] Coventry Univ, Fac Hlth & Life Sci, Priory St, Coventry CV1 5FB, W Midlands, England
[3] Imperial Innovat, 52 Princes Gate,Exhibit Rd, London SW7 2PG, England
关键词
Cancer; Chemotherapy; Resistance; Tyrosine kinase inhibitor; Apoptosis; Proliferation; DNA damage; Detoxification; Microenvironment; Heterogeneity; CELL LUNG-CANCER; GASTROINTESTINAL STROMAL TUMORS; GROWTH-FACTOR RECEPTOR; TYROSINE KINASE INHIBITORS; GLUTATHIONE S-TRANSFERASES; OVARIAN-CANCER; COMBINATION CHEMOTHERAPY; MULTIDRUG-RESISTANCE; BREAST-CANCER; COMPANION DIAGNOSTICS;
D O I
10.1186/s12885-016-2999-1
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: The development of resistance is a problem shared by both classical chemotherapy and targeted therapy. Patients may respond well at first, but relapse is inevitable for many cancer patients, despite many improvements in drugs and their use over the last 40 years. Review: Resistance to anti-cancer drugs can be acquired by several mechanisms within neoplastic cells, defined as (1) alteration of drug targets, (2) expression of drug pumps, (3) expression of detoxification mechanisms, (4) reduced susceptibility to apoptosis, (5) increased ability to repair DNA damage, and (6) altered proliferation. It is clear, however, that changes in stroma and tumour microenvironment, and local immunity can also contribute to the development of resistance. Cancer cells can and do use several of these mechanisms at one time, and there is considerable heterogeneity between tumours, necessitating an individualised approach to cancer treatment. As tumours are heterogeneous, positive selection of a drug-resistant population could help drive resistance, although acquired resistance cannot simply be viewed as overgrowth of a resistant cancer cell population. The development of such resistance mechanisms can be predicted from pre-existing genomic and proteomic profiles, and there are increasingly sophisticated methods to measure and then tackle these mechanisms in patients. Conclusion: The oncologist is now required to be at least one step ahead of the cancer, a process that can be likened to 'molecular chess'. Thus, as well as an increasing role for predictive biomarkers to clinically stratify patients, it is becoming clear that personalised strategies are required to obtain best results.
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