scholarly journals Toxicogenomics in Drug Development

2003 ◽  
Vol 31 (5) ◽  
pp. 471-479 ◽  
Author(s):  
Nelson Guerreiro ◽  
Frank Staedtler ◽  
Olivier Grenet ◽  
Jeanne Kehren ◽  
Salah-Dine Chibout
Keyword(s):  
Gene Expression ◽  
Drug Development ◽  
Expression Profiling ◽  
Development Process ◽  
Molecular Mechanisms ◽  
Biomarker Discovery ◽  
Expression Profiles ◽  
Dna Polymorphisms ◽  
Drug Development Process ◽  
Predictive Toxicology

Toxicogenomics represents the merging of toxicology with technologies that have been developed, together with bioinformatics, to identify and quantify global gene expression changes. It represents a new paradigm in drug development and risk assessment, which promises to generate a wealth of information towards an increased understanding of the molecular mechanisms that lead to drug toxicity and efficacy, and of DNA polymorphisms responsible for individual susceptibility to toxicity. Gene expression profiling, through the use of DNA microarray and proteomic technologies will aid in establishing links between expression profiles, mode of action and traditional toxic endpoints. Such patterns of gene expression, or `molecular fingerprints' could be used as diagnostic or predictive markers of exposure, that is characteristic of a specific mechanism of induction of that toxic or efficacious effect. It is anticipated that toxicogenomics will be increasingly integrated into all phases of the drug development process particularly in mechanistic and predictive toxicology, and biomarker discovery. This review provides an overview of the expression profiling technologies applied in toxicogenomics, and discusses the promises as well as the future challenges of applying this discipline to the drug development process.

Gene-expression profiling and array-based CGH classify CD4+CD56+ hematodermic neoplasm and cutaneous myelomonocytic leukemia as distinct disease entities

Blood ◽  
2006 ◽  
Vol 109 (4) ◽  
pp. 1720-1727 ◽  
Author(s):  
Remco Dijkman ◽  
Remco van Doorn ◽  
Károly Szuhai ◽  
Rein Willemze ◽  
Maarten H. Vermeer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Plasmacytoid Dendritic Cell ◽  
Chromosome 9 ◽  
Comparative Genomic ◽  
Genomic Amplification ◽  
Myelomonocytic Leukemia ◽  
Hematodermic Neoplasm

Abstract CD4+CD56+ hematodermic neoplasm (CD4+CD56+HN) is an aggressive hematopoietic malignancy with distinct clinicopathologic and immunophenotypic features that commonly involve the skin, bone marrow, and blood. Differentiation from cutaneous myelomonocytic leukemia (c-AML) may be exceedingly difficult and requires extensive phenotyping. The molecular mechanisms involved in the development of CD4+CD56+HN are largely unresolved. Moreover, recurrent chromosomal alterations have not yet been precisely defined in CD4+CD56+HN and c-AML. In the present study an integrated genomic analysis using expression profiling and array-based comparative genomic hybridization (CGH) was performed on lesional skin biopsy samples of patients with CD4+CD56+HN and c-AML. Our results demonstrate that CD4+CD56+HN and c-AML show distinct gene-expression profiles and distinct patterns of chromosomal aberrations. CD4+CD56+HN is characterized by recurrent deletion of regions on chromosome 4 (4q34), chromosome 9 (9p13-p11 and 9q12-q34), and chromosome 13 (13q12-q31) that contain several tumor suppressor genes with diminished expression (Rb1, LATS2). Elevated expression of the oncogenes HES6, RUNX2, and FLT3 was found but was not associated with genomic amplification. We noted high expression of various plasmacytoid dendritic-cell (pDC)–related genes, pointing to the cell of origin of this malignancy.

Gene expression profiling of sex differences in HIF1-dependent adaptive cardiac responses to chronic hypoxia

2010 ◽  
Vol 109 (4) ◽  
pp. 1195-1202 ◽  
Author(s):  
Romana Bohuslavová ◽  
František Kolář ◽  
Lada Kuthanová ◽  
Jan Neckář ◽  
Aleš Tichopád ◽  
...  
Keyword(s):  
Gene Expression ◽  
Right Ventricle ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Chronic Hypoxia ◽  
Expression Profiles ◽  
Adaptive Responses ◽  
Expression Change ◽  
The Right

Although physiological responses to chronic hypoxia, including pulmonary hypertension and right ventricular hypertrophy, have been well described, the molecular mechanisms involved in cardiopulmonary adaptations are still not fully understood. We hypothesize that adaptive responses to chronic hypoxia are the result of altered transcriptional regulations in the right and left ventricles. Here we report results from the gene expression profiling of adaptive responses in a chronically hypoxic heart. Of 11 analyzed candidate genes, the expression of seven and four genes, respectively, was significantly altered in the right ventricle of hypoxic male and female mice. In the transcriptional profile of the left ventricle, we identified a single expression change in hypoxic males ( Vegfa gene). To directly test the role of HIF1, we analyzed the expression profile in Hif1a partially deficient mice exposed to moderate hypoxia. Our data showed that Hif1a partial deficiency significantly altered transcriptional profiles of analyzed genes in hypoxic hearts. The expression changes were only detected in two genes in the right ventricle of Hif1a+/− males and in one gene in the right ventricle of Hif1a+/− females. First, our results suggest that hypoxia mainly affects adaptive expression profiles in the right ventricle and that each ventricle can respond independently. Second, our findings indicate that HIF1a plays an important role in adaptive cardiopulmonary responses and the dysfunction of HIF1 pathways considerably affects transcriptional regulation in the heart. Third, our data reveal significant differences between males and females in cardiac adaptive responses to hypoxia and indicate the necessity of optimizing diagnostic and therapeutic procedures in clinical practice, with respect to sex.

scholarly journals Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

2010 ◽  
Vol 28 (15) ◽  
pp. 2529-2537 ◽  
Author(s):  
Torsten Haferlach ◽  
Alexander Kohlmann ◽  
Lothar Wieczorek ◽  
Giuseppe Basso ◽  
Geertruy Te Kronnie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Clinical Utility ◽  
Biomarker Discovery ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Diagnostic Methods ◽  
Stage I ◽  
Data Set

Purpose The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. Methods The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling–based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. Results On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. Conclusion Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias.

Chemo-response biomarker discovery via expression profiling using soft-tissue sarcoma xenografts

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 9569-9569
Author(s):  
S. Bruheim ◽  
Y. Xi ◽  
J. Ju ◽  
O. Fodstad
Keyword(s):  
Gene Expression ◽  
Soft Tissue ◽  
Soft Tissue Sarcoma ◽  
Expression Profiling ◽  
Biomarker Discovery ◽  
Expression Profiles ◽  
Clinical Samples ◽  
Marker Genes ◽  
Candidate Marker ◽  
General Response

9569 Background: Soft-tissue sarcoma (STS) constitute a heterogeneous group of tumours of mesenchymal origin. Whereas the mainstay of treatment has been surgery and radiation, these tumours are generally considered as quite chemoresistant. However, it is well known that subgroups of patients benefit from chemotherapy. Markers that could predict drug response would therefore be beneficial for the management of this malignancy. We have previously established panel of 17 unique human soft tissue xenografts, representing 7 different histological subgroups and assessed their responsiveness to doxorubicin, ifosfamide, etoposide, and cisplatin. We wanted to utilize these xenografts as a model system to discover for novel candidate marker genes for STS chemo-response. Methods: GE Uniset Human 20K microarrays were used to obtain gene expression profiles from the each xenografts. One-way ANOVA test with a Benjamini-Hochberg multiple test correction allowing a false discovery rate of 5% was used to identify genes with significantly differential expression. Results: Doxorubicin, ifosfamide, etoposide and cisplatin were efficient in 6/17, 10/17, 1/17 and 7/17 xenografts respectively. However, in the expression profiles obtained none of the genes showed significantly correlation with chemo-responsiveness to any of the drugs. Two of the xenografts, TAX 1 and TAX 2, both originate from a malignant fibrous histiocytoma (MFH) in the same patient, but show strikingly different sensitivity to ifosfamide (TAX1 resistant, TAX2 sensitive). When triplicate hybridizations of TAX1 and 2 were compared, 294 genes met the above criteria. In addition we identified a subset of 122 genes that were flagged absent in one of the specimens, present in the other. Among genes with an already described role in mediating drug resistance are GST-pi and glutathione peroxidase. Taken together, these results indicate that discovery of general response markers in STSs may be difficult due to the heterogeneity of the different subgroups constituting this malignancy. Conclusions: Gene expression profiling of the TAX 1 and TAX 2 xenografts revealed a number of interesting candidate marker genes for ifosfamide sensitivity of MFH. This list of genes will be further refined by validation in clinical samples. No significant financial relationships to disclose.

Intelligent Drug Development

2014 ◽  
Author(s):  
Michael Tansey
Keyword(s):  
Clinical Trials ◽  
Cost Effectiveness ◽  
Drug Development ◽  
Clinical Research ◽  
Development Process ◽  
Drug Development Process ◽  
Individual Trial ◽  
Specific Technology

Clinical research is heavily regulated and involves coordination of numerous pharmaceutical-related disciplines. Each individual trial involves contractual, regulatory, and ethics approval at each site and in each country. Clinical trials have become so complex and government requirements so stringent that researchers often approach trials too cautiously, convinced that the process is bound to be insurmountably complicated and riddled with roadblocks. A step back is needed, an objective examination of the drug development process as a whole, and recommendations made for streamlining the process at all stages. With Intelligent Drug Development, Michael Tansey systematically addresses the key elements that affect the quality, timeliness, and cost-effectiveness of the drug-development process, and identifies steps that can be adjusted and made more efficient. Tansey uses his own experiences conducting clinical trials to create a guide that provides flexible, adaptable ways of implementing the necessary processes of development. Moreover, the processes described in the book are not dependent either on a particular company structure or on any specific technology; thus, Tansey's approach can be implemented at any company, regardless of size. The book includes specific examples that illustrate some of the ways in which the principles can be applied, as well as suggestions for providing a better context in which the changes can be implemented. The protocols for drug development and clinical research have grown increasingly complex in recent years, making Intelligent Drug Development a needed examination of the pharmaceutical process.

scholarly journals Modulation of the Immune Response by Deferasirox in Myelodysplastic Syndrome Patients

2021 ◽  
Vol 14 (1) ◽  
pp. 41
Author(s):  
Hana Votavova ◽  
Zuzana Urbanova ◽  
David Kundrat ◽  
Michaela Dostalova Merkerova ◽  
Martin Vostry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Blood Cell ◽  
Myelodysplastic Syndrome ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Adaptive Immune Response ◽  
Gene Expression Profiles ◽  
Iron Chelator ◽  
Multiple Cancer

Deferasirox (DFX) is an oral iron chelator used to reduce iron overload (IO) caused by frequent blood cell transfusions in anemic myelodysplastic syndrome (MDS) patients. To study the molecular mechanisms by which DFX improves outcome in MDS, we analyzed the global gene expression in untreated MDS patients and those who were given DFX treatment. The gene expression profiles of bone marrow CD34+ cells were assessed by whole-genome microarrays. Initially, differentially expressed genes (DEGs) were determined between patients with normal ferritin levels and those with IO to address the effect of excessive iron on cellular pathways. These DEGs were annotated to Gene Ontology terms associated with cell cycle, apoptosis, adaptive immune response and protein folding and were enriched in cancer-related pathways. The deregulation of multiple cancer pathways in iron-overloaded patients suggests that IO is a cofactor favoring the progression of MDS. The DEGs between patients with IO and those treated with DFX were involved predominantly in biological processes related to the immune response and inflammation. These data indicate DFX modulates the immune response mainly via neutrophil-related genes. Suppression of negative regulators of blood cell differentiation essential for cell maturation and upregulation of heme metabolism observed in DFX-treated patients may contribute to the hematopoietic improvement.

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