DNA derived from archival tumor specimens can be used for germline pharmacogenetic analyses

The frequencies of CYP2D6 alleles and their impact on clinical outcomes of adjuvant tamoxifen therapy in Syrian breast cancer patients

Background

Tamoxifen is one of the fundamental pillars of adjuvant endocrine therapy for hormone receptor-positive breast cancer; however, 30–50% of patients receiving tamoxifen experience tumor relapse. CYP2D6, encoded by an extremely polymorphic CYP2D6 gene, is the rate-limiting enzyme of tamoxifen bioactivation. This study aimed at determining the frequencies of the most clinically relevant CYP2D6 alleles and evaluating their impact on the responsiveness to tamoxifen in a cohort of Syrian breast cancer patients.

Methods

This case–control study encompassed positive estrogen and/or progesterone receptor, stage 1–3 breast cancer female patients receiving tamoxifen at Al-Bairouni University Hospital, the major National Oncology Center in Syria. Successfully genotyped eligible patients (n = 97) were classified according to their response into; no recurrence group (n = 39) who had completed a five-year recurrence-free adjuvant tamoxifen therapy, and recurrence group (n = 58) who had experienced recurrence. Several star alleles including CYP2D6*4, CYP2D6*10, CYP2D6*41, and CYP2D6*69 were identified via targeted sequencing of specific polymerase chain reaction (PCR) products and phenotypes were assigned according to activity score (AS). The correlation between genotypes and disease-free survival (DFS) was assessed using Kaplan–Meier method and log-rank test. Hazard ratios were estimated using Cox proportional hazards regression models.

Results

The allelic frequencies of CYP2D6*41, CYP2D6*10, CYP2D6*4, and CYP2D6*69 were found to be 9.28%, 7.22%, 7.22%, and 2.58%, respectively. No statistically significant differences were observed in the frequencies of CYP2D6 phenotypes between the two arms (P = 0.24), nor the incidence of tamoxifen-induced hot flashes (P = 0.109). Poor metabolizers (PMs) tended to display shorter DFS than intermediate metabolizers (IMs) and normal metabolizers (NMs) combined (adjusted HR = 2.34, 95% CI = 0.84–6.55, P = 0.104). Notably, patients homozygous for the null CYP2D6*4 allele (1847A/A) had an elevated risk of disease recurrence compared to patients with 1847G/G genotype (adjusted HR = 5.23, 95% CI = 1.22–22.49, P = 0.026).

Conclusions

Our findings show no association between CYP2D6 phenotype and treatment outcomes of tamoxifen in Syrian breast cancer patients. Nevertheless, a worse DFS was revealed in patients with 1847A/A genotype (*4/*4).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10148-8.

Planning and Conducting a Pharmacogenetics Association Study

Pharmacogenetics (PGx) association studies are used to discover, replicate, and validate the association between an inherited genotype and a treatment outcome. The objective of this tutorial is to provide trainees and novice PGx researchers with an overview of the major decisions that need to be made when designing and conducting a PGx association study. The first critical decision is to determine whether the objective of the study is discovery, replication, or validation. Next, the researcher must identify a patient cohort that has all of the data necessary to conduct the intended analysis. Then, the investigator must select and define the treatment outcome, or phenotype, that will be analyzed. Next, the investigator must determine what genotyping approach and genetic data will be included in the analysis. Finally, the association between the genotype and phenotype is tested using some statistical analysis methodology. This tutorial is divided into five sections; each section describes commonly used approaches and provides suggestions and resources for designing and conducting a PGx association study. Successful PGx association studies are necessary to discover and validate associations between inherited genetic variation and treatment outcomes, which enable clinical translation to improve efficacy and reduce toxicity of treatment.