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Results for “Expression profiling”

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PubMed2004

Stratification of acute myeloid leukemia based on gene expression profiles.

Acute myeloid leukemia (AML) is characterized by clonal growth of immature leukemic blasts and develops either de novo or secondarily to anticancer treatment or to other hematologic disorders. Given that the current classification of AML, which is based on blast karyotype and morphology, is not sufficiently robust to predict the prognosis of each affected individual, new stratification schemes that are of better prognostic value are needed. Global profiling of gene expression in AML blasts has the potential both to identify a small number of genes whose expression is associated with clinical outcome and to provide insight into the molecular pathogenesis of this condition. Emerging genomics tools, especially DNA microarray analysis, have been applied in attempts to isolate new molecular markers for the differential diagnosis of AML and to identify genes that contribute to leukemogenesis. Progress in bioinformatics has also yielded means with which to classify patients according to clinical parameters such as long-term prognosis. The application of such analysis to large sets of gene expression data has begun to provide the basis for a new AML classification that is more powerful with regard to prediction of prognosis.

Biomarkers, Tumor↗

PubMed2004

Gene expression profiling of porokeratosis demonstrates similarities with psoriasis.

BACKGROUND: Porokeratosis (PK) is a clinically heterogeneous entity associated with sharply demarcated, annular, or serpiginous lesions with a hyperkeratotic ridge. This disorder is associated with aberrant keratinocyte differentiation that histologically manifests as a stack of parakeratin termed the cornoid lamella; this structure represents the peripheral hyperkeratotic ridge of clinical lesions. Histologically, the keratinocytes forming the cornoid lamella demonstrate an altered differentiation program. However, the molecular basis of PK remains incompletely understood. METHODS: As a first step in characterizing PK at the molecular level, gene expression profiling was performed on a cornoid lamella isolated from a large, Mibelli-type porokeratotic lesion. As a control, gene expression profiling of peripheral uninvolved epidermis was also performed. The gene expression profile of cornoid lamellar keratinocytes was compared with similar profiles obtained from a psoriatic plaque and cutaneous squamous cell carcinoma. RESULTS: Our study demonstrates a striking similarity between the gene expression profiles of PK and psoriasis. In addition, novel markers of the porokeratotic keratinocytes were identified, including keratin 16, S-100 A8 and A9, and connexin 26. CONCLUSIONS: This study supports the hypothesis that PK is a disorder of hyperproliferative keratinocytes exhibiting similarity at the molecular level to psoriasis. Consequently, some therapeutic modalities efficacious for psoriasis may be of benefit in PK.

Gene Expression Profiling↗

PubMed2006

Platinum drug effects on the expression of genes in the polyamine pathway: time-course and concentration-effect analysis based on Affymetrix gene expression profiling of A2780 ovarian carcinoma cells.

PURPOSE: As a follow-up to our previous findings that platinum drugs induce a key enzyme in polyamine catabolism, gene expression profiling and mathematical modeling were used to define the effects of cisplatin and oxaliplatin on the expression of polyamine metabolic pathway genes in A2780 human ovarian carcinoma cells. METHODS: Time-course and concentration-effect experiments were each carried out with cisplatin or oxaliplatin in two separate experiments and cells subjected to gene expression profiling using Affymetrix array technology. Time-course data were modeled using exponential increase and decrease models. Concentration-effect data were modeled using a four parameter Hill model. RESULTS: Gene expression profiling of human ovarian carcinoma A2780 cells after exposure to either cisplatin or oxaliplatin indicates that the expression of several genes involved in polyamine pathway is affected by the platinum drugs. Mathematical/Statistical modeling of the data from time-course and concentration-effect experiments of gene expression from nine polyamine pathway genes represented on the HGU95Av2 chip, indicates that three biosynthetic pathway genes (SAMDC, ODC1 and SRM) are down-regulated and one catabolic pathway gene (SSAT) is up-regulated. Expression changes were similar for different probesets for a given gene on the array. Studies on the induction of SSAT by platinum drugs suggested by the Affymetrix data have been previously validated from this laboratory (Hector et al. in Mol Cancer Ther 3:813-822, 2004). Here, the effects of oxaliplatin exposure on SAMDC and ODC observed by Affymetix are validated with real time QRT-PCR. CONCLUSION: The data indicate a concerted effect of platinum drugs on the polyamine metabolic pathway with down-regulation in the expression of several enzyme genes involved in biosynthesis and many-fold up-regulation in expression of SSAT, an acetylating enzyme gene that is critically involved in polyamine catabolism and export.

Acyltransferases↗

PubMed2005

Gene expression profiles of serous, endometrioid, and clear cell subtypes of ovarian and endometrial cancer.

PURPOSE: The presence of similar histologic subtypes of epithelial ovarian and endometrial cancers has long been noted, although the relevance of this finding to pathogenesis and clinical management is unclear. Despite similar clinical characteristics, histologic subtypes of cancers of the ovary and endometrium are treated according to organ of origin. This study compares the gene expression profiles of analogous histologic subtypes of cancers of the ovary and endometrium using the same genomic platform to determine the similarities and differences between these tumors. EXPERIMENTAL DESIGN: Gene expression profiles of 75 cancers (endometrioid, serous, and clear cell) of the ovary and endometrium, five renal clear cell cancers, and seven normal epithelial brushings were determined using a 11,000-element cDNA array. All images were analyzed using BRB ArrayTools. Validation was done using real-time PCR on select genes and immunohistochemical staining. RESULTS: Comparison across endometrial and ovarian cancers and serous and endometrioid tumors showed expression patterns reflecting their organ of origin. Clear cell tumors, however, showed remarkably similar expression patterns regardless of their origin, even when compared with renal clear cell samples. A set of 43 genes was common to comparisons of each of the three histologic subtypes of ovarian cancer with normal ovarian surface epithelium. CONCLUSIONS: The comparison of the gene expression profiles of endometrioid and serous subtypes of ovarian and endometrial cancer are largely unique to the combination of a particular subtype in a specific organ. In contrast, clear cell cancers show a remarkable similarity in gene expression profiles across organs (including kidney) and could not be statistically distinguished.

Adenocarcinoma, Clear Cell↗

PubMed2006

Effect of hepatitis C virus core shadow protein expressed in human hepatoma cell line on human gene expression profiles.

BACKGROUND AND AIMS: The hepatitis C virus (HCV) C region has been reported to have overlapping genes or regions, and may encode a core shadow protein that has a role in HCV self-replication, pathogenesis and carcinogenesis. The aim of this study was to identify the effect of HCV core shadow protein expressed in a human hepatoma (Huh-7) cell line on human gene expression profiles. METHODS: Recombinants for expression of HCV genotype 1b core shadow protein and genotype 1b core protein were constructed, and an Huh-7 cell line was established that could express the shadow protein and the core protein constitutively. Affymetrix human gene chip, HG-U133 A and B microarray analysis and semiquantitative RT-PCR were employed to identify the expression profiles of two kinds of core proteins in the Huh-7 cell line. RESULTS: The microarray analysis showed that the core shadow protein caused expression of more genes to be up/down-regulation than the core protein, including signal transduction, protease activity, molecular transport and, particularly, immune responses genes. Surprisingly, the core shadow protein could increase/decrease expression of apoptosis and anti-apoptosis genes simultaneously. The expression profiles of three up-regulated genes were confirmed by semiquantitative RT-PCR, with results similar to the microarray analysis. CONCLUSIONS: Hepatitis C virus core shadow protein may play an important role in inhibiting or stimulating host cells apoptosis processing and carcinogenesis, which is useful for the understanding of HCV core shadow protein biological functions in vivo and in vitro.

Blotting, Western↗

PubMed2001

GenEST, a powerful bidirectional link between cDNA sequence data and gene expression profiles generated by cDNA-AFLP.

The release of vast quantities of DNA sequence data by large-scale genome and expressed sequence tag (EST) projects underlines the necessity for the development of efficient and inexpensive ways to link sequence databases with temporal and spatial expression profiles. Here we demonstrate the power of linking cDNA sequence data (including EST sequences) with transcript profiles revealed by cDNA-AFLP, a highly reproducible differential display method based on restriction enzyme digests and selective amplification under high stringency conditions. We have developed a computer program (GenEST) that predicts the sizes of virtual transcript-derived fragments (TDFs) of in silico-digested cDNA sequences retrieved from databases. The vast majority of the resulting virtual TDFs could be traced back among the thousands of TDFs displayed on cDNA-AFLP gels. Sequencing of the corresponding bands excised from cDNA-AFLP gels revealed no inconsistencies. As a consequence, cDNA sequence databases can be screened very efficiently to identify genes with relevant expression profiles. The other way round, it is possible to switch from cDNA-AFLP gels to sequences in the databases. Using the restriction enzyme recognition sites, the primer extensions and the estimated TDF size as identifiers, the DNA sequence(s) corresponding to a TDF with an interesting expression pattern can be identified. In this paper we show examples in both directions by analyzing the plant parasitic nematode Globodera rostochiensis. Various novel pathogenicity factors were identified by combining ESTs from the infective stage juveniles with expression profiles of approximately 4000 genes in five developmental stages produced by cDNA-AFLP.

Animals↗

PubMed2003

Expression profiling of blood samples from an SU5416 Phase III metastatic colorectal cancer clinical trial: a novel strategy for biomarker identification.

BACKGROUND: Microarray-based gene expression profiling is a powerful approach for the identification of molecular biomarkers of disease, particularly in human cancers. Utility of this approach to measure responses to therapy is less well established, in part due to challenges in obtaining serial biopsies. Identification of suitable surrogate tissues will help minimize limitations imposed by those challenges. This study describes an approach used to identify gene expression changes that might serve as surrogate biomarkers of drug activity. METHODS: Expression profiling using microarrays was applied to peripheral blood mononuclear cell (PBMC) samples obtained from patients with advanced colorectal cancer participating in a Phase III clinical trial. The PBMC samples were harvested pre-treatment and at the end of the first 6-week cycle from patients receiving standard of care chemotherapy or standard of care plus SU5416, a vascular endothelial growth factor (VEGF) receptor tyrosine kinase (RTK) inhibitor. Results from matched pairs of PBMC samples from 23 patients were queried for expression changes that consistently correlated with SU5416 administration. RESULTS: Thirteen transcripts met this selection criterion; six were further tested by quantitative RT-PCR analysis of 62 additional samples from this trial and a second SU5416 Phase III trial of similar design. This method confirmed four of these transcripts (CD24, lactoferrin, lipocalin 2, and MMP-9) as potential biomarkers of drug treatment. Discriminant analysis showed that expression profiles of these 4 transcripts could be used to classify patients by treatment arm in a predictive fashion. CONCLUSIONS: These results establish a foundation for the further exploration of peripheral blood cells as a surrogate system for biomarker analyses in clinical oncology studies.

Aged↗

PubMed2006

Effect of infliximab on mRNA expression profiles in synovial tissue of rheumatoid arthritis patients.

We examined the gene expression profiles in arthroscopic biopsies retrieved from 10 rheumatoid arthritis patients before and after anti-TNF treatment with infliximab to investigate whether such profiles can be used to predict responses to the therapy, and to study effects of the therapy on the profiles. Responses to treatment were assessed using European League Against Rheumatism response criteria. Three patients were found to be good responders, five patients to be moderate responders and two patients to be nonresponders. The TNF-alpha status of the biopsies from each of the patients before treatment was also investigated immunohistochemically, and it was detected in biopsies from four of the patients, including all three of the good responders. The gene expression data demonstrate that all patients had unique gene expression signatures, with low intrapatient variability between biopsies. The data also revealed significant differences between the good responding and nonresponding patients (279 differentially expressed genes were detected, with a false discovery rate < 0.025). Among the identified genes we found that MMP-3 was significantly upregulated in good responders (log2 fold change, 2.95) compared with nonresponders, providing further support for the potential of MMP-3 as a marker for good responses to therapy. An even more extensive list of 685 significantly differentially expressed genes was found between patients in whom TNF-alpha was found and nonresponders, indicating that TNF-alpha could be an important biomarker for successful infliximab treatment. Significant differences were also observed between biopsies taken before and after anti-TNF treatment, including 115 differentially expressed genes in the good responding group. Interestingly, the effect was even stronger in the group in which TNF-alpha was immunohistochemically detected before therapy. Here, 1,058 genes were differentially expressed, including many that were novel in this context (for example, CXCL3 and CXCL14). Subsequent Gene Ontology analysis revealed that several 'themes' were significantly over-represented that are known to be affected by anti-TNF treatment in inflammatory tissue; for example, immune response (GO:0006955), cell communication (GO:0007154), signal transduction (GO:0007165) and chemotaxis (GO:0006935). No genes reached statistical significance in the moderately responding or nonresponding groups. In conclusion, this pilot study suggests that further investigation is warranted on the usefulness of gene expression profiling of synovial tissue to predict and monitor the outcome of rheumatoid arthritis therapies.

Adult↗

PubMed2002

[Preliminary study on the gene expression profiles of oligodendrogliom as with cDNA array].

OBJECTIVE: To study the gene expression profiles of oligodendrogliomas with gene cDNA array. METHODS: (32)P tagged cDNA probes converted from the total RNA, which had been extracted from 2 fresh samples of oligodendroglioma and 1 of normal brain tissue, were hybridized with the Atlas array. After washing the membranes, the autoradiography was performed and the autoradiograms were analyzed through the special software. RESULTS: As compared to the normal brain tissue, there were 63 co-upregulated genes and 4 co-downregulated genes in these 2 tumor samples. However, a significant quantitative difference existed between them. The expression trend of some genes differed from the known information. CONCLUSION: cDNA array is effective for studying the gene expression profiles of oligodendrogliomas and provides new information for the further research on their molecular mechanisms.

Brain Neoplasms↗

PubMed2005

Gene-expression profiles and their association with drug resistance in adult acute myeloid leukemia.

BACKGROUND AND OBJECTIVES: From 20-50% of patients with acute myeloid leukemia (AML) are primarily resistant to induction chemotherapy. It has previously been shown that resistance to the first cycle of induction chemotherapy is an independent prognostic factor. We investigated whether resistance to chemotherapy be represented by gene-expression profiles, and which genes are associated with resistance. DESIGN AND METHODS: cDNA microarrays containing approximately 41,000 features were used to compare the gene-expression profile of AML blasts between 33 patients with good or poor response to induction chemotherapy. Data generated by cDNA-arrays were confirmed by quantitative reverse transcription polymerase chain reaction. RESULTS: Using significance analysis of microarrays, we identified a characteristic gene-expression profile which distinguished AML samples from patients with good or poor responses. In hierarchical clustering analysis poor responders clustered together with normal CD34+ cells. Moreover, 13/40 (32.5%) genes highly expressed in poor responders are also overexpressed in hematopoietic stem/progenitor cells. Prediction analysis using 10-fold cross-validation revealed an 80% overall accuracy. Using the treatment-response signature to predict the outcome in an independent test set of 104 AML patients, samples were separated into two subgroups with significantly inferior response rate (43.5% vs. 66.7%, p=0.04), significantly shorter event-free and overall survival (p=0.01 and p=0.03, respectively) in the poor-response compared to in the good-response signature group. In multivariate analysis, the treatment-response signature was an independent prognostic factor (hazard ratio, 2.1, 95% confidence interval 1.2 to 3.6, p=0.006). INTERPRETATION AND CONCLUSIONS: Resistance to chemotherapy in AML can be identified by gene-expression profiling before treatment and seems to be mediated by a transcriptional program active in hematopoietic stem/progenitor cells.

Adolescent↗

PubMed2006

Accurate prediction of BRCA1 and BRCA2 heterozygous genotype using expression profiling after induced DNA damage.

PURPOSE: In this study, the differential gene expression changes following radiation-induced DNA damage in healthy cells from BRCA1/BRCA1 mutation carriers have been compared with controls using high-density microarray technology. We aimed to establish if BRCA1/BRCA2 mutation carriers could be distinguished from noncarriers based on expression profiling of normal cells. EXPERIMENTAL DESIGN: Short-term primary fibroblast cultures were established from skin biopsies from 10 BRCA1 and 10 BRCA2 mutation carriers and 10 controls, all of whom had previously had breast cancer. The cells were subjected to 15 Gy ionizing irradiation to induce DNA damage. RNA was extracted from all cell cultures, preirradiation and at 1 hour postirradiation. For expression profiling, 15 K spotted cDNA microarrays manufactured by the Cancer Research UK DNA Microarray Facility were used. Statistical feature selection was used with a support vector machine (SVM) classifier to determine the best feature set for predicting BRCA1 or BRCA2 heterozygous genotype. To investigate prediction accuracy, a nonprobabilistic classifier (SVM) and a probabilistic Gaussian process classifier were used. RESULTS: In the task of distinguishing BRCA1 and BRCA2 mutation carriers from noncarriers and from each other following radiation-induced DNA damage, the SVM achieved 90%, and the Gaussian process classifier achieved 100% accuracy. This effect could not be achieved without irradiation. In addition, the SVM identified a set of BRCA genotype predictor genes. CONCLUSIONS: We conclude that after irradiation-induced DNA damage, BRCA1 and BRCA2 mutation carrier cells have a distinctive expression phenotype, and this may have a future role in predicting genotypes, with application to clinical detection and classification of mutations.

Adult↗

PubMed2006

Dose-response relationships in gene expression profiles in rainbow trout, Oncorhyncus mykiss, exposed to ethynylestradiol.

Determining how gene expression profiles change with toxicant dose will improve the utility of arrays in identifying biomarkers and modes of toxic action. Isogenic rainbow trout, Oncorhyncus mykiss,were exposed to 10, 50 or 100 ng/L ethynylestradiol (a xeno-estrogen) for 7 days. Following exposure hepatic RNA was extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNAs. Transcript expression in treated vs control fish was analyzed via Genespring (Silicon Genetics) to identify genes with altered expression, as well as to determine gene clustering patterns that can be used as "expression signatures". Array results were confirmed via qRT PCR. Our analysis indicates that gene expression profiles varied somewhat with dose. Established biomarkers of exposure to estrogenic chemicals, such as vitellogenin, vitelline envelope proteins, and the estrogen receptor alpha, were induced at every dose. Other genes were dose specific, suggesting that different doses induce distinct physiological responses. These findings demonstrate that cDNA microarrays could be used to identify both toxicant class and relative dose.

Animals↗

PubMed2006

Gene expression profiles of breast cancer obtained from core cut biopsies before neoadjuvant docetaxel, adriamycin, and cyclophoshamide chemotherapy correlate with routine prognostic markers and could be used to identify predictive signatures.

BACKGROUND: Neoadjuvant administration of chemotherapy provides a unique opportunity to monitor response to treatment in breast cancer and assesses response exactly. Global gene expression profiling by microarrays has been used as a valuable tool for the identification of prognostic and predictive marker genes. Even though this technology is now wide spread and relatively standardized, there are only few data available which compare established parameters with expression values to determine reliability of this method. Therefore we analyzed gene expression data of pretreatment biopsies of breast cancer patients and compared them with the results of the immunohistochemical receptor expression for ER/ PR and Her-2, as well as FISH testing for HER-2 amplification. We analyzed the change of expression of these markers before and after neoadjuvant chemotherapy. Furthermore we evaluated the predictive significance of prognostic gene signatures as described by Sorlie, van't Veer and Ahr for response to neoadjuvant chemotherapy. METHODS: Pretherapeutic core biopsies were obtained from 70 patients undergoing neoadjuvant TAC chemotherapy within the GEPARTRIO-trial. Samples were characterized according to standard pathology including ER, PR and HER2 IHC and amount of cancer cells. Only biopsies with more than 80 % tumor cells were considered for further examination. RNA was isolated and expression profiling performed using Affymetrix Hg U133 Arrays (22 500 genes). GeneData's Expressionist software was used for bioinformatic analyses. RESULTS: More than two thirds of the biopsies yielded sufficient amounts (> 5 microg) of RNA for expression profiling and high quality data were obtained for 50 samples. Unsupervised clustering broadly revealed a correlation with hormone receptor status. When ER-alpha, PR and HER2 as analyzed by immunohistochemistry were compared to the corresponding mRNA data from gene chips more than 90 % concordance was observed. We could observe a switch of receptor expression for ER, PR or HER-2 from positive to negative and vice versa in 16/35 cases (45.7 %) and 5/22 cases (22.7 %) respectively. The prognostic marker sets of Sorlie, van't Veer and Ahr could not discriminate responders from non-responders in our patient group. CONCLUSIONS: Our results demonstrate that reliable expression profiles can be achieved by using limited amounts of tissue obtained during neoadjuvant chemotherapy. Microarray data capture conventional prognostic markers but might contain additional informative gene sets correlated with treatment outcome. Prognostic marker sets are not suitable to predict tumor response in the neoadjuvant setting, suggesting the necessity of class prediction methods to identify marker sets predictive for the type of therapy used.

Adult↗

PubMed2000

Genomic-scale gene expression profiling of normal and malignant immune cells.

Gene expression variation is critical for the normal development and physiology of immune cells. Using cDNA microarrays, a systematic, genomic-scale view of gene expression in immune cells at many stages of differentiation and activation can be obtained. From the high vantagepoint provided by this technology, the gene expression physiology of immune cells appears remarkably ordered and logical. Each stage of lymphocyte differentiation can be defined by a characteristic gene expression signature. Genes that are co-regulated over hundreds of experimental conditions often encode functionally related proteins. Gene expression profiles also provide unprecedented ability to define the molecular and functional relationships between normal and malignant lymphocyte cell populations.

Algorithms↗

PubMed2002

A paradigm for class prediction using gene expression profiles.

We propose a general framework for prediction of predefined tumor classes using gene expression profiles from microarray experiments. The framework consists of 1) evaluating the appropriateness of class prediction for the given data set, 2) selecting the prediction method, 3) performing cross-validated class prediction, and 4) assessing the significance of prediction results by permutation testing. We describe an application of the prediction paradigm to gene expression profiles from human breast cancers, with specimens classified as positive or negative for BRCA1 mutations and also for BRCA2 mutations. In both cases, the accuracy of class prediction was statistically significant when compared to the accuracy of prediction expected by chance. The framework proposed here for the application of class prediction is designed to reduce the occurrence of spurious findings, a legitimate concern for high-dimensional microarray data. The prediction paradigm will serve as a good framework for comparing different prediction methods and may accelerate the development of molecular classifiers that are clinically useful.

Algorithms↗

PubMed2005

Use of gene expression profiling to direct in vivo molecular imaging of lung cancer.

Using gene expression profiling, we identified cathepsin cysteine proteases as highly up-regulated genes in a mouse model of human lung adenocarcinoma. Overexpression of cathepsin proteases in these lung tumors was confirmed by immunohistochemistry and Western blotting. Therefore, an optical probe activated by cathepsin proteases was selected to detect murine lung tumors in vivo as small as 1 mm in diameter and spatially separated. We generated 3D maps of the fluorescence signal and fused them with anatomical computed tomography images to show a close correlation between fluorescence signal and tumor burden. By serially imaging the same mouse, optical imaging was used to follow tumor progression. This study demonstrates the capability for molecular imaging of a primary lung tumor by using endogenous proteases expressed by a tumor. It also highlights the feasibility of using gene expression profiling to identify molecular targets for imaging lung cancer.

Adenocarcinoma, Bronchiolo-Alveolar↗

PubMed2006

Gene expression profiles give insight into the molecular pathology of bone in primary hyperparathyroidism.

Global gene expression profiling has been used to study the molecular mechanisms of increased bone remodeling caused by PHPT. This disease is a model for chronic over-stimulation of target organs by PTH due to an inappropriate overproduction of the hormone. Hyperactivity of osteoblasts and osteoclasts lead to increased calcium and phosphate mobilization from the skeleton and hypercalcaemia. The ensemble of genes that alter expression and thus is responsible for the effects of chronic PTH stimulation is today largely unknown. The differentiated gene expression profiles revealed characteristic molecular disease modalities which define the bone remodeling abnormalities occurring in PTH dependent osteodystrophy. We analyzed mRNAs in transiliacal bone biopsies from 7 patients with PHPT using Affymetrix HG-U133A Gene Chips containing more than 22000 different probe sets. Similar analyses of the global transcriptional activity were repeated in a second bone biopsy from the same patient taken one year after surgery and reversal of disease parameters. Real time PCR was carried out on many genes for corroboration of the results. Out of more than 14500 different genes examined, 99 which were related to bone and extra-cellular matrix, showed altered expression. Of these were 85 up- and 14 down-regulated before operation. The majority of regulated genes represented structural and adhesion proteins, but included also proteases and protease regulators which promote resorption. Increased expressions of collagen type 1 and osteocalcin mRNAs in disease reflecting the PTH anabolic action were paralleled by increased concentrations of these proteins in serum. In addition, genes encoding transcriptional factors and their regulators as well as cellular signal molecules were up-regulated during disease. The identified genetic signature represents the first extensive description of the ensemble of bone and matrix related mRNAs, which are regulated by chronic PTH action. These results identify the molecular basis for this skeletal disease, and provide new insight into this clinical condition with potential bearing on future treatment.

Absorptiometry, Photon↗

PubMed2005

Identification of Dll1 (Delta1) target genes during mouse embryogenesis using differential expression profiling.

The Notch signaling pathway has pleiotropic functions during mammalian embryogenesis. It is required for the patterning and differentiation of the presomitic and somitic paraxial mesoderm and of the neural tube. We used DNA-chip expression profiling and 2D-gel electrophoresis combined with peptide mass fingerprinting to identify genes and proteins differentially regulated in E10.5 Dll1 (delta-like 1, Delta1) mutant embryos. The differential expression profiling approach identified 47 regulated transcripts and 40 differentially expressed proteins. The majority of these genes has until now not been associated with Notch signaling. Subsequent whole-mount in situ hybridization confirmed that a subset of the identified transcripts has restricted and distinct patterns of expression in E10.5 mouse embryos. For most genes these expression patterns were affected in the presomitic mesoderm, in differentiating somites of Dll1 mutant embryos and in the neural tube and cells differentiating from it. Similar effects were observed in embryos homozygous for the Headturner (Htu) and pudgy (pu) mutations, which are alleles of the Notch ligands Jag1 and Dll3. The regulated expression of a subset of the proteins was validated by immunoblots. Remarkably six of the proteins down-regulated in Dll1 mutant embryos are proteasome subunits. The large set of regulated genes identified in this differential expression profiling approach is an important resource for further functional studies.

Animals↗