AMG 757, a Half-Life Extended, DLL3-Targeted Bispecific T-Cell Engager, Shows High Potency and Sensitivity in Preclinical Models of Small-Cell Lung Cancer.

Purpose: Small-cell lung cancer (SCLC) is an aggressive neuroendocrine tumor with a high relapse rate, limited therapeutic options, and poor prognosis. We investigated the antitumor activity of AMG 757, a half-life extended bispecific T-cell engager molecule targeting delta-like ligand 3 (DLL3)-a target that is selectively expressed in SCLC tumors, but with minimal normal tissue expression.

Experimental Design: AMG 757 efficacy was evaluated in SCLC cell lines and in orthotopic and patient-derived xenograft (PDX) mouse SCLC models.

MRGPRX2 activation as a rapid, high-throughput mechanistic-based approach for detecting peptide-mediated human mast cell degranulation liabilities.

Mast cells play key roles in allergy, anaphylaxis/anaphylactoid reactions, and defense against pathogens/toxins. These cells contain cytoplasmic granules with a wide spectrum of pleotropic mediators that are released upon activation. While mast cell degranulation (MCD) occurs upon clustering of the IgE receptor bound to IgE and antigen, MCD is also triggered through non-IgE-mediated mechanisms, one of which is via Mas-related G protein-coupled receptor X2 (MRGPRX2).

Oxopyrido[2,3-d]pyrimidines as Covalent L858R/T790M Mutant Selective Epidermal Growth Factor Receptor (EGFR) Inhibitors.

In nonsmall cell lung cancer (NSCLC), the threonine(790)-methionine(790) (T790M) point mutation of EGFR kinase is one of the leading causes of acquired resistance to the first generation tyrosine kinase inhibitors (TKIs), such as gefitinib and erlotinib. Herein, we describe the optimization of a series of 7-oxopyrido[2,3-d]pyrimidinyl-derived irreversible inhibitors of EGFR kinase. This led to the discovery of compound 24 which potently inhibits gefitinib-resistant EGFR(L858R,T790M) with 100-fold selectivity over wild-type EGFR.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods.

Dynamic zebrafish interactome reveals transcriptional mechanisms of dioxin toxicity.

Background: In order to generate hypotheses regarding the mechanisms by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin) causes toxicity, we analyzed global gene expression changes in developing zebrafish embryos exposed to this potent toxicant in the context of a dynamic gene network. For this purpose, we also computationally inferred a zebrafish (Danio rerio) interactome based on orthologs and interaction data from other eukaryotes.

Methodology/principal Findings: Using novel computational tools to analyze this interactome, we distinguished between dioxin-dependent and dioxin-independent interactions between proteins, and tracked the temporal propagation of dioxin-dependent transcriptional changes from a few genes that were altered initially, to large groups of biologically coherent genes at later times.

Multimodal regulation of E2F1 gene expression by progestins.

An analysis of mRNA expression in T47D breast cancer cells treated with the synthetic progestin R5020 revealed a subset of progesterone receptor (PR) target genes that are enriched for E2F binding sites. Following up on this observation, we determined that PR-B acts in both direct and indirect manners to positively upregulate E2F1 expression in T47D cells. The direct effects of PR on E2F1 expression were confirmed by chromatin immunoprecipitation (ChIP) analysis, which indicated that the agonist-bound receptor was recruited to several enhancer elements proximal to the E2F1 transcript.

Application of microarray-based analysis of gene expression in the field of toxicogenomics.

The field of toxicogenomics, which is becoming an important sub-discipline of toxicology, resulted from the natural convergence of the field of conventional toxicological research and the emergent field of functional genomics. One technology that has played a significant role in the field of toxicogenomics (in addition to many others) is the gene expression microarray. In this chapter, the authors provide an example of the application of gene expression microarrays to the field of toxicogenomics by detailing the strategy that was used for obtaining, analyzing, and interpreting gene expression data generated from RNA isolated from the liver of toxicant-exposed rats.

Glucocorticoids with different chemical structures but similar glucocorticoid receptor potency regulate subsets of common and unique genes in human trabecular meshwork cells.

Background: In addition to their well-documented ocular therapeutic effects, glucocorticoids (GCs) can cause sight-threatening side-effects including ocular hypertension presumably via morphological and biochemical changes in trabecular meshwork (TM) cells. In the present study, we directly compared the glucocorticoid receptor (GR) potency for dexamethasone (DEX), fluocinolone acetonide (FA) and triamcinolone acetonide (TA), examined the expression of known GRalpha and GRbeta isoforms, and used gene expression microarrays to compare the effects of DEX, FA, and TA on the complete transcriptome in two primary human TM cell lines.

Methods: GR binding affinity for DEX, FA, and TA was measured by a cell-free competitive radio-labeled GR binding assay.

Transcriptional effects of transfection: the potential for misinterpretation of gene expression data generated from transiently transfected cells.

Transfection is used to introduce a gene of interest into a cell. To interpret the downstream results, understanding which effects are the true biological responses to the gene and which, if any, are off-target effects can be difficult. In order to discriminate true biological effects from off-target effects, we transfected a breast cancer cell line, MCF7, with a vector encoding either a reporter gene or the identical vector without the reporter gene insert.

A newly-developed community microarray resource for transcriptome profiling in Brassica species enables the confirmation of Brassica-specific expressed sequences.

Background: The Brassica species include an important group of crops and provide opportunities for studying the evolutionary consequences of polyploidy. They are related to Arabidopsis thaliana, for which the first complete plant genome sequence was obtained and their genomes show extensive, although imperfect, conserved synteny with that of A. thaliana.

Comparative epigenomics of human and mouse mammary tumors.

Gene silencing by aberrant epigenetic chromatin alteration is a well-recognized event contributing to tumorigenesis. Although genetically engineered tumor-prone mouse models have proven a powerful tool in understanding many aspects of carcinogenesis, to date few studies have focused on epigenetic alterations in mouse tumors. To uncover epigenetically silenced tumor suppressor genes (TSGs) in mouse mammary tumor cells, we conducted initial genome-wide screening by combining the treatment of cultured cells with the DNA demethylating drug 5-aza-2'-deoxycytidine (5-azadC) and the histone deacetylase inhibitor trichostatin A (TSA) with expression microarray.

Herpes simplex virus-mediated expression of Pax3 and MyoD in embryoid bodies results in lineage-Related alterations in gene expression profiles.

The ability of embryonic stem cells to develop into multiple cell lineages provides a powerful resource for tissue repair and regeneration. Gene transfer offers a means to dissect the complex events in lineage determination but is limited by current delivery systems. We designed a high-efficiency replication-defective herpes simplex virus gene transfer vector (JDbetabeta) for robust and transient expression of the transcription factors Pax3 and MyoD, which are known to be involved in skeletal muscle differentiation.

Gene expression response in target organ and whole blood varies as a function of target organ injury phenotype.

This report details the standardized experimental design and the different data streams that were collected (histopathology, clinical chemistry, hematology and gene expression from the target tissue (liver) and a bio-available tissue (blood)) after treatment with eight known hepatotoxicants (at multiple time points and doses with multiple biological replicates). The results of the study demonstrate the classification of histopathological differences, likely reflecting differences in mechanisms of cell-specific toxicity, using either liver tissue or blood transcriptomic data.

Multicenter study of acetaminophen hepatotoxicity reveals the importance of biological endpoints in genomic analyses.

Gene expression profiling is a widely used technique with data from the majority of published microarray studies being publicly available. These data are being used for meta-analyses and in silico discovery; however, the comparability of toxicogenomic data generated in multiple laboratories has not been critically evaluated. Using the power of prospective multilaboratory investigations, seven centers individually conducted a common toxicogenomics experiment designed to advance understanding of molecular pathways perturbed in liver by an acute toxic dose of N-acetyl-p-aminophenol (APAP) and to uncover reproducible genomic signatures of APAP-induced toxicity.

Identification of primary transcriptional regulation of cell cycle-regulated genes upon DNA damage.

The changes in global gene expression in response to DNA damage may derive from either direct induction or repression by transcriptional regulation or indirectly by synchronization of cells to specific cell cycle phases, such as G1 or G2. We developed a model that successfully estimated the expression levels of >400 cell cycle-regulated genes in normal human fibroblasts based on the proportions of cells in each phase of the cell cycle. By isolating effects on the gene expression associated with the cell cycle phase redistribution after genotoxin treatment, the direct transcriptional target genes were distinguished from genes for which expression changed secondary to cell synchronization.

Developmental exposure to diethylstilbestrol alters uterine gene expression that may be associated with uterine neoplasia later in life.

Previously, we described a mouse model where the well-known reproductive carcinogen with estrogenic activity, diethylstilbestrol (DES), caused uterine adenocarcinoma following neonatal treatment. Tumor incidence was dose-dependent reaching >90% by 18 mo following neonatal treatment with 1000 microg/kg/d of DES. These tumors followed the initiation/promotion model of hormonal carcinogenesis with developmental exposure as initiator, and exposure to ovarian hormones at puberty as the promoter.

Hepatic transcript levels for genes coding for enzymes associated with xenobiotic metabolism are altered with age.

Metabolism studies are crucial for data interpretation from rodent toxicity and carcinogenicity studies. Metabolism studies are usually conducted in 6 to 8 week old rodents. Long-term studies often continue beyond 100 weeks of age.

Application of visualization tools to the analysis of histopathological data enhances biological insight and interpretation.

Gene expression profiling, metabolomic screens, and other high-dimensional methods have become an integral part of many biological investigations. To facilitate interpretation of these data, it is important to have detailed phenotypic data--including histopathology--to which these data can be associated, or anchored. However, as the amount of phenotypic data increases, associations within and across these data can be difficult to visualize and interpret.

Receptor-selective coactivators as tools to define the biology of specific receptor-coactivator pairs.

In the absence of specific high-affinity agonists and antagonists, it has been difficult to define the target genes and biological responses attributable to many of the orphan nuclear receptors (ONRs). Indeed, it appears that many members of this receptor superfamily are not regulated by classical small molecules but rather their activity is controlled by interacting cofactors. Motivated by this finding, we have developed an approach to genetically isolate specific receptor-cofactor pairs in cells, allowing us to define the biological responses attributable to each complex.

Rat toxicogenomic study reveals analytical consistency across microarray platforms.

To validate and extend the findings of the MicroArray Quality Control (MAQC) project, a biologically relevant toxicogenomics data set was generated using 36 RNA samples from rats treated with three chemicals (aristolochic acid, riddelliine and comfrey) and each sample was hybridized to four microarray platforms. The MAQC project assessed concordance in intersite and cross-platform comparisons and the impact of gene selection methods on the reproducibility of profiling data in terms of differentially expressed genes using distinct reference RNA samples. The real-world toxicogenomic data set reported here showed high concordance in intersite and cross-platform comparisons.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues.

Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project.

Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms.

Profiles of global gene expression in ionizing-radiation-damaged human diploid fibroblasts reveal synchronization behind the G1 checkpoint in a G0-like state of quiescence.

Cell cycle arrest and stereotypic transcriptional responses to DNA damage induced by ionizing radiation (IR) were quantified in telomerase-expressing human diploid fibroblasts. Analysis of cytotoxicity demonstrated that 1.5 Gy IR inactivated colony formation by 40-45% in three fibroblast lines; this dose was used in all subsequent analyses.

Temporal correlation of pathology and DNA damage with gene expression in a choline-deficient model of rat liver injury.

Hepatocellular carcinoma (HCC) is the terminal event in chronic liver diseases with repeated cycles of cellular injury and regeneration. Although much is known about the cellular pathogenesis and etiological agents leading to HCC, the molecular events are not well understood. The choline-deficient (CD) model of rodent HCC involves the consecutive emergence of a fatty liver, apoptosis, compensatory proliferation, fibrosis, and cirrhosis that is markedly similar to the sequence of events typified by human HCC.

Standardizing global gene expression analysis between laboratories and across platforms.

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories.