PURPOSE Acute lymphoblastic leukemia (ALL) is the most prevalent cause of childhood cancer and requires a long course of therapy consisting of three primary phases with interval intensification blocks. Although these phases are necessary to achieve remission, the primary chemotherapeutic agents have potentially serious toxicities, which may lead to delays or discontinuations of therapy. The purpose of this study was to perform a comprehensive pharmacogenomic evaluation of common antileukemic agents and develop a polygenic toxicity risk score predictive of the most common toxicities observed during ALL treatment. METHODS This cross-sectional study included 75 patients with pediatric ALL treated between 2012 and 2020 at the University of Florida. Toxicity data were collected within 100 days of initiation of therapy using CTCAE v4.0 for toxicity grading. For pharmacogenomic evaluation, single-nucleotide polymorphisms (SNPs) and genes were selected from previous reports or PharmGKB database. 116 unique SNPs were evaluated for incidence of various toxicities. A multivariable multi-SNP modeling for up to 3-SNP combination was performed to develop a polygenic toxicity risk score of prognostic value. RESULTS We identified several SNPs predictive of toxicity phenotypes in univariate analysis. Further multivariable SNP-SNP combination analysis suggest that susceptibility to chemotherapy-induced toxicities is likely multigenic in nature. For 3-SNPscore models, patients with high scores experienced increased risk of GI ( P = 2.07E-05, 3 SNPs: TYMS-rs151264360/FPGS-rs1544105/GSTM1-GSTM5-rs3754446), neurologic ( P = .0005, 3 SNPs: DCTD-rs6829021/SLC28A3-rs17343066/CTPS1-rs12067645), endocrine ( P = 4.77E-08, 3 SNPs: AKR1C3-rs1937840/TYMS-rs2853539/CTH-rs648743), and heme toxicities ( P = .053, 3 SNPs: CYP3A5-rs776746/ABCB1-rs4148737/CTPS1-rs12067645). CONCLUSION Our results imply that instead of a single-SNP approach, SNP-SNP combinations in multiple genes in drug pathways increases the robustness of prediction of toxicity. These results further provide promising SNP models that can help establish clinically relevant biomarkers allowing for greater individualization of cancer therapy to maximize efficacy and minimize toxicity for each patient.
Introduction: Despite cure rates in acute lymphoblastic leukemia (ALL) exceeding 90% in clinical trials, morbidity due to drug toxicities is high. Genetic polymorphisms can influence gene expression and activity, impacting pharmacokinetics and causing inter-individual variation in drug levels, which contributes to toxicity if levels are high or relapse if levels are low. We hypothesize that pharmacogenomic testing will identify patient specific variations in genes involved in metabolism of cytotoxic agents. This knowledge will allow clinicians to optimize therapy by providing pharmacogenomics based biomarkers related to increased toxicities. Data has shown that treatment interruptions and omissions due to toxicities affect outcomes and morbidities in children with cancer. Objective : To correlate pharmacogenomic biomarkers with toxicity phenotypes in children receiving therapy for ALL. Methods: This cross-sectional study involved subjects at a tertiary academic center (Fig. 1A). Subjects aged 1 year to 26 years with ALL treated after May 2012 were eligible. A total of 75 patients treated between 2012 and 2020 were included. Pharmacogenomic testing was performed on peripheral blood. Genomic DNA was tested for 118 single-nucleotide polymorphisms (SNP) in 55 genes for transport and metabolism of cytarabine, vincristine, methotrexate, dauno/doxorubicin, and mercaptopurine/thioguanine were analyzed using the Sequenom-based genotyping that uses MALDI-TOF based chemistry. SNPs were tested using logistic regression models for association with toxicities in additive, dominant, and recessive modes of inheritance. CTCAE v4.0 was used for grading all toxicities during the first 100 days of therapy. For endocrine (endo) and neurological (neuro) toxicities, 25 patients exhibited between grade 1-3 toxicities. For gastrointestinal (GI) toxicities, 25 patients exhibited between grade 2-3 toxicities. For hematological (heme) toxicities, 11 patients exhibited between grade 2-4 toxicities. Odds ratio and 95% confidence interval were calculated for each test and SNPs with association P-value <0.05 were considered significant. To conduct multivariable SNP combinations analysis, SNPs with univariate association p-value <0.1 were selected for each toxicity, and then SNP combinations (up to 3 SNPs per model) were tested for association with each toxicity. The combination model with the 1000 permutation p-value <0.05 and lowest BIC value was selected to build a SNP score after considering the mode of inheritance and the direction of association with the toxicity for the individual genotypes. A SNP score was generated by summation of genotype scores for the individual SNPs passing the top model. Patients were further classified into either of the 3 following SNP score groups: >0, 0 or <0. Results: For a GI toxicity score derived from 3 SNPs (TYMS-rs151264360, FPGS-rs1544105, and GSTM5-rs3754446), patients with >0 score had 79% incidence of GI toxicity (N=67) as compared to 10% in patients with score of 0 and 8% in patients with score <0 (p=2.07E-05, Fig 1B). For the SNP score (AKR1C3-rs6621365, ABCB1-rs4148737, and CTPS1-rs12067645) generated for heme toxicity, higher SNP scores were associated with high toxicity (p=0.003, Figure 1C). For neurotoxicity, the 3 SNPs (DCTD-rs6829021, SCL28A3-rs17343066, and CTPS1-rs12067635) involved were all in cytarabine metabolic pathway and predicted greater neurotoxicity (56%) with a score of >0; no toxicity was observed in patients with neurotoxicity score of <0 (p=0.0005, Fig. 1D). For SNP endo toxicity score (AKR1C3-rs1937840, TYMS-rs2853539, and CTS-rs648743), we observed 91% incidence of endo toxicity in patients with toxicity score of >0 (p=4.7E-08, Fig. 1E). None of the patients with a score of <0 experienced endo toxicity. Discussion: We identified germline SNPs predictive of toxicity phenotypes in a cohort of 75 subjects with ALL. The results of our multivariable SNP combination analysis suggest susceptibility to chemotherapy-induced toxicities is likely multigenic in nature. Instead of a single SNP approach, identification of combinations of mutations in drug pathways increases the robustness of predicting a patient's response to chemotherapy. Our results provide promising SNP models that can help establish clinically relevant biomarkers allowing for individualization of cancer therapy to optimize treatment for each patient. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.
MDM2 amplification, which is often seen in different cancer types, indicates that its plays an important role in tumorigenesis and also in cancer metastasis. Amplification of the MDM2 gene correlates with poor prognosis, aggressive growth, and reoccurrence. Thrombospondin-1 (TSP-1) that is expressed by THBS1 gene is a matricellular protein, and is known to have differential expression in cancers. When TSP-1 activates Transforming Growth Factor-β1 (TGF-β1) through latent cytokine complexation, the activated TGF-β1 contributes to the Epithelial to Mesenchymal Transition (EMT) which is known to impart stem-cell like characteristics and drug resistance to the cancer cells. However, no studies regarding MDM2’s role in THBS1 regulation have been carried out so far. Therefore, the objective of this study was to determine the correlation between MDM2 and THBS1 expression in MDM2 overexpressing cancers. For this purpose the SJSA-1 osteosarcoma cells were cultured at 37 oC under humidified air/CO2 (19:1) in RPMI-1640 complete medium supplemented with 10% FBS, 10,000 U/mL penicillin, 10,000 µg/mL streptomycin, 1% (+)-L-glutamine, and 1% amphotericin B. The cells were incubated in the presence of 20 µM of Nutlin-3 for 24 hrs, following which, RNA and protein were extracted and subsequently purity and concentration were determined. Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) and western blotting were performed using specific primers, primary and the secondary antibodies respectively. Interestingly elevated levels of TSP-1 and TGFβ1 were observed in these SJSA-1 cells. However, after treatment with Nutlin-3, an MDM2-p53 interaction inhibitor, a significant increase in p53 was noted. However, contrary to the existing literature, where studies have shown p53 to positively regulate TSP-1 levels, we observed an opposite outcome. Despite the Nutlin-3 induced elevation in p53 levels, a significant decrease in TSP-1 level was observed indicating that MDM2 may be regulating THBS1 gene expression in a p53 independent manner, in MDM2 overexpressing SJSA-1 cells. The findings of this study suggest a novel, p53 independent role for MDM2 in THBS1 regulation. Since MDM2 amplification can positively induce TSP-1 levels, which is one of the natural activators of TGF-β1, it is anticipated that stimulatory signal flowing through MDM2 - TSP-1 - TGF-β1 axis may induce the cancer cells to undergo EMT, thereby increasing their metastatic ability and promote cancer stem cell characteristics. This novel MDM2-regulated pathway can very well serve as a drug target and might play a biologically relevant role in the treatment of cancer metastasis. Our future studies will include validation of this correlation in multiple cancer cell lines, to further elucidate the mechanism through which MDM2 is regulating THBS1 gene expression. (This project was supported by The Royal Dames of Cancer Research Inc., Ft. Lauderdale, Florida). Citation Format: Priya Dondapati, Jason Maragh, Karna Mangrola, Ali Alaseem, Khadija Cheema, Thiagarajan Venkatesan, Sivanesan Dhandayuthapani, Appu Rathinavelu. Thrombospondin-1 regulation by MDM2 in aggressive cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4449. doi:10.1158/1538-7445.AM2017-4449
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