Safety, pharmacokinetics, and preliminary efficacy of E6201 in patients with advanced solid tumours, including melanoma: results of a phase 1 study.

BACKGROUND: This phase 1 first-in-human study aimed to determine the maximum-tolerated dose (MTD), dose-limiting toxicities, and safety of E6201, and to establish recommended dosing in patients with advanced solid tumours, expanded to advanced melanoma. METHODS: Part A (dose escalation): sequential cohorts received E6201 intravenously (IV) over 30 min (once-weekly [qw; days (D)1 + 8 + 15 of a 28-day cycle]), starting at 20 mg/m2, increasing to 720 mg/m2 or the MTD. Part B (expansion): patients with BRAF-mutated or wild-type (WT) melanoma received E6201 320 mg/m2 IV over 60 minutes qw (D1 + 8 + 15 of a 28-day cycle) or 160 mg/m2 IV twice-weekly (D1 + 4 + 8 + 11 + 15 + 18 of a 28-day cycle; BRAF-mutated only). RESULTS: MTD in Part A (n = 25) was 320 mg/m2 qw, confirmed in Part B (n = 30). Adverse events included QT prolongation (n = 4) and eye disorders (n = 3). E6201 exposure was dose-related, with PK characterised by extensive distribution and fast elimination. One patient achieved PR during Part A (BRAF-mutated papillary thyroid cancer; 480 mg/m2 qw) and three during Part B (2 BRAF-mutated melanoma; 1 BRAF-WT melanoma; all receiving 320 mg/m2 qw). CONCLUSIONS: An intermittent regimen of E6201 320 mg/m2 IV qw for the first 3 weeks of a 28-day cycle was feasible and reasonably well-tolerated in patients with advanced solid tumours, including melanoma with brain metastases, with evidence of clinical efficacy.

Improved prediction of prostate cancer recurrence through systems pathology.

We have developed an integrated, multidisciplinary methodology, termed systems pathology, to generate highly accurate predictive tools for complex diseases, using prostate cancer for the prototype. To predict the recurrence of prostate cancer following radical prostatectomy, defined by rising serum prostate-specific antigen (PSA), we used machine learning to develop a model based on clinicopathologic variables, histologic tumor characteristics, and cell type-specific quantification of biomarkers. The initial study was based on a cohort of 323 patients and identified that high levels of the androgen receptor, as detected by immunohistochemistry, were associated with a reduced time to PSA recurrence. The model predicted recurrence with high accuracy, as indicated by a concordance index in the validation set of 0.82, sensitivity of 96%, and specificity of 72%. We extended this approach, employing quantitative multiplex immunofluorescence, on an expanded cohort of 682 patients. The model again predicted PSA recurrence with high accuracy, concordance index being 0.77, sensitivity of 77% and specificity of 72%. The androgen receptor was selected, along with 5 clinicopathologic features (seminal vesicle invasion, biopsy Gleason score, extracapsular extension, preoperative PSA, and dominant prostatectomy Gleason grade) as well as 2 histologic features (texture of epithelial nuclei and cytoplasm in tumor only regions). This robust platform has broad applications in patient diagnosis, treatment management, and prognostication.

Effect of enzyme inhibition on perampanel pharmacokinetics: Why study design matters.

OBJECTIVES: Perampanel, a selective, noncompetitive AMPA receptor antagonist, is indicated as adjunctive therapy for the treatment of partial seizures with or without secondarily generalized seizures and primary generalized tonic-clonic seizures in patients with epilepsy aged 12years and older. In vitro studies and Phase I trials indicate that perampanel is metabolized almost exclusively by CYP3A, with an elimination half-life (t1/2) averaging approximately 105h. Understanding of pharmacokinetic (PK) interactions-enzyme inhibition or induction-and anticipating their occurrence are important for management of patients with epilepsy. Here we report PK results from a Phase I drug-drug interaction (DDI) study (Study 005) combining perampanel with the CYP3A inhibitor ketoconazole, as well as supplementary in silico predictions further exploring this interaction. METHODS: A Phase I, randomized, open-label, two-period, two-treatment, two-way crossover study was conducted in 26 healthy adult male volunteers. Subjects were randomized to 1 of 2 treatment sequences. In one period, subjects received a single 1-mg fasting dose of perampanel (Day1); in the other period, subjects received ketoconazole 400mg once daily for 10days with a single 1-mg perampanel dose while fasting (Day3). Blood samples were drawn at multiple time points up to 288h after the perampanel dose. Pharmacokinetic parameters of perampanel were calculated by noncompartmental analysis, and safety was recorded. An integrated, physiologically based PK model built in Simcyp® provided additional insight into this interaction. Drug-drug interaction intensity was measured by the ratio of systemic exposure (area under plasma concentration-time curve [AUC]) of perampanel in the presence or absence of concomitant ketoconazole. RESULTS: Single oral doses of 1mg perampanel and once-daily oral doses of ketoconazole 400mg were safe and well tolerated. Maximum perampanel plasma concentration (Cmax) and time to Cmax showed no apparent differences when perampanel was administered alone versus with ketoconazole. Ketoconazole co-administration resulted in an approximate 20% increase in perampanel AUC (P<0.001). This increase, although statistically significant, was a<2.0-fold AUC change and alone would suggest a modest effect of ketoconazole. To further explore these results, DDI simulations were performed to query the findings and test additional study conditions. Using the actual trial conditions of Study 005, the simulations also predicted an AUC ratio increase <2-fold, providing verification of the simulation assumptions and the modest effect of ketoconazole for 10days. Simulations further suggested that an interaction effect of ketoconazole on perampanel exposure (>2-fold) of potential clinical significance could be predicted when using larger doses of ketoconazole (e.g., 200mg every 6h) coadministered for a greater time period (e.g., 30days), with AUC ratio as high as 3.36. Additionally, simulations suggested that a significant interaction with co-administration of perampanel and an inhibitor more potent than ketoconazole (such as itraconazole) could not be ruled out. CONCLUSIONS: Selecting an appropriate study design is critical to fully characterize the PK interaction for drugs such as perampanel that have a long t1/2. Although a negligible effect on perampanel PK was observed following co-administration of ketoconazole 400mg/day for 10days, this is likely due in part to the relatively brief co-administration period of ketoconazole and perampanel (<3 times the t1/2 of perampanel). While short-term administration of a CYP3A inhibitor may not significantly increase perampanel exposure, such increases may be expected following chronic and larger dosing or with a more potent inhibitor.

Nomogram for overall survival of patients with progressive metastatic prostate cancer after castration.

PURPOSE: To develop a pretreatment prognostic model for survival of patients with progressive metastatic prostate cancer after castration using parameters that are measured during routine clinical management. PATIENTS AND METHODS: Pretreatment clinical and biochemical determinants from 409 patients enrolled onto 19 consecutive therapeutic protocols from June 1989 through January 2000 were evaluated. The factors selected were age, Karnofsky performance status (KPS), hemoglobin (HGB), prostate-specific antigen (PSA), lactate dehydrogenase (LDH), alkaline phosphatase (ALK), and albumin. These factors were combined in an accelerated failure time regression model to produce a nomogram to predict median, 1-year, and 2-year survival. The nomogram was validated internally and externally using data from a multicenter randomized trial of suramin plus hydrocortisone versus hydrocortisone alone. RESULTS: The median survival of the entire group was 15.8 months (range, 0.9 to 77.8 months); 87% have died. In multivariable analysis, KPS, HGB, ALK, albumin, and LDH were significantly associated with survival (P <.05), whereas age and PSA were not. All seven factors were included in the nomogram. When applied to the external validation data set, the nomogram achieved a concordance index of 0.67. Calibration plots suggested that the nomogram was well calibrated for all predictions. CONCLUSION: A nomogram derived from pretreatment parameters that are measured on a routine basis was constructed. It can be used to predict the median, 1-year, and 2-year survival of patients with progressive castrate metastatic disease with reasonable accuracy. The information is useful to assess prognosis, guide treatment selection, and design clinical trials.

Quantifying the amount of variation in survival explained by prostate-specific antigen.

PURPOSE: Post-therapy changes in prostate-specific antigen(PSA) have been proposed as surrogates for survival in clinical trials due to observed statistical associations. However, association alone does not satisfy the conditions of surrogacy. A measure that quantifies the amount of association is important. Using a population-based approach, we explore the relationship between PSA and survival and generate a measure to demonstrate the amount of the variation in survival explained by PSA. EXPERIMENTAL DESIGN: With serial PSA measurements from 254 patients with androgen-independent prostate cancer, we use a time-dependent Cox model with a nonlinear log relative risk function to quantify the strength of the association between time-dependent PSA and survival. The nonlinear log relative risk function provides a flexible Cox model and a more accurate measure of the strength of association between PSA and survival. RESULTS: Among these 254 patients, there were 247 deaths (median survival time = 13.0 months). Median follow-up time for those alive or censored was 59.3 months (range, 36.8-71.3 months). An association was observed between PSA and survival (P < 0.01, two-sided test). However, time-dependent PSA explains only 17% of the variation in survival. CONCLUSIONS: Use of this methodology demonstrates that there remains sufficient variation in survival unaccounted for by PSA measurements in this patient cohort. Other factors, perhaps unknown, exist that determine survival outcome. Consideration of PSA alone as a surrogate can produce misleading information regarding the risk of death; its use as a surrogate for survival is not warranted when designing a clinical trial in this patient population.

Two-stage designs for gene-disease association studies.

The goal of this article is to describe a two-stage design that maximizes the power to detect gene-disease associations when the principal design constraint is the total cost, represented by the total number of gene evaluations rather than the total number of individuals. In the first stage, all genes of interest are evaluated on a subset of individuals. The most promising genes are then evaluated on additional subjects in the second stage. This will eliminate wastage of resources on genes unlikely to be associated with disease based on the results of the first stage. We consider the case where the genes are correlated and the case where the genes are independent. Using simulation results, it is shown that, as a general guideline when the genes are independent or when the correlation is small, utilizing 75% of the resources in stage 1 to screen all the markers and evaluating the most promising 10% of the markers with the remaining resources provides near-optimal power for a broad range of parametric configurations. This translates to screening all the markers on approximately one quarter of the required sample size in stage 1.

Loss of the tumor suppressor PML in human cancers of multiple histologic origins.

BACKGROUND: The PML gene is fused to the RARalpha gene in the vast majority of acute promyelocytic leukemias (APL) and has been implicated in the control of key tumor-suppressive pathways. However, its role in the pathogenesis of human cancers other than APL is still unclear. We therefore assessed the status and expression of the PML gene in solid tumors of multiple histologic origins. METHODS: We created tumor tissue microarrays (TTMs) with samples from patients with colon adenocarcinoma (n = 109), lung carcinoma (n = 19), prostate adenocarcinoma (n = 36), breast carcinoma (n = 38), central nervous system (CNS) tumors (n = 51), germ cell tumors (n = 60), thyroid carcinoma (n = 32), adrenal cortical carcinoma (n = 12), and non-Hodgkin's lymphoma (n = 251) and from normal tissue corresponding to each histotype and analyzed PML protein and mRNA expression by immunohistochemistry and in situ hybridization, respectively. Tumor cell lines (n = 64) of various histologic origins were analyzed for PML protein and mRNA expression by immunofluorescence and northern blotting, respectively. DNA from microdissected tumor samples and cell lines was analyzed for PML mutations and loss of heterozygosity (LOH). For some tumor types, the association between PML expression and tumor stage and grade was analyzed. Statistical tests were two-sided. RESULTS: All normal tissues expressed PML protein. PML protein expression was reduced or abolished in prostate adenocarcinomas (63% [95% confidence interval [CI] = 48% to 78%] and 28% [95% CI = 13% to 43%], respectively), colon adenocarcinomas (31% [95% CI = 22% to 40%] and 17% [95% CI = 10% to 24%]), breast carcinomas (21% [95% CI = 8% to 34%] and 31% [95% CI = 16% to 46%]), lung carcinomas (36% [95% CI = 15% to 57%] and 21% [95% = 3% to 39%]), lymphomas (14% [95% CI = 10% to 18%] and 69% [95% CI = 63% to 75%]), CNS tumors (24% [95% CI = 13% to 35%] and 49% [95% CI = 36% to 62%]), and germ cell tumors (36% [95% CI = 24% to 48%] and 48% [95% CI = 36% to 60%]) but not in thyroid or adrenal carcinomas. Loss of PML protein expression was associated with tumor progression in prostate cancer (the progression from prostatic intraepithelial neoplasia to invasive carcinoma was associated with complete PML loss; P<.001), breast cancer (complete PML loss was associated with lymph node metastasis; P =.01), and CNS tumors (complete PML loss was associated with high-grade tumors; P =.003). PML mRNA was expressed in all tumor and cell line samples. The PML gene was rarely mutated and was not subject to LOH. CONCLUSIONS: PML protein expression is frequently lost in human cancers of various histologic origins, and its loss associates with tumor grade and progression in some tumor histotypes.