DMPK 3' untranslated repeat expansions in unexplained sudden cardiac death in the young.
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DMPK↗
Biomedical subjects
Cristin G Print
Publications and source records attributed to Cristin G Print.
Whole genome and exome sequencing of pancreatic neuroendocrine tumour to investigate PRRT response.
Patients with pancreatic neuroendocrine tumours (PNETs) often have similar baseline clinical characteristics, including grade and molecular imaging phenotype, yet have highly variable responses to peptide receptor radionuclide therapy (PRRT). To identify genomic alterations and mutational patterns associated with PRRT treatment response and acquired somatic changes following PRRT exposure, whole genome or exome sequencing was applied to 40 PNET samples from 32 patients, including eight paired pre- or post-PRRT samples. The genomic profile of tumours reflected the known mutational landscape of PNET with MEN1 (34%), ATRX/DAXX (47%) alterations and a recurrent pattern of aneuploidy (38%) detected. A recurrent PSIP1::TBL1X fusion of unknown function was also identified in four tumours. The disease control rate following PRRT using RECIST1.1 and molecular imaging criteria was 88% (28/32). No mutational features were found to be statistically associated with progression-free survival. There was no significant increase in tumour mutational burden in the post-PRRT tumours, nor recurrent emergent mutational changes in cancer driver genes to explain progression to higher-grade disease, when observed. However, a small indel signature (ID8) previously associated with DNA damage repair by non-homologous end joining (NHEJ) was higher in PRRT-exposed compared with PRRT-naive samples (23.8 vs 4.8%, respectively; P < 0.001). Thus, comprehensive DNA analysis of pancreatic NETs did not identify biomarkers predictive of PRRT response nor evidence for high-level PRRT-induced genomic instability or hypermutation, yet mutation signature analysis supports NHEJ as being important for DNA repair and survival of neuroendocrine cells following exposure to beta-particle radiation.
Humans↗
Changes in gene expression during Wolffian duct development.
BACKGROUND: Wolffian ducts (WDs) are the embryonic precursors of the male reproductive tract. Their development is induced by testosterone, which interacts with the androgen receptor (AR). The molecular pathways underlying androgen-dependent WD development are largely unknown. We aimed to identify AR target genes important in this process. METHODS: RNA was isolated from rat WDs at E17.5 and E20.5. Affymetrix GeneChip expression arrays were used to identify transcripts up- or downregulated more than 2-fold. Regulation of seven transcripts was confirmed using quantitative PCR. RESULTS: Transcripts from 76 known genes were regulated, including modulators of insulin-like growth factor and transforming growth factor-beta signalling. By controlling these modulators, androgens may indirectly affect growth factor signalling pathways important in epithelial-mesenchymal interactions and organ development. Caveolin-1, also upregulated, may play a role in modifying as well as mediating AR signalling. Differentiation of WD epithelium and smooth muscle, innervation and extracellular matrix synthesis were reflected in regulation of other transcripts. Several genes were previously suggested to be regulated by androgens or contained functional or putative androgen/glucocorticoid response elements, indicating they may be direct targets of androgen signalling. CONCLUSION: Our results suggest novel cohorts of signals that may contribute to androgen-dependent WD development and provide hypotheses that can be tested by future studies.
Androgens↗
Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles.
We propose a computational strategy for discovering gene networks affected by a chemical compound. Two kinds of DNA microarray data are assumed to be used: One dataset is short time-course data that measure responses of genes following an experimental treatment. The other dataset is obtained by several hundred single gene knock-downs. These two datasets provide three kinds of information; (i) A gene network is estimated from time-course data by the dynamic Bayesian network model, (ii) Relationships between the knocked-down genes and their regulatees are estimated directly from knock-down microarrays and (iii) A gene network can be estimated by gene knock-down data alone using the Bayesian network model. We propose a method that combines these three kinds of information to provide an accurate gene network that most strongly relates to the mode-of-action of the chemical compound in cells. This information plays an essential role in pharmacogenomics. We illustrate this method with an actual example where human endothelial cell gene networks were generated from a novel time course of gene expression following treatment with the drug fenofibrate, and from 270 novel gene knock-downs. Finally, we succeeded in inferring the gene network related to PPAR-alpha, which is a known target of fenofibrate.
Bayes Theorem↗
Independent component analysis of microarray data in the study of endometrial cancer.
Gene microarray technology is highly effective in screening for differential gene expression and has hence become a popular tool in the molecular investigation of cancer. When applied to tumours, molecular characteristics may be correlated with clinical features such as response to chemotherapy. Exploitation of the huge amount of data generated by microarrays is difficult, however, and constitutes a major challenge in the advancement of this methodology. Independent component analysis (ICA), a modern statistical method, allows us to better understand data in such complex and noisy measurement environments. The technique has the potential to significantly increase the quality of the resulting data and improve the biological validity of subsequent analysis. We performed microarray experiments on 31 postmenopausal endometrial biopsies, comprising 11 benign and 20 malignant samples. We compared ICA to the established methods of principal component analysis (PCA), Cyber-T, and SAM. We show that ICA generated patterns that clearly characterized the malignant samples studied, in contrast to PCA. Moreover, ICA improved the biological validity of the genes identified as differentially expressed in endometrial carcinoma, compared to those found by Cyber-T and SAM. In particular, several genes involved in lipid metabolism that are differentially expressed in endometrial carcinoma were only found using this method. This report highlights the potential of ICA in the analysis of microarray data.
Endometrial Neoplasms↗
Bioinformatic analysis of primary endothelial cell gene array data illustrated by the analysis of transcriptome changes in endothelial cells exposed to VEGF-A and PlGF.
We recently published a review in this journal describing the design, hybridisation and basic data processing required to use gene arrays to investigate vascular biology (Evans et al. Angiogenesis 2003; 6: 93-104). Here, we build on this review by describing a set of powerful and robust methods for the analysis and interpretation of gene array data derived from primary vascular cell cultures. First, we describe the evaluation of transcriptome heterogeneity between primary cultures derived from different individuals, and estimation of the false discovery rate introduced by this heterogeneity and by experimental noise. Then, we discuss the appropriate use of Bayesian t-tests, clustering and independent component analysis to mine the data. We illustrate these principles by analysis of a previously unpublished set of gene array data in which human umbilical vein endothelial cells (HUVEC) cultured in either rich or low-serum media were exposed to vascular endothelial growth factor (VEGF)-A165 or placental growth factor (PlGF)-1(131). We have used Affymetrix U95A gene arrays to map the effects of these factors on the HUVEC transcriptome. These experiments followed a paired design and were biologically replicated three times. In addition, one experiment was repeated using serial analysis of gene expression (SAGE). In contrast to some previous studies, we found that VEGF-A and PlGF consistently regulated only small, non-overlapping and culture media-dependant sets of HUVEC transcripts, despite causing significant cell biological changes.
Cells, Cultured↗
Transcriptome analysis of endometrial cancer identifies peroxisome proliferator-activated receptors as potential therapeutic targets.
Endometrial cancer is the most common gynecologic malignancy, frequently arising in association with obesity and diabetes mellitus. To identify gene pathways contributing to endometrial cancer development, we studied the transcriptome of 20 endometrial cancers and 11 benign endometrial tissues using cDNA microarrays. Among the transcript changes identified in endometrial cancer were up-regulation of the nuclear hormone receptors peroxisome proliferator-activated receptors (PPAR) alpha and gamma, whereas retinoid X receptor beta was down-regulated. To clarify the contribution of PPARalpha to endometrial carcinogenesis, we did experiments on cultured endometrial carcinoma cells expressing this transcript. Treatment with fenofibrate, an activating ligand for PPARalpha, significantly reduced proliferation and increased cell death, suggesting that altered expression of nuclear hormone receptors involved with fatty acid metabolism leads to deregulated cellular proliferation and apoptosis. These results support further investigation of members of the PPAR/retinoid X receptor pathway as novel therapeutic targets in endometrial cancer.
Cell Death↗
Endothelial cells preparing to die by apoptosis initiate a program of transcriptome and glycome regulation.
The protein-based changes that underlie the cell biology of apoptosis have been extensively studied. In contrast, mRNA- and polysaccharide-based changes have received relatively little attention. We have combined transcriptome and glycome analyses to show that apoptotic endothelial cell cultures undergo programmed changes to RNA transcript abundance and cell surface polysaccharide profiles. Although a few of the transcriptome changes were protective, most appeared to prepare cells for apoptosis by decreasing the reception and transduction of pro-survival signals, increasing pro-death signals, increasing abundance of apoptotic machinery, inhibiting cellular proliferation, recruiting phagocytes to regions of cell death, and promoting phagocytosis. Additional transcriptomal changes appeared to alter the synthesis and modification of cell surface glycosaminoglycans. The resultant reduced abundance of sulphated cell surface glycosaminoglycans may further promote cell death by inhibiting the presentation of extracellular matrix-tethered survival factors to their receptors on dying cells. We propose that the transcriptome and glycome regulation presented here synergize with previously described protein-based changes to guide the apoptotic program.
Apoptosis↗
Generation and use of a tailored gene array to investigate vascular biology.
Vasculogenesis, angiogenesis and vascular remodelling are complex processes where the fate of several cell types is determined by different signalling networks. Many of these networks ultimately function by changing the abundance of RNA transcripts within the cells which constitute blood vessel walls. Researchers can now map these transcript abundance changes using gene array technology. In this review, we describe the design, production and use of a gene array specifically tailored to investigate vascular biology. We describe the advantages of tailored gene arrays, and give detailed protocols based on our experience to allow the reader to use such gene arrays to generate meaningful data. We list the issues to consider when choosing and verifying the genes and splice variants included in an array, and describe our use of Arabidopsis sp. RNA spikes for quality control. We present data that illustrates the absolute necessity for both technical and biological replicates to be incorporated in the design of gene array experiments using primary cells such as HUVECS. Finally, we describe methods for the normalisation and interpretation of the data that gene arrays produce. The approach to gene array technology described here is easily within reach of the budget and expertise of most academic research groups.
Cardiovascular Physiological Phenomena↗
VavCre transgenic mice: a tool for mutagenesis in hematopoietic and endothelial lineages.
Cre transgenic mice can be used to delete gene sequences flanked by loxP sites in specific somatic tissues. We have generated vavCre transgenic mice, which can be used to inactivate genes specifically in adult hematopoietic and endothelial cells. In these animals, a Cre transgene is expressed under control of murine vav gene regulatory elements. To assess their usefulness, vavCre transgenic mice were bred with R26R mice, which express a lacZ reporter gene only in cells where Cre-mediated recombination has occurred. VavCre/R26R double-heterozygous offspring were analyzed by beta-galactosidase histochemistry and flow cytometry. VavCre-mediated recombination occurred in most hematopoietic cells of all hematopoietic organs, including the hematopoietic progenitor-rich bone marrow. Recombination also occurred in most endothelial and germ cells, but only rarely in other cell types. The recombination in both hematopoietic and endothelial lineages may partly reflect their putative shared ontogeny and provides a unique tool for simultaneous pan-hematopoietic and endothelial mutagenesis.
Animals↗