HLA-B*57:01 Confers Susceptibility to Pazopanib-Associated Liver Injury in Patients with Cancer.

PURPOSE: Pazopanib is an effective treatment for advanced renal cell carcinoma and soft-tissue sarcoma. Transaminase elevations have been commonly observed in pazopanib-treated patients. We conducted pharmacogenetic analyses to explore mechanistic insight into pazopanib-induced liver injury. EXPERIMENTAL DESIGN: The discovery analysis tested association between four-digit HLA alleles and alanine aminotransferase (ALT) elevation in pazopanib-treated patients with cancer from eight clinical trials (N = 1,188). We conducted confirmatory analysis using an independent dataset of pazopanib-treated patients from 23 additional trials (N = 1,002). Genome-wide association study (GWAS) for transaminase elevations was also conducted. RESULTS: The discovery study identified an association between HLA-B*57:01 carriage and ALT elevation [P = 5.0 × 10(-5) for maximum on-treatment ALT (MaxALT); P = 4.8 × 10(-4) for time to ALT > 3× upper limit of normal (ULN) event; P = 4.1 × 10(-5) for time to ALT > 5× ULN event] that is significant after adjustment for number of HLA alleles tested. We confirmed these associations with time to ALT elevation event (P = 8.1 × 10(-4) for ALT > 3× ULN, P = 9.8 × 10(-3) for ALT > 5× ULN) in an independent dataset. In the combined data, HLA-B*57:01 carriage was associated with ALT elevation (P = 4.3 × 10(-5) for MaxALT, P = 5.1 × 10(-6) for time to ALT > 3×ULN event, P = 5.8 × 10(-6) for time to ALT > 5× ULN event). In HLA-B*57:01 carriers and noncarriers, frequency of ALT > 3× ULN was 31% and 19%, respectively, and frequency of ALT > 5× ULN was 18% and 10%, respectively. GWAS revealed a possible borderline association, which requires further evaluation. CONCLUSIONS: These data indicate that HLA-B*57:01 carriage confers higher risk of ALT elevation in patients receiving pazopanib and provide novel insight implicating an immune-mediated mechanism for pazopanib-associated hepatotoxicity in some patients.

Rash in lapatinib-treated patients is not associated with human leukocyte antigen polymorphisms.

Rash is a common side effect of lapatinib treatment. Since human leukocyte antigen (HLA) alleles have been implicated in multiple drug-induced cutaneous reactions, this study investigated the association of HLA alleles with lapatinib-induced rash. 1191 participants from a large lapatinib monotherapy trial underwent HLA genotyping, and allele carriage frequencies between rash cases and controls were compared. This analysis had adequate power to detect an association of common HLA alleles with rash, similar to those reported previously. No HLA alleles were significantly associated with lapatinib-induced rash, including the previously identified lapatinib hepatotoxicity biomarker HLA-DRB1*07:01 (p = 0.87). The present study is consistent with the view that lapatinib-induced rash is not the consequence of HLA-restricted, immune-mediated mechanisms.

Effect of lapatinib on oral digoxin absorption in patients.

The potential for an interaction between lapatinib and absorption of the P-glycoprotein (ABCB1) substrate digoxin at a therapeutic dose in breast cancer patients was characterized. Seventeen women with HER2-positive metastatic breast cancer received a single oral 0.5-mg dose of digoxin on days 1 and 9 and oral lapatinib 1500 mg once daily on days 2 through 9. Digoxin pharmacokinetic parameters were determined on day 1 (digoxin administration alone) and on day 9 (coadministration of lapatinib and digoxin), and parameters were compared to determine the effects of lapatinib on digoxin absorption. Concomitant medications that could affect ABCB1 were accounted for. Lapatinib 1500 mg/day increased digoxin absorption approximately 80%, implicating lapatinib inhibition of intestinal ABCB1-mediated efflux. In summary, coadministration of lapatinib with narrow therapeutic index drugs that are substrates of ABCB1 should be undertaken with caution and dose adjustment should be considered.

HLA-DQA1*02:01 is a major risk factor for lapatinib-induced hepatotoxicity in women with advanced breast cancer.

PURPOSE: Hepatobiliary adverse events (AEs) have been observed in a small proportion of patients with metastatic breast cancer (MBC) treated with lapatinib. This study sought to identify gene variants associated with lapatinib-induced ALT elevation and hepatobiliary AEs. PATIENTS AND METHODS: A two-stage pharmacogenetic investigation of ALT elevation was conducted in lapatinib-treated patients with MBC. Exploratory marker identification evaluated classical HLA alleles, candidate genes, and genome-wide screening in 37 cases with ALT greater than 3 times the upper limit of normal (ULN) and 286 controls with ALT ≤ 1× ULN, selected from 901 lapatinib-treated patients in 12 trials. Markers achieving prespecified association thresholds were progressed to an independent confirmatory data set of 24 ALT cases and 155 controls selected from a subsequent trial of 374 lapatinib-treated patients. RESULTS: Of 58 variants associated with ALT elevation in the exploratory data set, four exceeded the prespecified significance threshold in the confirmatory analysis. These variants reside in the same MHC genomic locus and include HLA-DQA1*02:01. In the confirmatory study, DQA1*02:01 allele carriage was present in 71% of ALT cases and in 21% of controls (P < .001; odds ratio, 9.0; 95% CI, 3.2 to 27.4). As a predictor of liver safety risk in ALT cases versus noncases, DQA1*02:01 had negative and positive predictive values of 0.97 (95% CI, 0.95 to 0.99) and 0.17 (95% CI 0.10 to 0.26), respectively. CONCLUSION: These results support a role for immune mechanisms in lapatinib-induced hepatotoxicity. Further work is required to determine whether testing for DQA1*02:01 allele carriage is clinically useful in managing liver safety risk during lapatinib treatment.

The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research.

Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetics research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This growing resource was initially genotyped with a commercially available genome-wide 500,000 single-nucleotide polymorphism panel. This project includes nearly 6,000 subjects of African-American, East Asian, South Asian, Mexican, and European origin. Seven informative axes of variation identified via principal-component analysis (PCA) of these data confirm the overall integrity of the data and highlight important features of the genetic structure of diverse populations. The potential value of such extensively genotyped collections is illustrated by selection of genetically matched population controls in a genome-wide analysis of abacavir-associated hypersensitivity reaction. We find that matching based on country of origin, identity-by-state distance, and multidimensional PCA do similarly well to control the type I error rate. The genotype and demographic data from this reference sample are freely available through the NCBI database of Genotypes and Phenotypes (dbGaP).

Case-control single-marker and haplotypic association analysis of pedigree data.

Related individuals collected for use in linkage studies may be used in case-control linkage disequilibrium analysis, provided one takes into account correlations between individuals due to identity-by-descent (IBD) sharing. We account for these correlations by calculating a weight for each individual. The weights are used in constructing a composite likelihood, which is maximized iteratively to form likelihood ratio tests for single-marker and haplotypic associations. The method scales well with increasing pedigree size and complexity, and is applicable to both autosomal and X chromosomes. We apply the approach to an analysis of association between type 2 diabetes and single-nucleotide polymorphism markers in the PPAR-gamma gene. Simulated data are used to check validity of the test and examine power. Analysis of related cases has better power than analysis of population-based cases because of the increased frequencies of disease-susceptibility alleles in pedigrees with multiple cases compared to the frequencies of these alleles in population-based cases. Also, utilizing all cases in a pedigree rather than just one per pedigree improves power by increasing the effective sample size. We demonstrate that our method has power at least as great as that of several competing methods, while offering advantages in the ability to handle missing data and perform haplotypic analysis.