Gene expression profiling of copper-resistant Caco-2 clones

Metallomics ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1521-1529
Author(s):  
Charles O’Doherty ◽  
Joanne Keenan ◽  
Fiona O’Neill ◽  
Martin Clynes ◽  
Indre Sinkunaite ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Patterns ◽  
Cu Resistance

Multiple Caco-2 clones resistant to CuSO4 and Cu proteinate were characterised to evaluate transcriptomic expression patterns associated with intestinal Cu-resistance

scholarly journals Three Years Follow-Up Study Showed Prenatal Methamphetamine Exposure May Cause Chronic Abnormalities In Transcriptomic Pattern

2021 ◽  
Author(s):  
Arvin Haghighatfard ◽  
Soha Seifollahi ◽  
Pegah Rajabi ◽  
Niloofar Rahmani ◽  
Rojin Ghannadzadeh
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Rna Extraction ◽  
Childbearing Age ◽  
Methamphetamine Use ◽  
Methamphetamine Use Disorder

Abstract Background: The high rate of methamphetamine use disorder among young adults and women of childbearing age makes it imperative to clarify the long-term effects of Methamphetamine exposure on the offspring. Behavioral and cognitive problems had been reported in children with parental Methamphetamine exposure (PME). The present study aimed to assess the acute and chronic effects of PME in molecular regulations and gene expression profiles of children during their first years of life.Methods: All subjects were recruited before birth, and sampling was conducted from the first ten days of birth, twelve months, twenty months, and thirty-six months of age. Finally, 2658 children with PME and 3573 normal children had been finished the follow-up. RNA extraction was operated from blood samples and gene expression profiling was conducted by using the Affymetrix GeneChip Human Genome U133 plus 2.0 Array Platform. Gene expression data were confirmed by Real-time PCR. Results: Gene expression profiling during thirty-six months showed several constant mRNA level alterations in children with PME compared with normal. These genes are involved in several gene ontologies and pathways involved with the immune system, neuronal functions, and bioenergetic metabolism. It seems that Methamphetamine use disorder before and during the pregnancy period may affect the expression profile of children, and these changes could remain years after birth. Affected genes have some similarities with the gene expression patterns of addiction, psychiatric disorders, neurodevelopmental disabilities, and immune deficiencies. Conclusion: Findings may shed light on the molecular effects of prenatal methamphetamine exposure and may lead to new psychological and somatic caring protocols for these children based on their potential abnormalities.

scholarly journals What can we learn from gene expression profiling of mouse oocytes?

Reproduction ◽  
2008 ◽  
Vol 135 (5) ◽  
pp. 581-592 ◽  
Author(s):  
Toshio Hamatani ◽  
Mitsutoshi Yamada ◽  
Hidenori Akutsu ◽  
Naoaki Kuji ◽  
Yoshiyuki Mochimaru ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Oocyte Quality ◽  
Preimplantation Development ◽  
Preimplantation Embryos ◽  
Gene Expressions ◽  
Oocyte Competence

Mammalian ooplasm supports the preimplantation development and reprograms the introduced nucleus transferred from a somatic cell to confer pluripotency in a cloning experiment. However, the underlying molecular mechanisms of oocyte competence remain unknown. Recent advances in microarray technologies have allowed gene expression profiling of such tiny specimens as oocytes and preimplantation embryos, generating a flood of information about gene expressions. So, what can we learn from it? Here, we review the initiative global gene expression studies of mouse and/or human oocytes, focusing on the lists of maternal transcripts and their expression patterns during oogenesis and preimplantation development. Especially, the genes expressed exclusively in oocytes should contribute to the uniqueness of oocyte competence, driving mammalian development systems of oocytes and preimplantation embryos. Furthermore, we discuss future directions for oocyte gene expression profiling, including discovering biomarkers of oocyte quality and exploiting the microarray data for ‘making oocytes’.

scholarly journals Cellular-resolution gene expression profiling in the neonatal marmoset brain reveals dynamic species- and region-specific differences

2021 ◽  
Vol 118 (18) ◽  
pp. e2020125118
Author(s):  
Yoshiaki Kita ◽  
Hirozumi Nishibe ◽  
Yan Wang ◽  
Tsutomu Hashikawa ◽  
Satomi S. Kikuchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Neural Circuit ◽  
Expression Patterns ◽  
Three Dimensional ◽  
Control Of Gene Expression ◽  
Cellular Resolution

Precise spatiotemporal control of gene expression in the developing brain is critical for neural circuit formation, and comprehensive expression mapping in the developing primate brain is crucial to understand brain function in health and disease. Here, we developed an unbiased, automated, large-scale, cellular-resolution in situ hybridization (ISH)–based gene expression profiling system (GePS) and companion analysis to reveal gene expression patterns in the neonatal New World marmoset cortex, thalamus, and striatum that are distinct from those in mice. Gene-ontology analysis of marmoset-specific genes revealed associations with catalytic activity in the visual cortex and neuropsychiatric disorders in the thalamus. Cortically expressed genes with clear area boundaries were used in a three-dimensional cortical surface mapping algorithm to delineate higher-order cortical areas not evident in two-dimensional ISH data. GePS provides a powerful platform to elucidate the molecular mechanisms underlying primate neurobiology and developmental psychiatric and neurological disorders.

Gene expression profiling reveals the profound upregulation of hypoxia-responsive genes in primary human astrocytes

2006 ◽  
Vol 25 (3) ◽  
pp. 435-449 ◽  
Author(s):  
S. M. Mense ◽  
A. Sengupta ◽  
M. Zhou ◽  
C. Lan ◽  
G. Bentsman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Hela Cells ◽  
Expression Profiling ◽  
Target Genes ◽  
Expression Patterns ◽  
Angiogenic Growth Factors ◽  
Microarray Gene Expression ◽  
Human Astrocytes ◽  
The Brain

Oxygen is vital for the development and survival of mammals. In response to hypoxia, the brain initiates numerous adaptive responses at the organ level as well as at the molecular and cellular levels, including the alteration of gene expression. Astrocytes play critical roles in the proper functioning of the brain; thus the manner in which astrocytes respond to hypoxia is likely important in determining the outcome of brain hypoxia. Here, we used microarray gene expression profiling and data-analysis algorithms to identify and analyze hypoxia-responsive genes in primary human astrocytes. We also compared gene expression patterns in astrocytes with those in human HeLa cells and pulmonary artery endothelial cells (ECs). Remarkably, in astrocytes, five times as many genes were induced as suppressed, whereas in HeLa and pulmonary ECs, as many as or more genes were suppressed than induced. More genes encoding hypoxia-inducible functions, such as glycolytic enzymes and angiogenic growth factors, were strongly induced in astrocytes compared with HeLa cells. Furthermore, gene ontology and computational algorithms revealed that many target genes of the EGF and insulin signaling pathways and the transcriptional regulators Myc, Jun, and p53 were selectively altered by hypoxia in astrocytes. Indeed, Western blot analysis confirmed that two major signal transducers mediating insulin and EGF action, Akt and MEK1/2, were activated by hypoxia in astrocytes. These results provide a global view of the signaling and regulatory network mediating oxygen regulation in human astrocytes.

scholarly journals Prenatal Methamphetamine Exposure could Cause Chronic Abnormalities in Transcriptomic Pattern; an Extended Follow-up Cohort Study

2021 ◽  
Author(s):  
Arvin Haghighatfard ◽  
Soha Seifollahi ◽  
Pegah Rajabi ◽  
Niloofar Rahmani ◽  
Rojin Ghannad zadeh
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Rna Extraction ◽  
High Rate ◽  
Childbearing Age ◽  
Methamphetamine Abuse

Abstract BackgroundThe high rate of methamphetamine abuse among young adults and women of childbearing age makes it imperative to clarify the long-term effects of Methamphetamine exposure on the offspring. Behavioral and cognitive problems had reported in children with parental Methamphetamine exposure (PME). The present study aimed to assess the acute and chronic effects of PME in molecular regulations and gene expression profiles of children during their first years of life.ResultsAll subjects were recruited before birth, and sampling was conducted from the first ten days of birth, twelve months, twenty months and thirty-six months of age. Finally, 2658 children with PME and 3573 normal children had been finished the follow-up. RNA extraction was operated from blood samples and gene expression profiling was conducted by using the Affymetrix GeneChip Human Genome U133 plus 2.0 Array Platform. Gene expression data were confirmed by Real-time PCR. Gene expression profiling during thirty-six months showed several constant mRNA level alterations in children with PME compared with normal. These genes are involved in several gene ontology and pathways involved with the immune system, neuronal functions and bioenergetic metabolism. It seems that Methamphetamine abuse before and during the pregnancy period may affect the expression profile of children, and these changes could be remain years after birth. Affected genes have some similarities to the gene expression patterns of addiction, psychiatric disorders, neurodevelopmental disabilities and immune deficiencies. ConclusionFindings may shed light on the molecular effects of prenatal methamphetamine exposure and may lead to new psychological and somatic caring protocols for these children based on their potential abnormalities.

Impact of Gene Expression Profiling on Diagnosis and Prognostication in Cytogenetically Normal AML.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1487-1487
Author(s):  
Lars Bullinger ◽  
Thomas Hielscher ◽  
Ursula Botzenhardt ◽  
Sabrina Heinrich ◽  
Richard Schlenk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Patterns ◽  
Wald Test ◽  
Gene Expression Patterns ◽  
Molecular Heterogeneity ◽  
Prognostic Impact ◽  
Prognostic Information ◽  
Data Set

Abstract Cytogenetically normal acute myeloid leukemia (CN-AML) comprises a biologically and clinically heterogeneous group of AML. In the past years, molecular markers like FLT3, CEBPA and NPM1 gene mutations have been identified in CN-AML, and the presence of such mutations carries important prognostic information. Furthermore, DNA microarray-based gene expression profiling (GEP) has been shown to capture the molecular heterogeneity of cancers, and has been applied to build classifiers and clinical outcome predictors in AML. While prior studies have defined gene expression patterns associated with NPM1, CEBPA, and FLT3, we assessed the clinical relevance of gene signatures. We profiled a large set of clinically well annotated CN-AML specimens (n=296 entered on two multicenter trials for patients <60 years (AMLSG HD98A and AMLSG 07-04). The 142 cases from the AMLSG HD98A trial were analyzed using a 40k cDNA microarray platform and the 154 cases from trial AMLSG 07-04 using Affymetrix microarrays (Human Genome U133 Plus 2.0 Arrays). In this data set we applied supervised analyses (LASSO penalized logistic regression) to define gene expression patterns characterizing FLT3 internal tandem duplication (ITD), CEPBA and NPM1 mutations as well as outcome signatures. We were able to define distinct signatures associated with NPM1, CEBPA, and FLT3 consisting of 39, 27, and 47 genes, respectively. The NPM1 signature revealed a high prediction accuracy of >95% in leave-one-out cross validated classification. Prediction of FLT3-ITD or CEBPA mutation performed less well with accuracies of 80% and 73%, respectively. However, for both CEBPA and FLT3-ITD the predicted mutation class labels performed slightly better than the marker itself with regard to the prognostic impact on overall survival (CEPBA: p=0.006 vs. p=0.007, FLT3-ITD p=9.57e-06 vs. p=5.11e-05; logrank test). In addition, using LASSO we also could define a signature associated with event free survival (EFS) in the cases from the AMLSG 07-04 trial. Adjusted for age, NPM1, and FLT3-ITD mutational status this signature was significantly associated with EFS (p=0.005; Wald test), and validation in our independent cDNA data set also provided significant prognostic information (p=0.02; Wald test). Thus, GEP-based classification of CN-AML might help to identify alternative genetic changes that either phenocopy or block the effects of common molecular aberrations. Furthermore, gene expression patterns of yet unknown aberrations are reflected in prognostic signatures. Therefore, signature genes also provide a starting point to dissect “mutations” pathways, and our findings underscore the potential clinical utility of a gene expression based measure in CN-AML.

scholarly journals Distinct Gene Expression Profiling after Infection of Immature Human Monocyte-Derived Dendritic Cells by the Attenuated Poxvirus Vectors MVA and NYVAC

2007 ◽  
Vol 81 (16) ◽  
pp. 8707-8721 ◽  
Author(s):  
Susana Guerra ◽  
José Luis Nájera ◽  
José Manuel González ◽  
Luis A. López-Fernández ◽  
Nuria Climent ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dendritic Cells ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Human Monocyte ◽  
Type I ◽  
Mrna Levels ◽  
Antigen Uptake

ABSTRACT Although recombinants based on the attenuated poxvirus vectors MVA and NYVAC are currently in clinical trials, the nature of the genes triggered by these vectors in antigen-presenting cells is poorly characterized. Using microarray technology and various analysis conditions, we compared specific changes in gene expression profiling following MVA and NYVAC infection of immature human monocyte-derived dendritic cells (MDDC). Microarray analysis was performed at 6 h postinfection, since these viruses induced extensive cytopathic effects, rRNA breakdown, and apoptosis at late times postinfection. MVA- and NYVAC-infected MDDC shared upregulation of 195 genes compared to uninfected cells: MVA specifically upregulated 359 genes, and NYVAC upregulated 165 genes. Microarray comparison of NYVAC and MVA infection revealed 544 genes with distinct expression patterns after poxvirus infection and 283 genes specifically upregulated after MVA infection. Both vectors upregulated genes for cytokines, cytokine receptors, chemokines, chemokine receptors, and molecules involved in antigen uptake and processing, including major histocompatibility complex genes. mRNA levels for interleukin 12β (IL-12β), beta interferon, and tumor necrosis factor alpha were higher after MVA infection than after NYVAC infection. The expression profiles of transcription factors such as NF-κB/Rel and STAT were regulated similarly by both viruses; in contrast, OASL, MDA5, and IRIG-I expression increased only during MVA infection. Type I interferon, IL-6, and Toll-like receptor pathways were specifically induced after MVA infection. Following MVA or NYVAC infection in MDDC, we found similarities as well as differences between these virus strains in the expression of cellular genes with immunological function, which should have an impact when these vectors are used as recombinant vaccines.

All Clinically Relevant Leukemia Subtypes Can Be Diagnosed and Classified Based Solely on Gene Expression Profiling with an Accuracy of 95.1%: A Study on 1337 Adult Patients.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 143-143
Author(s):  
Torsten Haferlach ◽  
Alexander Kohlmann ◽  
Susanne Schnittger ◽  
Martin Dugas ◽  
Sylvia Merk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Sensitivity And Specificity ◽  
Diagnostic Tool ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Second Step ◽  
Support Vector ◽  
Therapeutic Decisions

Abstract So far, comprehensive diagnosis of leukemia requires a combination of cytomorphology, immunophenotyping, and genetic methods. We aimed at developing a new diagnostic tool based solely on gene expression profiling to accurately predict all clinically relevant subtypes of leukemia in adults and to distinguish these from normal bone marrow. Therefore, we analyzed samples from 1337 untreated patients at diagnosis and healthy donors using oligonucleotide microarrays. The first series of 937 cases was hybridized to HG-U133A+B microarrays (Affymetrix). The following 13 subgroups were included: 620 AML (42 t(15;17); 38 t(8;21); 49 inv(16); 47 t(11q23); 75 complex aberrant karyotype; 193 normal karyotype; 176 other cytogenetic abn.); 152 ALL (26 Pro-B-ALL/t(11q23); 12 ALL-t(8;14); 32 T-ALL; 82 c-ALL/Pre-B-ALL); 75 CML, 45 CLL, and 45 bone marrows from healthy volunteers or non-leukemia pts. (nBM). For each disease entity the top 100 differentially expressed genes were calculated in a one-versus-all (OVA) approach. Class prediction was performed using support vector machines (SVM). Prediction accuracy was estimated by 10-fold cross validation (CV) and assessed for robustness in a resampling approach. 891 of the 937 samples (95.1%) were correctly classified (10-fold CV). A resampling approach with 2/3 training and 1/3 test cohort (100 runs of SVM) confirmed this high accuracy (median, 93.8%). In particular, a median of 100% sensitivity and specificity was achieved for AML with t(15;17), t(8;21), and inv(16), as well as for Pro-B-ALL/t(11q23), and CLL. The median specificity was at least 99.7% in all subgroups except for AML normal/other (median specificity, 93.7%). In a second step T-ALL cases were separated into cortical and immature ones (accuracy, 84.4%) and c-ALL/Pre-B-ALL into cases with and without t(9;22) (accuracy, 82.9%). The second prospective series comprized 400 unselected cases which were hybridized to the new generation HG-U133 Plus 2.0 microarrays (Affymetrix). To validate the diagnostic accuracy of our approach these cases were processed blinded in parallel to routine diagnostic work-up and classified based on the gene expression signatures discovered in the first series described above. Applying a first classification step as described above the 13 different diagnoses were predicted with an accuracy of 94.5%. Failures were mostly due to misclassification into biologically related subgroups, e.g. AML with del(5q) aberrations classified as AML with complex aberrant karyotype. In the second step (separation of the two T-ALL subtypes, and c-ALL/Pre-B-ALL with or without t(9;22)) accuracies of 100% and 70.6% respectively were achieved. In conclusion, we were able to identify within a routine diagnostic workflow distinct expression profiles for all clinically and prognostically relevant adult leukemia subtypes and their discrimination from nBM based only on gene expression data. Accuracy, sensitivity, and specificity were higher than achieved with each of the gold standard techniques alone used today. Thus, gene expression patterns analyzed by microarrays qualify as a diagnostic tool in a routine setting for leukemia diagnosis and classification and may guide relevant therapeutic decisions.

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