Mandrekar, Sumithra J.

Abstract SR13668, an orally active Akt pathway inhibitor, has demonstrated cancer chemopreventive potential in preclinical studies. To accelerate the clinical development of this promising agent, we designed and conducted the first-ever phase 0 chemoprevention trial to evaluate and compare the effects of food and formulation on SR13668 bioavailability. Healthy adult volunteers were randomly assigned to receive a single, 38-mg oral dose of SR13668 in one of five different formulations, with or without food. On the basis of existing animal data, SR13668 in a PEG400/Labrasol oral solution was defined as the reference formulation. Blood samples were obtained pre- and post-agent administration for pharmacokinetic analyses. Area under the plasma concentration–time curve (AUC0–∞) was defined as the primary endpoint. Data were analyzed and compared using established statistical methods for phase 0 trials with a limited sample size. Participants (n = 20) were rapidly accrued over a 5-month period. Complete pharmacokinetic data were available for 18 randomized participants. AUC0–∞ values were highest in the fed state (range = 122–439 ng/mL × hours) and were statistically significantly different across formulations (P = 0.007), with Solutol HS15 providing the highest bioavailability. SR13668 time to peak plasma concentration (3 hours; range, 2–6 hours) and half-life were (11.2 ± 3.1 hours) were not formulation-dependent. Using a novel, highly efficient study design, we rapidly identified a lead formulation of SR13668 for further clinical testing. Our findings support application of the phase 0 trial paradigm to accelerate chemoprevention agent development. Cancer Prev Res; 4(3); 347–53. ©2011 AACR.

Abstract Purpose: SR13668, an orally active AKT pathway inhibitor, has demonstrated cancer chemopreventive potential in preclinical studies. To accelerate the clinical development of this promising agent, we designed and conducted the first-ever phase 0 chemoprevention trial to evaluate and compare the effects of food and formulation on SR13668 bioavailability. Patients and Methods: Healthy adult volunteers were randomly assigned to receive a single 38-mg oral dose of SR13668 in one of five different formulations, with or without food. Based on existing animal data, SR13668 in a PEG400/Labrasol@ oral solution (formulation 1) was defined as the reference formulation. Four self-emulsifying solid dispersion test formulations in capsules were also investigated: Solutol@ HS 15 (formulation 2), Solutol@ HS 15/Vitamin E TGPS (50/50 w/w %) (formulation 3), Vitamin E TGPS (formulation 4), and Myrj 53 (formulation 5). SR163668 bioavailability was compared using a two-stage study design. In stage I, participants were randomized to receive the formulation 1 with or without a high-fat meal after an overnight fast. In Stage II, participants were randomly assigned to receive the test formulations, using the preferred dietary condition identified in stage I. Blood samples were obtained pre- and post-agent administration for pharmacokinetic analyses. Area under the plasma concentration-time curve (AUC) was defined as the primary endpoint. Data were analyzed and compared using established statistical methods for phase 0 trials with a limited sample size. Results: Participants (N=20) were rapidly accrued over a 5-month period. Complete pharmacokinetic data were available for 18 randomized participants. The time to peak plasma concentration and half-life values for SR13668 were 3 hours (range, 2 — 6 hours) and 11.2 ± 3.1 hours, respectively, and were not dependent on the formulation. In stage I, the oral bioavailability of SR13668 in formulation 1 was greater under the fed versus fasting dietary state (p = 0.05, Wilcoxon rank-sum test). Therefore, the fed state was selected as the preferred dietary condition for stage II. In stage II, the bioavailability of SR13668 for each of the test formulations were compared with the bioavailability of formulation 1 in the fed state. While not significantly different from formulation 1, formulation 2 AUC0-24h was significantly different (p = 0.004, ANOVA) from formulation 3, 4, and 5 (AUC0-24h, formulation 1- 222 ± 53 ng/ml·hr; AUC0-24h, formulation 2 — 302 ± 78 ng/ml·hr; AUC-177±39ng/ml·hr; AUC-144±29 0-24h, formulation30-24h, formulation 4 ng/ml·hr; AUC0-24h, formulation 5- 98 ± 21 ng/ml·hr). Formulation 1 AUC0-24h was almost 40% lower than the value achieved with formulation 2, and not significantly different from formulation 3, 4, and 5. Thus, formulation 2 provided the highest bioavailability of SR13668. Conclusions: Using a novel, highly efficient study design, we rapidly identified a lead formulation (Solutol@ HS 15) of SR13668 for further clinical testing. Our findings support application of the phase 0 trial paradigm to accelerate chemoprevention agent development. Supported by NIH grants N01-CN-35000, CA15083-34C3 and UL1 RR024150. Citation Information: Cancer Prev Res 2010;3(12 Suppl):CN02-03.

Abstract Sulindac, atorvastatin, or prebiotic dietary fiber may reduce colorectal cancer (CRC) risk. However, clinical trial data are currently limited. We conducted a randomized, phase II chemoprevention trial involving subjects 40 years or older, with previously resected colon cancer or multiple/advanced colorectal adenomas. Magnification chromoendoscopy (MCE) was performed to identify and characterize rectal aberrant crypt foci (ACF); eligibility criteria required five or more rectal ACFs at baseline. Intervention assignments were as follows: (a) atorvastatin 20 mg qd; (b) sulindac 150 mg bid; (c) oligofructose-enriched inulin (as ORAFTI®Synergy1) 6 gm bid; or (d) control (maltodextrin) 6 gm bid, for 6 months. Percent change in rectal ACF number (%ΔACF) within arm was the primary endpoint. Secondary endpoints included changes in proliferation (Ki67) and apoptosis (caspase-3), as measured from normal mucosa biopsy samples. Among 85 eligible randomized subjects, 76 (86%) completed the trial per protocol. The median (range) of rectal ACF was 9 (5–34) and 8 (0–37) at baseline and postintervention, respectively. The median (SD) for %ΔACF was 5.6 (−69% to 143%), −18.6 (−83% to 160%), −3.6 (−88% to 83%), and −10.0 (−100% to 117%) in the atorvastatin, sulindac, ORAFTI®Synergy1 and control arms, respectively. Neither within-arm (P = 0.12–0.59) nor between-arm (P = 0.30–0.92) comparisons of %ΔACF were statistically significant. The active and control interventions also seemed to have similar effects on mucosal proliferation and apoptosis (P > 0.05 for each comparison). Data from this multicenter, phase II trial do not provide convincing evidence of CRC risk reduction from 6-month interventions with atorvastatin, sulindac, or ORAFTI®Synergy1, although statistical power was limited by the relatively small sample size. Cancer Prev Res; 4(2); 259–69. ©2011 AACR.

Purpose In March 1998, Common Toxicity Criteria (CTC) version 2.0 introduced the collection of attribution of adverse events (AEs) to study drug. We investigate whether attribution adds value to the interpretation of AE data. Patients and Methods Patients in the placebo arm of two phase III trials—North Central Cancer Treatment Group Trial 97-24-51 (carboxyamino-triazole v placebo in advanced non–small-cell lung cancer) and American College of Surgeons Oncology Group Trial Z9001 (imatinib mesylate v placebo after resection of primary gastrointestinal stromal tumors)—were studied. Attribution was categorized as unrelated (not related or unlikely) and related (possible, probable, or definite). Results In total, 398 patients (84 from Trial 97-24-51 and 314 from Trial Z9001) and 7,736 AEs were included; 47% and 50% of the placebo-arm AEs, respectively, were reported as related. When the same AE was reported in the same patient on multiple visits, the attribution category changed at least once 36% and 31% of the time. AE type and sex (Trial Z9001) and AE type and performance status (Trial 97-24-51) were associated with a higher likelihood of AEs being deemed related. Conclusion Nearly 50% of AEs were reported as attributed to study drug on the placebo arm of two randomized clinical trials. These data provide strong evidence that AE attribution is difficult to determine, unreliable, and of questionable value in interpreting AE data in randomized clinical trials.

Background With the advent of targeted therapies, biomarkers provide a promising means of individualizing therapy through an integrated approach to prediction using the genetic makeup of the disease and the genotype of the patient. Biomarker validation has therefore become a central topic of discussion in the field of medicine, primarily due to the changing landscape of therapies for treatment of a disease and these therapies purported mechanism(s) of action. Purpose In this report, we discuss the merits and limitations of some of the clinical trial designs for predictive biomarker validation using examples from ongoing or completed clinical trials. Methods The designs are broadly classified as retrospective (i.e., using data from previously well-conducted randomized controlled trials (RCT)) versus prospective (enrichment or targeted, unselected or all-comers, hybrid, and adaptive analysis). We discuss some of these designs in the context of real trials. Results Well-designed retrospective analysis of prospective RCT can bring forward effective treatments to marker defined subgroup of patients in a timely manner. An example is the KRAS gene status in colorectal cancer — the benefit from cetuximab and panitumumab was demonstrated to be restricted to patients with wild type status based on prospectively specified analyses using data from previously conducted RCTs. Prospective enrichment designs are appropriate when compelling preliminary evidence suggests that not all patients will benefit from the study treatment under consideration; however, this may sometimes leave questions unanswered. An example is the established benefit of trastuzumab as adjuvant therapy for breast cancer; a clear definition of HER2-positivity and the assay reproducibility have, however, remained unanswered. An all-comers design is optimal where preliminary evidence regarding treatment benefit and assay reproducibility is uncertain (e.g., EGFR expression and tyrosine kinase inhibitors in lung cancer), or to identify the most effective therapy from a panel of regimens (e.g., chemotherapy options in breast cancer). Limitations The designs discussed here rest on the assumption that the technical feasibility, assay performance metrics, and the logistics of specimen collection are well established and that initial results demonstrate promise with regard to the predictive ability of the marker(s). Conclusions The choice of a clinical trial design is driven by a combination of scientific, clinical, statistical, and ethical considerations. There is no one size fits all solution to predictive biomarker validation. Clinical Trials 2010; 7: 567—573. http://ctj.sagepub.com

Purpose To evaluate the efficacy and toxicity of pemetrexed combined with bevacizumab as second-line therapy for patients with advanced non–small-cell lung cancer (NSCLC) and to correlate allelic variants in pemetrexed-metabolizing genes with clinical outcome. Patients and Methods Patients with previously treated NSCLC received pemetrexed (500 mg/m2 intravenous) combined with bevacizumab (15 mg/kg intravenous) every 3 weeks. The primary end point, evaluated using a one-stage Fleming design for detecting a true success rate of at least 70%, was the proportion of patients who were progression free and on treatment at 3 months. Polymorphisms in genes responsible for pemetrexed transport (reduced folate carrier [SLC19A1]) and metabolism (folylpolyglutamate synthase [FPGS] and gamma-glutamyl hydrolase [GGH]) evaluated in germline DNA (blood) were correlated with treatment outcome. Results Forty-eight evaluable patients (14 females and 34 males) received a median of four cycles (range, one to 20 cycles). The most common grade 3 or 4 nonhematologic adverse events (AEs) were fatigue (13%), dyspnea (10%), and thrombosis (10%). Grade 3 or 4 hematologic AEs were neutropenia (19%) and lymphopenia (13%). Twenty-four (57%; 95% CI, 41% to 72%) of the first 42 patients met the success criteria. Median overall survival (OS) and progression-free survival (PFS) times were 8.6 and 4.0 months, respectively. The exon 6 (2522)C→T polymorphism in SLC19A1 correlated with 3-month progression-free status (P = .01) and with PFS (P = .05). The IVS1(1307)C→T polymorphism in GGH correlated with OS (P = .04). Conclusion The study did not meet its primary end point. However, the median PFS time of 4 months is promising. Pharmacogenetic studies in larger cohorts are needed to definitively identify polymorphisms that predict for survival and toxicity of pemetrexed.

Purpose Thalidomide and lenalidomide are immunomodulatory drugs (IMiDs) that produce high remission rates in the treatment of multiple myeloma. Pomalidomide is a new IMiD with high in vitro potency. We report, to our knowledge, the first phase II trial of pomalidomide administered in combination with low-dose dexamethasone for the treatment of relapsed or refractory multiple myeloma. Patients and Methods Pomalidomide was administered orally at a dose of 2 mg daily on days 1 through 28 of a 28-day cycle. Dexamethasone 40 mg daily was administered orally on days 1, 8, 15, and 22 of each cycle. Responses were recorded using the criteria of the International Myeloma Working Group. Results Sixty patients were enrolled. Thirty-eight patients (63%) achieved confirmed response including complete response in three patients (5%), very good partial response in 17 patients (28%), and partial response in 18 patients (30%). Responses were seen in 40% of lenalidomide-refractory patients, 37% of thalidomide-refractory patients, and 60% of bortezomib-refractory patients. Responses were seen in 74% of patients with high-risk cytogenetic or molecular markers. Toxicity consisted primarily of myelosuppression. Grade 3 or 4 hematologic toxicity consisted of anemia (5%), thrombocytopenia (3%), and neutropenia (32%). One patient (1.6%) had a thromboembolic event. The median progression-free survival time was 11.6 months and was not significantly different in patients with high-risk disease compared with patients with standard-risk disease. Conclusion The combination of pomalidomide and low-dose dexamethasone is extremely active in the treatment of relapsed multiple myeloma, including high response rates in patients refractory to other novel agents.

Purpose Biomarkers can add substantial value to current medical practice by providing an integrated approach to prediction using the genetic makeup of the tumor and the genotype of the patient to guide patient-specific treatment selection. We discuss and evaluate various clinical trial designs for the validation of biomarker-guided therapy. Methods Designs for predictive marker validation are broadly classified as retrospective (ie, using data from previously well-conducted randomized controlled trials [RCTs]) versus prospective (enrichment, unselected, hybrid, or adaptive analysis). We discuss the salient features of each design in the context of real trials. Results Well-designed retrospective analysis from well-conducted prospective RCTs can bring forward effective treatments to marker-defined subgroups of patients in a timely manner (eg, KRAS and colorectal cancer). Enrichment designs are appropriate when preliminary evidence suggest that patients with or without that marker profile do not benefit from the treatments in question; however, this may sometimes leave questions unanswered (eg, trastuzumab and breast cancer). An unselected design is optimal where preliminary evidence regarding treatment benefit and assay reproducibility is uncertain (eg, epidermal growth factor receptor and lung cancer). Hybrid designs are appropriate when preliminary evidence demonstrate the efficacy of certain treatments for a marker-defined subgroup, making it unethical to randomly assign patients with that marker status to other treatments (eg, multigene assay and breast cancer). Adaptive analysis designs allow for prespecified marker-defined subgroup analyses of data from an RCT. Conclusion The implementation of these design strategies will lead to a more rapid clinical validation of biomarker-guided therapy.

Abstract Purpose: Topotecan resistance can result from drug efflux by P-glycoprotein (Pgp) and breast cancer resistance protein (BCRP) as well as survival signals initiated by epidermal growth factor receptor family members. The present studies were done to determine the effect of combining topotecan and the dual epidermal growth factor receptor/HER2 inhibitor lapatinib in tissue culture, a murine xenograft model, and a phase I clinical trial. Experimental Design: The effects of lapatinib on topotecan accumulation and cytotoxicity in vitro were examined in paired cell lines lacking or expressing Pgp or BCRP. Antiproliferative effects of the combination were assessed in mice bearing HER2+ BT474 breast cancer xenografts. Based on tolerability in this preclinical model, 37 patients with advanced-stage cancers received escalating doses of lapatinib and topotecan in a phase I trial. Results: Lapatinib increased topotecan accumulation in BCRP- or Pgp-expressing cells in vitro, and the combination showed enhanced efficacy in HER2+ BT474 xenografts. In the phase I study, nausea, vomiting, diarrhea, and fatigue were dose limiting. The maximum tolerated doses were 1,250 mg/d lapatinib by mouth for 21 or 28 days with 3.2 mg/m2 topotecan i.v. on days 1, 8, and 15 of 28-day cycles. Pharmacokinetic analyses showed that combined drug administration resulted in decreased topotecan clearance consistent with transporter-mediated interactions. Seventeen (46%) patients had disease stabilization. Conclusions: The lapatinib/topotecan combination is well tolerated and warrants further study.