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A specific antibody to detect transcription factor T-Pit: a reliable marker of corticotroph cell differentiation and a tool to improve the classification of pituitary neuroendocrine tumours
KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-0327-7377
KTH, Centres, Science for Life Laboratory, SciLifeLab.
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2017 (English)In: Acta Neuropathologica, ISSN 0001-6322, E-ISSN 1432-0533, Vol. 134, no 4, p. 675-677Article in journal, Letter (Refereed) Published
Place, publisher, year, edition, pages
SPRINGER , 2017. Vol. 134, no 4, p. 675-677
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-214869DOI: 10.1007/s00401-017-1768-9ISI: 000409369000012Scopus ID: 2-s2.0-85027889508OAI: oai:DiVA.org:kth-214869DiVA, id: diva2:1152330
Note

QC 20171024

Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2018-10-17Bibliographically approved
In thesis
1. Towards a deeper understanding of the human brain
Open this publication in new window or tab >>Towards a deeper understanding of the human brain
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Identifying the proteome variation in different parts of the body provides fundamental molecular details, enabling further findings and mapping of tissue specific proteins. By combining quantitative transcriptomics with qualitative antibody based proteomics, the Human Protein Atlas (HPA) project aims to protein profile each human protein-coding gene. Genes with varying expression levels in the different tissue types are categorized as tissue elevated in one tissue compared to others, thus connecting genes to potential tissue specific functions. This thesis focuses on the most complex organ in the human body, the brain. With its billions of neurons specifically organized and interconnected, the ability of not only controlling the body but also responsible for higher cognitive functions, the brain is still not fully understood.

In my search for brain important proteins, genes were classified at different stages based on expression levels. In Paper I and II the transcriptome of cerebral cortex was compared with peripheral organs to classify genes with elevated expression in the brain. Brain expression information was expanded by including external data (GTEx and FANTOM5) into the analysis, in Paper III. Thereafter, in Paper IV, the three datasets (HPA, GTEx and FANTOM5) were aligned and combined, enabling a consensus classification with an improved representation of the brain complexity. The most recent classification provided whole body gene expression profiles and out of the 19,670 protein-coding genes, 2,501 were expressed at elevated levels in the brain compared to the other tissue types. Twelve individual regions represented the brain as an organ, and were further analyzed and compared for regional classification of gene expression. One thousand genes showed regional variation in expression level, thus classified as regionally elevated within the brain. Interestingly, less than 500 of the genes classified as brain elevated on the whole body level, and were also regionally elevated in the brain. Many genes with regionally variable expression within the brain showed higher expression in a peripheral organ than in the brain when comparing whole body expression. Based on elevated expression in the brain or brain regions, more than 3,000 genes were suggested to be of high importance to the brain.

In addition, this high-throughput approach to combine transcriptomics and protein profiles in tissues and cells further generated new knowledge in several different other aspects: better understanding of uncharacterized and “missing proteins” (Paper III), validation of an antibody improving classification of pituitary adenoma (Paper V) and in Paper VI the possibility to explore cancer specific expression in relation to clinical data and normal tissue expression.

There are multiple diseases of the brain that are poorly understood on both a cellular and molecular level. While my work mainly focused on identifying and understanding the molecular organization of the normal brain, the ultimate goal of mapping and studying the normal expression baseline is to understand the molecular aspects of disease and identify ways to prevent, treat and cure diseases.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 83
Series
TRITA-CBH-FOU ; 50
Keywords
Brain, organization, RNA, classification, mapping, proteins, antibodies
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-235670 (URN)978-91-7729-983-7 (ISBN)
Public defence
2018-11-15, Gard aulan, Nobels väg 18, Solna, 10:00 (English)
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Note

QC 20181018

Available from: 2018-10-18 Created: 2018-10-17 Last updated: 2018-10-18Bibliographically approved

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Sjöstedt, Evelina

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