| 1. |
- Scheele, Camilla, et al.
(författare)
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Altered regulation of the PINK1 locus: a link between Type 2 diabetes and neurodegeneration?
- 2007
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Ingår i: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 21:13, s. 3653-3665
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Tidskriftsartikel (refereegranskat)abstract
- Mutations in PINK1 cause the mitochondrial-related neurodegenerative disease Parkinson’s. Here we investigate whether obesity, type 2 diabetes, or inactivity alters transcription from the PINK1 locus. We utilized a cDNA-array and quantitative real-time PCR for gene expression analysis of muscle from healthy volunteers following physical inactivity, and muscle and adipose tissue from nonobese or obese subjects with normal glucose tolerance or type 2 diabetes. Functional studies of PINK1 were performed utilizing RNA interference in cell culture models. Following inactivity, the PINK1 locus had an opposing regulation pattern (PINK1 was down-regulated while natural antisense PINK1 was up-regulated). In type 2 diabetes skeletal muscle, all transcripts from the PINK1 locus were suppressed and gene expression correlated with diabetes status. RNA interference of PINK1 in human neuronal cell lines impaired basal glucose uptake. In adipose tissue, mitochondrial gene expression correlated with PINK1 expression although remained unaltered following siRNA knockdown of Pink1 in primary cultures of brown preadipocytes. In conclusion, regulation of the PINK1 locus, previously linked to neurodegenerative disease, is altered in obesity, type 2 diabetes and inactivity, while the combination of RNAi experiments and clinical data suggests a role for PINK1 in cell energetics rather than in mitochondrial biogenesis.
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| 2. |
- Timmons, James A, et al.
(författare)
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Myogenic gene expression signature establishes that brown and white adipocytes originate from distinct cell lineages.
- 2007
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 104:11, s. 4401-4406
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Tidskriftsartikel (refereegranskat)abstract
- Attainment of a brown adipocyte cell phenotype in white adipocytes, with their abundant mitochondria and increased energy expenditure potential, is a legitimate strategy for combating obesity. The unique transcriptional regulators of the primary brown adipocyte phenotype are unknown, limiting our ability to promote brown adipogenesis over white. In the present work, we used microarray analysis strategies to study primary preadipocytes, and we made the striking discovery that brown preadipocytes demonstrate a myogenic transcriptional signature, whereas both brown and white primary preadipocytes demonstrate signatures distinct from those found in immortalized adipogenic models. We found a plausible SIRT1-related transcriptional signature during brown adipocyte differentiation that may contribute to silencing the myogenic signature. In contrast to brown preadipocytes or skeletal muscle cells, white preadipocytes express Tcf21, a transcription factor that has been shown to suppress myogenesis and nuclear receptor activity. In addition, we identified a number of developmental genes that are differentially expressed between brown and white preadipocytes and that have recently been implicated in human obesity. The interlinkage between the myocyte and the brown preadipocyte confirms the distinct origin for brown versus white adipose tissue and also represents a plausible explanation as to why brown adipocytes ultimately specialize in lipid catabolism rather than storage, much like oxidative skeletal muscle tissue.
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| 3. |
- Tobin, Nicholas P., et al.
(författare)
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An Endothelial Gene Signature Score Predicts Poor Outcome in Patients with Endocrine-Treated, Low Genomic Grade Breast Tumors
- 2016
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Ingår i: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 22:10, s. 2417-2426
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The ability of vascular genes to provide treatment predictive information in breast cancer patients remains unclear. As such, we assessed the expression of genes representative of normal endothelial microvasculature (MV) in relation to treatment-specific patient subgroups. Experimental Design: We used expression data from 993 breast tumors to assess 57 MV genes (summarized to yield an MV score) as well as the genomic grade index (GGI) and PAM50 signatures. MV score was compared with CD31 staining by correlation and gene ontology (GO) analysis, along with clinicopathologic characteristics and PAM50 subtypes. Uni-, multivariate, and/or t-test analyses were performed in all and treatment-specific subgroups, along with a clinical trial cohort of patients with metastatic breast cancer, seven of whom received antiangiogenic therapy. Results: MV score did not correlate with microvessel density (correlation = 0.096), but displayed enrichment for angiogenic GO terms, and was lower in Luminal B tumors. In endocrine-treated patients, a high MV score was associated with decreased risk of metastasis [HR 0.58; 95% confidence interval (CI), 0.38-0.89], even after adjusting for histologic grade, but not GGI or PAM50. Subgroup analysis showed the prognostic strength of the MV score resided in low genomic grade tumors and MV score was significantly increased in metastatic breast tumors after treatment with sunitinib + docetaxel (P = 0.031). Conclusions: MV score identifies two groups of better and worse survival in low-risk endocrine-treated breast cancer patients. We also show normalization of tumor vasculature on a transcriptional level in response to an angiogenic inhibitor in human breast cancer samples.
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| 4. |
- Wennmalm, Kristian
(författare)
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Analytical strategies for identifying relevant phenotypes in microarray data
- 2007
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With microarray technology, the transcription thousands of genes can be determined simultaneously. The large number of genes, often assessed in a relatively small number of samples, presents a challenge. The risk of making false positive discoveries is substantial, and making biological sense of hundreds of identified genes is difficult. In response to this, a variety of methods for computerized analysis have been developed yet implementation of these is still fraught with challenges. This thesis focuses on the application of such methods in three areas of biomedical science, where the underlying biology needs more detailed characterization; cellular senescence, cell differentiation, and breast cancer. Cellular senescence describes a state of growth arrest in vitro (cell cultures) believed to be of relevance for aging in mammals. In a comparison of seven microarray data sets addressing aging in human mouse and rat, and four data sets addressing cellular senescence in human and mouse, we discovered similarities between gene expression changes in the aging and senescence experiments, respectively. Resemblance between aging and cellular senescence could only be demonstrated between senescent cells and aging mice, not human. This finding indicates that aging in mice and humans can be substantially different, and that the cellular senescence process may not be a prominent feature of aging human tissues in vivo. Adipogenesis requires exquisite control of cell-cycle proteins in two diverse types of adipocytes, brown and white. Brown adipose tissue, in contrast to white, can consume energy to generate heat. In a microarray experiment contrasting brown and white preadipocyte differentiation, we identified a novel transcriptional program in brown cells involving early expression of myogenic transcription factors previously thought to be unique to differentiation of muscle. We applied a novel array analysis strategy to understand which genes may be responsible for the brown adipocyte maturation and final unique cell phenotype. Our findings add a new dimension to current ideas on the developmental origin of brown adipose tissue. In the last 40 years, survival in breast cancer patients has improved through the combined effects of earlier detection through mammography screening and adjuvant therapies. To achieve further progress, developing new prognostic markers, treatment predictive markers, and tailored therapy is important. In two population based cohorts with 402 expression profiled primary breast cancers, we found that five proposed molecular subtypes of breast cancer could be collapsed to form two groups on the basis of gene expression in the long arm of chromosome 16, in agreement with histological grade. We also explored the possibility to predict the sites of distant recurrences and found that lung and liver metastasis could be predicted. Prediction was characterized by poor sensitivity, numerous false positives, and strong dependence on biology underpinning histopathological grade and HER-2/neu status. These findings indicate an important role for biology related to histopathological grade in breast cancer, and further investigation may provide means for better prognostication and treatment prediction.
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| 5. |
- Wennmalm, Kristian, et al.
(författare)
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Gene expression in 16q is associated with survival and differs between Sørlie breast cancer subtypes
- 2007
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Ingår i: Genes, Chromosomes and Cancer. - : Wiley. - 1045-2257 .- 1098-2264. ; 46:1, s. 87-97
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Tidskriftsartikel (refereegranskat)abstract
- We have investigated the relationship between gene expression and chromosomal positions in 402 breast cancer patients. Using an overrepresentation approach based on Fisher's exact test, we identified disproportionate contributions of specific chromosomal positions to genes associated with survival. Our major finding is that the gene expression in the long arm of chromosome 16 stands out in its relationship to survival. This arm contributes 36 (18%) and 55 (11%) genes to lists negatively associated with recurrence-free survival (set to sizes 200 and 500). This is a highly disproportionate contribution from the 313 (2%) genes in this arm represented on the used Affymetrix U133A and B microarray platforms (Bonferroni corrected Fisher test: P < 2.2 x 10(-16)). We also demonstrate differential expression in 16q across tumor subtypes, which suggests that the ERBB2, basal, and luminal B tumors progress along a high grade-poor prognosis path, while luminal A and normal-like tumors progress along a low grade-good prognosis path, in accordance with a previously proposed model of tumor progression. We conclude that important biological information can be extracted from gene expression data in breast cancer by studying non-random connections between chromosomal positions and gene expression. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.
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