KRAS mutational subtype and copy number predict in vitro response of human pancreatic cancer cell lines to MEK inhibition.

BACKGROUND: To study the molecular mechanism regulating sensitivity to MEK inhibition in pancreatic cancer cell lines. METHODS: A growth inhibition assay determined sensitivity to MEK162 in a panel of 29 pancreatic cancer cell lines. For the same panel, KRAS mutational status and copy-number variation (CNV) was determine using PCR, array CGH and FISH. Two sensitive and two resistant cell lines were further interrogated for difference in baseline and MEK162-induced gene expression, as well as signal transduction using microarray and western blotting. Cell cycle and apoptosis analysis was measured by flow cytometry. RESULTS: We report a strong correlation between both specific KRAS mutational subtype and CNV, and sensitivity to MEK inhibition. Cell lines with a KRAS (V12) mutation and KRAS gains or loss (n=7) are ∼10 times more resistant than those having neither a KRAS (V12) mutation nor KRAS CNV (n=14). Significant differences in baseline and MEK162-induced gene expression exist between the sensitive and resistant lines, especially in genes involved in RAS, EGF receptor and PI3K pathways. This was further supported by difference in signal transduction. MEK 162 blocked ERK1/2, as well as inhibited PI3K and S6 and increased p27KIP1 levels in the sensitive lines. CONCLUSIONS: Given the potency of MEK162, it may be a promising new therapy for patients with pancreatic cancer and KRAS mutational subtypes, and CNV may serve as important biomarkers for selecting patients that benefit from MEK-targeting based on these preclinical data.

Population pharmacokinetics/toxicodynamics (PK/TD) relationship of SAM486A in phase I studies in patients with advanced cancers.

SAM486A (previously termed CGP 48664), a potent inhibitor of S-adenosylmethionine decarboxylase, is under clinical development for the treatment of advanced refractory malignancies. Hematological toxicity manifested by dose-dependent neutropenia has been observed in phase I studies. Population methods were used to investigate pharmacokinetics (PK) as a prognostic factor for safety end point (hematological toxicity) in patients with advanced cancers. SAM486A plasma concentrations and neutrophil counts were collected from three ascending-dose tolerability and PK studies (study 1: single 5-day continuous intravenous (IV) infusion with doses ranging from 24-700 mg/m2/cycle; study 2: 10-minute to 3-hour IV infusion once weekly with doses ranging from 16-325 mg/m2/week; study 3: 1-hour IV infusion once daily for 5 days with doses ranging from 3.6-202.8 mg/m2/day). The PK of SAM486A were best estimated by a population linear three-compartment model with NONMEM (version 5) using data from 9 patients in studies 1 through 3. The population pharmacokinetic parameters (SD) were CL = 6.2 (0.4) l/h/m2, Q2 = 15.4 (1.5) l/h/m2, Q3 = 33.6 (5.3) l/h/m2, V1 = 9.5 (1.6) l/m2, V2 = 672 (52) l/m2, and V3 = 39.9 (8.3) l/m2, and the corresponding intersubject variability was 45.4%, 74.0%, 85.3%, 80.1%, 37.0%, and 103%, respectively, where CL is total body clearance, Q2 and Q3 are intercompartmental clearances, and V1, V2, and V3 are the volumes of distribution in central and peripheral compartments, respectively. The intrasubject variability was 24.0%. The cumulative AUC before the onset of neutrophil nadir count (AUC) and the duration of exposure over threshold SAM486A concentrations in the range of 0.05 to 0.1 microM based on Bayesian PK parameter estimates significantly correlated with absolute neutrophil count nadir (< 5 x 10(9)/l). AUC showed the best correlation (R2 = 0.72) with absolute neutrophil count nadir by an inhibitory sigmoid Emax model and also correlated with percent decrease in neutrophil count from baseline to nadir by a simple Emax model (R2 = 0.53). Logistic regression analysis indicated that AUC and the duration of exposure over 0.05 to 0.1 microM, but not Cmax, were strong predictors of grade 4 neutropenia (< 0.5 x 10(9)/l). Drug exposure parameters such as AUC derived from population analysis may be used clinically as a useful predictor of drug-induced neutropenia.