1. Pharmacogenomics of 5-fluorouracil in colorectal cancer: review and update
- Author
-
Li-Ming Tan, Pan Xie, Xi Li, Zhao-Qian Liu, Hong-Hao Zhou, Jin-Hong Liu, Jun-Luan Mo, and Wei Zhang
- Subjects
0301 basic medicine ,Drug ,Oncology ,Cancer Research ,medicine.medical_specialty ,Colorectal cancer ,media_common.quotation_subject ,Disease ,Drug resistance ,03 medical and health sciences ,0302 clinical medicine ,Internal medicine ,Autophagy ,Animals ,Humans ,Medicine ,media_common ,biology ,business.industry ,General Medicine ,medicine.disease ,Clinical trial ,030104 developmental biology ,Drug Resistance, Neoplasm ,Pharmacogenetics ,Fluorouracil ,030220 oncology & carcinogenesis ,Pharmacogenomics ,Methylenetetrahydrofolate reductase ,biology.protein ,Molecular Medicine ,Colorectal Neoplasms ,business ,Signal Transduction ,medicine.drug - Abstract
Colorectal cancer (CRC) is a disease with high morbidity and mortality rates. 5-fluorouracil (5-FU) is the first-line recommended drug for chemotherapy in patients with CRC, and it has a good effect on a variety of other solid tumors as well. Unfortunately, however, due to the emergence of drug resistance the effectiveness of treatment may be greatly reduced. In the past decade, major progress has been made in the field of 5-FU drug resistance in terms of molecular mechanisms, pre-clinical (animal) models and clinical trials. In this article we systematically review and update current knowledge on 5-FU pharmacogenomics related to drug uptake and activation, the expression and activity of target enzymes (DPD, TS and MTHFR) and key signaling pathways in CRC. Furthermore, a summary of drug combination strategies aimed at targeting specific genes and/or pathways to reverse 5-FU resistance is provided. Based on this, we suggest that causal relationships between genes, pathways and drug sensitivity should be systematically considered from a multidimensional perspective. In the design of research methods, emerging technologies such as CRISPR-Cas, TALENS and patient-derived xenograft models should be applied as far as possible to improve the accuracy of clinically relevant results.
- Published
- 2020