Citations

Abstract Anticancer drugs are combined in an effort to treat a heterogeneous tumor or to maximize the pharmacodynamic effect. The development of combination regimens, while desirable, poses unique challenges. These include the selection of agents for combination therapy that may lead to improved efficacy while maintaining acceptable toxicity, the design of clinical trials that provide informative results for individual agents and combinations, and logistic and regulatory challenges. The phase I trial is often the initial step in the clinical evaluation of a combination regimen. In view of the importance of combination regimens and the challenges associated with developing them, the Clinical Trial Design (CTD) Task Force of the National Cancer Institute Investigational Drug Steering Committee developed a set of recommendations for the phase I development of a combination regimen. The first two recommendations focus on the scientific rationale and development plans for the combination regimen; subsequent recommendations encompass clinical design aspects. The CTD Task Force recommends that selection of the proposed regimens be based on a biologic or pharmacologic rationale supported by clinical and/or robust and validated preclinical evidence, and accompanied by a plan for subsequent development of the combination. The design of the phase I clinical trial should take into consideration the potential pharmacokinetic and pharmacodynamic interactions as well as overlapping toxicity. Depending on the specific hypothesized interaction, the primary endpoint may be dose optimization, pharmacokinetics, and/or pharmacodynamics (i.e., biomarker). Clin Cancer Res; 20(16); 4210–7. ©2014 AACR.

AbstractWe compiled and analyzed a database of cooperative group trials in advanced pancreatic cancer to develop historical benchmarks for overall survival (OS) and progression-free survival (PFS). Such benchmarks are essential for evaluating new therapies in a single-arm setting. The analysis included patients with untreated metastatic pancreatic cancer receiving regimens that included gemcitabine, between 1995 and 2005. Prognostic baseline factors were selected by their significance in Cox regression analysis. Outlier trial arms were identified by comparing individual 6-month OS and PFS rates against the entire group. The dataset selected for the generation of OS and PFS benchmarks was then tested for intertrial arm variability using a logistic-normal model with the selected baseline prognostic factors as fixed effects and the individual trial arm as a random effect. A total of 1,132 cases from eight trials qualified. Performance status and sex were independently significant for OS, and performance status was prognostic for PFS. Outcomes for one trial (NCCTG-034A) were significantly different from the other trial arms. When this trial was excluded, the remaining trial arms were homogeneous for OS and PFS outcomes after adjusting for performance status and sex. Benchmark values for 6-month OS and PFS are reported along with a method for using these values in future study design and analysis. The benchmark survival values were generated from a dataset that was homogeneous between trials. The benchmarks can be used to enable single-arm phase II trials using a gemcitabine platform, especially under certain circumstances. Such circumstances might be when a randomized control arm is not practically feasible, an early signal of activity of an experimental agent is being explored such as in expansion cohorts of phase I studies, and in patients who are not candidates for combination cytotoxic therapy. Clin Cancer Res; 20(16); 4176–85. ©2014 AACR.

Abstract New approaches to drug development are critically needed to lessen the time, cost, and resources necessary to identify and optimize active agents. Strategies to accelerate drug development include testing drugs earlier in the disease process, such as the neoadjuvant setting. The U.S. Food and Drug Administration (FDA) has issued guidance designed to accelerate drug approval through the use of neoadjuvant studies in which the surrogate short-term endpoint, pathologic response, can be used to identify active agents and shorten the time to approval of both efficacious drugs and biomarkers identifying patients most likely to respond. However, this approach has unique challenges. In particular, issues of patient safety are paramount, given the exposure of potentially curable patients to investigational agents with limited safety experience. Key components to safe drug development in the neoadjuvant setting include defining a study population at sufficiently poor prognosis with standard therapy to justify exposure to investigational agents, defining the extent and adequacy of safety data from phase I, detecting potentially harmful interactions between investigational and standard therapies, improving study designs, such as adaptive strategies, that limit patient exposure to ineffective agents, and intensifying safety monitoring in the course of the trial. The I-SPY2 trial is an example of a phase II neoadjuvant trial of novel agents for breast cancer in which these issues have been addressed, both in the design and conduct of the trial. These adaptations of phase II design enable acceleration of drug development by reducing time and cost to screen novel therapies for activity without compromising safety. Clin Cancer Res; 19(11); 2817–23. ©2013 AACR.

Abstract Background: Genome-wide association studies (GWAS) identified variants at 19p13.1 and ZNF365 (10q21.2) as risk factors for breast cancer among BRCA1 and BRCA2 mutation carriers, respectively. We explored associations with ovarian cancer and with breast cancer by tumor histopathology for these variants in mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Methods: Genotyping data for 12,599 BRCA1 and 7,132 BRCA2 mutation carriers from 40 studies were combined. Results: We confirmed associations between rs8170 at 19p13.1 and breast cancer risk for BRCA1 mutation carriers [HR, 1.17; 95% confidence interval (CI), 1.07–1.27; P = 7.42 × 10−4] and between rs16917302 at ZNF365 (HR, 0.84; 95% CI, 0.73–0.97; P = 0.017) but not rs311499 at 20q13.3 (HR, 1.11; 95% CI, 0.94–1.31; P = 0.22) and breast cancer risk for BRCA2 mutation carriers. Analyses based on tumor histopathology showed that 19p13 variants were predominantly associated with estrogen receptor (ER)-negative breast cancer for both BRCA1 and BRCA2 mutation carriers, whereas rs16917302 at ZNF365 was mainly associated with ER-positive breast cancer for both BRCA1 and BRCA2 mutation carriers. We also found for the first time that rs67397200 at 19p13.1 was associated with an increased risk of ovarian cancer for BRCA1 (HR, 1.16; 95% CI, 1.05–1.29; P = 3.8 × 10−4) and BRCA2 mutation carriers (HR, 1.30; 95% CI, 1.10–1.52; P = 1.8 × 10−3). Conclusions: 19p13.1 and ZNF365 are susceptibility loci for ovarian cancer and ER subtypes of breast cancer among BRCA1 and BRCA2 mutation carriers. Impact: These findings can lead to an improved understanding of tumor development and may prove useful for breast and ovarian cancer risk prediction for BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev; 21(4); 645–57. ©2012 AACR.

Abstract Background: BRCA1 and BRCA2 mutation carriers have a lifetime breast cancer risk of 40% to 80%, suggesting the presence of risk modifiers. We previously identified significant associations in genetic variants in the insulin-like growth factor (IGF) signaling pathway. Here, we investigate additional IGF signaling genes as risk modifiers for breast cancer development in BRCA carriers. Methods: A cohort of 1,019 BRCA1 and 500 BRCA2 mutation carriers were genotyped for 99 single-nucleotide polymorphisms (SNP) in 13 genes. Proportional hazards regression was used to model time from birth to diagnosis of breast cancer for BRCA1 and BRCA2 carriers separately. For linkage disequilibrium (LD) blocks with multiple SNPs, an additive genetic model was used. For an SNP analysis, no additivity assumptions were made. Results: Significant associations were found between risk of breast cancer and LD blocks in IGF2 for BRCA1 and BRCA2 mutation carriers (global P values of 0.009 for BRCA1 and 0.007 for BRCA2), HTRA1 for BRCA1 carriers (global P value of 0.005), and MMP3 for BRCA2 carriers (global P = 0.0000007 for BRCA2). Conclusions: We identified significant associations of genetic variants involved in IGF signaling. With the known interaction of BRCA1 and IGF signaling and the loss of PTEN in a majority of BRCA1 tumors, this suggests that signaling through AKT may modify breast cancer risk in BRCA1 carriers. Impact: These results suggest potential avenues for future research targeting the IGF signaling pathway in modifying risk in BRCA1and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev; 20(8); 1690–702. ©2011 AACR.

Abstract A phase I trial of ABT-888 (veliparib), a PARP inhibitor, in combination with topotecan, a topoisomerase I–targeted agent, was carried out to determine maximum tolerated dose (MTD), safety, pharmacokinetics, and pharmacodynamics of the combination in patients with refractory solid tumors and lymphomas. Varying schedules and doses of intravenous topotecan in combination with ABT-888 (10 mg) administered orally twice a day (BID) were evaluated. Plasma and urine pharmacokinetics were assessed and levels of poly(ADP-ribose) (PAR) and the DNA damage marker γH2AX were measured in tumor and peripheral blood mononuclear cells (PBMC). Twenty-four patients were enrolled. Significant myelosuppression limited the ability to coadminister ABT-888 with standard doses of topotecan, necessitating dose reductions. Preclinical studies using athymic mice carrying human tumor xenografts also informed schedule changes. The MTD was established as topotecan 0.6 mg/m2/d and ABT-888 10 mg BID on days one to five of 21-day cycles. Topotecan did not alter the pharmacokinetics of ABT-888. A more than 75% reduction in PAR levels was observed in 3 paired tumor biopsy samples; a greater than 50% reduction was observed in PBMCs from 19 of 23 patients with measurable levels. Increases in γH2AX response in circulating tumor cells (CTC) and PBMCs were observed in patients receiving ABT-888 with topotecan. We show a mechanistic interaction of a PARP inhibitor, ABT-888, with a topoisomerase I inhibitor, topotecan, in PBMCs, tumor, and CTCs. Results of this trial reveal that PARP inhibition can modulate the capacity to repair topoisomerase I–mediated DNA damage in the clinic. Cancer Res; 71(17); 5626–34. ©2011 AACR.

Abstract The optimal design of phase II studies continues to be the subject of vigorous debate, especially studies of newer molecularly targeted agents. The observations that many new therapeutics “fail” in definitive phase III studies, coupled with the numbers of new agents to be tested as well as the increasing costs and complexity of clinical trials, further emphasize the critical importance of robust and efficient phase II design. The Clinical Trial Design Task Force (CTD-TF) of the National Cancer Institute (NCI) Investigational Drug Steering Committee (IDSC) has published a series of discussion papers on phase II trial design in Clinical Cancer Research. The IDSC has developed formal recommendations about aspects of phase II trial design that are the subject of frequent debate, such as endpoints (response versus progression-free survival), randomization (single-arm designs versus randomization), inclusion of biomarkers, biomarker-based patient enrichment strategies, and statistical design (e.g., two-stage designs versus multiple-group adaptive designs). Although these recommendations in general encourage the use of progression-free survival as the primary endpoint, randomization, inclusion of biomarkers, and incorporation of newer designs, we acknowledge that objective response as an endpoint and single-arm designs remain relevant in certain situations. The design of any clinical trial should always be carefully evaluated and justified based on characteristic specific to the situation. Clin Cancer Res; 16(6); 1764–9

Abstract Inherited BRCA1/2 mutations confer elevated ovarian cancer risk. Knowledge of factors that can improve ovarian cancer risk assessment in BRCA1/2 mutation carriers is important because no effective early detection for ovarian cancers exists. A cohort of 1,575 BRCA1 and 856 BRCA2 mutation carriers was used to evaluate haplotypes at ATM, BARD1, BRIP1, CTIP, MRE11, NBS1, RAD50, RAD51, and TOPBP1 in ovarian cancer risk. In BRCA1 carriers, no associations were observed with ATM, BARD1, CTIP, RAD50, RAD51, or TOPBP1. At BRIP1, an association was observed for one haplotype with a multiple testing corrected P (Pcorr) = 0.012, although no individual haplotype was significant. At MRE11, statistically significant associations were observed for one haplotype (Pcorr = 0.007). At NBS1, we observed a Pcorr = 0.024 for haplotypes. In BRCA2 carriers, no associations were observed with CTIP, NBS1, RAD50, or TOPBP1. Rare haplotypes at ATM (Pcorr = 0.044) and BARD1 (Pcorr = 0.012) were associated with ovarian cancer risk. At BRIP1, two common haplotypes were significantly associated with ovarian cancer risk (Pcorr = 0.011). At MRE11, we observed a significant haplotype association (Pcorr = 0.012), and at RAD51, one common haplotype was significantly associated with ovarian cancer risk (Pcorr = 0.026). Variants in genes that interact biologically withBRCA1 and/or BRCA2 may be associated with modified ovarian cancer risk in women who carry BRCA1/2 mutations. [Cancer Res 2009;69(14):5801–10]

Abstract As the use of molecularly targeted agents, which are anticipated to increase overall survival (OS)and progression-free survival (PFS) but not necessarily tumor response, has increased in oncology, there has been a corresponding increase in the recommendation and use of randomized phase II designs. Such designs reduce the potential for bias, existent in comparisons with historical controls, but also substantially increase the sample size requirements. We review the principal statistical designs for historically controlled and randomized phase II trials, along with their advantages, disadvantages, and statistical design considerations. We review the arguments for and against the use of randomization in phase II studies, the situations in which the use of historical controls is preferred, and the situations in which the use of randomized designs is preferred. We review methods used to calculate predicted OS or PFS values from historical controls, adjusted so as to be appropriate for an experimental sample with particular prognostic characteristics. We show how adjustment of the type I and type II error bounds for randomized studies can facilitate the detection of appropriate target increases in median PFS or OS with sample sizes appropriate for phase II studies. Although there continue to be differences among investigators concerning the use of randomization versus historical controls in phase II trials, there is agreement that each approach will continue to be appropriate, and the optimal approach will depend upon the circumstances of the individual trial.