Molecular chess? Hallmarks of anti-cancer drug resistance. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Cree, Ian; Charlton, Peter
• Is Part Of: BMC cancer. Volume 17:Issue 1(2017)
• Page Start: 1
• Page End: 8
• Publication Date: 2017-12
• Subjects: Cancer -- Chemotherapy -- Resistance -- Tyrosine kinase inhibitor -- Apoptosis -- Proliferation -- DNA damage -- Detoxification -- Microenvironment -- Heterogeneity; Cancer -- Periodicals; 616.994005
• DOI: 10.1186/s12885-016-2999-1
• Languages: English
• ISSNs: 1471-2407

Abstract

Abstract 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.