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Publications (8 of 8) Show all publications
Fasterius, E., Uhlén, M. & Al-Khalili Szigyarto, C. (2019). Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer. Scientific Reports, 9, Article ID 9524.
Open this publication in new window or tab >>Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer
2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 9524Article in journal (Refereed) Published
Abstract [en]

Inter-and intra-tumour heterogeneity is caused by genetic and non-genetic factors, leading to severe clinical implications. High-throughput sequencing technologies provide unprecedented tools to analyse DNA and RNA in single cells and explore both genetic heterogeneity and phenotypic variation between cells in tissues and tumours. Simultaneous analysis of both DNA and RNA in the same cell is, however, still in its infancy. We have thus developed a method to extract and analyse information regarding genetic heterogeneity that affects cellular biology from single-cell RNA-seq data. The method enables both comparisons and clustering of cells based on genetic variation in single nucleotide variants, revealing cellular subpopulations corroborated by gene expression-based methods. Furthermore, the results show that lymph node metastases have lower levels of genetic heterogeneity compared to their original tumours with respect to variants affecting protein function. The analysis also revealed three previously unknown variants common across cancer cells in glioblastoma patients. These results demonstrate the power and versatility of scRNA-seq variant analysis and highlight it as a useful complement to already existing methods, enabling simultaneous investigations of both gene expression and genetic variation.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Medical Genetics
Identifiers
urn:nbn:se:kth:diva-255413 (URN)10.1038/s41598-019-45934-1 (DOI)000473417000015 ()31267007 (PubMedID)2-s2.0-85069268174 (Scopus ID)
Note

QC 20190814

Available from: 2019-08-14 Created: 2019-08-14 Last updated: 2019-08-14Bibliographically approved
Charitou, T., Srihari, S., Lynn, M. A., Jarboui, M.-A., Fasterius, E., Moldovan, M., . . . Lynn, D. J. (2019). Transcriptional and metabolic rewiring of colorectal cancer cells expressing the oncogenic KRAS(G13D) mutation. British Journal of Cancer, 121(1), 37-50
Open this publication in new window or tab >>Transcriptional and metabolic rewiring of colorectal cancer cells expressing the oncogenic KRAS(G13D) mutation
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2019 (English)In: British Journal of Cancer, ISSN 0007-0920, E-ISSN 1532-1827, Vol. 121, no 1, p. 37-50Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, leading to resistance to EGFRtargeted therapies. METHODS: To better understand the cellular reprogramming which occurs in mutant KRAS cells, we have undertaken a systems-level analysis of four CRC cell lines which express either wild type (wt) KRAS or the oncogenic KRAS(G13D) allele (mtKRAS). RESULTS: RNAseq revealed that genes involved in ribosome biogenesis, mRNA translation and metabolism were significantly upregulated in mtKRAS cells. Consistent with the transcriptional data, protein synthesis and cell proliferation were significantly higher in the mtKRAS cells. Targeted metabolomics analysis also confirmed the metabolic reprogramming in mtKRAS cells. Interestingly, mtKRAS cells were highly transcriptionally responsive to EGFR activation by TGF alpha stimulation, which was associated with an unexpected downregulation of genes involved in a range of anabolic processes. While TGF alpha treatment strongly activated protein synthesis in wtKRAS cells, protein synthesis was not activated above basal levels in the TGF alpha-treated mtKRAS cells. This was likely due to the defective activation of the mTORC1 and other pathways by TGF alpha in mtKRAS cells, which was associated with impaired activation of PKB signalling and a transient induction of AMPK signalling. CONCLUSIONS: We have found that mtKRAS cells are substantially rewired at the transcriptional, translational and metabolic levels and that this rewiring may reveal new vulnerabilities in oncogenic KRAS CRC cells that could be exploited in future.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-255415 (URN)10.1038/s41416-019-0477-7 (DOI)000473525700007 ()31133691 (PubMedID)2-s2.0-85068397826 (Scopus ID)
Note

QC 20190815

Available from: 2019-08-15 Created: 2019-08-15 Last updated: 2019-08-15Bibliographically approved
Fasterius, E. & Al-Khalili Szigyarto, C. (2018). Analysis of public RNA-sequencing data reveals biological consequences of genetic heterogeneity in cell line populations. Scientific Reports, 8, Article ID 11226.
Open this publication in new window or tab >>Analysis of public RNA-sequencing data reveals biological consequences of genetic heterogeneity in cell line populations
2018 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, article id 11226Article in journal (Refereed) Published
Abstract [en]

Meta-analysis of datasets available in public repositories are used to gather and summarise experiments performed across laboratories, as well as to explore consistency of scientific findings. As data quality and biological equivalency across samples may obscure such analyses and consequently their conclusions, we investigated the comparability of 85 public RNA-seq cell line datasets. Thousands of pairwise comparisons of single nucleotide variants in 139 samples revealed variable genetic heterogeneity of the eight cell line populations analysed as well as variable data quality. The H9 and HCT116 cell lines were found to be remarkably stable across laboratories (with median concordances of 99.2% and 98.5%, respectively), in contrast to the highly variable HeLa cells (89.3%). We show that the genetic heterogeneity encountered greatly affects gene expression between same-cell comparisons, highlighting the importance of interrogating the biological equivalency of samples when comparing experimental datasets. Both the number of differentially expressed genes and the expression levels negatively correlate with the genetic heterogeneity. Finally, we demonstrate how comparing genetically heterogeneous datasets affect gene expression analyses and that high dissimilarity between same-cell datasets alters the expression of more than 300 cancer-related genes, which are often the focus of studies using cell lines.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
National Category
Medical Genetics
Identifiers
urn:nbn:se:kth:diva-232882 (URN)10.1038/s41598-018-29506-3 (DOI)000439686700049 ()30046134 (PubMedID)2-s2.0-85050698721 (Scopus ID)
Note

QC 20180809

Available from: 2018-08-09 Created: 2018-08-09 Last updated: 2019-05-15Bibliographically approved
Fasterius, E. (2018). Exploring genetic heterogeneity in cancer using high-throughput DNA and RNA sequencing. (Doctoral dissertation). Stockholm: Kungliga tekniska högskolan
Open this publication in new window or tab >>Exploring genetic heterogeneity in cancer using high-throughput DNA and RNA sequencing
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

High-throughput sequencing (HTS) technology has revolutionised the biomedical sciences, where it is used to analyse the genetic makeup and gene expression patterns of both primary patient tissue samples and models cultivated in vitro. This makes it especially useful for research on cancer, a disease that is characterised by its deadliness and genetic heterogeneity. This inherent genetic variation is an important aspect that warrants exploration, and the depth and breadth that HTS possesses makes it well-suited to investigate this facet of cancer.

The types of analyses that may be accomplished with HTS technologies are many, but they may be divided into two groups: those that analyse the DNA of the sample in question, and those that work on the RNA. While DNA-based methods give information regarding the genetic landscape of the sample, RNA-based analyses yield data regarding gene expression patterns; both of these methods have already been used to investigate the heterogeneity present in cancer. While RNA-based methods are traditionally used exclusively for expression analyses, the data they yield may also be utilised to investigate the genetic variation present in the samples. This type of RNA-based analysis is seldom performed, however, and valuable information is thus ignored.

The aim of this thesis is the development and application of DNA- and RNA- based HTS methods for analysing genetic heterogeneity within the context of cancer. The present investigation demonstrates that not only may RNA-based sequencing be used to successfully differentiate different in vitro cancer models through their genetic makeup, but that this may also be done for primary patient data. A pipeline for these types of analyses is established and evaluated, showing it to be both robust to several technical parameters as well as possess a broad scope of analytical possibilities. Genetic variation within cancer models in public databases are evaluated and demonstrated to affect gene expression in several cases. Both inter- and intra-patient genetic heterogeneity is shown using the established pipeline, in addition to demonstrating that cancerous cells are more heterogeneous than their normal neighbours. Finally, two bioinformatic open source software packages are presented.

The results presented herein demonstrate that genetic analyses using RNA-based methods represent excellent complements to already existing DNA-based techniques, and further increase the already large scope of how HTS technologies may be utilised.

Place, publisher, year, edition, pages
Stockholm: Kungliga tekniska högskolan, 2018. p. 83
Series
TRITA-CBH-FOU ; 2018:31
Keywords
Biotechnology, bioinformatics, RNA-seq, WGS, WES, systems biology, variant analysis, single nucleotide variant, gene expression, machine learning, clustering, open source, R, bioconductor, Python
National Category
Medical Biotechnology Bioinformatics and Systems Biology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-234265 (URN)978-91-7729-918-9 (ISBN)
Public defence
2018-10-05, FR4, Oskar Klein's Auditorium, Albanova, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20180906

Available from: 2018-09-06 Created: 2018-09-05 Last updated: 2018-09-06Bibliographically approved
Danielsson, F., Fasterius, E., Sullivan, D., Hases, L., Sanli, K., Zhang, C., . . . Lundberg, E. (2018). Transcriptome profiling of the interconnection of pathways involved in malignant transformation and response to hypoxia. OncoTarget, 9(28), 19730-19744
Open this publication in new window or tab >>Transcriptome profiling of the interconnection of pathways involved in malignant transformation and response to hypoxia
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2018 (English)In: OncoTarget, ISSN 1949-2553, E-ISSN 1949-2553, Vol. 9, no 28, p. 19730-19744Article in journal (Refereed) Published
Abstract [en]

In tumor tissues, hypoxia is a commonly observed feature resulting from rapidly proliferating cancer cells outgrowing their surrounding vasculature network. Transformed cancer cells are known to exhibit phenotypic alterations, enabling continuous proliferation despite a limited oxygen supply. The four-step isogenic BJ cell model enables studies of defined steps of tumorigenesis: the normal, immortalized, transformed, and metastasizing stages. By transcriptome profiling under atmospheric and moderate hypoxic (3% O2) conditions, we observed that despite being highly similar, the four cell lines of the BJ model responded strikingly different to hypoxia. Besides corroborating many of the known responses to hypoxia, we demonstrate that the transcriptome adaptation to moderate hypoxia resembles the process of malignant transformation. The transformed cells displayed a distinct capability of metabolic switching, reflected in reversed gene expression patterns for several genes involved in oxidative phosphorylation and glycolytic pathways. By profiling the stage-specific responses to hypoxia, we identified ASS1 as a potential prognostic marker in hypoxic tumors. This study demonstrates the usefulness of the BJ cell model for highlighting the interconnection of pathways involved in malignant transformation and hypoxic response.

Place, publisher, year, edition, pages
Impact Journals LLC, 2018
Keywords
Hypoxia, Malignant transformation, Transcriptomics
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-227616 (URN)10.18632/oncotarget.24808 (DOI)2-s2.0-85045315705 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180522

Available from: 2018-05-22 Created: 2018-05-22 Last updated: 2019-04-26Bibliographically approved
Kennedy, S., Fasterius, E., Al-Khalili Szigyarto, C., Kolch, W. & et al., .Adaptive rewiring of protein-protein interactions and signal flow in the EGFR signaling network by mutant RAS.
Open this publication in new window or tab >>Adaptive rewiring of protein-protein interactions and signal flow in the EGFR signaling network by mutant RAS
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(English)Manuscript (preprint) (Other academic)
National Category
Bioinformatics and Systems Biology Medical Biotechnology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-234291 (URN)
Note

QC 20180906

Available from: 2018-09-06 Created: 2018-09-06 Last updated: 2018-09-06Bibliographically approved
Fasterius, E.seqCAT: a Bioconductor R-package for variant analysis of high throughput sequencing data.
Open this publication in new window or tab >>seqCAT: a Bioconductor R-package for variant analysis of high throughput sequencing data
(English)Manuscript (preprint) (Other academic)
National Category
Bioinformatics and Systems Biology Medical Biotechnology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-234292 (URN)
Note

QC 20180906

Available from: 2018-09-06 Created: 2018-09-06 Last updated: 2018-09-06Bibliographically approved
Fasterius, E., Uhlén, M. & Al-Khalili Szigyarto, C.Single cell RNA-seq variant analysis for exploration of inter- and intra-tumour genetic heterogeneity.
Open this publication in new window or tab >>Single cell RNA-seq variant analysis for exploration of inter- and intra-tumour genetic heterogeneity
(English)Manuscript (preprint) (Other academic)
National Category
Medical Biotechnology Bioinformatics and Systems Biology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-234293 (URN)
Note

QC 20180906

Available from: 2018-09-06 Created: 2018-09-06 Last updated: 2018-09-06Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-0492-9960

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