Background: Currently real time PCR is the most precise method by which to measure gene expression. The method generates a large amount of raw numerical data and processing may notably influence final results. The data processing is based either on standard curves or on PCR efficiency assessment. At the moment, the PCR efficiency approach is preferred in relative PCR whilst the standard curve is often used for absolute PCR. However, there are no barriers to employ standard curves for relative PCR. This article provides an implementation of the standard curve method and discusses its advantages and limitations in relative real time PCR. Results: We designed a procedure for data processing in relative real time PCR. The procedure completely avoids PCR efficiency assessment, minimizes operator involvement and provides a statistical assessment of intra-assay variation. The procedure includes the following steps. (I) Noise is filtered from raw fluorescence readings by smoothing, baseline subtraction and amplitude normalization. (II) The optimal threshold is selected automatically from regression parameters of the standard curve. (III) Crossing points (CPs) are derived directly from coordinates of points where the threshold line crosses fluorescence plots obtained after the noise filtering. (IV) The means and their variances are calculated for CPs in PCR replicas. (V) The final results are derived from the CPs' means. The CPs' variances are traced to results by the law of error propagation. A detailed description and analysis of this data processing is provided. The limitations associated with the use of parametric statistical methods and amplitude normalization are specifically analyzed and found fit to the routine laboratory practice. Different options are discussed for aggregation of data obtained from multiple reference genes. Conclusion: A standard curve based procedure for PCR data processing has been compiled and validated. It illustrates that standard curve design remains a reliable and simple alternative to the PCR-efficiency based calculations in relative real time PCR.

Purpose: To investigate the impact of human epidermal growth factor receptor (HER) 1 and HER2 gene amplification on endocrine therapy responsiveness, a fluorescence in situ hybridization (FISH) study was conducted on tumor samples from 305 postmenopausal patients with stage II and III estrogen receptor (ER) –positive (ER ≥ 10%) breast cancers treated on two independent neoadjuvant endocrine therapy trials.Patients and Methods: FISH analysis focused on HER1 and/or HER2 immunohistochemistry (IHC) -positive patients and a random selection of HER1/2 IHC-negative patients. HER2 FISH status was correlated with response and changes in the proliferation marker Ki67.Results: HER1 was rarely amplified (< 1%), and HER2 amplification was observed in 9.2% of patients. Letrozole response by clinical measurement (71% HER2 FISH positive v 71% HER2 FISH negative), mammogram (44% HER2 FISH positive v 47% HER2 FISH negative), or ultrasound (47% HER2 FISH positive v 54% HER2 FISH negative) was not impaired by HER2 FISH-positive status. In contrast, HER2 FISH-positive tumors showed higher histologic grade (P = .009), higher pretreatment Ki67 (P = .005), and less Ki67 suppression after letrozole when compared with HER2 FISH-negative tumors (P = .0001). Similar observations regarding Ki67 were made in a smaller cohort of tamoxifen-treated tumors.Conclusion: Neoadjuvant letrozole is clinically effective in ER-positive HER2 FISH-positive tumors, indicating sensitivity to short-term estrogen deprivation. However, continued proliferation despite ongoing letrozole or tamoxifen treatment in the majority of ER-positive HER2 FISH-positive samples (88%) could imply therapeutic resistance that may manifest later in the clinical course of the disease. Discordance between clinical and biomarker findings in this study serves to emphasize the need for surrogate end point validation in neoadjuvant endocrine trials through correlation with information on long-term outcomes.

Pediatric aspects are nowadays integrated early in the development process of a new drug. The stronger enforcement to obtain pediatric information by the regulatory agencies in recent years resulted in an increased number of trials in children. Specific guidelines and requirements from, in particular, the European Medicines Agency (EMA) and the Food and Drug Administration (FDA) form the regulatory framework. This review summarizes the regulatory requirements and strategies for pediatric drug development from an industry perspective. It covers pediatric study planning and conduct, considerations for first dose in children, appropriate sampling strategies, and different methods for data generation and analysis to generate knowledge about the pharmacokinetics (PK) and pharmacodynamics (PD) of a drug in children. The role of Modeling and Simulation (M&S) in pediatrics is highlighted—including the regulatory basis—and examples of the use of M&S are illustrated to support pediatric drug development.

The aim of the study was to identify changes in tumour expression profiling associated with short-term therapy of breast cancer patients with letrozole. Microarray analysis was performed on RNA extracted from paired tumour core biopsies taken before and after 14 days of treatment with letrozole (2.5 mg/daily) in 58 patients. Changes in expression profile were identified by three different approaches on the basis of frequency of changes, magnitude of changes and significance analysis of microarray. No single gene was consistently changed by therapy in all cases. Fifty-two genes, however, were downregulated and 36 upregulated in at least 45 of the 58 cases. In terms of quantitative change, 46 genes showed at least a median 1.5-fold change in expression. Significance analysis of microarray identified 62 genes that were significantly changed by therapy (P<0.0001, 56 downregulated and six upregulated). All three approaches showed that greater numbers of genes were downregulated rather than upregulated. Merging data produced a total of 143 genes, which were subject to gene ontology and cluster analysis. The ontology of the 91 downregulated genes showed that they were functionally associated with cell cycle progression, particularly mitosis. In contrast, upregulated genes were associated with organ development, connective tissue extracellular matrix regulation and inflammatory response. Cluster analysis segregated the patients into four groups differing in patterns of gene expression. Genes have been identified which either change markedly or consistently in breast cancer after 14 days treatment with letrozole. These are new important data in understanding letrozole's molecular mechanism of action in breast cancers.

Chronic allograft rejection (CR) is the major cause of failure of long-term graft survival and is so far irreversible. Early prognosis of CR by molecular markers before overt histologic manifestation would be a valuable aid for the optimization of treatment regimens and the design of clinical CR trials. Oligonucleotide microarray-based approaches have proven to be useful for the diagnosis and prognosis of a variety of diseases and were chosen for the unbiased identification of prognostic biomarkers. Renal allograft biopsies were taken at month 6 posttransplantation (PT) from two groups who were, at that time, healthy recipients: one group developed CR at month-12 PT, the other group remained healthy. Gene expression profiles from the two groups at month-6 PT biopsies were analyzed to identify differentially expressed genes with prognostic value for CR development at month 12. A set of 10 genes was identified that showed differential expression profiles between the two patient groups and had a complete separation of the 15% to 85% quantile range for each individual gene. This set of genes was sufficient to allow the correct prediction of the occurrence or nonoccurrence of CR in 15 of 17 (88%) patients using cross-validation (occurrence for a patient was predicted on the basis of the other patients' data only). In addition, a correct prediction could be made that a recipient with a normal biopsy 12 months PT developed CR within the following 6 months. Identified expression patterns seem to be highly prognostic of the development of renal CR.

Purpose Endocrine agents, such as letrozole, are established in the treatment of hormone-dependent breast cancer. However, response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Thus there is a need to identify novel markers predicting for response and to understand molecular mechanisms of resistance. Patients and Methods Sequential tumor biopsies were taken before and after 10 to 14 days of neoadjuvant treatment with letrozole in patients with estrogen receptor–rich breast cancer. Expression profiles on high-density microarray chips were then related to clinical responses as assessed from tumor volume measurements after 3 months of treatment. Results Of 52 patients, 37 (71%) were classified as having a clinical response to letrozole and 15 being clinically resistant. Bioinformatic analysis identified 205 covariables (69 baseline expression, 45 day 14 expression, and 91 change in expression with treatment) which differentiated between clinical responders and nonrespon...