PGX6848: Exploratory PGx investigation of trametinib efficacy in a melanoma monotherapy study MEK114267

Trial description: Trametinib (GSK1120212), a selective inhibitor of MEK1 and MEK2 kinases, is approved for the treatment of BRAF V600E/K mutated metastatic melanoma as a monotherapy and in combination with dabrafenib (GSK2118436); a selective inhibitor of V600 mutated BRAF kinase. Inherited genetic variability may be one of several contributing factors that underlie individual treatment response to metastatic melanoma treatment. So far, there have been no previous pharmacogenetic (PGx) data generated around the genetics of treatment response to trametinib with regard to efficacy. The primary objective of this study is to identify germline genetic variants that may predict differential response to trametinib, measured by the progression free survival (PFS) endpoint, in metastatic melanoma subjects from MEK114267 study.The primary endpoint is PFS, defined as the time from randomization until the first documented sign of disease progression or death due to any cause. DNA samples from the subjects enrolled in MEK114267 were genotyped on the Affymetrix Axiom Biobank Plus SNP array to generate genome wide data. This data will be further stratified into 2 tiers for candidate gene analysis: (1) Tier 1: three functional variants in 2 candidate genes KRAS and IL8, which showed suggestive evidence of association with PFS in meta-analysis of dabrafenib studies (200632/PGx6847); (2) Tier 2: 67 other functional variants in 23 candidate genes from the BRAF-MEK and related signalling pathways as well as angiogenesis pathways, which have been implicated in resistance to various kinase inhibitors.Prior to the PGx analysis, quality control (QC) will be conducted on the genetic markers and on the subjects. No markers will be removed prior to the analysis based on their HWE p-values. However, markers showing substantial evidence of departure from HWE (p<1×10-8) will be investigated thoroughly for laboratory errors or other causes of departure from equilibrium and, if the cause remains undetermined, may be removed from the list of associated markers. Genetic ancestry estimates will be obtained by principal components analysis (PCA) using the SNPRelate R package. Plots will be created using the principal components overlaid with self-reported ethnic groups to aid in visualization of the data clustering and to determine the number of principal components required to infer genetic ancestry. The PGx analysis population will consist of subjects enrolled in clinical study, MEK114267 (n=260), who were treated with trametinib (n=172) or chemotherapy (n=88) and who provided written informed consent for PGx research and a blood sample for genotyping, were successfully genotyped, had valid phenotype data and passed genotyping QC. Since subjects with V600E mutation positive tumors demonstrated better tumor responses compared to subjects with V600K tumors in trametinib study, the PGx analysis will focus on subjects with V600E positive melanomas treated with trametinib (n=143) and chemotherapy (n=80) respectively.Genotype association tests will be performed assuming an additive genetic model. Cox proportional hazards model will be used to assess the association of genotype with time to event outcome (PFS). Covariates, which were listed in clinical RAPs as potential covariates or evaluated in sensitivity analyses or subgroup analysis of the clinical study, will be evaluated for association with PFS using Cox regression model and proportional hazard assumptions will be checked. Covariates for consideration will be individually evaluated for association with PFS by a univariate Cox model. All covariates that are significantly associated with PFS at p ≤ 0.05 will be included in a multivariate Cox model for further evaluation. Any covariate that is significant at p ≤ 0.05 in the multivariate Cox model will be included as covariate in PGx analysis model. If a covariate violated the proportional hazard assumptions, covariate by survival time interaction will be included for evaluation. The Bonferroni method will be used to adjust for multiple testing for the 2 independent Tier I and 67 Tier II SNPs respectively. The p-value thresholds for declaring statistical significance are 2.5E-02 and 7.46E-04, respectively.