Although DNA variants could influence drug response, pharmacogenomics (PGx) is not yet widely implemented clinically. Variations in DPYD and CYP2D6 affect the metabolism of anticancer (fluorouracil, capecitabine) and analgesic drugs (codeine, tramadol), respectively. My PhD project focuses on PGx of opioids used for advanced cancer pain: so far, we identified germline variants influencing interindividual variability in opioid efficacy (https://doi.org/10.1002/ejp.4764) and toxicity (https://doi.org/10.1016/j.jpainsymman.2024.10.033). This project aims to validate these findings using UK Biobank data and to explore the potential of pre-emptive PGx in oncology.
1. GWAS on pain and nausea/vomiting intensity. To replicate results for opioid efficacy, we will analyse 4,795 UK Biobank cancer patients treated with morphine, oxycodone, fentanyl or buprenorphine (DF 2003). Pain intensity (DF 120101,29153,120022,2956) and pain relief (DF 120090) will be regressed on genetic variants, adjusting for age (DF 33,120128), sex, tumour type, opioid type/dose and population stratification. For toxicity, the same cohort and covariates will be used, adding chemotherapy and antiemetic treatment data (DF 28603-28605,21059).
2. Case-control GWAS on cancer pain susceptibility. A GWAS between cancer patients with and without pain (DF 120002,2453) will identify associations with pain susceptibility, adjusted for age, sex, tumour type, and opioid exposure.
3. Pre-emptive PGx relevance. Allele frequencies of variants in selected PGx genes will be estimated across patients. Genetic ancestry will be used to detect substructures and admixture; allele frequency differences between subgroups will be compared.
This project will validate pharmacogenomic markers of opioid response in cancer pain and support pre-emptive PGx strategies to improve the therapeutic treatments in oncology.
