Doxorubicin is a member of the anthracycline group of chemotherapy drugs prescribed to approximately 60% of pediatric cancer patients suffering with sarcomas, blastomas, leukemia, and lymphoma. Although doxorubicin is highly effective in these patients, ~16% of pediatric patients suffer doxorubicin-induced cardiotoxicity (DIC) which can lead to heart failure requiring heart transplant. Our recent work has shown that DIC is 2.5x more prevalent in African American (AA) survivors of childhood cancer. Despite more than 50 years of research in this field, there is still, at present, little potential for either predicting or preventing DIC. There is an obvious need for novel and innovative approaches to overcome this hurdle. Candidate gene and genome-wide association studies, predominantly in Europeans, have identified >100 single nucleotide polymorphisms (SNPs) that are statistically correlated with DIC, yet experimental validation has not been feasible due to the difficulty in isolating and culturing human cardiomyocytes in vitro. In our recent work, we showed that patient-specific human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are efficient predictors of a patient’s likelihood of developing DIC, confirming for the first time that there is a genomic basis to DIC. Here, we hypothesize that hiPSC-CMs can be utilized in three different modalities to study genetic variants associated with DIC in AA survivors: firstly, to discover novel predictive SNPs; secondly, to validate SNPs; and thirdly, to examine the modulated pathways and determine genotype-specific cardioprotective methodologies. In Aim 1, we will generate hiPSC from 100 AA adult survivors of childhood cancer with diverse biological covariates who were exposed to doxorubicin assess their response to doxorubicin in vitro to validate our previous findings and verify the power of this tool. In Aim 2, we will use these 100 patient-specific lines to identify drug response differential expression, splicing and chromatin accessibility quantitative trait loci (deQTL, dsQTL and dcaQTL), assessing biological covariates such as doxorubicin dose, age at cancer diagnosis, attained age, sex, BMI, radiotherapy (other than involving chest), and cancer diagnosis both individually and combined. We will then validate these variants with genome editing, and mechanistically examine pathways causative to DIC susceptibility concentrating on genes with known roles in cardiomyopathy, cardioprotection, and doxorubicin metabolism. We will then use the discoveries above to discover/repurpose genome-informed cardioprotective drugs to prevent DIC in a genotype-specific manner. In Aim 3, we will build a risk prediction model for DIC among AA survivors incorporating clinical risk factors and functionally assessed genetic variants above, evaluate its prediction performance, validate it in independent AA survivors, and implement it in a web-based and userfriendlytool for broader clinical and research use. In summary, this work will deliver us the genetic rationale for why AA survivors experience DIC and provide 1, fully human validated SNP data for clinical application through a user-friendly tool, and 2, novel cardioprotective pathways that can be targeted to protect against DIC.
|Effective start/end date||8/5/21 → 7/31/26|
- National Cancer Institute (5R01CA261898-02)
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