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Al-Khalili Szigyarto, CristinaORCID iD iconorcid.org/0000-0001-6990-1905
Alternative names
Publications (10 of 43) 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
Edfors, F., Hober, A., Linderbäck, K., Maddalo, G., Azimi, A., Sivertsson, Å., . . . Uhlén, M. (2018). Enhanced validation of antibodies for research applications. Nature Communications, 9, Article ID 4130.
Open this publication in new window or tab >>Enhanced validation of antibodies for research applications
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2018 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 9, article id 4130Article in journal (Refereed) Published
Abstract [en]

There is a need for standardized validation methods for antibody specificity and selectivity. Recently, five alternative validation pillars were proposed to explore the specificity of research antibodies using methods with no need for prior knowledge about the protein target. Here, we show that these principles can be used in a streamlined manner for enhanced validation of research antibodies in Western blot applications. More than 6,000 antibodies were validated with at least one of these strategies involving orthogonal methods, genetic knockdown, recombinant expression, independent antibodies, and capture mass spectrometry analysis. The results show a path forward for efforts to validate antibodies in an application-specific manner suitable for both providers and users.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018
National Category
Immunology in the medical area
Identifiers
urn:nbn:se:kth:diva-237096 (URN)10.1038/s41467-018-06642-y (DOI)000446566000016 ()30297845 (PubMedID)2-s2.0-85054574300 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg Foundation
Note

QC 20181030

Available from: 2018-10-30 Created: 2018-10-30 Last updated: 2018-10-30Bibliographically approved
Spitali, P., Hettne, K., Tsonaka, R., Charrout, M., van den Bergen, J., Koeks, Z., . . . Aartsma-Rus, A. (2018). Tracking disease progression non-invasively in Duchenne and Becker muscular dystrophies. Journal of Cachexia, Sarcopenia and Muscle, 9(4), 715-726
Open this publication in new window or tab >>Tracking disease progression non-invasively in Duchenne and Becker muscular dystrophies
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2018 (English)In: Journal of Cachexia, Sarcopenia and Muscle, ISSN 2190-5991, E-ISSN 2190-6009, Vol. 9, no 4, p. 715-726Article in journal (Refereed) Published
Abstract [en]

Background Analysis of muscle biopsies allowed to characterize the pathophysiological changes of Duchenne and Becker muscular dystrophies (D/BMD) leading to the clinical phenotype. Muscle tissue is often investigated during interventional dose finding studies to show in situ proof of concept and pharmacodynamics effect of the tested drug. Less invasive readouts are needed to objectively monitor patients' health status, muscle quality, and response to treatment. The identification of serum biomarkers correlating with clinical function and able to anticipate functional scales is particularly needed for personalized patient management and to support drug development programs. Methods A large-scale proteomic approach was used to identify serum biomarkers describing pathophysiological changes (e.g. loss of muscle mass), association with clinical function, prediction of disease milestones, association with in vivo(31)P magnetic resonance spectroscopy data and dystrophin levels in muscles. Cross-sectional comparisons were performed to compare DMD patients, BMD patients, and healthy controls. A group of DMD patients was followed up for a median of 4.4years to allow monitoring of individual disease trajectories based on yearly visits. Results Cross-sectional comparison enabled to identify 10 proteins discriminating between healthy controls, DMD and BMD patients. Several proteins (285) were able to separate DMD from healthy, while 121 proteins differentiated between BMD and DMD; only 13 proteins separated BMD and healthy individuals. The concentration of specific proteins in serum was significantly associated with patients' performance (e.g. BMP6 serum levels and elbow flexion) or dystrophin levels (e.g. TIMP2) in BMD patients. Analysis of longitudinal trajectories allowed to identify 427 proteins affected over time indicating loss of muscle mass, replacement of muscle by adipose tissue, and cardiac involvement. Over-representation analysis of longitudinal data allowed to highlight proteins that could be used as pharmacodynamic biomarkers for drugs currently in clinical development. Conclusions Serum proteomic analysis allowed to not only discriminate among DMD, BMD, and healthy subjects, but it enabled to detect significant associations with clinical function, dystrophin levels, and disease progression.

Place, publisher, year, edition, pages
Wiley-VCH Verlagsgesellschaft, 2018
Keywords
Biomarker, Duchenne muscular dystrophy, Becker muscular dystrophy, Longitudinal analysis, Proteomics, Sarcopenia
National Category
Clinical Laboratory Medicine
Identifiers
urn:nbn:se:kth:diva-234633 (URN)10.1002/jcsm.12304 (DOI)000442345000009 ()29682908 (PubMedID)2-s2.0-85052068809 (Scopus ID)
Note

QC 20180913

Available from: 2018-09-13 Created: 2018-09-13 Last updated: 2018-11-13Bibliographically 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
Fasterius, E., Raso, C., Kennedy, S., Rauch, N., Lundin, P., Kolch, W., . . . Al-Khalili Szigyarto, C. (2017). A novel RNA sequencing data analysis method for cell line authentication. PLoS ONE, 12(2), Article ID e0171435.
Open this publication in new window or tab >>A novel RNA sequencing data analysis method for cell line authentication
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2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 2, article id e0171435Article in journal (Refereed) Published
Abstract [en]

We have developed a novel analysis method that can interrogate the authenticity of biological samples used for generation of transcriptome profiles in public data repositories. The method uses RNA sequencing information to reveal mutations in expressed transcripts and subsequently confirms the identity of analysed cells by comparison with publicly available cell-specific mutational profiles. Cell lines constitute key model systems widely used within cancer research, but their identity needs to be confirmed in order to minimise the influence of cell contaminations and genetic drift on the analysis. Using both public and novel data, we demonstrate the use of RNA-sequencing data analysis for cell line authentication by examining the validity of COLO205, DLD1, HCT15, HCT116, HKE3, HT29 and RKO colorectal cancer cell lines. We successfully authenticate the studied cell lines and validate previous reports indicating that DLD1 and HCT15 are synonymous. We also show that the analysed HKE3 cells harbour an unexpected KRAS-G13D mutation and confirm that this cell line is a genuine KRAS dosage mutant, rather than a true isogenic derivative of HCT116 expressing only the wild type KRAS. This authentication method could be used to revisit the numerous cell line based RNA sequencing experiments available in public data repositories, analyse new experiments where whole genome sequencing is not available, as well as facilitate comparisons of data from different experiments, platforms and laboratories.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE, 2017
National Category
Biological Sciences
Identifiers
urn:nbn:se:kth:diva-204084 (URN)10.1371/journal.pone.0171435 (DOI)000394423800024 ()28192450 (PubMedID)2-s2.0-85012231859 (Scopus ID)
Note

QC 20170329

Available from: 2017-03-29 Created: 2017-03-29 Last updated: 2018-09-05Bibliographically approved
Lourbakos, A., Yau, N., de Bruijn, P., Hiller, M., Kozaczynska, K., Jean-Baptiste, R., . . . Spitali, P. (2017). Evaluation of serum MMP-9 as predictive biomarker for antisense therapy in Duchenne. Scientific Reports, 7, Article ID 17888.
Open this publication in new window or tab >>Evaluation of serum MMP-9 as predictive biomarker for antisense therapy in Duchenne
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2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 17888Article in journal (Refereed) Published
Abstract [en]

Duchenne Muscular Dystrophy (DMD) is a severe muscle disorder caused by lack of dystrophin. Predictive biomarkers able to anticipate response to the therapeutic treatments aiming at dystrophin re-expression are lacking. The objective of this study is to investigate Matrix Metalloproteinase-9 (MMP-9) as predictive biomarker for Duchenne. Two natural history cohorts were studied including 168 longitudinal samples belonging to 66 patients. We further studied 1536 samples obtained from 3 independent clinical trials with drisapersen, an antisense oligonucleotide targeting exon 51: an open label study including 12 patients; a phase 3 randomized, double blind, placebo controlled study involving 186 patients; an open label extension study performed after the phase 3. Analysis of natural history cohorts showed elevated MMP-9 levels in patients and a significant increase over time in longitudinal samples. MMP-9 decreased in parallel to clinical stabilization in the 12 patients involved in the open label study. The phase 3 study and subsequent extension study clarified that the decrease in MMP-9 levels was not predictive of treatment response. These data do not support the inclusion of serum MMP-9 as predictive biomarker for DMD patients.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2017
National Category
Clinical Laboratory Medicine
Identifiers
urn:nbn:se:kth:diva-220826 (URN)10.1038/s41598-017-17982-y (DOI)000418388700008 ()2-s2.0-85038627721 (Scopus ID)
Note

QC 20180111

Available from: 2018-01-11 Created: 2018-01-11 Last updated: 2018-02-20Bibliographically approved
Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., . . . Pontén, F. (2015). Tissue-based map of the human proteome. Science, 347(6220), 1260419
Open this publication in new window or tab >>Tissue-based map of the human proteome
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2015 (English)In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 347, no 6220, p. 1260419-Article in journal (Refereed) Published
Abstract [en]

Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Keywords
isoprotein, membrane protein, protein, proteome, tumor protein
National Category
Biological Sciences
Identifiers
urn:nbn:se:kth:diva-160035 (URN)10.1126/science.1260419 (DOI)000348225800036 ()25613900 (PubMedID)2-s2.0-84925582323 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg Foundation
Note

QC 20150216

Available from: 2015-02-13 Created: 2015-02-13 Last updated: 2018-10-17Bibliographically approved
Fagerberg, L., Hallström, B. M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., . . . Uhlén, M. (2014). Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Molecular & Cellular Proteomics, 13(2), 397-406
Open this publication in new window or tab >>Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics
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2014 (English)In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 13, no 2, p. 397-406Article in journal (Refereed) Published
Abstract [en]

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.

Keywords
article, gene expression, human, human tissue, immunohistochemistry, priority journal, protein analysis, protein expression, proteomics, spermatogenesis, transcriptomics
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-142992 (URN)10.1074/mcp.M113.035600 (DOI)000331369000002 ()24309898 (PubMedID)2-s2.0-84893276590 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg FoundationEU, FP7, Seventh Framework Programme, HEALTH-F4-2008-201648/PROSPECTS
Note

QC 20140314

Available from: 2014-03-14 Created: 2014-03-14 Last updated: 2017-12-05Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-6990-1905

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