Publications by authors named "Holly K Dressman"

45 Publications

The Pediatric Obesity Microbiome and Metabolism Study (POMMS): Methods, Baseline Data, and Early Insights.

Obesity (Silver Spring) 2021 Mar;29(3):569-578

Department of Pediatrics, Duke University, Durham, North Carolina, USA.

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.
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http://dx.doi.org/10.1002/oby.23081DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927749PMC
March 2021

RNA splicing and aggregate gene expression differences in lung squamous cell carcinoma between patients of West African and European ancestry.

Lung Cancer 2021 03 14;153:90-98. Epub 2021 Jan 14.

Department of Medicine, Division of Medical Oncology, Duke University School of Medicine, Durham, NC, 27710, USA; Duke Cancer Institute, Duke University School of Medicine, Durham, NC, 27710, USA. Electronic address:

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.
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http://dx.doi.org/10.1016/j.lungcan.2021.01.015DOI Listing
March 2021

Short-Chain Fatty Acid Production by Gut Microbiota from Children with Obesity Differs According to Prebiotic Choice and Bacterial Community Composition.

mBio 2020 08 11;11(4). Epub 2020 Aug 11.

Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, North Carolina, USA

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 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 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. 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."
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http://dx.doi.org/10.1128/mBio.00914-20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439474PMC
August 2020

Rationale and design of "Hearts & Parks": study protocol for a pragmatic randomized clinical trial of an integrated clinic-community intervention to treat pediatric obesity.

BMC Pediatr 2020 06 26;20(1):308. Epub 2020 Jun 26.

Duke Clinical Research Institute, Duke University, Durham, NC, 27710, USA.

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 .
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http://dx.doi.org/10.1186/s12887-020-02190-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318397PMC
June 2020

Genomic profiling in locally advanced and inflammatory breast cancer and its link to DCE-MRI and overall survival.

Int J Hyperthermia 2015 Jun 26;31(4):386-95. Epub 2015 Mar 26.

Department of Radiation Oncology, Duke University Medical Center , Durham , North Carolina .

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.
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http://dx.doi.org/10.3109/02656736.2015.1016557DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4955681PMC
June 2015

A translatable predictor of human radiation exposure.

PLoS One 2014 25;9(9):e107897. Epub 2014 Sep 25.

Division of Hematologic Malignancies and Cellular Therapy, Department of Medicine, Duke University Medical Center, Durham, NC, United States of America; Division of Hematology/Oncology, Department of Medicine, Broad Stem Cell Research Center, Jonnson Comprehensive Cancer Center, U.C.L.A., Los Angeles, CA, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107897PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177872PMC
June 2015

A methodology for utilization of predictive genomic signatures in FFPE samples.

BMC Med Genomics 2011 Jul 11;4:58. Epub 2011 Jul 11.

Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, NC 27708, USA.

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.
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http://dx.doi.org/10.1186/1755-8794-4-58DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3146808PMC
July 2011

Retraction: A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N Engl J Med 2006;355:570-80.

N Engl J Med 2011 Mar 2;364(12):1176. Epub 2011 Mar 2.

Chapel Hill, NC, USA..

To the Editor: We would like to retract our article, "A Genomic Strategy to Refine Prognosis in Early-Stage Non-Small-Cell Lung Cancer,"(1) which was published in the Journal on August 10, 2006. Using a sample set from a study by the American College of Surgeons Oncology Group (ACOSOG) and a collection of samples from a study by the Cancer and Leukemia Group B (CALGB), we have tried and failed to reproduce results supporting the validation of the lung metagene model described in the article. We deeply regret the effect of this action on the work of other investigators.
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http://dx.doi.org/10.1056/NEJMc1101915DOI Listing
March 2011

Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.

PLoS One 2010 Jul 12;5(7):e11535. Epub 2010 Jul 12.

Division of Cellular Therapy, Department of Medicine, Duke University, Durham, North Carolina, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0011535PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2902517PMC
July 2010

Intratumor heterogeneity and precision of microarray-based predictors of breast cancer biology and clinical outcome.

J Clin Oncol 2010 May 5;28(13):2198-206. Epub 2010 Apr 5.

Department of Biostatistics, Duke University Medical Center, Medical Center Box 3712, Durham, NC 27710, USA.

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.
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http://dx.doi.org/10.1200/JCO.2009.26.7245DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2860437PMC
May 2010

Ovarian cancer tumor infiltrating T-regulatory (T(reg)) cells are associated with a metastatic phenotype.

Gynecol Oncol 2010 Mar 14;116(3):556-62. Epub 2009 Dec 14.

Division of Gynecologic Oncology/Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC 27710, USA.

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.
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http://dx.doi.org/10.1016/j.ygyno.2009.11.020DOI Listing
March 2010

Microarray analysis of early stage serous ovarian cancers shows profiles predictive of favorable outcome.

Clin Cancer Res 2009 Apr 24;15(7):2448-55. Epub 2009 Mar 24.

Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina 27710, USA.

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.
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http://dx.doi.org/10.1158/1078-0432.CCR-08-2430DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3050629PMC
April 2009

Characterizing the developmental pathways TTF-1, NKX2-8, and PAX9 in lung cancer.

Proc Natl Acad Sci U S A 2009 Mar 11;106(13):5312-7. Epub 2009 Mar 11.

Institute for Genome Sciences and Policy, Department of Medicine, and Institute for Statistics and Decision Sciences, Duke University, Durham, NC 27710, USA.

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.
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http://dx.doi.org/10.1073/pnas.0900827106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2664027PMC
March 2009

Novel tumor sampling strategies to enable microarray gene expression signatures in breast cancer: a study to determine feasibility and reproducibility in the context of clinical care.

Breast Cancer Res Treat 2009 Dec 18;118(3):635-43. Epub 2009 Feb 18.

Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA.

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.
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http://dx.doi.org/10.1007/s10549-008-0301-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3786337PMC
December 2009

Failure of terminal erythroid differentiation in EKLF-deficient mice is associated with cell cycle perturbation and reduced expression of E2F2.

Mol Cell Biol 2008 Dec 13;28(24):7394-401. Epub 2008 Oct 13.

Hematopoiesis Section, Genetics and Molecular Biology Branch, NHGRI, NIH, 49 Convent Drive, Bethesda, Maryland 20892-44421, USA.

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.
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http://dx.doi.org/10.1128/MCB.01087-08DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2593440PMC
December 2008

Unfolded protein response genes regulated by CED-1 are required for Caenorhabditis elegans innate immunity.

Dev Cell 2008 Jul;15(1):87-97

Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC 27710, USA.

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.
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http://dx.doi.org/10.1016/j.devcel.2008.05.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2517226PMC
July 2008

Gene expression signatures, clinicopathological features, and individualized therapy in breast cancer.

JAMA 2008 Apr;299(13):1574-87

Duke Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina 27708, USA.

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.
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http://dx.doi.org/10.1001/jama.299.13.1574DOI Listing
April 2008

Gene expression signatures of radiation response are specific, durable and accurate in mice and humans.

PLoS One 2008 Apr 2;3(4):e1912. Epub 2008 Apr 2.

Division of Cellular Therapy, Duke University Medical Center, Durham, North Carolina, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0001912PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2271127PMC
April 2008

An integrated approach to the prediction of chemotherapeutic response in patients with breast cancer.

PLoS One 2008 Apr 2;3(4):e1908. Epub 2008 Apr 2.

Duke Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0001908PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2270912PMC
April 2008

Pharmacogenomic strategies provide a rational approach to the treatment of cisplatin-resistant patients with advanced cancer.

J Clin Oncol 2007 Oct;25(28):4350-7

Division of Medical Oncology, Department of Medicine, Duke University, Durham, NC 27710, USA.

Purpose: Standard treatment for advanced non-small-cell lung cancer (NSCLC) includes the use of a platinum-based chemotherapy regimen. However, response rates are highly variable. Newer agents, such as pemetrexed, have shown significant activity as second-line therapy and are currently being evaluated in the front-line setting. We utilized a genomic strategy to develop signatures predictive of chemotherapeutic response to both cisplatin and pemetrexed to provide a rational approach to effective individualized medicine.

Methods: Using in vitro drug sensitivity data, coupled with microarray data, we developed gene expression signatures predicting sensitivity to cisplatin and pemetrexed. Signatures were validated with response data from 32 independent ovarian and lung cancer cell lines as well as 59 samples from patients previously treated with cisplatin.

Results: Genomic-derived signatures of cisplatin and pemetrexed sensitivity were shown to accurately predict sensitivity in vitro and, in the case of cisplatin, to predict treatment response in patients treated with cisplatin. The accuracy of the cisplatin predictor, based on available clinical data, was 83.1% (sensitivity, 100%; specificity 57%; positive predictive value, 78%; negative predictive value, 100%). Interestingly, an inverse correlation was seen between in vitro cisplatin and pemetrexed sensitivity, and importantly, between the likelihood of cisplatin and pemetrexed response in patients.

Conclusion: The use of genomic predictors of response to cisplatin and pemetrexed can be incorporated into strategies to optimize therapy for advanced solid tumors.
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http://dx.doi.org/10.1200/JCO.2007.11.0593DOI Listing
October 2007

Gene expression signatures that predict radiation exposure in mice and humans.

PLoS Med 2007 Apr;4(4):e106

Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, United States of America.

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.
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http://dx.doi.org/10.1371/journal.pmed.0040106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1845155PMC
April 2007

An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer.

J Clin Oncol 2007 Feb;25(5):517-25

Division of Gynecologic Surgical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.

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.
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http://dx.doi.org/10.1200/JCO.2006.06.3743DOI Listing
February 2007

Genomic signatures in non-small-cell lung cancer: targeting the targeted therapies.

Curr Oncol Rep 2006 Jul;8(4):252-7

Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC 27708, USA.

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.
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http://dx.doi.org/10.1007/s11912-006-0029-1DOI Listing
July 2006

Genomic signatures to guide the use of chemotherapeutics.

Nat Med 2006 Nov 22;12(11):1294-300. Epub 2006 Oct 22.

Duke Institute for Genome Sciences and Policy, Duke University, Box 3382, Durham, North Carolina 27710, USA.

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.
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http://dx.doi.org/10.1038/nm1491DOI Listing
November 2006

Assessing incomplete deprotection of microarray oligonucleotides in situ.

Nucleic Acids Res 2006 4;34(19):e131. Epub 2006 Oct 4.

Center for Genome Technology, Institute for Genome Science and Policy, Duke University, Durham, NC, USA.

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.
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http://dx.doi.org/10.1093/nar/gkl713DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1636491PMC
December 2006

A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer.

N Engl J Med 2006 Aug;355(6):570-80

Institute for Genome Sciences and Policy, Duke University, Durham, NC 27708, USA.

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.
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http://dx.doi.org/10.1056/NEJMoa060467DOI Listing
August 2006

Phase I trial of sequential low-dose 5-aza-2'-deoxycytidine plus high-dose intravenous bolus interleukin-2 in patients with melanoma or renal cell carcinoma.

Clin Cancer Res 2006 Aug;12(15):4619-27

Department of Medicine, Division of Medical Oncology, Duke University Medical Center, Durham, NC 27710, USA.

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.
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http://dx.doi.org/10.1158/1078-0432.CCR-06-0883DOI Listing
August 2006

Toxicogenomic studies of the rat brain at an early time point following acute sarin exposure.

Neurochem Res 2006 Mar 13;31(3):367-81. Epub 2006 May 13.

Department of Pharmacology and Cancer Biology, Duke University Medical Center, P.O. Box 3813, Durham, NC, 27710, USA.

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.
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http://dx.doi.org/10.1007/s11064-005-9023-5DOI Listing
March 2006