Abtract
Poster #1. Alexander Ling[1]; R. Stephanie Huang[1]. Clinical trial outcomes for cancer drug combinations can be predicted using cancer cell line monotherapy screens and a model of independent drug action.
Drug combinations are a cornerstone of cancer therapy; however, the vast number of possible drug combinations makes it infeasible to experimentally evaluate all of these possibilities when identifying new therapies. For example, testing all possible 4-drug combinations for 200 compounds in 100 cell lines would require more than 6 billion experiments. To solve this problem, efforts have been made to develop computational models capable of accurately predicting drug combination efficacy without the need to experimentally test all of them. While these models have traditionally aimed to predict drug synergy, recent evidence has emerged suggesting that many cancer drug combinations may derive their efficacy from independent drug action (IDA), where patients only receive benefit from the single most effective drug in a drug combination.
In light of these findings, we developed IDACombo, a computational method which uses IDA to predict the efficacy of drug combinations based on monotherapy data from high-throughput cancer cell line drug screens. We have demonstrated that IDACombo predictions closely agree with measured drug combination efficacies both in vitro (Pearson’s correlation = 0.94 when comparing predicted efficacies to measured efficacies for >5000 combinations) and in a systematically selected set of clinical trials (accuracy > 88% for predicting progression free survival/time to progression or overall survival benefit in 26 first line therapy trials). This work provides a framework for translating monotherapy cell line screening data into clinically meaningful efficacy predictions for hundreds of thousands of 2-drug combinations and millions of combinations of 3 or more drugs.
Poster #2: Zachary Rivers, David D. Stenehjem, Pamala Jacobson, Emil Lou, Andrew Nelson,
Karen M Kuntz. A cost-effectiveness analysis of pretreatment DPYD and UGT1A1 screening in patients with metastatic colorectal cancer (mCRC) treated with
FOLFIRI+bevacizumab (FOLFIRI+Bev).
Background:
Variants in DPYD and UGT1A1 impact toxicities experienced by patients being treated with FOLFIRI+bev. Testing allows providers to preemptively adjust dosing, reducing the toxicity that patients experience. We assessed the cost-effectiveness of pre-treatment testing for variants in DPYD and UGT1A1 in patients with mCRC receiving FOLFIRI+bev.
Methods:
We developed a six-state Markov model to compare pre-treatment genetic testing to no testing. The genetic testing arm screened for UGT1A1 and DPYD using a multi-gene panel. Patients were dosed per proposed guidelines (Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group) and allowed dose reductions based on toxicity. In the no-test arm, patients received full doses of FOLFIRI+bev, and dose reductions based on toxicity. Costs included medications, clinic visits, and hospitalizations to treat the disease and adverse events, and were obtained from the literature, adjusted to 2019 $US. Quality-adjusted life years (QALYs) were used to assess effectiveness. We used a US health care system perspective with a 16 week horizon, the average length of time patients were exposed to FOLFIRI+bev in clinical trials. We conducted sensitivity analyses to determine the impact of uncertainty on outcomes.
Results:
Genetic testing cost $25,563, generating 0.21 QALYs. Standard of care cost $25,515, generating 0.20 QALYs. This resulted in an incremental cost-effectiveness ratio (ICER) of $4963 per QALY gained. Results were sensitive to costs of post-progression care, the probability of carrying UGT1A1 variants, and the impact of low-functioning DPYD variants on side effects.
Conclusions:
Pre-treatment testing for DPYD and UGT1A1 in patients receiving FOLFIRI+bev for mCRC is cost-effective, well below typical oncology ICERs of $50,000-100,000 per QALY. Further work is needed to characterize the impact of post-progression treatment and supportive care medications.
Poster #3: Josiah D. Allen, BA[1,2]; Amy L. Pittenger, PharmD, PhD[1]; Jeffrey R. Bishop, PharmD, MS, BCPP[1]. Patient experience with pharmacogenomic testing: systematic review and implications for pharmacogenomic literacy.
Background
Pharmacogenomic (PGx) testing is increasingly entering psychiatric practice, buoyed by interest from patients and providers alike. Meanwhile, patients’ knowledge of pharmacogenetic concepts remains an implementation barrier. Disease risk genomics research indicates that individuals with greater genomic literacy are better equipped to make informed decisions about whether to obtain genetic testing, understand results, and take appropriate action. While researchers have created survey instruments to evaluate disease risk genomic literacy, no validated pharmacogenomic literacy assessments currently exist. As a first step toward assessment creation, we completed a systematic review of published literature regarding patient perspectives/experiences with PGx testing.
Objectives
Perform systematic review of published literature regarding patient experiences of PGx testing to inform development of semi-structured interview guide.
Methods
Systematic PubMed search was performed using discrete search strings. Eligible studies were required to include patients or consumers and report on participants’ actual or expected subjective experience with PGx testing. Thematic analysis of abstracted results will be performed.
Results
The PubMed search produced 38 full-text articles. Seven themes (and 23 subthemes) emerged: (1) reasons for undergoing PGx testing, (2) understanding of test results, (3), psychological response to test results, (4) perceived utility of results, (5) impact of testing on patient/provider relationship, (6) actions taken on the basis of results, and (7) harms/concerns associated with testing.
Conclusions
Consistent themes emerged across all of the studies, though heterogeneity of opinion at the patient level certainly exists. The analysis identified several consistent themes that can be addressed by targeted education and can inform development of a knowledge assessment tool.
Poster 4: Jennifer M. Nelson, BS[1]; Robert J. Straka, PharmD[2]; Ya-Feng Wen, PharmD[3]. Role of protein prenylation in the pathogenesis of Alzheimer’s disease.
Background: Current medication treatment for depression is trial-and-error with as few as 37% of patients achieving remission by 8 weeks of receiving their first treatment. Within a Eurocentric population, genomic-guided treatment for depression shows improved remission rates vs. usual-care. The Hmong have a higher prevalence of untreated and unrecognized mental health conditions. In addition, the Hmong differ compare to non-Hmong in genetic variant frequencies.
Objective: Examine the potential impact of CYP2C19 and CYP2D6 genotypes, determined by two testing panels in order to identify possible differences in treatment recommendations for anti-depressants and other psychiatric medications.
Methods: Genotype and phenotypes were determined in 12, self-identified Hmong adults using RightMedTM panel (OneOme, MN, USA) and an in-house panel (University of Minnesota). Consequential medication recommendations were made, based on guidance from the FDA, PharmGKB, and guidelines from Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group (DPWG).
Results: Moderate or major CYP2D6 and/or CYP2C19 “gene-drug interactions” with at least one psychiatric medication, including at least one antidepressant, occurred in 12/12 patients. For 15/16 anti-depressants reported, at least 1 patient had dose change recommendations. For 11/16 of these medications at least 1 patient had dose alternate recommendations. 9 patients had CYP2D6 OneOme phenotypes that differed from the in-house panel. Both panels resulted in same phenotype for CYP2C19.
Conclusion: Our results imply pharmacogenomics could improve antidepressant success metrics after the first trial for our Hmong participants. A comprehensive pharmacogenomics panel appears superior to more focused panels to guide treatment for mental health in Hmong.
Poster #5: M. Mohamud [1], A. Alharbi[2], T. Takahashi [1], A. R. Smith [1], P. A. Jacobson [1], J. Fisher [1], N. Rubin [1], M. Kirstein [1]. The Role of CYP2C19 Genetic Variants on Voriconazole Pharmacokinetics in Pediatric Hematopoietic Stem Cell Transplant Recipients.
Statement of Purpose, Innovation or Hypothesis: Voriconazole (VCZ) is used to treat invasive aspergillosis and candidiasis and also as prophylaxis for patients following allogeneic hematopoietic stem cell transplantation (HSCT; immunocompromised). Unfortunately, opportunistic invasive fungal infections are associated with high morbidity and mortality rates. Voriconazole displays broad interpatient pharmacokinetic (PK) variability, in part due to variation in CYP2C19. The drug is also a substrate for several other drug metabolizing enzymes and transporters. We conducted a Phase 1 study of VCZ as prophylaxis in pediatric patients following allogeneic HSCT.
Description of Methods and Materials: This was a prospective, open‐label, single‐center study to assess the maximum tolerated and minimum efficacious dose (trough concentration 1.5–5 mg/L). Patients were stratified into three groups according to age: <2 yrs, 2–<12 yrs and 12–21 yrs. Pretransplant genomic DNA was collected. Up to three dose levels per age group were evaluated using a 3+3 dose escalation design with an expansion cohort. Voriconazole intravenous (IV) infusion was initiated post‐transplant. Voriconazole trough concentrations were measured for therapeutic drug monitoring on Days 5, 12 and 21 and dosage adjustments made if necessary. Observational intensive sampling PK studies were also performed on Days 5 and 12. Concentration‐time data were analyzed with noncompartmental and population PK analysis (NONMEM®). Genotyping was performed using a custom SNP panel and CYP2C19 phenotypes were assigned according to Clinical Pharmacogenomics Implementation Consortium guidelines.
Data and Results: Fifty‐eight patients (75.9% non‐Hispanic Caucasian, 6.90% African American, 62.1% male) were evaluated for the first PK study. Twelve subjects were <2 yrs old, 22 subjects were 2–<12 and 24 were 12–21 yrs old. Acute myeloid leukemia was the most common indication for HSCT (24.1%). Dose‐normalized VCZ AUCs ranged from 0.59–18.4 mg/L*hr (per mg/kg dose normalized) and n‐oxide metabolite to VCZ AUC ratios ranged from 0.53–12.8 for the first PK study. Over 250 variants have been assessed with the custom SNP panel. Initial analysis included CYP2C19*2 (rs4244285), CYP2C19*3 (rs4986893) and CYP2C19*17 (rs12248560) and were in Hardy Weinberg equilibrium (p>0.05). Observed minor allele frequencies for *2 and *17 were 0.16 and 0.14, respectively. No *3 variants were observed. Interpatient variability on typical value of clearance was 80.4% CV. Typical value of clearance (scaled by allometry to weight) estimate was 13.7 L/hr for normal, rapid and ultrarapid CYP2C19 metabolizers and 8.54 L/hr for poor‐ and intermediate metabolizers (decreased objective function value = 6). CYP2C19 variants accounted for 6.59% of interpatient voriconazole clearance variability.
Interpretation, Conclusion or Significance: Less than 10% of interpatient variability in voriconazole clearance variability is accounted for by CYP2C19 phenotype. Future analysis will evaluate the association between the remaining variants in the SNP panel (e.g. CYP3A4/5, FMO3 and ABCB1) and voriconazole clearance to develop an IV VCZ dosing equation for children following HSCT. Keywords: Voriconazole, prophylaxis, pharmacokinetics, pharmacogenetics, hematopoietic stem cell transplantation and pediatrics. Clinical trial information: NCT02227797 (https://doi.org/10.1002/cpdd.724)
Poster #6: Yuting Shan, BS[1]; Aritro Nath, PhD[2]; Siddhika Pareek, PhD[1]; Adam M. Lee, PhD[1]; Stephanie R. Huang, PhD[1]. High Expression of GAS5, A Long Non-coding RNA, Leads to Higher Sensitivity to Multiple Chemotherapeutic Drugs in Triple-Negative Breast Cancer.
Introduction: Triple negative breast cancer (TNBC) is usually difficult to treat and the overall survival rate is also low due to its lack of ER, PR, and HER-2 treatment targets. Therefore, looking for novel and effective biomarkers to optimize treatments for TNBC is urgently needed. Previous studies from our lab have shown that expression level of Growth Arrest Specific 5 (GAS5), a long non-coding RNA, has significant associations with therapeutic response of over a hundred anticancer agents including standard treatments for TNBC. The main purpose of this study is to validate the association between GAS5 expression and anticancer drug sensitivity in the TNBC cell line experimentally and elucidate the underlying biological mechanism.
Methods: MD-AMB-231 was selected as the TNBC cell line model. Treated with docetaxel and vorinostat, the sensitivity of unmodified MDA-MB-231 was examined by calculating the IC50. GAS5 knockdown and overexpression were then performed by introducing short interfering RNA (siRNA) transfection and lentivirus transduction respectively, after which the drug sensitivity was examined again using the same method.
Result: IC50 values of docetaxel and vorinostat on unmodified MDA-MB-231 were calculated to be 14.4nM and 2.22uM respectively. After siRNA transfection, GAS5 was successfully knockdown with an efficiency of over 98%. In vitro cytotoxicity suggested that after 72 hours treatments, the sensitivity of GAS5 knockdown MDA-MB-231 to vorinostat was significantly reduced (95%CI [0.09209 to 0.3615]) comparing with control groups. The overexpression experiment is still under optimization.
Conclusion: GAS5 sensitizes vorinostat in MDA-MB-231 cell line and can potentially serve as a biomarker to predict the treatment responses in TNBC patients.
Poster #7: Yuqi Zhou, BS, PharmD candidate [1], Aritro Nath, PhD[2], Siddhika Pareek, PhD[3], Adam Lee, PhD[4], Yingbo Huang, MS [5], R. Stephanie Huang, PhD[6]. Assess the underlying mechanism of ZEB2AS1 as a multi-drug response biomarker.
Long noncoding RNAs (lncRNAs) are RNAs with more than 200 nucleotides and do not encode proteins. Although present in over 70% of the human genome, lncRNAs are not as intensively studied as protein-coding genes which only present in 3% of the human genome. Even less is known about the role of lncRNA in drug response predictors. A few recent studies highlighted the importance of lncRNAs in cancer, imposing the possibility of using lincRNA as biomarkers.
To select lncRNA biomarker candidates, our research team performed comprehensive analysis using two independent high-throughput drug screening datasets (GDSC and CTRP). Among all statistically significant lncRNA and drug sensitivity associations identified, ZEB2AS1 was of most interest due to its association of expression with (p<0.05) 190 drugs in the GDSC and 346 drugs in the CTRP. Through literature search and cluster/enrichment analysis of ZEB2AS1 associated drugs, it was found that a large portion of drugs highly correlated with ZEB2AS1 expression are involved in the MAPK pathway. This observation could be explained by the association of ZEB2AS1 on MAPK pathway through its association with SMAD3, ZEB2, TGF-β signaling pathway and JNK. My preliminary data analysis also confirms the significant correlation between JNK and SMAD3 (p=2.4x10-11, Pearson correlation= -0.83). Therefore, I hypothesized that a portion of ZEB2AS1’s multiple drug sensitivity association is due to ZEB2AS1’s regulation of MAPK pathway through JNK. This hypothesis is evaluated by measuring MDAMB231 cell line’s response (WST-1 assay) to doxorubicin before and after ZEB2AS1 knockdown with siRNA.
Poster #8: Shen Cheng,MS[1], Tim Tracy,Ph.D[2], Richard Brundage, PharmD, Ph.D[3]. Evaluation of the Impact of CYP2C9 Genetic Polymorphism on Warfarin Drug-Drug Interactions using Pharmacometrics Approach.
Warfarin is one of the most commonly prescribed oral anticoagulant drugs for preventing long-term thromboembolic events worldwide. Warfarin is highly effective in reducing the risk of stroke and the death of myocardial infarction. However, high inter-individual variability in the dose-exposure relationship and a narrow therapeutic index complicates its dosing. Numerous factors contribute to the variability of warfarin response.
Warfarin is administered as a mixture of two enantiomers, S-warfarin and R-warfarin, as 1:1 molar ratio. Although both R- and S-warfarin possess pharmacological effects, S-warfarin is a 7-fold more potent than R-warfarin. CYP2C9 is highly associated with the metabolic clearance of S-warfarin. Thus, the genetic polymorphism influencing CYP2C9 metabolic activity is critical in explaining the high inter-individual variability in pharmacokinetics (PK) of warfarin.
Additionally, taking interacting drugs simultaneously with warfarin further complicates the dose-exposure relationship of warfarin. For instance, taking CYP2C9 inhibitors together with warfarin may increase warfarin exposure which increases the risk of bleeding. Taking CYP2C9 inducers together with warfarin may decrease warfarin exposure which reduces its effectiveness.
My research is investigating the impact of CYP2C9 genetic polymorphism on drug-drug interactions (DDIs) of warfarin using a pharmacometric modeling approach. We found a target mediated drug disposition (TMDD) model is able to adequately fit both S warfarin and R warfarin PK profiles under different co-medications simultaneously. Our preliminary results suggest, compared to warfarin alone, taking warfarin together with fluconazole (a CYP inhibitor), the clearance of S warfarin for patients with the CYP2C9 *1/*1 genotype reduced to 29.5%. However, under the same situation, the clearance of S warfarin for patients with the CYP2C9 *3/*3 genotypes reduced to 49.9%. In addition, compared to warfarin alone, taking warfarin together with rifampin (a CYP inducer), the clearance of S warfarin for patients with the CYP2C9 *1/*1 genotype increased to 226.6%. However, under the same situation, the clearance of S warfarin for patients with the CYP2C9 *3/*3 genotypes increased to 288.6%. Our results suggest patients with different CYP2C9 genotypes need different warfarin dose adjustments when they taking warfarin together with CYP inhibitors and CYP inducers.
Poster #9: Siddhee A. Sahasrabudhe[1], Lisa D. Coles[1], Usha Mishra[1], James C. Cloyd[1], Kathryn R. Cullen[2], Reena V. Kartha[1]. N-acetylcysteine Clinical Pharmacology in Non-Suicidal Self-Injury.
Background:
Non-suicidal self-injury (NSSI) is a psychiatric disorder described as intentional injuring of one’s own body without suicidal intent. In Minnesota, about 22% adolescent girls have a tendency to self-harm. Unfortunately, there is no approved treatment for NSSI. N-acetylcysteine (NAC) has been used in psychiatric disorders, although there is no consensus regarding its clinical benefits. We hypothesize that oral NAC in patients with NSSI can reduce episodes of self-harm in relation to NAC exposure. Toward this end we have developed an analytical method to measure expected range of blood NAC concentrations.
Methods
A double-blind, randomized, placebo-controlled study designed to enroll 12 adolescent girls in each of the treatment arms (3600mg/day or 5400 mg/ day) and placebo, is underway. Blood samples from research participants will be collected and analyzed for NAC using the developed LC/MS/MS assay. Population PK model using concentration-time profiles obtained from a previous study, was developed. This model was then used to predict NAC concentrations for this study. These simulations were used to help set the lower and upper limit of quantitation for our analytical method.
Results
Based on the pharmacokinetic simulations, we developed a method that can reliably measure NAC concentrations in patients with NSSI in the range 200-20,000 ng/mL.
Conclusion
This work demonstrates amalgamation of pharmacometric and analytical techniques for the development of reliable assay of NAC concentrations in patient-derived blood samples. This study is a first step in evaluating the effectiveness of NAC in the management of NSSI.