Pilot Findings of Pharmacogenomics in Perioperative Care: Initial Results From the First Phase of the ImPreSS Trial.

BACKGROUND: Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care. METHODS: The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers. RESULTS: Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P < .0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow. CONCLUSIONS: Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.

Clinically actionable genotypes for anticancer prescribing among >1500 patients with pharmacogenomic testing.

BACKGROUND: In recent years, there has been increasing evidence supporting the role of germline pharmacogenomic factors predicting toxicity for anticancer therapies. Although somatic genomic data are used frequently in oncology care planning, germline pharmacogenomic testing is not. This study hypothesizes that comprehensive germline pharmacogenomic profiling could have high relevance for cancer care. METHODS: Between January 2011 and August 2020, patients at the University of Chicago Medical Center were genotyped across custom germline pharmacogenomic panels for reasons unrelated to cancer care. Actionable anticancer pharmacogenomic gene/drug interactions identified by the FDA were defined including: CYP2C9 (erdafitinib), CYP2D6 (gefitinib), DPYD (5-fluorouracil and capecitabine), TPMT (thioguanine and mercaptopurine), and UGT1A1 (belinostat, irinotecan, nilotinib, pazopanib, and sacituzumab-govitecan hziy). The primary objective was to determine the frequency of individuals with actionable or high-risk genotypes across these 5 key pharmacogenes, thus potentially impacting prescribing for at least 1 of these 11 commonly prescribed anticancer therapies. RESULTS: Data from a total of 1586 genotyped individuals were analyzed. The oncology pharmacogene with the highest prevalence of high-risk, actionable genotypes was UGT1A1, impacting 17% of genotyped individuals. Actionable TPMT and DPYD genotypes were found in 9% and 4% of patients, respectively. Overall, nearly one-third of patients genotyped across all 5 genes (161/525, 31%) had at least one actionable genotype. CONCLUSIONS: These data suggest that germline pharmacogenomic testing for 5 key pharmacogenes could identify a substantial proportion of patients at risk with standard dosing, an estimated impact similar to that of somatic genomic profiling. LAY SUMMARY: Differences in our genes may explain why some drugs work safely in certain individuals but can cause side effects in others. Pharmacogenomics is the study of how genetic variations affect an individual's response to medications. In this study, an evaluation was done for important genetic variations that can affect the tolerability of anticancer therapy. By analyzing the genetic results of >1500 patients, it was found that nearly one-third have genetic variations that could alter recommendations of what drug, or how much of, an anticancer therapy they should be given. Performing pharmacogenomic testing before prescribing could help to guide personalized oncology care.

Applicability of Pharmacogenomically Guided Medication Treatment during Hospitalization of At-Risk Minority Patients.

Known disparities exist in the availability of pharmacogenomic information for minority populations, amplifying uncertainty around clinical utility for these groups. We conducted a multi-site inpatient pharmacogenomic implementation program among self-identified African-Americans (AA; n = 135) with numerous rehospitalizations (n = 341) from 2017 to 2020 (NIH-funded ACCOuNT project/clinicaltrials.gov#NCT03225820). We evaluated the point-of-care availability of patient pharmacogenomic results to healthcare providers via an electronic clinical decision support tool. Among newly added medications during hospitalizations and at discharge, we examined the most frequently utilized medications with associated pharmacogenomic results. The population was predominantly female (61%) with a mean age of 53 years (range 19-86). On average, six medications were newly prescribed during each individual hospital admission. For 48% of all hospitalizations, clinical pharmacogenomic information was applicable to at least one newly prescribed medication. Most results indicated genomic favorability, although nearly 29% of newly prescribed medications indicated increased genomic caution (increase in toxicity risk/suboptimal response). More than one of every five medications prescribed to AA patients at hospital discharge were associated with cautionary pharmacogenomic results (most commonly pantoprazole/suboptimal antacid effect). Notably, high-risk pharmacogenomic results (genomic contraindication) were exceedingly rare. We conclude that the applicability of pharmacogenomic information during hospitalizations for vulnerable populations at-risk for experiencing health disparities is substantial and warrants continued prospective investigation.

Validation of a Large Custom-Designed Pharmacogenomics Panel on an Array Genotyping Platform.

BACKGROUND: Pharmacogenomics has the potential to improve patient outcomes through predicting drug response. We designed and evaluated the analytical performance of a custom OpenArray® pharmacogenomics panel targeting 478 single-nucleotide variants (SNVs). METHODS: Forty Coriell Institute cell line (CCL) DNA samples and DNA isolated from 28 whole-blood samples were used for accuracy evaluation. Genotyping calls were compared to at least 1 reference method: next-generation sequencing, Sequenom MassARRAY®, or Sanger sequencing. For precision evaluation, 23 CCL samples were analyzed 3 times and reproducibility of the assays was assessed. For sensitivity evaluation, 6 CCL samples and 5 whole-blood DNA samples were analyzed at DNA concentrations of 10 ng/µL and 50 ng/µL, and their reproducibility and genotyping call rates were compared. RESULTS: For 443 variants, all samples assayed had concordant calls with at least 1 reference genotype and also demonstrated reproducibility. However, 6 of these 443 variants showed an unsatisfactory performance, such as low PCR amplification or insufficient separation of genotypes in scatter plots. Call rates were comparable between 50 ng/µL DNA (99.6%) and 10 ng/µL (99.2%). Use of 10 ng/µL DNA resulted in an incorrect call for a single sample for a single variant. Thus, as recommended by the manufacturer, 50 ng/µL is the preferred concentration for patient genotyping. CONCLUSIONS: We evaluated a custom-designed pharmacogenomics panel and found that it reliably interrogated 437 variants. Clinically actionable results from selected variants on this panel are currently used in clinical studies employing pharmacogenomics for clinical decision-making.

Influence of N-acetyltransferase 2 gene polymorphisms on the in vitro metabolism of the epidermal growth factor receptor inhibitor rociletinib.

AIMS: Rociletinib showed activity in T790M-positive non-small cell lung cancer patients. It undergoes amide hydrolysis to form M502, followed by N-acetylation to M544 or amide hydrolysis to M460. We identified the enzymes responsible for rociletinib metabolism, and investigated the relationship between M544 formation and N-acetyltransferase 2 (NAT2) polymorphisms. METHODS: Rociletinib and metabolites were incubated with carboxylesterase (CES)1b, CES1c, CES2, NAT1, NAT2, arylacetamide deacetylase, inhibitors, pooled human liver microsomes (HLM) and cytosols (HLC). Cytosols (n = 107) were genotyped for NAT2 polymorphisms (rs1041983 and rs1801280) and incubated with M502. Human hepatocytes from intermediate (NAT2*6/*12A) and slow (NAT2*5B/*5B) acetylators were incubated with 10 µM rociletinib and metabolites for 24 hours. Metabolites were measured by high-performance liquid chromatography. RESULTS: M502 was formed from rociletinib and M544 by CES2 and HLM; M544 and N-acetyl-M460 were formed by NAT2 and HLC; M460 was not formed by CES or arylacetamide deacetylase. M502 formation by HLM was inhibited by bis-(4-nitrophenyl)phosphate and eserine (10 µM). M544 formation in HLC was inhibited by 100 µM quercetin and was associated with NAT2 genotype (P < .0001). M460 formation in HLM was inhibited by eserine, and M460 was N-acetylated in HLC. Hepatocytes formed M502, M544 and M460. The intermediate acetylator showed higher production (range: 3.4-5.1-fold) of N-acetylated metabolites than the slow acetylator. CONCLUSIONS: Results indicate that NAT2 and CES2 are involved in rociletinib metabolism, and polymorphic NAT2 could alter drug exposure in patients. Slow NAT2 acetylators would have higher exposure to M502 and M460 and consequently, be at increased risk of experiencing hyperglycaemia and QTc prolongation.

Prolonged Pharmacokinetic Interaction Between Capecitabine and a CYP2C9 Substrate, Celecoxib.

This study investigated the time course and magnitude of the pharmacokinetic interaction between capecitabine and the cytochrome P450 (CYP) 2C9 substrate celecoxib, with implications for coadministration of fluoropyrimidines with CYP2C9 substrates such as warfarin. Patients received celecoxib 200 mg orally twice daily continuously, with capecitabine (1000 mg/m2 orally twice daily for 14 days every 21 days) starting 7 days later. Assessment of the drug-drug interaction (DDI) potential was performed using equivalence testing, which assumes that there is no clinically relevant DDI when the calculated 90% confidence intervals (CIs) of the drug exposure ratios fall within the range of 0.80 to 1.25. Comparison of steady-state pharmacokinetic parameters of celecoxib between day 7 (cycle 0, celecoxib only) and day 14 (cycle 1, celecoxib + capecitabine) showed geometric mean ratios of 1.24 (90%CI, 1.04-1.49), 1.30 (1.11-1.53) and 1.28 (1.11-1.47) for maximum plasma concentration, minimum plasma concentration, and area under the concentration-time curve from time zero to 8 hours, respectively. Comparison of day 7 vs day 21 (cycle 1, after 1 week washout of capecitabine) showed a further increase in the geometric mean ratio of maximum plasma concentration (1.39; 90%CI, 1.16-1.66), minimum plasma concentration (1.53; 1.10-2.12) and area under the concentration-time curve from time zero to 8 hours (1.41; 1.19-1.68). Because the 90%CIs fell outside the prespecified equivalence margin, we conclude that coadministration results in a DDI (increased celecoxib exposure) that persists for at least 7 days after capecitabine discontinuation. Close monitoring should be undertaken when administering fluoropyrimidines with CYP2C9 substrates with narrow therapeutic indexes while also weighing the benefits and risks for individual patients.

Metabolism of megestrol acetate in vitro and the role of oxidative metabolites.

1. There is limited knowledge regarding the metabolism of megestrol acetate (MA), as it was approved by FDA in 1971, prior to the availability of modern tools for identifying specific drug-metabolizing enzymes. We determined the cytochrome P450s (P450s) and UDP-glucuronosyltransferases (UGTs) that metabolize MA, identified oxidative metabolites and determined pharmacologic activity at the progesterone, androgen and glucocorticoid receptors (PR, AR and GR, respectively). 2. Oxidative metabolites were produced using human liver microsomes (HLMs), and isolated for mass spectral (MS) and nuclear magnetic resonance (NMR) analyses. We screened recombinant P450s using MA at 62 µM (HLM Km for metabolite 1; M1) and 28 µM (HLM Km for metabolite 2; M2). UGT isoforms were simultaneously incubated with UDPGA, nicotinamide adenine dinucleotide phosphate (NADPH), CYP3A4 and MA. Metabolites were evaluated for pharmacologic activity on the PR, AR and GR. CYP3A4 and CYP3A5 are responsible for oxidative metabolism of 62 µM MA. 3. At 28 µM substrate concentration, CYP3A4 was the only contributing enzyme. Mass spectral and NMR data suggest metabolism of MA to two alcohols. After oxidation, MA is converted into two secondary glucuronides by UGT2B17 among other UGTs. MA, M1 and M2 had significant pharmacologic activity on the PR while only MA showed activity on the AR and GR.

In vitro glucuronidation of aprepitant: a moderate inhibitor of UGT2B7.

1. Aprepitant, an oral antiemetic, commonly used in the prevention of chemotherapy-induced nausea and vomiting, is primarily metabolized by CYP3A4. Aprepitant glucuronidation has yet to be evaluated in humans. The contribution of human UDP-glucuronosyltransferase (UGT) isoforms to the metabolism of aprepitant was investigated by performing kinetic studies, inhibition studies and correlation analyses. In addition, aprepitant was evaluated as an inhibitor of UGTs. 2. Glucuronidation of aprepitant was catalyzed by UGT1A4 (82%), UGT1A3 (12%) and UGT1A8 (6%) and Kms were 161.6 ± 15.6, 69.4 ± 1.9 and 197.1 ± 28.2 µM, respectively. Aprepitant glucuronidation was significantly correlated with both UGT1A4 substrates anastrazole and imipramine (rs = 0.77, p < 0.0001 for both substrates; n = 44), and with the UGT1A3 substrate thyroxine (rs = 0.58, p < 0.0001; n = 44). 3. We found aprepitant to be a moderate inhibitor of UGT2B7 with a Ki of ∼10 µM for 4-MU, morphine and zidovudine. Our results suggest that aprepitant can alter clearance of drugs primarily eliminated by UGT2B7. Given the likelihood for first-pass metabolism by intestinal UGT2B7, this is of particular concern for oral aprepitant co-administered with oral substrates of UGT2B7, such as zidovudine and morphine.

Glucuronidation of OTS167 in Humans Is Catalyzed by UDP-Glucuronosyltransferases UGT1A1, UGT1A3, UGT1A8, and UGT1A10.

OTS167 is a potent maternal embryonic leucine zipper kinase inhibitor undergoing clinical testing as antineoplastic agent. We aimed to identify the UDP-glucuronosyltransferases (UGTs) involved in OTS167 metabolism, study the relationship between UGT genetic polymorphisms and hepatic OTS167 glucuronidation, and investigate the inhibitory potential of OTS167 on UGTs. Formation of a single OTS167-glucuronide (OTS167-G) was observed in pooled human liver (HLM) (Km = 3.4 ± 0.2 µM), intestinal microsomes (HIM) (Km = 1.7 ± 0.1 µM), and UGTs. UGT1A1 (64 µl/min/mg) and UGT1A8 (72 µl/min/mg) exhibited the highest intrinsic clearances (CLint) for OTS167, followed by UGT1A3 (51 µl/min/mg) and UGT1A10 (47 µl/min/mg); UGT1A9 was a minor contributor. OTS167 glucuronidation in HLM was highly correlated with thyroxine glucuronidation (r = 0.91, P < 0.0001), SN-38 glucuronidation (r = 0.79, P < 0.0001), and UGT1A1 mRNA (r = 0.72, P < 0.0001). Nilotinib (UGT1A1 inhibitor) and emodin (UGT1A8 and UGT1A10 inhibitor) exhibited the highest inhibitory effects on OTS167-G formation in HLM (68%) and HIM (47%). We hypothesize that OTS167-G is an N-glucuronide according to mass spectrometry. A significant association was found between rs6706232 and reduced OTS167-G formation (P = 0.03). No or weak UGT inhibition (range: 0-21%) was observed using clinically relevant OTS167 concentrations (0.4-2 µM). We conclude that UGT1A1 and UGT1A3 are the main UGTs responsible for hepatic formation of OTS167-G. Intestinal UGT1A1, UGT1A8, and UGT1A10 may contribute to first-pass OTS167 metabolism after oral administration.

Dose-finding and pharmacokinetic study to optimize the dosing of irinotecan according to the UGT1A1 genotype of patients with cancer.

PURPOSE: The risk of severe neutropenia from treatment with irinotecan is related in part to UGT1A1*28, a variant that reduces the elimination of SN-38, the active metabolite of irinotecan. We aimed to identify the maximum-tolerated dose (MTD) and dose-limiting toxicity (DLT) of irinotecan in patients with advanced solid tumors stratified by the *1/*1, *1/*28, and *28/*28 genotypes. PATIENTS AND METHODS: Sixty-eight patients received an intravenous flat dose of irinotecan every 3 weeks. Forty-six percent of the patients had the *1/*1 genotype, 41% had the *1/*28 genotype, and 13% had the *28/*28 genotype. The starting dose of irinotecan was 700 mg in patients with the *1/*1 and *1/*28 genotypes and 500 mg in patients with the *28/*28 genotype. Pharmacokinetic evaluation was performed at cycle 1. RESULTS: In patients with the *1/*1 genotype, the MTD was 850 mg (four DLTs per 16 patients), and 1,000 mg was not tolerated (two DLTs per six patients). In patients with the *1/*28 genotype, the MTD was 700 mg (five DLTs per 22 patients), and 850 mg was not tolerated (four DLTs per six patients). In patients with the *28/*28 genotype, the MTD was 400 mg (one DLT per six patients), and 500 mg was not tolerated (three DLTs per three patients). The DLTs were mainly myelosuppression and diarrhea. Irinotecan clearance followed linear kinetics. At the MTD for each genotype, dosing by genotype resulted in similar SN-38 areas under the curve (AUCs; r(2) = 0.0003; P = .97), but the irinotecan AUC was correlated with the actual dose (r(2) = 0.39; P < .001). Four of 48 patients with disease known to be responsive to irinotecan achieved partial response. CONCLUSION: The UGT1A1*28 genotype can be used to individualize dosing of irinotecan. Additional studies should evaluate the effect of genotype-guided dosing on efficacy in patients receiving irinotecan.

Evaluation of utility of pharmacokinetic studies in phase I trials of two oncology drugs.

PURPOSE: There are many phase I trials of oncology drug combinations, very few of which report clinically significant pharmacokinetic interactions. We hypothesized that the utility of such pharmacokinetic drug-drug interaction (DDI) studies is low in the absence of a mechanistic hypothesis. EXPERIMENTAL DESIGN: We retrospectively reviewed 152 phase I (two drug) combination studies published between 2007 and 2011. RESULTS: Only 28 (18%) studies had an implicit or explicit rationale, either inhibition/induction of a drug-metabolizing enzyme or transporter, cosubstrates for the same enzyme or transporter, potential for end-organ toxicity, or protein binding. Only 12 (8%) studies demonstrated a statistically significant DDI, on the basis of change in clearance (or area under the curve) of parent drug and/or active metabolite. There was a strong association between a rationale and a demonstrable drug interaction, as only 2% of studies without a rationale demonstrated a DDI, compared with 32% of studies with a rationale (Fisher exact test; P < 10(-6)). CONCLUSION: DDI studies should not be routinely performed as part of phase I trials of oncology combinations.

Next-generation sequencing for lung cancer.

Lung cancer is biologically aggressive and is the leading cause of cancer-related deaths. The development of lung cancer is unique in each patient according to clinical characterizations, prognosis, response and tolerance to treatment. Traditional capillary-based single-gene sequencing by a first-generation technique (known as Sanger sequencing) has been replaced by next-generation sequencing (NGS) since it allows massive parallel sequencing with lower cost and higher throughput. The NGS approach has made remarkable advances compared with traditional methods. We expect these methodologies to comprehensively interpret the global landscape of cancer and provide more information to fulfill the needs of personalized medicine. This review covers a brief introduction and summary on various NGS technologies, applications and important findings by NGS in lung cancer advances, including further discoveries in previously known target genes (EGFR, ALK and KRAS), the identification of additional lung cancer mutations and the global coordination of cancer genome studies.

Personalized targeted therapy for lung cancer.

Lung cancer has long been recognized as an extremely heterogeneous disease, since its development is unique in every patient in terms of clinical characterizations, prognosis, response and tolerance to treatment. Personalized medicine refers to the use of markers to predict which patient will most likely benefit from a treatment. In lung cancer, the well-developed epidermal growth factor receptor (EGFR) and the newly emerging EML4-anaplastic lymphoma kinase (ALK) are important therapeutic targets. This review covers the basic mechanism of EGFR and EML4-ALK activation, the predictive biomarkers, the mechanism of resistance, and the current targeted tyrosine kinase inhibitors. The efficacy of EGFR and ALK targeted therapies will be discussed in this review by summarizing the prospective clinical trials, which were performed in biomarker-based selected patients. In addition, the revolutionary sequencing and systems strategies will also be included in this review since these technologies will provide a comprehensive understanding in the molecular characterization of cancer, allow better stratification of patients for the most appropriate targeted therapies, eventually resulting in a more promising personalized treatment. The relatively low incidence of EGFR and ALK in non-Asian patients and the lack of response in mutant patients limit the application of the therapies targeting EGFR or ALK. Nevertheless, it is foreseeable that the sequencing and systems strategies may offer a solution for those patients.

Phase I studies of sirolimus alone or in combination with pharmacokinetic modulators in advanced cancer patients.

PURPOSE: Sirolimus is the eponymous inhibitor of the mTOR; however, only its analogs have been approved as cancer therapies. Nevertheless, sirolimus is readily available, has been well studied in organ transplant patients, and shows efficacy in several preclinical cancer models. EXPERIMENTAL DESIGN: Three simultaneously conducted phase I studies in advanced cancer patients used an adaptive escalation design to find the dose of oral, weekly sirolimus alone or in combination with either ketoconazole or grapefruit juice that achieves similar blood concentrations as its intravenously administered and approved prodrug, temsirolimus. In addition, the effect of sirolimus on inhibition of p70S6 kinase phosphorylation in peripheral T cells was determined. RESULTS: Collectively, the three studies enrolled 138 subjects. The most commonly observed toxicities were hyperglycemia, hyperlipidemia, and lymphopenia in 52%, 43%, and 41% of subjects, respectively. The target sirolimus area under the concentration curve (AUC) of 3,810 ng-h/mL was achieved at sirolimus doses of 90, 16, and 25 mg in the sirolimus alone, sirolimus plus ketoconazole, and sirolimus plus grapefruit juice studies, respectively. Ketoconazole and grapefruit juice increased sirolimus AUC approximately 500% and 350%, respectively. Inhibition of p70 S6 kinase phosphorylation was observed at all doses of sirolimus and correlated with blood concentrations. One partial response was observed in a patient with epithelioid hemangioendothelioma. CONCLUSION: Sirolimus can be feasibly administered orally, once weekly with a similar toxicity and pharmacokinetic profile compared with other mTOR inhibitors and warrants further evaluation in studies of its comparative effectiveness relative to recently approved sirolimus analogs.

The effect of thalidomide on the pharmacokinetics of irinotecan and metabolites in advanced solid tumor patients.

PURPOSE: Irinotecan and thalidomide are commonly administered antineoplastic drugs. Combination treatment may potentiate their antitumor effect and protect against irinotecan's intestinal toxicity. We investigated whether thalidomide can modulate the pharmacokinetics of irinotecan and metabolites. METHODS: The study employed a crossover design in which advanced solid tumor patients were randomized to two arms and treated with irinotecan 350 mg/m(2) intravenously (IV) every 3 weeks and thalidomide orally (p.o.) 400 mg daily. Pharmacokinetic data when irinotecan was administered as a single agent in each arm were compared to data when the two study agents were co-administered using paired t tests. Eighty percent and 90% confidence intervals for the true difference were also calculated. RESULTS: The differences in pharmacokinetic parameters and metabolic markers after thalidomide administration were small and unlikely to be clinically significant. With the exception of APC T (1/2), none of the upper confidence limits exceeds a 50% increase. CONCLUSIONS: This study did not find any clinically meaningful effects of thalidomide on the pharmacokinetics of irinotecan or its metabolites.

Two drug interaction studies of sirolimus in combination with sorafenib or sunitinib in patients with advanced malignancies.

PURPOSE: Sirolimus is the prototypical mTOR inhibitor. Sorafenib and sunitinib are small molecule inhibitors of multiple kinases including VEGF receptor (VEGFR) kinases. These agents have different mechanisms of action, providing a strong rationale for combination. EXPERIMENTAL DESIGN: Patients with advanced cancer were assigned to receive either sirolimus or the VEGFR inhibitor alone for a 2-week lead-in period, followed by combination therapy. The primary end point of each trial was to determine whether a drug interaction exists between sirolimus and either sorafenib or sunitinib, as defined by a difference in C(max) for each drug alone compared with its C(max) during combination therapy. RESULTS: The sorafenib and sunitinib trials enrolled 34 and 23 patients, respectively. There were no clinically significant differences in C(max) for any of the drugs alone compared with the C(max) during combination therapy. Toxicity profiles were similar to those expected for each drug alone. One patient with adrenal cortical cancer had a partial response to sirolimus and sunitnib. CONCLUSIONS: Sirolimus can be safely combined with sorafenib or sunitinib. Our trial design is feasible and informative in screening for potential drug-drug interactions, using a relatively small number of patients and limited pharmacokinetic sampling.

A pharmacogenetic study of vorinostat glucuronidation.

High interindividual pharmacokinetic variability was observed in phase 1 studies of vorinostat (suberoylanilide hydroxamic acid), an oral histone deacetylase inhibitor. Thus, we hypothesized that the variability can be explained by genetic variants of the uridine 5'-diphosphate-glucuronosyltransferases (UGTs) involved in vorinostat metabolism. Baculosomes expressing human UGTs and 52 human liver microsomes were screened for vorinostat glucuronidation activity to identify the potential enzymes and functional variants. UGT2B17 had the largest activity. Human liver microsomes with at least one copy of UGT2B17 showed significantly greater enzymatic activity than those with UGT2B17 null genotype (P<0.004). UGT2B17 plays an important role in vorinostat hepatic glucuronidation and the gene deletion polymorphism may influence vorinostat biotransformation and clearance. The clinical impact of this UGT2B17 genetic variant on vorinostat metabolism and drug effect is unknown.

The UGT1A1*28 polymorphism correlates with erlotinib's effect on SN-38 glucuronidation.

The combination of irinotecan and erlotinib has been evaluated in clinical trials, although toxicity has been significant. We aimed to investigate the effect of erlotinib on SN-38 glucuronidation and the association between UGT1A polymorphisms and SN-38 glucuronidation activity in the presence of erlotinib. The inhibitory effect of erlotinib on SN-38 glucuronidation was determined by measuring the formation rates for SN-38 glucuronide, using recombinant human UGT1A1, pooled human liver microsomes (HLMs) and 52 Caucasian liver microsomes in the absence or presence of erlotinib. Inhibition kinetic studies were conducted. AUC ratios were used to predict the risk of potential drug-drug interactions (DDI) in vivo. Our data showed that erlotinib exhibited potent non-competitive inhibition against SN-38 glucuronidation in pooled HLMs and UGT1A1. Using the physiological and pharmacokinetic parameters obtained from the literature, we estimated the in vivo concentrations of unbound erlotinib available for UGT1A1 active site and thus the AUC ratios of SN-38 were also quantitatively predicted. It is estimated that erlotinib administered at 50mg/day or higher doses may result in at least a 24% increase in SN-38 AUC. Significant correlations were observed between SN-38 glucuronidation activity in the presence of erlotinib and UGT1A1*28 in 52 Caucasian liver microsomes. Our results suggest that erlotinib is a potent inhibitor of SN-38 glucuronidation via UGT1A1 inhibition. The coadministration of erlotinib with irinotecan may result in clinically significant DDI. UGT1A1*28 polymorphism correlates with erlotinib's effect on SN-38 glucuronidation. The present findings shed light on the development and optimisation of combinations involving irinotecan and erlotinib.