The molecular genetics of chemotherapy–induced peripheral neuropathy: A systematic review and meta-analysis. (December 2017)

• Record Type: Journal Article
• Authors: Cliff, J.; Jorgensen, A.L.; Lord, R.; Azam, F.; Cossar, L.; Carr, D.F.; Pirmohamed, M.
• Is Part Of: Critical reviews in oncology/hematology. Volume 120(2017)
• Page Start: 127
• Page End: 140
• Publication Date: 2017-12
• Subjects: Chemotherapy -- Neurotoxicity -- Oxaliplatin -- Pharmacogenetics -- Taxane -- Vincristine; Oncology -- Periodicals; Hematology -- Periodicals; 616.994
• DOI: 10.1016/j.critrevonc.2017.09.009
• Languages: English
• ISSNs: 1040-8428

Abstract

Highlights: Evidence for genetic variants associated with CIPN is currently inconclusive. Several SNPs are of interest and warrant further study. Clear and consistent definition of phenotype is crucial in further research. Research consortia have aided phenotype standardisation in similar fields of study. Creation of consortia in cancer drug toxicity may be beneficial to future research. Abstract: Chemotherapy-induced peripheral neuropathy (CIPN) can adversely affect completion of systemic anti-cancer treatment and cause long-term morbidity. Increasingly pharmacogenetic studies have been performed to explore susceptibility to this important adverse effect. A systematic review was conducted to identify pharmacogenetic studies, assess their quality and findings and undertake meta-analysis where possible. 93 studies were included. Notable methodological issues included lack of standardisation and detail in phenotype definition and acknowledgement of potential confounding factors. Insufficient data was presented in many studies meaning only a minority could be included in meta-analysis showing mainly non-significant effects. Nonetheless, SNPs in CYP2C8, CYP3A4, ARHGEF10, EPHA and TUBB2A genes (taxanes), FARS2, ACYP2 and TAC1 (oxaliplatin), and CEP75 and CYP3A5 (vincristine) are of potential interest. These require exploration in large cohort studies with robust methodology and well-defined phenotypes. Seeking standardisation of phenotype, collaboration and subsequently, individual-patient-data meta-analysis may facilitate identifying contributory SNPs which could be combined in a polygenic risk score to predict those most at risk of CIPN.