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Background: Clinical trials have indicated a benefit of adjuvant chemotherapy for patients with stage IB, II, or IIIA--but not stage IA--non-small-cell lung cancer (NSCLC). This classification scheme is probably an imprecise predictor of the prognosis of an individual patient. Indeed, approximately 25 percent of patients with stage IA disease have a recurrence after surgery, suggesting the need to identify patients in this subgroup for more effective therapy.Methods: We identified gene-expression profiles that predicted the risk of recurrence in a cohort of 89 patients with early-stage NSCLC (the lung metagene model). We evaluated the predictor in two independent groups of 25 patients from the American College of Surgeons Oncology Group (ACOSOG) Z0030 study and 84 patients from the Cancer and Leukemia Group B (CALGB) 9761 study.Results: The lung metagene model predicted recurrence for individual patients significantly better than did clinical prognostic factors and was consistent across all early stages of NSCLC. Applied to the cohorts from the ACOSOG Z0030 trial and the CALGB 9761 trial, the lung metagene model had an overall predictive accuracy of 72 percent and 79 percent, respectively. The predictor also identified a subgroup of patients with stage IA disease who were at high risk for recurrence and who might be best treated by adjuvant chemotherapy.Conclusions: The lung metagene model provides a potential mechanism to refine the estimation of a patient's risk of disease recurrence and, in principle, to alter decisions regarding the use of adjuvant chemotherapy in early-stage NSCLC. [ABSTRACT FROM AUTHOR]

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast trnL -P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data, trnL metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall, trnL metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.

Objective: To design and establish a prospective biospecimen repository that integrates multi-omics assays with clinical data to study mechanisms of controlled injury and healing., Background: Elective surgery is an opportunity to understand both the systemic and focal responses accompanying controlled and well-characterized injury to the human body. The overarching goal of this ongoing project is to define stereotypical responses to surgical injury, with the translational purpose of identifying targetable pathways involved in healing and resilience, and variations indicative of aberrant peri-operative outcomes., Methods: Clinical data from the electronic medical record combined with large-scale biological data sets derived from blood, urine, fecal matter, and tissue samples are collected prospectively through the peri-operative period on patients undergoing 14 surgeries chosen to represent a range of injury locations and intensities. Specimens are subjected to genomic, transcriptomic, proteomic, and metabolomic assays to describe their genetic, metabolic, immunologic, and microbiome profiles, providing a multidimensional landscape of the human response to injury., Results: The highly multiplexed data generated includes changes in over 28,000 mRNA transcripts, 100 plasma metabolites, 200 urine metabolites, and 400 proteins over the longitudinal course of surgery and recovery. In our initial pilot dataset, we demonstrate the feasibility of collecting high quality multi-omic data at pre- and postoperative time points and are already seeing evidence of physiologic perturbation between timepoints., Conclusions: This repository allows for longitudinal, state-of-the-art geno-mic, transcriptomic, proteomic, metabolomic, immunologic, and clinical data collection and provides a rich and stable infrastructure on which to fuel further biomedical discovery., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: The purpose of this study was to establish a biorepository of clinical, metabolomic, and microbiome samples from adolescents with obesity as they undergo lifestyle modification., Methods: A total of 223 adolescents aged 10 to 18 years with BMI ≥95th percentile were enrolled, along with 71 healthy weight participants. Clinical data, fasting serum, and fecal samples were collected at repeated intervals over 6 months. Herein, the study design, data collection methods, and interim analysis-including targeted serum metabolite measurements and fecal 16S ribosomal RNA gene amplicon sequencing among adolescents with obesity (n = 27) and healthy weight controls (n = 27)-are presented., Results: Adolescents with obesity have higher serum alanine aminotransferase, C-reactive protein, and glycated hemoglobin, and they have lower high-density lipoprotein cholesterol when compared with healthy weight controls. Metabolomics revealed differences in branched-chain amino acid-related metabolites. Also observed was a differential abundance of specific microbial taxa and lower species diversity among adolescents with obesity when compared with the healthy weight group., Conclusions: The Pediatric Metabolism and Microbiome Study (POMMS) biorepository is available as a shared resource. Early findings suggest evidence of a metabolic signature of obesity unique to adolescents, along with confirmation of previously reported findings that describe metabolic and microbiome markers of obesity., (© 2021 The Obesity Society.)

Objectives: Despite disparities in lung cancer incidence and mortality, the molecular landscape of lung cancer in patients of African ancestry remains underexplored, and race-related differences in RNA splicing remain unexplored., Materials and Methods: We identified differentially spliced genes (DSGs) and differentially expressed genes (DEGs) in biobanked lung squamous cell carcinoma (LUSC) between patients of West African and European ancestry, using ancestral genotyping and Affymetrix Clariom D array. DSGs and DEGs were validated independently using the National Cancer Institute Genomic Data Commons. Associated biological processes, overlapping canonical pathways, enriched gene sets, and cancer relevance were identified using Gene Ontology Consortium, Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, and CancerMine, respectively. Association with LUSC survival was conducted using The Cancer Genome Atlas., Results: 4,829 DSGs and 267 DEGs were identified, including novel targets in NSCLC as well as genes identified previously to have relevance to NSCLC. RNA splicing events within 3 DSGs as well as 1 DEG were validated in the independent cohort. 853 DSGs and 29 DEGs have been implicated as potential drivers, oncogenes and/or tumor suppressor genes. Biological processes enriched among DSGs and DEGs included metabolic process, biological regulation, and multicellular organismal process and, among DSGs, ion transport. Overlapping canonical pathways among DSGs included neuronal signaling pathways and, among DEGs, cell metabolism involving biosynthesis. Gene sets enriched among DSGs included KRAS Signaling, UV Response, E2 F Targets, Glycolysis, and Coagulation. 355 RNA splicing events within DSGs and 18 DEGs show potential association with LUSC patient survival., Conclusion: These DSGs and DEGs, which show potential biological and clinical relevance, could have the ability to drive novel biomarker and therapeutic development to mitigate LUSC disparities., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Pediatric obesity remains a public health burden and continues to increase in prevalence. The gut microbiota plays a causal role in obesity and is a promising therapeutic target. Specifically, the microbial production of short-chain fatty acids (SCFA) from the fermentation of otherwise indigestible dietary carbohydrates may protect against pediatric obesity and metabolic syndrome. Still, it has not been demonstrated that therapies involving microbiota-targeting carbohydrates, known as prebiotics, will enhance gut bacterial SCFA production in children and adolescents with obesity (age, 10 to 18 years old). Here, we used an in vitro system to examine the SCFA production by fecal microbiota from 17 children with obesity when exposed to five different commercially available over-the-counter (OTC) prebiotic supplements. We found microbiota from all 17 patients actively metabolized most prebiotics. Still, supplements varied in their acidogenic potential. Significant interdonor variation also existed in SCFA production, which 16S rRNA sequencing supported as being associated with differences in the host microbiota composition. Last, we found that neither fecal SCFA concentration, microbiota SCFA production capacity, nor markers of obesity positively correlated with one another. Together, these in vitro findings suggest the hypothesis that OTC prebiotic supplements may be unequal in their ability to stimulate SCFA production in children and adolescents with obesity and that the most acidogenic prebiotic may differ across individuals. IMPORTANCE Pediatric obesity remains a major public health problem in the United States, where 17% of children and adolescents are obese, and rates of pediatric "severe obesity" are increasing. Children and adolescents with obesity face higher health risks, and noninvasive therapies for pediatric obesity often have limited success. The human gut microbiome has been implicated in adult obesity, and microbiota-directed therapies can aid weight loss in adults with obesity. However, less is known about the microbiome in pediatric obesity, and microbiota-directed therapies are understudied in children and adolescents. Our research has two important findings: (i) dietary prebiotics (fiber) result in the microbiota from adolescents with obesity producing more SCFA, and (ii) the effectiveness of each prebiotic is donor dependent. Together, these findings suggest that prebiotic supplements could help children and adolescents with obesity, but that these therapies may not be "one size fits all.", (Copyright © 2020 Holmes et al.)

Background: The prevalence of child and adolescent obesity and severe obesity continues to increase despite decades of policy and research aimed at prevention. Obesity strongly predicts cardiovascular and metabolic disease risk; both begin in childhood. Children who receive intensive behavioral interventions can reduce body mass index (BMI) and reverse disease risk. However, delivering these interventions with fidelity at scale remains a challenge. Clinic-community partnerships offer a promising strategy to provide high-quality clinical care and deliver behavioral treatment in local park and recreation settings. The Hearts & Parks study has three broad objectives: (1) evaluate the effectiveness of the clinic-community model for the treatment of child obesity, (2) define microbiome and metabolomic signatures of obesity and response to lifestyle change, and (3) inform the implementation of similar models in clinical systems., Methods: Methods are designed for a pragmatic randomized, controlled clinical trial (n = 270) to test the effectiveness of an integrated clinic-community child obesity intervention as compared with usual care. We are powered to detect a difference in body mass index (BMI) between groups at 6 months, with follow up to 12 months. Secondary outcomes include changes in biomarkers for cardiovascular disease, psychosocial risk, and quality of life. Through collection of biospecimens (serum and stool), additional exploratory outcomes include microbiome and metabolomics biomarkers of response to lifestyle modification., Discussion: We present the study design, enrollment strategy, and intervention details for a randomized clinical trial to measure the effectiveness of a clinic-community child obesity treatment intervention. This study will inform a critical area in child obesity and cardiovascular risk research-defining outcomes, implementation feasibility, and identifying potential molecular mechanisms of treatment response., Clinical Trial Registration: NCT03339440 .

Purpose: We have previously reported that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion patterns obtained from locally advanced breast cancer (LABC) patients prior to neoadjuvant therapy predicted pathologic clinical response. Genomic analyses were also independently conducted on the same patient population. This retrospective study was performed to test two hypotheses: (1) gene expression profiles are associated with DCE-MRI perfusion patterns, and (2) association between long-term overall survival data and gene expression profiles can lead to the identification of novel predictive biomarkers., Methods: We utilised RNA microarray and DCE-MRI data from 47 LABC patients, including 13 inflammatory breast cancer (IBC) patients. Association between gene expression profile and DCE-MRI perfusion patterns (centrifugal and centripetal) was determined by Wilcoxon rank sum test. Association between gene expression level and survival was assessed using a Cox rank score test. Additional genomic analysis of the IBC subset was conducted, with a period of follow-up of up to 11 years. Associations between gene expression and overall survival were further assessed in The Cancer Genome Atlas Data Portal., Results: Differences in gene expression profiles were seen between centrifugal and centripetal perfusion patterns in the sulphotransferase family, cytosolic, 1 A, phenol-preferring, members 1 and 2 (SULT1A1, SULT1A2), poly (ADP-ribose) polymerase, member 6 (PARP6), and metastasis tumour antigen1 (MTA1). In the IBC subset our analyses demonstrated that differential expression of 45 genes was associated with long-term survival., Conclusions: Here we have demonstrated an association between DCE-MRI perfusion patterns and gene expression profiles. In addition we have reported on candidate prognostic biomarkers in IBC patients, with some of the genes being significantly associated with survival in IBC and LABC.

Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

Background: Gene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, thus potentially identifying therapeutic options for subgroups of patients. To facilitate broad use, including in a clinical setting, the ability to generate data from formalin-fixed, paraffin-embedded (FFPE) tissues is essential., Methods: Patterns of pathway activity in matched fresh-frozen and FFPE xenograft tumor samples were generated using the MessageAmp Premier methodology in combination with assays using Affymetrix arrays. Results generated were compared with those obtained from fresh-frozen samples using a standard Affymetrix assay. In addition, gene expression data from patient matched fresh-frozen and FFPE melanomas were also utilized to evaluate the consistency of predictions of oncogenic signaling pathway status., Results: Significant correlation was observed between pathway activity predictions from paired fresh-frozen and FFPE xenograft tumor samples. In addition, significant concordance of pathway activity predictions was also observed between patient matched fresh-frozen and FFPE melanomas., Conclusions: Reliable and consistent predictions of oncogenic pathway activities can be obtained from FFPE tumor tissue samples. The ability to reliably utilize FFPE patient tumor tissue samples for genomic analyses will lead to a better understanding of the biology of disease progression and, in the clinical setting, will provide tools to guide the choice of therapeutics to those most likely to be effective in treating a patient's disease.

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.

Purpose: Identifying sources of variation in expression microarray data and the effect of variance in gene expression measurements on complex predictive and diagnostic models is essential when translating microarray-based experimental approaches into clinical assays. The technical reproducibility of microarray platforms is well established. Here, we investigate the additional impact of intratumor heterogeneity, a largely unstudied component of variance, on the performance of several microarray-based assays in breast cancer., Patients and Methods: Genome-wide expression profiling was performed on 50 core needle biopsies from 18 breast cancer patients using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Global profiles of expression were characterized using unsupervised clustering methods and variance components models. Array-based measures of estrogen receptor (ER) and progesterone receptor (PR) status were compared with immunohistochemistry. The precision of genomic predictors of ER pathway status, recurrence risk, and sensitivity to chemotherapeutics was evaluated by interclass correlation., Results: Global patterns of gene expression demonstrated that intratumor variation was substantially less than the total variation observed across the patient population. Nevertheless, a fraction of genes exhibited significant intratumor heterogeneity in expression. A high degree of reproducibility was observed in single-gene predictors of ER (intraclass correlation coefficient [ICC] = 0.94) and PR expression (ICC = 0.90), and in a multigene predictor of ER pathway activation (ICC = 0.98) with high concordance with immunohistochemistry. Substantial agreement was also observed for multigene signatures of cancer recurrence (ICC = 0.71) and chemotherapeutic sensitivity (ICC = 0.72 and 0.64)., Conclusion: Intratumor heterogeneity, although present at the level of individual gene expression, does not preclude precise microarray-based predictions of tumor behavior or clinical outcome in breast cancer patients.

Objective: The objective of this study was to examine the clinicopathologic correlates of T-regulatory (T(reg)) cell infiltration in serous ovarian cancers and to define gene signatures associated with high T(reg)s., Methods: Tumor infiltrating T(reg) and cytotoxic T-cells (CTLs) were quantitated in 232 primary serous ovarian cancers by immunostaining for FOXP3 and CD8. Expression microarray analysis was performed in a subset of 48 advanced cancers with the highest and lowest numbers of infiltrating T(reg)s and a genomic signature was developed using binary regression. ANOVA analysis was performed to assess the most differentially expressed genes and these genes were further assessed using Ingenuity Pathway Analysis (IPA) software., Results: High T(reg) infiltration in ovarian cancers was associated with high grade (p<0.0001), advanced stage (p=0.004) and suboptimal debulking (p<0.04), but not with survival. In contrast, high tumor infiltrating CD8 CTL infiltration was associated with favorable survival (median survival 48.7 vs. 34.6 months, p=0.01). A microarray-based genomic signature for high tumor-infiltrating T(reg) cells had a 77% predictive accuracy using leave-one-out cross-validation. ANOVA of microarray data revealed the antigen presentation pathway as the most differentially expressed canonical pathway (p<0.00001) between cancers with high and low T(reg) cells., Conclusions: These data suggest that there may be an association between increased T(reg) cell infiltration in ovarian cancers and advanced stage. Increased T(reg) infiltration is characterized by a genomic signature enriched with several immunologic pathway genes. Therapeutic strategies that reduce tumor infiltrating T(reg) cells are under investigation and may prove useful in ovarian cancers with high numbers of these cells.

Feasibility and reproducibility of microarray biomarkers in clinical settings are doubted because of reliance on fresh frozen tissue. We sought to develop and validate a paradigm of frozen tissue collection from early breast tumors to enable use of microarray in oncology practice. Frozen core needle biopsies (CNBx) were collected from 150 clinical stage I patients during image-guided diagnostic biopsy and/or surgery. Histology and tumor content from frozen cores were compared to diagnostic specimens. Twenty-eight patients had microarray analysis to examine accuracy and reproducibility of predictive gene signatures developed for estrogen receptor (ER) and HER2. One hundred twenty-seven (85%) of 150 patients had at least one frozen core containing cancer suitable for microarray analysis. Larger tumor size, ex vivo biopsy, and use of a new specimen device increased the likelihood of obtaining adequate specimens. Sufficient quality RNA was obtained from 90% of tumor cores. Microarray signatures predicting ER and HER2 expression were developed in training sets of up to 363 surgical samples and were applied to microarray data obtained from core samples collected in clinical settings. In these samples, prediction of ER and HER2 expression achieved a sensitivity/specificity of 94%/100%, and 82%/72%, respectively. Predictions were reproducible in 83-100% of paired samples. Frozen CNBx can be readily obtained from most breast cancers without interfering with pathologic evaluation in routine clinical settings. Collection of tumor tissue at diagnostic biopsy and/or at surgery from lumpectomy specimens using image guidance resulted in sufficient samples for array analysis from over 90% of patients. Sampling of breast cancer for microarray data is reproducible and feasible in clinical practice and can yield signatures predictive of multiple breast cancer phenotypes.

Purpose: Although few women with advanced serous ovarian cancer are cured, detection of the disease at an early stage is associated with a much higher likelihood of survival. We previously used gene expression array analysis to distinguish subsets of advanced cancers based on disease outcome. In the present study, we report on gene expression of early-stage cancers and validate our prognostic model for advanced-stage cancers., Experimental Design: Frozen specimens from 39 stage I/II, 42 stage III/IV, and 20 low malignant potential cancers were obtained from four different sites. A linear discriminant model was used to predict survival based upon array data., Results: We validated the late-stage survival model and show that three of the most differentially expressed genes continue to be predictive of outcome. Most early-stage cancers (38 of 39 invasive, 15 of 20 low malignant potential) were classified as long-term survivors (median probabilities 0.97 and 0.86). MAL, the most differentially expressed gene, was further validated at the protein level and found to be an independent predictor of poor survival in an unselected group of advanced serous cancers (P = 0.0004)., Conclusions: These data suggest that serous ovarian cancers detected at an early stage generally have a favorable underlying biology similar to advanced-stage cases that are long-term survivors. Conversely, most late-stage ovarian cancers seem to have a more virulent biology. This insight suggests that if screening approaches are to succeed it will be necessary to develop approaches that are able to detect these virulent cancers at an early stage.

We investigated the clinical implications of lung developmental transcription factors (TTF-1, NKX2-8, and PAX9) that we recently discovered as cooperating oncogenes activated by way of gene amplification at chromosome 14q13 in lung cancer. Using stable transfectants of human bronchial epithelial cells, RNA expression profiles (signatures) representing activation of the biological pathways defined by each of the 3 genes were determined and used to risk stratify a non-small-cell lung cancer (NSCLC) clinical data set consisting of 91 early stage tumors. Coactivation of the TTF-1 and NKX2-8 pathways identified a cluster of patients with poor survival, representing approximately 20% of patients with early stage NSCLC, whereas activation of individual pathways did not reveal significant prognostic power. Importantly, the poor prognosis associated with coactivation of TTF-1 and NKX2-8 was validated in 2 other independent clinical data sets. Furthermore, lung cancer cell lines showing coactivation of the TTF-1 and NKX2-8 pathways were shown to exhibit resistance to cisplatin, the standard of care for the treatment of NSCLC. This suggests that the cohort of patients with coactivation of TTF-1 and NKX2-8 pathways appears to be resistant to standard cisplatin therapy, suggesting the need for alternative therapies in this cohort of high-risk patients.

Erythroid Krüppel-like factor (EKLF) is a Krüppel-like transcription factor identified as a transcriptional activator and chromatin modifier in erythroid cells. EKLF-deficient (Eklf(-/-)) mice die at day 14.5 of gestation from severe anemia. In this study, we demonstrate that early progenitor cells fail to undergo terminal erythroid differentiation in Eklf(-/-) embryos. To discover potential EKLF target genes responsible for the failure of erythropoiesis, transcriptional profiling was performed with RNA from wild-type and Eklf(-/-) early erythroid progenitor cells. These analyses identified significant perturbation of a network of genes involved in cell cycle regulation, with the critical regulator of the cell cycle, E2f2, at a hub. E2f2 mRNA and protein levels were markedly decreased in Eklf(-/-) early erythroid progenitor cells, which showed a delay in the G(1)-to-S-phase transition. Chromatin immunoprecipitation analysis demonstrated EKLF occupancy at the proximal E2f2 promoter in vivo. Consistent with the role of EKLF as a chromatin modifier, EKLF binding sites in the E2f2 promoter were located in a region of EKLF-dependent DNase I sensitivity in early erythroid progenitor cells. We propose a model in which EKLF-dependent activation and modification of the E2f2 locus is required for cell cycle progression preceding terminal erythroid differentiation.

The endoplasmic reticulum stress response, also known as the unfolded protein response (UPR), has been implicated in the normal physiology of immune defense and in several disorders, including diabetes, cancer, and neurodegenerative disease. Here, we show that the apoptotic receptor CED-1 and a network of PQN/ABU proteins involved in a noncanonical UPR response are required for proper defense to pathogen infection in Caenorhabditis elegans. A full-genome microarray analysis indicates that CED-1 functions to activate the expression of pqn/abu genes. We also show that ced-1 and pqn/abu genes are required for the survival of C. elegans exposed to live Salmonella enterica, and that overexpression of pqn/abu genes confers protection against pathogen-mediated killing. The results indicate that unfolded protein response genes, regulated in a CED-1-dependent manner, are involved in the C. elegans immune response to live bacteria.

Background: A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective., Methods and Results: Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide) chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06). Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8%) of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), representing a viable alternative therapy., Conclusions: Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles. Importantly, we also present evidence to support the concept that analysis of molecular variables can present a rational strategy to identifying alternative therapeutic opportunities.

Context: Gene expression profiling may be useful for prognostic and therapeutic strategies in breast carcinoma., Objectives: To demonstrate the value in integrating genomic information with clinical and pathological risk factors, to refine prognosis, and to improve therapeutic strategies for early stage breast cancer., Design, Setting, and Patients: Retrospective study of patients with early stage breast carcinoma who were candidates for adjuvant chemotherapy; 964 clinically annotated breast tumor samples (573 in the initial discovery set and 391 in the validation cohort) with corresponding microarray data were used. All patients were assigned relapse risk scores based on their respective clinicopathological features. Signatures representing oncogenic pathway activation and tumor biology/microenvironment status were applied to these samples to obtain patterns of deregulation that correspond with relapse risk scores to refine prognosis with the clinicopathological prognostic model alone. Predictors of chemotherapeutic response were also applied to further characterize clinically relevant heterogeneity in early stage breast cancer., Main Outcome Measures: Gene expression signatures and clinicopathological variables in early stage breast cancer to determine a refined estimation of relapse-free survival and sensitivity to chemotherapy., Results: In the initial data set of 573 patients, prognostically significant clusters representing patterns of oncogenic pathway activation and tumor biology/microenvironment states were identified within the low-risk (log-rank P = .004), intermediate-risk (log-rank P = .01), and high-risk (log-rank P = .003) model cohorts, representing clinically important genomic subphenotypes of breast cancer. As an example, in the low-risk cohort, of 6 prognostically significant clusters, patients in cluster 4 had an inferior relapse-free survival vs patients in cluster 1 (log-rank P = .004) and cluster 5 (log-rank P = .03). Median relapse-free survival for patients in cluster 4 was 16 months less than for patients in cluster 1 (95% CI, 7.5-24.5 months) and 19 months less than for patients in cluster 5 (95% CI, 10.5-27.5 months). Multivariate analyses confirmed the independent prognostic value of the genomic clusters (low risk, P = .05; high risk, P = .02). The reproducibility and validity of these patterns of pathway deregulation in predicting relapse risk was established using related but not identical clusters in the independent validation cohort. The prognostic clinicogenomic clusters also have unique sensitivity patterns to commonly used cytotoxic therapies., Conclusions: These results provide preliminary evidence that incorporation of gene expression signatures into clinical risk stratification can refine prognosis. Prospective studies are needed to determine the value of this approach for individualizing therapeutic strategies.

Background: Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures., Methods and Findings: We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively., Conclusions: We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.

Background: The capacity to assess environmental inputs to biological phenotypes is limited by methods that can accurately and quantitatively measure these contributions. One such example can be seen in the context of exposure to ionizing radiation., Methods and Findings: We have made use of gene expression analysis of peripheral blood (PB) mononuclear cells to develop expression profiles that accurately reflect prior radiation exposure. We demonstrate that expression profiles can be developed that not only predict radiation exposure in mice but also distinguish the level of radiation exposure, ranging from 50 cGy to 1,000 cGy. Likewise, a molecular signature of radiation response developed solely from irradiated human patient samples can predict and distinguish irradiated human PB samples from nonirradiated samples with an accuracy of 90%, sensitivity of 85%, and specificity of 94%. We further demonstrate that a radiation profile developed in the mouse can correctly distinguish PB samples from irradiated and nonirradiated human patients with an accuracy of 77%, sensitivity of 82%, and specificity of 75%. Taken together, these data demonstrate that molecular profiles can be generated that are highly predictive of different levels of radiation exposure in mice and humans., Conclusions: We suggest that this approach, with additional refinement, could provide a method to assess the effects of various environmental inputs into biological phenotypes as well as providing a more practical application of a rapid molecular screening test for the diagnosis of radiation exposure.

Purpose: The purpose of this study was to develop an integrated genomic-based approach to personalized treatment of patients with advanced-stage ovarian cancer. We have used gene expression profiles to identify patients likely to be resistant to primary platinum-based chemotherapy and also to identify alternate targeted therapeutic options for patients with de novo platinum-resistant disease., Patients and Methods: A gene expression model that predicts response to platinum-based therapy was developed using a training set of 83 advanced-stage serous ovarian cancers and tested on a 36-sample external validation set. In parallel, expression signatures that define the status of oncogenic signaling pathways were evaluated in 119 primary ovarian cancers and 12 ovarian cancer cell lines. In an effort to increase chemotherapy sensitivity, pathways shown to be activated in platinum-resistant cancers were subject to targeted therapy in ovarian cancer cell lines., Results: Gene expression profiles identified patients with ovarian cancer likely to be resistant to primary platinum-based chemotherapy with greater than 80% accuracy. In patients with platinum-resistant disease, we identified expression signatures consistent with activation of Src and Rb/E2F pathways, components of which were successfully targeted to increase response in ovarian cancer cell lines., Conclusion: We have defined a strategy for treatment of patients with advanced-stage ovarian cancer that uses therapeutic stratification based on predictions of response to chemotherapy, coupled with prediction of oncogenic pathway deregulation, as a method to direct the use of targeted agents.

Using in vitro drug sensitivity data coupled with Affymetrix microarray data, we developed gene expression signatures that predict sensitivity to individual chemotherapeutic drugs. Each signature was validated with response data from an independent set of cell line studies. We further show that many of these signatures can accurately predict clinical response in individuals treated with these drugs. Notably, signatures developed to predict response to individual agents, when combined, could also predict response to multidrug regimens. Finally, we integrated the chemotherapy response signatures with signatures of oncogenic pathway deregulation to identify new therapeutic strategies that make use of all available drugs. The development of gene expression profiles that can predict response to commonly used cytotoxic agents provides opportunities to better use these drugs, including using them in combination with existing targeted therapies.

Although the transition from early- to advanced-stage ovarian cancer is a critical determinant of survival, little is known about the molecular underpinnings of ovarian metastasis. We hypothesize that microarray analysis of global gene expression patterns in primary ovarian cancer and metastatic omental implants can identify genes that underlie the metastatic process in epithelial ovarian cancer. We utilized Affymetrix U95Av2 microarrays to characterize the molecular alterations that underlie omental metastasis from 47 epithelial ovarian cancer samples collected from multiple sites in 20 patients undergoing primary surgical cytoreduction for advanced-stage (IIIC/IV) serous ovarian cancer. Fifty-six genes demonstrated differential expression between ovarian and omental samples (P < 0.01), and twenty of these 56 differentially expressed genes have previously been implicated in metastasis, cell motility, or cytoskeletal function. Ten of the 56 genes are involved in p53 gene pathways. A Bayesian statistical tree analysis was used to identify a 27-gene expression pattern that could accurately predict the site of tumor (ovary versus omentum). This predictive model was evaluated using an external data set. Nine of the 27 predictive genes have previously been shown to be involved in oncogenesis and/or metastasis, and 10/27 genes have been implicated in p53 pathways. Microarray findings were validated by real-time quantitative PCR. We conclude that gene expression patterns that distinguish omental metastasis from primary epithelial ovarian cancer can be identified and that many of the genes have functions that are biologically consistent with a role in oncogenesis, metastasis, and p53 gene networks.

Purpose: The silencing of gene expression through DNA methylation contributes to defects in antigen presentation and apoptosis in melanoma and renal cell cancer. To determine how a hypomethylating agent would modulate the toxicity and antitumor activity of immunotherapy, we initiated a phase I trial of 5-aza-2'-deoxycytidine (decitabine) plus high-dose interleukin 2 (IL-2)., Experimental Design: Patients received s.c. decitabine daily x 5 days on weeks 1 and 2 of a 12-week cycle. High-dose IL-2, consisting of two cycles of IL-2 600,000 IU/kg i.v. q8 hours x 14 doses separated by a 2-week break, was administered starting on week 3. Decitabine was escalated from 0.1 to 0.25 mg/kg. The hypomethylating activity of decitabine was assessed during cycle 1 by measuring hemoglobin F levels and changes in DNA methylation in peripheral blood mononuclear cells., Results: Twenty-one patients with melanoma or renal cell cancer were enrolled. Decitabine did not alter the tolerability of IL-2 but caused grade 4 neutropenia in most patients. Grade 4 neutropenia lasting more than 7 days was the only dose-limiting toxicity, with a trend toward a higher incidence with increasing decitabine doses. Infection occurred in only one patient despite the high incidence of neutropenia, and granulocyte colony-stimulating factor use in several patients expedited neutrophil recovery. Decitabine augmented hemoglobin F levels and altered DNA methylation and gene expression in peripheral blood mononuclear cells in a dose-independent manner that overlapped with the administration of IL-2. Objective responses occurred in 31% of melanoma patients., Conclusions: Decitabine can be safely administered with high-dose IL-2 and may enhance the activity of IL-2 in melanoma.

Despite major developments in targeted biologic agents, patients with advanced non-small-cell lung cancer have a poor prognosis. Recent development of targeted biologic agents have given us insight into possibilities of matching therapy with disease; however, the success of these agents has been marginal. In this article, we discuss the use of genomic signatures that have been developed to identify unique aspects of individual lung tumors and provide insight on how novel strategies can be used to identify populations susceptible to specific targeted agents.

Recent progress has been made in the identification of the osteoblastic cellular niche for hematopoietic stem cells (HSCs) within the bone marrow (BM). Attempts to identify the soluble factors that regulate HSC self-renewal have been less successful. We have demonstrated that primary human brain endothelial cells (HUBECs) support the ex vivo amplification of primitive human BM and cord blood cells capable of repopulating non-obese diabetic/severe combined immunodeficient repopulating (SCID) mice (SCID repopulating cells [SRCs]). In this study, we sought to characterize the soluble hematopoietic activity produced by HUBECs and to identify the growth factors secreted by HUBECs that contribute to this HSC-supportive effect. Extended noncontact HUBEC cultures supported an eight-fold increase in SRCs when combined with thrombopoietin, stem cell factor, and Flt-3 ligand compared with input CD34(+) cells or cytokines alone. Gene expression analysis of HUBEC biological replicates identified 65 differentially expressed, nonredundant transcripts without annotated hematopoietic activity. Gene ontology studies of the HUBEC transcriptome revealed a high concentration of genes encoding extracellular proteins with cell-cell signaling function. Functional analyses demonstrated that adrenomedullin, a vasodilatory hormone, synergized with stem cell factor and Flt-3 ligand to induce the proliferation of primitive human CD34(+)CD38(-)lin(-) cells and promoted the expansion of CD34(+) progenitors in culture. These data demonstrate the potential of primary HUBECs as a reservoir for the discovery of novel secreted proteins that regulate human hematopoiesis.

Background: TGF-beta1 is an important angiogenic factor involved in the different aspects of angiogenesis and vessel maintenance. TGF-beta signalling is mediated by the TbetaRII/ALK5 receptor complex activating the Smad2/Smad3 pathway. In endothelial cells TGF-beta utilizes a second type I receptor, ALK1, activating the Smad1/Smad5 pathway. Consequently, a perturbance of ALK1, ALK5 or TbetaRII activity leads to vascular defects. Mutations in ALK1 cause the vascular disorder hereditary hemorrhagic telangiectasia (HHT)., Methods: The identification of ALK1 and not ALK5 regulated genes in endothelial cells, might help to better understand the development of HHT. Therefore, the human microvascular endothelial cell line HMEC-1 was infected with a recombinant constitutively active ALK1 adenovirus, and gene expression was studied by using gene arrays and quantitative real-time PCR analysis., Results: After 24 hours, 34 genes were identified to be up-regulated by ALK1 signalling. Analysing ALK1 regulated gene expression after 4 hours revealed 13 genes to be up- and 2 to be down-regulated. Several of these genes, including IL-8, ET-1, ID1, HPTPeta and TEAD4 are reported to be involved in angiogenesis. Evaluation of ALK1 regulated gene expression in different human endothelial cell types was not in complete agreement. Further on, disparity between constitutively active ALK1 and TGF-beta1 induced gene expression in HMEC-1 cells and primary HUVECs was observed., Conclusion: Gene array analysis identified 49 genes to be regulated by ALK1 signalling and at least 14 genes are reported to be involved in angiogenesis. There was substantial agreement between the gene array and quantitative real-time PCR data. The angiogenesis related genes might be potential HHT modifier genes. In addition, the results suggest endothelial cell type specific ALK1 and TGF-beta signalling.

We have studied sarin-induced global gene expression patterns at an early time point (2 h: 0.5 x LD50) using Affymetrix Rat Neurobiology U34 chips and male Sprague-Dawley rats. A total of 46 genes showed statistically significant alterations from control levels. Three gene categories contained more of the altered genes than any other groups: ion channel (8 genes) and calcium channel and binding proteins (6 genes). Alterations were also found in the following gene groups: ATPases and ATP-based transporters (4), growth factors (4), G-protein-coupled receptor pathway-related molecules (3), neurotransmission and neurotransmitter transporters (3), cytoskeletal and cell adhesion molecules (2), hormones (2), mitochondria-associated proteins (2), myelin proteins (2), stress-activated molecules (2), cytokine (1), caspase (1), GABAnergic (1), glutamergic (1), immediate early gene (1), prostaglandin (1), transcription factor (1), and tyrosine phosphorylation molecule (1). Persistent alteration of the following genes also were noted: Arrb1, CaMKIIa, CaMKIId, Clcn5, IL-10, c-Kit, and Plp1, suggesting altered GPCR, kinase, channel, and cytokine pathways. Selected genes from the microarray data were further validated using relative RT-PCR. Some of those genes (GFAP, NF-H, CaMKIIa, Calm, and MBP) have been shown by other laboratories and ours, to be involved in the pathogenesis of sarin-induced pathology and organophosphate-induced delayed neurotoxicity (OPIDN). Induction of both proapoptotic (Bcl2l11, Casp6) and antiapoptotic (Bcl-X) genes, besides suppression of p21, suggest complex cell death/protection-related mechanisms operating early on. Principal component analysis (PCA) of the expression data confirmed that the changes in gene expression are a function of sarin exposure, since the control and treatment groups separated clearly. Our model (based on current and previous studies) indicates that both degenerative and regenerative pathways are activated early and contribute to the level of neurodegeneration at a later time, leading to neuro-pathological alterations.

Antiphospholipid antibody syndrome (APS) is a complex autoimmune thrombotic disorder with defined clinical phenotypes. Although not all patients with elevated antiphospholipid antibody (aPLA) levels develop complications, the severity of these potential events mandates aggressive and extended lifelong anti-thrombotic therapy. One hundred twenty-nine patients (57 patients with APS and venous thromboembolism [VTE], 32 patients with VTE without aPLA, 32 patients with aPLA only, and 8 healthy patients) were enrolled. RNA from peripheral-blood collection was used for DNA microarray analysis. Patterns of gene expression that characterize APS as well as thrombosis in the presence of aPLA were identified by hierarchical clustering and binary regression methods. Gene-expression profiles identify and predict individuals with APS from patients with VTE without aPLA. Importantly, similar methods identified expression profiles that accurately predicted those patients with aPLA at high risk for thrombotic events. All profiles were validated in independent cohorts of patients. The ability to predict APS, but more importantly, those patients at risk for venous thrombosis, represents a paradigm for a genomic approach that can be applied to other populations of patients with venous thrombosis, providing for more effective clinical management of disease, while also reflecting the possible underlying biologic processes.

We have studied sarin-induced global gene expression patterns at an early time point (15 min; 0.5xLD50) and a later time point (3 months; 1xLD50) using Affymetrix: Rat Neurobiology U34 chips in male, Sprague-Dawley rats and have identified a total of 65 (early) and 38 (late) genes showing statistically significant alterations from control levels at 15 min and 3 months, respectively. At the early time point, those that are classified as ion channel, cytoskeletal and cell adhesion molecules, in addition to neuropeptides and their receptors predominated over all other groups. The other groups included: cholinergic signaling, calcium channel and binding proteins, transporters, chemokines, GABAnergic, glutamatergic, aspartate, catecholaminergic, nitric oxide synthase, purinergic, and serotonergic signaling molecules. At the late time point, genes that are classified as calcium channel and binding proteins, cytoskeletal and cell adhesion molecules and GABAnergic signaling molecules were most prominent. Seven molecules (Ania-9, Arrb-1, CX-3C, Gabab-1d, Nos-2a, Nrxn-1b, PDE2) were identified that showed altered persistent expression in both time points. Selected genes from each of these time points were further validated using semi quantitative RT-PCR approaches. Some of the genes that were identified in the present study have been shown to be involved in organophosphate-induced neurotoxicity by both other groups as well as ours. Principal component analysis (PCA) of the expression data from both time points was used for comparative analysis of the gene expression, which indicated that the changes in gene expression were a function of dose and time of euthanasia after the treatment. Our model also predicts that besides dose and duration of post-treatment period, age and possibly other factors may be playing important roles in the regulation of pathways, leading to the neurotoxicity.

Purpose: Breast cancer is a heterogeneous disease, and markers for disease subtypes and therapy response remain poorly defined. For that reason, we employed a prospective neoadjuvant study in locally advanced breast cancer to identify molecular signatures of gene expression correlating with known prognostic clinical phenotypes, such as inflammatory breast cancer or the presence of hypoxia. In addition, we defined molecular signatures that correlate with response to neoadjuvant chemotherapy., Experimental Design: Tissue was collected under ultrasound guidance from patients with stage IIB/III breast cancer before four cycles of neoadjuvant liposomal doxorubicin paclitaxel chemotherapy combined with local whole breast hyperthermia. Gene expression analysis was done using Affymetrix U133 Plus 2.0 GeneChip arrays., Results: Gene expression patterns were identified that defined the phenotypes of inflammatory breast cancer as well as tumor hypoxia. In addition, molecular signatures were identified that predicted the persistence of malignancy in the axillary lymph nodes after neoadjuvant chemotherapy. This persistent lymph node signature significantly correlated with disease-free survival in two separate large populations of breast cancer patients., Conclusions: Gene expression signatures have the capacity to identify clinically significant features of breast cancer and can predict which individual patients are likely to be resistant to neoadjuvant therapy, thus providing the opportunity to guide treatment decisions.

The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate. The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways. Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics.

En masse analysis of gene structure and function by array technologies will have a lasting and profound effect on biology and medicine. This impact can be compromised by low quality of probes within arrays, which we show can be caused by incomplete removal of chemical protecting groups. To solve this quality control problem, we present a sensitive, specific and facile method to detect these groups in situ on arrays using monoclonal antibodies and existing instrumentation. Screening of microarrays with these monoclonal antibodies should guide the consideration given to data derived from these and should enhance the accuracy of the results obtained.

The E2F family of transcription factors provides essential activities for coordinating the control of cellular proliferation and cell fate. Both E2F1 and E2F3 proteins have been shown to be particularly important for cell proliferation, whereas the E2F1 protein has the capacity to promote apoptosis. To explore the basis for this specificity of function, we used DNA microarray analysis to probe for the distinctions in the two E2F activities. Gene expression profiles that distinguish either E2F1- or E2F3-expressing cells from quiescent cells are enriched in genes encoding cell cycle and DNA replication activities, consistent with many past studies. E2F1 profile is also enriched in genes known to function in apoptosis. We also identified patterns of gene expression that specifically differentiate the activity of E2F1 and E2F3; this profile is enriched in genes known to function in mitosis. The specificity of E2F function has been attributed to protein interactions mediated by the marked box domain, and we now show that chimeric E2F proteins generate expression signatures that reflect the origin of the marked box, thus linking the biochemical mechanism for specificity of function with specificity of gene activation.

IFN-gamma plays a role in the response to melanoma indirectly through its effect on the immune system and directly through its antiproliferative and proapoptotic effects on melanoma cells. To understand the molecular basis for the direct antimelanoma effect of IFN-gamma, we studied IFN-induced changes in gene expression and signaling among three human melanoma cell lines (DM6, DM93, and 501mel). These were resistant to the antimelanoma effect of IFN-alpha, and only DM6 cells exhibited growth inhibition and apoptosis with IFN-gamma. Through DNA microarray analysis, we found that the antimelanoma effect of IFN-gamma in DM6 was associated with the down-regulation of multiple genes involved in G-protein signaling and phospholipase C activation (including Rap2B and calpain 3) as well as the down-regulation of genes involved in melanocyte/melanoma survival (MITF and SLUG), apoptosis inhibition (Bcl2A1 and galectin-3), and cell cycling (CDK2). The antimelanoma effect of IFN-gamma was also associated with the up-regulation of the proapoptotic dependence receptor UNC5H2 and the Wnt inhibitor Dkk-1. Whereas both IFNs were able to activate Stat1 in all cell lines, the delayed activation of the extracellular signal-regulated kinase, p38, and c-Jun NH2-terminal kinase mitogen-activated protein kinases occurred only in DM6 with IFN-gamma, and the effect of IFN-gamma on cell growth and survival as well as gene expression in DM6 was dependent on the coordinate activation of MEK1 and p38. These findings provide new insights into the signaling events and gene expression changes associated with growth inhibition and apoptosis in melanoma and may thereby assist in identifying new targets for the treatment of melanoma.

Despite the strikingly grave prognosis for older patients with glioblastomas, significant variability in patient outcome is experienced. To explore the potential for developing improved prognostic capabilities based on the elucidation of potential biological relationships, we did analyses of genes commonly mutated, amplified, or deleted in glioblastomas and DNA microarray gene expression data from tumors of glioblastoma patients of age >50 for whom survival is known. No prognostic significance was associated with genetic changes in epidermal growth factor receptor (amplified in 17 of 41 patients), TP53 (mutated in 11 of 41 patients), p16INK4A (deleted in 15 of 33 patients), or phosphatase and tensin homologue (mutated in 15 of 41 patients). Statistical analysis of the gene expression data in connection with survival involved exploration of regression models on small subsets of genes, based on computational search over multiple regression models with cross-validation to assess predictive validity. The analysis generated a set of regression models that, when weighted and combined according to posterior probabilities implied by the statistical analysis, identify patterns in expression of a small subset of genes that are associated with survival and have value in assessing survival risks. The dominant genes across such multiple regression models involve three key genes-SPARC (Osteonectin), Doublecortex, and Semaphorin3B-which play key roles in cellular migration processes. Additional analysis, based on statistical graphical association models constructed using similar computational analysis methods, reveals other genes which support the view that multiple mediators of tumor invasion may be important prognostic factor in glioblastomas in older patients.

Purpose: A better understanding of the underlying biology of invasive serous ovarian cancer is critical for the development of early detection strategies and new therapeutics. The objective of this study was to define gene expression patterns associated with favorable survival., Experimental Design: RNA from 65 serous ovarian cancers was analyzed using Affymetrix U133A microarrays. This included 54 stage III/IV cases (30 short-term survivors who lived <3 years and 24 long-term survivors who lived >7 years) and 11 stage I/II cases. Genes were screened on the basis of their level of and variability in expression, leaving 7,821 for use in developing a predictive model for survival. A composite predictive model was developed that combines Bayesian classification tree and multivariate discriminant models. Leave-one-out cross-validation was used to select and evaluate models., Results: Patterns of genes were identified that distinguish short-term and long-term ovarian cancer survivors. The expression model developed for advanced stage disease classified all 11 early-stage ovarian cancers as long-term survivors. The MAL gene, which has been shown to confer resistance to cancer therapy, was most highly overexpressed in short-term survivors (3-fold compared with long-term survivors, and 29-fold compared with early-stage cases). These results suggest that gene expression patterns underlie differences in outcome, and an examination of the genes that provide this discrimination reveals that many are implicated in processes that define the malignant phenotype., Conclusions: Differences in survival of advanced ovarian cancers are reflected by distinct patterns of gene expression. This biological distinction is further emphasized by the finding that early-stage cancers share expression patterns with the advanced stage long-term survivors, suggesting a shared favorable biology.

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. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

Objective: The purpose of this study was to define gene expression patterns that are associated with the optimal versus suboptimal debulking of advanced-stage serous ovarian cancers., Study Design: RNA from 44 advanced serous ovarian cancers (19 optimal, 25 suboptimal) was evaluated with microarrays that contain >22,000 genes. Genes were screened on the basis of their association with debulking status to obtain the top 120 differentially expressed genes. These genes were then used to develop a predictive model for debulking status, which was subjected to out-of-sample cross validation., Results: We found that patterns of expression of 32 genes can distinguish between optimal and suboptimal debulking with 72.7% predictive accuracy. An analysis of the data that were based on clusters of co-ordinately expressed genes resulted in only a marginal improvement in predictive accuracy (75%)., Conclusion: These data support the hypothesis that favorable survival that is associated with optimal debulking of advanced ovarian cancers is due to, at least in part, the underlying biologic characteristics of these cancers.

p185 Bcr-Abl has a more aggressive biological/clinical leukemia phenotype than p210 Bcr-Abl. In this study, we examined differential gene expression using microarrays to determine if upregulation or downregulation of specific genes may explain the distinct phenotypes produced by the two Bcr-Abl forms. RNA was collected from mouse bone marrow mononuclear cells expressing equivalent levels of p185 or p210, and the RNAs were subjected to microarray analysis. Significant differences in gene expression were observed on hierarchical clustering. A group of interferon-gamma-inducible genes, including those encoding a family of 47 kDa GTPases, were significantly increased in p185 versus p210. This family of GTPases has previously been implicated in interferon-gamma-induced resistance against intracellular pathogens, however their exact cellular functions are unknown. Our data suggest that their increased expression may contribute to the biological/clinical phenotype associated with p185.

Objective: Human brain arteriovenous malformations (BAVMs) display abnormal expression of various angiogenesis-related genes and their products. We examined gene expression patterns in BAVMs by the gene microarray technique., Methods: We analyzed BAVM and control brain samples obtained by temporal lobectomy for medically intractable seizure by Affymetrix Human Gene Set U95Av2 (Affymetrix, Inc., Santa Clara, CA). The gene microarray data were compared with new and previously published data that used conventional molecular biology techniques., Results: We analyzed six BAVM and five control brain samples. From 12,625 gene probes assayed, 1781 gene probes showed differential expression between BAVMs and controls. BAVM samples had a gene expression pattern that was distinct from those of control brain samples. Increased messenger ribonucleic acid expression of vascular endothelial growth factor A was accompanied by increased expression of its protein product. A majority of the gene data was in agreement with previously published data. The gene microarray data generated a new testable hypothesis regarding integrin, and we found increased expression of integrin alphavbeta3 protein in BAVMs., Conclusion: The gene expression pattern of BAVMs was distinct from those of control brain samples. We verified the gene microarray data by demonstrating that increased gene expression levels for angiogenesis-related molecules were accompanied by increased levels of their protein product expression. The gene microarray technique may be a useful tool to study multiple pathways simultaneously in BAVM specimens.

Objective: To identify gene expression patterns that characterize advanced stage serous ovarian cancers by using microarray expression analysis., Methods: Using genome-wide expression analysis, we compared a series of 31 advanced stage (III or IV) serous ovarian cancers from patients who survived either less than 2 years or more than 7 years with three normal ovarian epithelial samples. Array findings were validated by analysis of expression of the insulin-like growth factor binding protein 2 (IGFBP2) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) genes using quantitative real-time polymerase chain reaction (QRT-PCR)., Results: Hierarchical clustering identified patterns of gene expression that distinguished cancer from normal ovarian epithelium. We also identified gene expression patterns that distinguish cancers on the basis of patient survival. These genes include many that are associated with immune function. Expression of IGFBP2 and TRAIL genes measured by array and QRT-PCR analysis demonstrated correlation coefficients of 0.63 and 0.78, respectively., Conclusion: Global expression analysis can identify expression patterns and individual genes that contribute to ovarian cancer development and outcome. Many of the genes that determine ovarian cancer survival are associated with the immune response, suggesting that immune function influences ovarian cancer virulence. With the generation of newer arrays with more transcripts, larger studies are possible to fully characterize genetic signatures that predict survival that may ultimately be used to guide therapeutic decision-making.

Bacteriophage RB69 encodes a replicative B-family DNA polymerase (RB69 gp43) with an associated proofreading 3' exonuclease. Crystal structures have been determined for this enzyme with and without DNA substrates. We previously described the mutation rates and kinds of mutations produced in vivo by the wild-type (Pol(+) Exo(+)) enzyme, an exonuclease-deficient mutator variant (Pol(+) Exo(-)), mutator variants with substitutions at Tyr(567) in the polymerase active site (Pol(M) Exo(+)), and the double mutator Pol(M) Exo(-). Comparing the mutational spectra of the Pol(+) Exo(-) and Pol(+) Exo(+) enzymes revealed the patterns and efficiencies of proofreading, while Tyr(567) was identified as an important determinant of base-selection fidelity. Here, we sought to determine how well the fidelities of the same enzymes are reflected in vitro. Compared to their behavior in vivo, the three mutator polymerases exhibited modestly higher mutation rates in vitro and their mutational predilections were also somewhat different. Although the RB69 gp43 accessory proteins exerted little or no effect on total mutation rates in vitro, they strongly affected mutation rates at many specific sites, increasing some rates and decreasing others.

The DNA polymerases (gp43s) of the related bacteriophages T4 and RB69 are B family (polymerase alpha class) enzymes that determine the fidelity of phage DNA replication. A T4 whose gene 43 has been mutationally inactivated can be replicated by a cognate RB69 gp43 encoded by a recombinant plasmid in T4-infected Escherichia coli. We used this phage-plasmid complementation assay to obtain rapid and sensitive measurements of the mutational specificities of mutator derivatives of the RB69 enzyme. RB69 gp43s lacking proofreading function (Exo(-) enzymes) and/or substituted with alanine, serine, or threonine at the conserved polymerase function residue Tyr(567) (Pol(Y567(A/S/T)) enzymes) were examined for their effects on the reversion of specific mutations in the T4 rII gene and on forward mutation in the T4 rI gene. The results reveal that Tyr(567) is a key determinant of the fidelity of base selection and that the Pol and Exo functions are strongly coupled in this B family enzyme. In vitro assays show that the Pol(Y567A) Exo(-) enzyme generates mispairs more frequently but extends them less efficiently than does a Pol(+) Exo(-) enzyme. Other replicative DNA polymerases may control fidelity by strategies similar to those used by RB69 gp43.