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Majority of differentially expressed genes are down-regulated during malignant transformation in a four-stage model
KTH, Centres, Science for Life Laboratory, SciLifeLab. (HPR/M UHLÉN)ORCID iD: 0000-0002-7692-1100
KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-2998-3077
KTH, Centres, Science for Life Laboratory, SciLifeLab. (HPR/M UHLÉN)
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2013 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 110, no 17, 6853-6858 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2013. Vol. 110, no 17, 6853-6858 p.
Keyword [en]
Breast-Cancer, Annexin A1, Cell-Migration, Tumor-Growth, T-Antigen, Carcinogenesis, Metastasis, Hallmarks, Carcinoma, Oncogenes
National Category
Biological Sciences Medical and Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-123630DOI: 10.1073/pnas.1216436110ISI: 000318677300059Scopus ID: 2-s2.0-84876846983OAI: oai:DiVA.org:kth-123630DiVA: diva2:628457
Funder
Knut and Alice Wallenberg FoundationScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20130614

Available from: 2013-06-14 Created: 2013-06-13 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Integration of RNA and protein expression profiles to study human cells
Open this publication in new window or tab >>Integration of RNA and protein expression profiles to study human cells
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cellular life is highly complex. In order to expand our understanding of the workings of human cells, in particular in the context of health and disease, detailed knowledge about the underlying molecular systems is needed. The unifying theme of this thesis concerns the use of data derived from sequencing of RNA, both within the field of transcriptomics itself and as a guide for further studies at the level of protein expression. In paper I, we showed that publicly available RNA-seq datasets are consistent across different studies, requiring only light processing for the data to cluster according to biological, rather than technical characteristics. This suggests that RNA-seq has developed into a reliable and highly reproducible technology, and that the increasing amount of publicly available RNA-seq data constitutes a valuable resource for meta-analyses. In paper II, we explored the ability to extrapolate protein concentrations by the use of RNA expression levels. We showed that mRNA and corresponding steady-state protein concentrations correlate well by introducing a gene-specific RNA-to-protein conversion factor that is stable across various cell types and tissues. The results from this study indicate the utility of RNA-seq also within the field of proteomics.

The second part of the thesis starts with a paper in which we used transcriptomics to guide subsequent protein studies of the molecular mechanisms underlying malignant transformation. In paper III, we applied a transcriptomics approach to a cell model for defined steps of malignant transformation, and identified several genes with interesting expression patterns whose corresponding proteins were further analyzed with subcellular spatial resolution. Several of these proteins were further studied in clinical tumor samples, confirming that this cell model provides a relevant system for studying cancer mechanisms. In paper IV, we continued to explore the transcriptional landscape in the same cell model under moderate hypoxic conditions.

To conclude, this thesis demonstrates the usefulness of RNA-seq data, from a transcriptomics perspective and beyond; to guide in analyses of protein expression, with the ultimate goal to unravel the complexity of the human cell, from a holistic point of view.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. 54 p.
Series
TRITA-BIO-Report, ISSN 1654-2312
Keyword
RNA-seq, Transcriptomics, Proteomics, Malignant transformation, Cancer, Functional enrichment
National Category
Biological Sciences
Research subject
Biotechnology; Medical Technology
Identifiers
urn:nbn:se:kth:diva-196700 (URN)978-91-7729-209-8 (ISBN)
Public defence
2016-12-16, Rockefeller, Nobels väg 11, Solna, 13:00 (English)
Opponent
Supervisors
Funder
Knut and Alice Wallenberg Foundation
Note

QC 20161121

Available from: 2016-11-21 Created: 2016-11-18 Last updated: 2016-11-21Bibliographically approved

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Skogs, MarieUhlén, MathiasLundberg, Emma

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