Personalized medicine in non-small cell lung cancer: a review from a pharmacogenomics perspective.
10.1016/j.apsb.2018.04.005
- Author:
Wenxiao JIANG
1
;
Guiqing CAI
1
;
Peter C HU
2
;
Yue WANG
3
Author Information
1. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
2. The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
3. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
- Publication Type:Journal Article
- Keywords:
Anaplastic lymphoma kinase;
Inhibitor;
Monoclonal antibody;
Non-small cell lung cancer;
Personalized medicine;
Pharmacogenomics;
Tyrosine kinase
- From:
Acta Pharmaceutica Sinica B
2018;8(4):530-538
- CountryChina
- Language:English
-
Abstract:
Non-small cell lung cancer is a prevalent and rapidly-expanding challenge to modern medicine. While generalized medicine with traditional chemotherapy yielded comparatively poor response rates and treatment results, the cornerstone of personalized medicine using genetic profiling to direct treatment has exalted the successes seen in the field and raised the standard for patient treatment in lung and other cancers. Here, we discuss the current state and advances in the field of personalized medicine for lung cancer, reviewing several of the mutation-targeting strategies that are approved for clinical use and how they are guided by patient genetic information. These classes include inhibitors of tyrosine kinase (TKI), anaplastic lymphoma kinase (ALK), and monoclonal antibodies. Selecting from these treatment plans and determining the optimal dosage requires in-depth genetic guidance with consideration towards not only the underlying target genes but also other factors such as individual metabolic capability and presence of resistance-conferring mutations both directly on the target gene and along its cascade(s). Finally, we provide our viewpoints on the future of personalized medicine in lung cancer, including target-based drug combination, mutation-guided drug design and the necessity for data of population genetics, to provide rough guidance on treating patients who are unable to get genetic testing.
