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Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity.

New biomarkers of safety and efficacy are becoming powerful tools in drug development. Their application can be accelerated if a consensus can be reached about their qualification for regulatory applications. This consensus requires a review structure within the US Food and Drug Administration (FDA) that can evaluate qualification data for these biomarkers and determine whether these biomarkers can be qualified. A pilot process and corresponding Biomarker Qualification Review Team have been developed to test how the FDA can work on biomarker qualification.

Drug developers have been using genomic information in drug development strategies for a number of years, but it was unclear how this information would be reviewed by the Food and Drug Administration (FDA). In order to evaluate the regulatory impact of genomic data in current drug development, a workshop was held in May 2002 to discuss aspects surrounding genomic data submission to the FDA (Figure 1).

How can microarray data best be exploited and integrated into the regulatory decision-making process?

How can we encourage the application of novel genomic biomarkers in drug development? A major step in this direction would be a consensus on how to interpret results from measurements of these biomarkers in regulatory submissions. A transparent process for genomic biomarker validation would be of value both for the pharmaceutical industry as well as for regulatory agencies associated with it. A discussion on process map proposals for genomic biomarker validation can help with drafting of guidance documents for this process.

Background The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. Results We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. Conclusion Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control.

Over the past five years, denaturing high-performance liquid chromatography (DHPLC) has emerged as one of the most versatile technologies for the analysis of genetic variations. With the benefit of novel polymer chemistries used for separation, the accuracy, sensitivity, and the throughput of DHPLC for DNA and RNA analysis have greatly improved. DHPLC has been adopted in many laboratories for the screening of mutations and single-nucleotide polymorphisms (SNPs). The ability of DHPLC to detect known and unknown mutations simultaneously has put this technology at the forefront of genetic analysis for a wide variety of diseases. In addition, the high sensitivity of DHPLC combined with the accuracy of the heteroduplex analysis has allowed the development of applications beyond the scope of traditional sequencing or genotyping, e.g., the early detection of cancer. This article reviews the methods, which made DHPLC a widely used tool for diagnosis in molecular genetics and pharmacogenetics. The article provides an overview of current applications in these fields and points to novel applications in areas like epigenetics and the analysis of heteroplasmic mitochondrial DNA, in which DHPLC is becoming the leading technology.

One mechanism by which cells adapt to environmental changes is by altering gene expression. Here, we have used cDNA microarrays to identify genes whose expression is altered by exposure to the environmental contaminant 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD). The goal of our study was to enhance our understanding of toxicity mediated through the pathway by which TCDD stimulates gene expression. To model this toxicity response, we exposed human hepatoma (HepG2) cells to TCDD (10 nM for 18 h) and analyzed mRNA by two-color fluorescent hybridization to cDNA sequences immobilized on glass microscope slides (2.5×7.5 cm) covering a surface area of 2.25 cm 2 . We analyzed approximately one-third of the genes expressed in HepG2 cells and found that TCDD up- or down-regulates 112 genes two-fold or more. Most changes are relatively subtle (two- to four-fold). We verified the regulation of protooncogene cot, XMP, and human enhancer of filamentation-1 (HEF1), genes involved in cellular proliferation, as well as metallothionein, plasminogen activator inhibitor (PAI1), and HM74, genes involved in cellular signaling and regeneration. To characterize the response in more detail, we performed time-course, dose-dependence studies, and cycloheximide experiments. We observed direct and indirect responses to TCDD implying that adaptation to TCDD (and other related environmental stimuli) is substantially more complex than we previously realized.

Background: Tamoxifen is a selective estrogen receptor modulator (SERM) commonly used to treat and prevent estrogen-receptor-positive (ERP) breast cancer. However, despite its established efficacy, recent studies indicate that 1 in 2 patients will discontinue use of the drug prior to completing the recommended five-year treatment cycle. The alleviation of unpleasant side effects through personalized targeting of tamoxifen dose and, as appropriate, concomitant administration of a CYP2D6 inhibitor could increase adherence and increase the likelihood that patients will receive the amount of the drug needed to protect them against disease onset and/or recurrence. Materials and Methods: A retrospective cohort study was implemented to assess whether overlapping therapy with highdose tamoxifen and CYP2D6 inhibitors influence medication adherence during the first 540 days of therapy. Subjects (N = 17,242) were identified in an integrated medical and pharmacy claims database and selected for inclusion in the study if they 1) filled a new tamoxifen prescription between 7/1/2008 and 6/30/2009 and 2) were continuously eligible to receive pharmacy benefits during the 6 months preceding and 12 months after initiation of therapy. Eligible participants were then cross-classified according to tamoxifen dose (NORMAL, HIGH) and CYP2D6 inhibitor status (NO, YES), and a Cox regression model was fitted to the data to obtain covariate-adjusted hazard ratios (HR) and 95% confidence intervals for each treatment combination relative to the HIGH/NO group. Results: The lowest and highest hazard ratios were observed in the NORMAL/YES [HR = 0.924 (0.88, 0.97)] and HIGH/NO [HR = 2.33 (2.07, 2.62)] categories. Moreover, the risk of discontinuation was significantly reduced when high-dose tamoxifen was administered in concert with a CYP2D6 inhibitor [HR = 1.31 (0.953, 1.802)]. Discussion: These study suggests that joint treatment with high-dose tamoxifen and a CYP2D6 inhibitor may improve tamoxifen adherence in breast cancer patients. The findings also highlight the need for 1) education and research regarding tamoxifen dosing and 2) careful consideration for when–and under what circumstances–concomitant medications should be prescribed to enhance patient tolerance of tamoxifen-related negative symptoms. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P4-02-15.

558 Background: Tamoxifen is a selective estrogen receptor modulator (SERM) that is commonly used to treat breast cancer. However, despite its established efficacy, recent studies indicate that 1) more than 50 percent of individuals will discontinue treatment prior to completing the recommended five-year therapeutic regimen and 2) the likelihood of discontinuation is moderated by the presence of polymorphisms in the gene encoding cytochrome P450 2D6 (CYP2D6), the enzyme responsible for metabolizing tamoxifen into its active form. Methods: We measured tamoxifen persistency rates in a cohort of breast cancer patients to test the hypothesis that tamoxifen adherence is modified by the dose administered and concomitant use of anti-depressant (SSRI) drugs known to interfere with CYP2D6 metabolism. Study subjects (N = 12,742) were identified in a large transactional claims database, cross-classified by tamoxifen dose (HIGH, NORMAL) and SSRI status (YES, NO), and followed for 360 days after initiation of therapy....

7077 Background: Recommendations for baseline and quarterly measurement of the BCR-ABL fusion transcript to monitor imatinib response in patients with chronic myelogenous leukemia (CML) were formally introduced in October 2006, and have been incorporated into nationally recognized treatment guidelines. Methods: To assess BCR-ABL testing rates, we conducted a retrospective cohort analysis using a >10 million-member health plan database comprised of integrated pharmacy and medical claims. The study cohort was defined as patients with an index imatinib pharmacy claim from July 1, 2006, to December 31, 2006, who had a CML diagnosis (ICD-9 205.1X; N = 504), and a minimum of 3 months continuous follow-up by claims history (N = 465). Over a period of up to four quarters from the index imatinib prescription date, BCR-ABL testing in each quarter was assessed by the presence of any of a set of 19 CPT-4 codes. BCR-ABL testing rates in each individual quarter and in consecutive quarters were measured. Results: The overall study cohort was 57% male; mean (±SD) age was 52±14 y/o, with 26% 19–44 y/o, 57% 45–64 y/o, and 15% ≥65 y/o. Median duration of f/u was 559 days (interquartile range 302–628 days), and a cohort of 359 patients had 4 quarters of f/u. At least one BCR-ABL test was recorded in 60% of patients. The rate of first quarter BCR-ABL testing was 40%, and remained at 42%-43% in quarters 2 thru 4. Consecutive quarterly testing rates were 24% through the second quarter, 18% through the third quarter, and 14% through the fourth quarter. Conclusions: In this retrospective claims database analysis, only 14% of a large cohort of CML patients treated with imatinib had BCR-ABL testing recorded in each of 4 consecutive quarters. Inadequate compliance with recommended BCR-ABL testing can delay treatment decisions, and may be associated with poor clinical outcome. [Table: see text]

14696 Background: Epidermal growth factor receptor (EGFR) is an attractive target for anti-cancer agents, which have shown activity against various types of tumors. Skin/eye toxicity is a class adverse effect associated with anti-EGFR therapy. This project aims to determine whether skin/eye toxicity can be used as a biomarker for dose selection of anti-EGFR agents. Methods: Extract information on dose and skin/eye toxicity from datasets of FDA approved anti-EGFR agents; Tabulate the percentage of subjects with skin/eye toxicity and perform sigmoidal Emax modeling to estimate the dose associated with maximum skin/eye toxicity; Compare the model estimated dose and the label recommended dose; Determine the capability using skin/eye toxicity as a measure for dose selection for anti-EGFR agents. Results: Skin/eye toxicity data were obtained from all six FDA approved anti-EGFR agents. The sigmoidal Emax model fit the data from trials of Drug A, Drug B and Drug C well, and the predicted dose matched the label re...

Background Microarray-based measurement of mRNA abundance assumes a linear relationship between the fluorescence intensity and the dye concentration. In reality, however, the calibration curve can be nonlinear. Results By scanning a microarray scanner calibration slide containing known concentrations of fluorescent dyes under 18 PMT gains, we were able to evaluate the differences in calibration characteristics of Cy5 and Cy3. First, the calibration curve for the same dye under the same PMT gain is nonlinear at both the high and low intensity ends. Second, the degree of nonlinearity of the calibration curve depends on the PMT gain. Third, the two PMTs (for Cy5 and Cy3) behave differently even under the same gain. Fourth, the background intensity for the Cy3 channel is higher than that for the Cy5 channel. The impact of such characteristics on the accuracy and reproducibility of measured mRNA abundance and the calculated ratios was demonstrated. Combined with simulation results, we provided explanations to the existence of ratio underestimation, intensity-dependence of ratio bias, and anti-correlation of ratios in dye-swap replicates. We further demonstrated that although Lowess normalization effectively eliminates the intensity-dependence of ratio bias, the systematic deviation from true ratios largely remained. A method of calculating ratios based on concentrations estimated from the calibration curves was proposed for correcting ratio bias. Conclusion It is preferable to scan microarray slides at fixed, optimal gain settings under which the linearity between concentration and intensity is maximized. Although normalization methods improve reproducibility of microarray measurements, they appear less effective in improving accuracy.