Anuj Tyagi

The association of cytochrome P450 genetic polymorphisms with sulfolane formation and the efficacy of a busulfan-based conditioning regimen in pediatric patients undergoing hematopoietic stem cell transplantation

Cytochrome P450 enzymes (CYPs) and flavin-containing monooxygenases (FMOs) likely have a role in the oxidation of intermediate metabolites of busulfan (Bu). In vitro studies to investigate the involvement of these enzymes are cumbersome because of the volatile nature of the intermediate metabolite tetrahydrothiophene (THT) and the lack of sensitive quantitation methods. This study explored the association between the CYP2C9, CYP2C19, CYP2B6 and FMO3 genotypes and sulfolane (Su, a water soluble metabolite of Bu) plasma levels in children undergoing hematopoietic stem cell transplantation (HSCT). The relationship between these genotypes and the effectiveness of myeloablative conditioning was also analyzed. Sixty-six children receiving an intravenous Bu-based myeloablative conditioning regimen were genotyped for common functional variant alleles in CYP2C9 (*2 and *3), CYP2C19 (*2 and *17), FMO3 (rs2266780, rs2266782 and rs1736557) and CYP2B6 (*5 and *9). The plasma levels of Bu and its metabolite Su were measured after the ninth Bu dose in a subset of 44 patients for whom plasma samples were available. The ratio of Bu to Su was considered the metabolic ratio (MR) and was compared across the genotype groups. Higher MRs were observed in CYP2C9*2 and *3 allele carriers (mean±s.d.: 7.8±3.6 in carriers vs 4.4±2.2 in non-carriers; P=0.003). An increased incidence of graft failure was observed among patients with an MR>5 compared with those with MR values <5 (20% vs 0%; P=0.02). In contrast, a significantly higher incidence of relapse and graft failure (evaluated as event-free survival) was observed in patients with malignant disease who carried CYP2B6 alleles with reduced function on both chromosomes compared with carriers of at least one normal allele (100% vs 40%; P=0.0001). These results suggest that CYP2C9 has a role in the oxidation reactions of THT and indicate that it may be possible to predict the efficacy of Bu-based myeloablative conditioning before HSCT on the basis of CYP genotypes and Bu MRs.

Pharmacogenetic aspects of drug metabolizing enzymes in busulfan based conditioning prior to allogenic hematopoietic stem cell transplantation in children.

Allogenic hematopoietic stem cell transplantation (HSCT) is a well established but complex treatment option for malignant and non-malignant disorders in pediatric patients. Most commonly used myeloablative and non-myeloablative conditioning regimens in children comprise alkylating agents, such as busulfan (BU) and cyclophosphamide. Inter-individual variability in the pharmacokinetics of BU can result in altered conditioning of the patient and therefore lead to relapse or rejection due to under exposures, or occurrence of toxicities due to over exposures. With the introduction of the intravenous formulation of BU, this variability has been reduced but still cannot be fully predicted. Inter and intra-individual variability of BU kinetics is more common in children compared to adults and toxicity of BU based regimens is still a concern. It has been hypothesized that some of this variability in BU pharmacokinetics and treatment outcomes, especially the toxicity, might be predicted by genetic variants of enzymes involved in the metabolism of BU. This review intends to summarize the studies performed to date on the pharmacokinetics and pharmacogenetics of BU based conditioning, specifically in relation to children.

Validation of SYBR Green based quantification assay for the detection of human Torque Teno virus titers from plasma

BackgroundQuantification of titers of ubiquitous viruses such as Torque teno virus (TTV) that do not cause clinical symptoms might be helpful in assessing the immune status of an individual. We hereby describe the validation of a SYBR Green-based TTV quantification method for plasma samples.MethodsPlasmids with TTV specific inserts were used for preparing standards and absolute quantification of TTV was performed using SYBR Green methodology. The method was assessed for its accuracy and precision (intra and inter-day) on four non-consecutive days. TTV was also quantified from plasma samples of 20 healthy volunteers and from 30 hematopoietic stem cell transplant (HSCT) recipients.ResultsThe assay was specific and showed satisfactory efficiency (82.2%, R2=0.99) with the limit of quantification defined as 100 copies per reaction. The assay had good precision (inter and intra-day coefficient of variation in cycle threshold (CT) < 4%) and accuracy (100 ± 10%) in the range of 100 to 1010 copies/reaction. We found TTV loads ranging from 2.5 – 4.07 log copies/mL of plasma with CT (mean ± SD) of 33.8 ± 1.77 in healthy individuals and 2.06 – 8.49 log copies/mL of plasma with CT (mean ± SD) of 24.3 ± 1.04 in HSCT recipients.ConclusionSYBR Green-based q-PCR assay combines simplicity with satisfactory sensitivity and may be suitable for monitoring the immune status of transplant recipients, where TTV loads over time may serve as a marker for immune reconstitution in human plasma samples.

Predictive Simulation Approach for Designing Cancer Therapeutic Regimens with Novel Biological Mechanisms

Introduction Ursolic acid (UA) is a pentacyclic triterpene acid present in many plants, including apples, basil, cranberries, and rosemary. UA suppresses proliferation and induces apoptosis in a variety of tumor cells via inhibition of nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB). Given that single agent therapy is a major clinical obstacle to overcome in the treatment of cancer, we sought to enhance the anti-cancer efficacy of UA through rational design of combinatorial therapeutic regimens that target multiple signaling pathways critical to carcinogenesis. Methodology Using a predictive simulation-based approach that models cancer disease physiology by integrating signaling and metabolic networks, we tested the effect of UA alone and in combination with 100 other agents across cell lines from colorectal cancer, non-small cell lung cancer and multiple myeloma. Our predictive results were validated in vitro using standard molecular assays. The MTT assay and flow cytometry were used to assess cellular proliferation. Western blotting was used to monitor the combinatorial effects on apoptotic and cellular signaling pathways. Synergy was analyzed using isobologram plots. Results We predictively identified c-Jun N-terminal kinase (JNK) as a pathway that may synergistically inhibit cancer growth when targeted in combination with NFκB. UA in combination with the pan-JNK inhibitor SP600125 showed maximal reduction in viability across a panel of cancer cell lines, thereby corroborating our predictive simulation assays. In HCT116 colon carcinoma cells, the combination caused a 52% reduction in viability compared with 18% and 27% for UA and SP600125 alone, respectively. In addition, isobologram plot analysis reveals synergy with lowered doses of the drugs in combination. The combination synergistically inhibited proliferation and induced apoptosis as evidenced by an increase in the percentage sub-G1 phase cells and cleavage of caspase 3 and poly ADP ribose polymerase (PARP). Combination treatment resulted in a significant reduction in the expression of cyclin D1 and c-Myc as compared with single agent treatment. Conclusions Our findings underscore the importance of targeting NFκB and JNK signaling in combination in cancer cells. These results also highlight and validate the use of predictive simulation technology to design therapeutics for targeting novel biological mechanisms using existing or novel chemistry.

Abstract 1706: Individualized therapy identified using simulation for bortezomib resistant patient with ex-vivo validation

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Background: The unique signature of a patients tumor mandates the need to rationally design personalized therapies employing N=1 segmentation conceptually. By focusing on rationally designed personalized treatments, our strategy targets key pathways to address the clinical problem of therapy resistance. To overcome bortezomib resistance, we have (1) employed predictive simulation modeling using patient genomic profiling to design patient specific combinatorial therapeutic regimens and (2) validated designed therapy ex-vivo in patient-derived cell lines. Methods: Clinical patient samples were analyzed for chromosomal alterations using array Comparative Genomic Hybridization (aCGH) by GenPath Diagnostics and cytogenetic chromosome analysis by NYU. Using this information, we created a patient simulation avatar. To identify effective personalized therapeutics, we focused on molecularly targeted agents with clinical data. The predictive simulation based approach from Cellworks provides a comprehensive representation of plasma cell myeloma (PCM) disease physiology incorporating signaling and metabolic networks with an integrated phenotype view. Therapeutic hits were shortlisted from over 1000 pharmacodynamic dose-response simulation studies using efficacy and synergy criteria. Simulation modeling identified therapeutic mechanisms that impact proliferation and agent combinations that overcome bortezomib resistance. These predictive findings are in the process of being assessed ex vivo using patient primary cells and prospectively validated. Results: A loss of the CUL1 due to deletion of chromosome 7q36.1 region and CCND1 as a result of gain of chromosome 11q13 region was detected. Simulation of this patients avatar showed high proliferation phenotype as a consequence of stated aberrations. CUL1 deletion caused increase in NFKB and CTNNB1 and a synergistic increase in CCND1. CUL1 deletion excludes target proteins from proteasomal degradation, thereby making cells resistant bortezomib effect. Simulation screening identified adjuvant NVP-BEZ235 (pan PI3K/mTORC1 and mTORC2 inhibitor) with current background of bortezomib to show enhanced efficacy in this patient. NFKB is reduced by this mechanism and along with reduction in translation of pro-proliferative genes mediated by mTOR inhibition. IC20 concentrations with respect to proliferation of the single agents in combination showed 38% inhibition of proliferation in simulation. These findings are currently being prospectively validated ex-vivo in patient primary cells. Conclusions: This study demonstrates and validates simulation for developing novel therapeutics and technologies to truly leverage “big data”. This level of individualization, beyond linking point mutations to associated drugs targeting the same mutations, truly incorporates the complete patient tumor signature with a clinical translation pathway. Citation Format: Nicole A. Doudican, Shireen Vali, Annette Leon, Ansu Kumar, Neeraj Kumar Singh, Anuj Tyagi, Shweta Kapoor, Zeba Sultana, Taher Abbasi, Amitabha Mazumder. Individualized therapy identified using simulation for bortezomib resistant patient with ex-vivo validation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1706. doi:10.1158/1538-7445.AM2014-1706