| 1. |
- Danielsson, Frida, et al.
(författare)
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Majority of differentially expressed genes are down-regulated during malignant transformation in a four-stage model
- 2013
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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. ; 110:17, s. 6853-6858
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Tidskriftsartikel (refereegranskat)abstract
- The transformation of normal cells to malignant, metastatic tumor cells is a multistep process caused by the sequential acquirement of genetic changes. To identify these changes, we compared the transcriptomes and levels and distribution of proteins in a four-stage cell model of isogenically matched normal, immortalized, transformed, and metastatic human cells, using deep transcriptome sequencing and immunofluorescence microscopy. The data show that similar to 6% (n = 1,357) of the human protein-coding genes are differentially expressed across the stages in the model. Interestingly, the majority of these genes are down-regulated, linking malignant transformation to dedifferentiation. The up-regulated genes are mainly components that control cellular proliferation, whereas the down-regulated genes consist of proteins exposed on or secreted from the cell surface. As many of the identified gene products control basic cellular functions that are defective in cancers, the data provide candidates for follow-up studies to investigate their functional roles in tumor formation. When we further compared the expression levels of four of the identified proteins in clinical cancer cohorts, similar differences were observed between benign and cancer cells, as in the cell model. This shows that this comprehensive demonstration of the molecular changes underlying malignant transformation is a relevant model to study the process of tumor formation.
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| 2. |
- Fagerberg, Linn, et al.
(författare)
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Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics
- 2014
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Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 13:2, s. 397-406
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Tidskriftsartikel (refereegranskat)abstract
- Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody- based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to 80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.
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| 3. |
- Lindskog, Cecilia, et al.
(författare)
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The human cardiac and skeletal muscle proteomes defined by transcriptomics and antibody-based profiling
- 2015
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- Background: To understand cardiac and skeletal muscle function, it is important to define and explore their molecular constituents and also to identify similarities and differences in the gene expression in these two different striated muscle tissues. Here, we have investigated the genes and proteins with elevated expression in cardiac and skeletal muscle in relation to all other major human tissues and organs using a global transcriptomics analysis complemented with antibody-based profiling to localize the corresponding proteins on a single cell level. Results: Our study identified a comprehensive list of genes expressed in cardiac and skeletal muscle. The genes with elevated expression were further stratified according to their global expression pattern across the human body as well as their precise localization in the muscle tissues. The functions of the proteins encoded by the elevated genes are well in line with the physiological functions of cardiac and skeletal muscle, such as contraction, ion transport, regulation of membrane potential and actomyosin structure organization. A large fraction of the transcripts in both cardiac and skeletal muscle correspond to mitochondrial proteins involved in energy metabolism, which demonstrates the extreme specialization of these muscle tissues to provide energy for contraction. Conclusions: Our results provide a comprehensive list of genes and proteins elevated in striated muscles. A number of proteins not previously characterized in cardiac and skeletal muscle were identified and localized to specific cellular subcompartments. These proteins represent an interesting starting point for further functional analysis of their role in muscle biology and disease.
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| 4. |
- Ståhl, Patrik, Dr., et al.
(författare)
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Visualization and analysis of gene expression in tissue sections by spatial transcriptomics
- 2016
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Ingår i: Science. - : AMER ASSOC ADVANCEMENT SCIENCE. - 0036-8075 .- 1095-9203. ; 353:6294, s. 78-82
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of the pattern of proteins or messenger RNAs (mRNAs) in histological tissue sections is a cornerstone in biomedical research and diagnostics. This typically involves the visualization of a few proteins or expressed genes at a time. We have devised a strategy, which we call "spatial transcriptomics," that allows visualization and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections. By positioning histological sections on arrayed reverse transcription primers with unique positional barcodes, we demonstrate high-quality RNA-sequencing data with maintained two-dimensional positional information from the mouse brain and human breast cancer. Spatial transcriptomics provides quantitative gene expression data and visualization of the distribution of mRNAs within tissue sections and enables novel types of bioinformatics analyses, valuable in research and diagnostics.
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