Genome-Wide Associations and Functional Genomic Studies of Musculoskeletal Adverse Events in Women Receiving Aromatase Inhibitors

University of Toronto, Toronto, Ontario, Canada
Journal of Clinical Oncology (Impact Factor: 18.43). 09/2010; 28(31):4674-82. DOI: 10.1200/JCO.2010.28.5064
Source: PubMed


We performed a case-control genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with musculoskeletal adverse events (MS-AEs) in women treated with aromatase inhibitors (AIs) for early breast cancer.
A nested case-control design was used to select patients enrolled onto the MA.27 phase III trial comparing anastrozole with exemestane. Cases were matched to two controls and were defined as patients with grade 3 or 4 MS-AEs (according to the National Cancer Institute's Common Terminology Criteria for Adverse Events v3.0) or those who discontinued treatment for any grade of MS-AE within the first 2 years. Genotyping was performed with the Illumina Human610-Quad BeadChip.
The GWAS included 293 cases and 585 controls. A total of 551,358 SNPs were analyzed, followed by imputation and fine mapping of a region of interest on chromosome 14. Four SNPs on chromosome 14 had the lowest P values (2.23E-06 to 6.67E-07). T-cell leukemia 1A (TCL1A) was the gene closest (926-7000 bp) to the four SNPs. Functional genomic studies revealed that one of these SNPs (rs11849538) created an estrogen response element and that TCL1A expression was estrogen dependent, was associated with the variant SNP genotypes in estradiol-treated lymphoblastoid cells transfected with estrogen receptor alpha and was directly related to interleukin 17 receptor A (IL17RA) expression.
This GWAS identified SNPs associated with MS-AEs in women treated with AIs and with a gene (TCL1A) which, in turn, was related to a cytokine (IL17). These findings provide a focus for further research to identify patients at risk for MS-AEs and to explore the mechanisms for these adverse events.

Download full-text


Available from: Richard Weinshilboum,
  • Source
    • "They scanned 551,395 single nucleotide polymorphisms (SNPs) and identified four variants close to T-cell leukemia 1A (TCL1A) gene, which were found to be associated with musculoskeletal toxicity risk. Interestingly, the subsequent in vitro analysis revealed altered estrogen response for the above TCL1A variants compared to the wild alleles and the imputed SNP rs11849538 created a new estrogen response element.11 The gene encoding TCL1A protein, belonging to the TCL1 family is expressed in activated T lymphocytes and B lymphocytes. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Introduction: Decline in circulating estrogen levels causes lessening of bone mass accompanied with musculoskeletal pain, which is the primary cause of treatment discontinuation in patients taking aromatase inhibitors. Evidence from recent genome-wide association studies (GWAS) suggests that the genetic variability underlying TCL1A gene increases the risk of aromatase inhibitors (AIs) - induced musculoskeletal toxicity. Currently, no data is available on the frequency distribution of TCL1A gene polymorphisms in Indians. Methods: In this pilot study, we used TaqMan fluorescent probes to assess the genotypes of four TCL1A gene polymorphisms associated with musculoskeletal toxicity in 247 healthy homogenous South Indian subjects on real time thermocycler. Haplotype estimation and pairwise linkage disequilibrium (LD) analysis were executed by Haploview. Results: The incidence of polymorphic variant allele (G) frequencies of rs7158782, rs7159713, rs2369049 and rs11849538 were 22.1%, 23.5%, 18.2% and 22.9% in the study population, respectively. The polymorphisms were found to be in complete LD with each other. Four different haplotypes, each of which having a frequency of above 1% were inferred in South Indians using an expectation-maximization algorithm. Notably, three haplotypes were found to be population specific viz H4 A-A-A-G (1.2%) for South India, H5 G-G-A-C (1.3%) for JPT and H6 G-G-G-C (40.4%) for YRI. Further, H3 G-G-A-G (2.3-16.3%) haplotype occurs primarily in Asians and is virtually absent in Africans. Overall, the genetic variability and haplotype profile of South Indian population revealed significant inter-racial variability compared with HapMap data. Conclusion: This documentation contributes for further investigations on the pharmacogenetics of AIs in South Indians.
    BioImpacts 06/2014; 4(2):95-100. DOI:10.5681/bi.2014.016
  • Source
    • "Severe musculoskeletal pain has been reported in up to half of women treated with aromatase inhibitors contributing to a treatment discontinuation rate of about 10% (Crew et al., 2007; Henry et al., 2008; Ingle et al., 2010). Ingle et al. found four single nucleotide polymorphisms (SNPs) mapping to the T-cell leukemia 1A (TCL1A) gene were associated with the development of musculoskeletal adverse events in patients receiving adjuvant aromatase inhibitors (Ingle et al., 2010). Subsequent functional studies revealed that TCL1A was induced by estrogen with higher levels of expression in cells with the variant alleles for these SNPs. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Cancer pharmacogenomics have contributed a number of important discoveries to current cancer treatment, changing the paradigm of treatment decisions. Both somatic and germline mutations are utilized to better understand the underlying biology of cancer growth and treatment response. The level of evidence required to fully translate pharmacogenomic discoveries into the clinic has relied heavily on randomized control trials. In this review, the use of observational studies, as well as, the use of adaptive trials and next generation sequencing to develop the required level of evidence for clinical implementation are discussed.
    Frontiers in Genetics 04/2014; 5:73. DOI:10.3389/fgene.2014.00073
  • Source
    • "We previously used the “Human Variation Panel”, a genomic data-rich lymphoblastoid cell line model system, to identify markers that might contribute to variation in response to these two cytidine analogues [17,18]. These cell lines have proven to be a powerful tool for both the identification of pharmacogenomic hypotheses and for the pursuit of hypotheses from the clinical GWAS [19-21]. However, the earlier studies were performed with less dense SNP coverage, in the present study, we expanded our previous 550 K SNP data to include a total of 1.3 million SNPs obtained with both Illumina and Affymetrix SNP genotyping platforms in an attempt to identify additional genes or SNPs that might be associated with drug response. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Two cytidine analogues, gemcitabine and cytosine arabinoside (AraC), are widely used in the treatment of a variety of cancers with a large individual variation in response. To identify potential genetic biomarkers associated with response to these two drugs, we used a human lymphoblastoid cell line (LCL) model system with extensive genomic data, including 1.3 million SNPs and 54,000 basal expression probesets to perform genome-wide association studies (GWAS) with gemcitabine and AraC IC50 values. We identified 11 and 27 SNP loci significantly associated with gemcitabine and AraC IC50 values, respectively. Eleven candidate genes were functionally validated using siRNA knockdown approach in multiple cancer cell lines. We also characterized the potential mechanisms of genes by determining their influence on the activity of 10 cancer-related signaling pathways using reporter gene assays. Most SNPs regulated gene expression in a trans manner, except 7 SNPs in the PIGB gene that were significantly associated with both the expression of PIGB and gemcitabine cytotoxicity. These results suggest that genetic variation might contribute to drug response via either cis- or trans- regulation of gene expression. GWAS analysis followed by functional pharmacogenomics studies might help identify novel biomarkers contributing to variation in response to these two drugs and enhance our understanding of underlying mechanisms of drug action.
    BMC Genomics 02/2014; 15(1):93. DOI:10.1186/1471-2164-15-93 · 3.99 Impact Factor
Show more