| 21. |
- Fasterius, Erik, 1987-
(författare)
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Exploring genetic heterogeneity in cancer using high-throughput DNA and RNA sequencing
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 22. |
- Fasterius, Erik, 1987-, et al.
(författare)
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SeqCAT : A bioconductor R-package for variant analysis of high throughput sequencing data [version 1; peer review: 1 approved with reservations, 1 not approved]
- 2018
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Ingår i: F1000 Research. - : F1000 Research Ltd. - 2046-1402. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- High throughput sequencing technologies are flourishing in the biological sciences, enabling unprecedented insights into e.g. genetic variation, but require extensive bioinformatic expertise for the analysis. There is thus a need for simple yet effective software that can analyse both existing and novel data, providing interpretable biological results with little bioinformatic prowess. We present seqCAT, a Bioconductor toolkit for analysing genetic variation in high throughput sequencing data. It is a highly accessible, easy-to-use and well-documented R-package that enables a wide range of researchers to analyse their own and publicly available data, providing biologically relevant conclusions and publication-ready figures. SeqCAT can provide information regarding genetic similarities between an arbitrary number of samples, validate specific variants as well as define functionally similar variant groups for further downstream analyses. Its ease of use, installation, complete data-to-conclusions functionality and the inherent flexibility of the R programming language make seqCAT a powerful tool for variant analyses compared to already existing solutions. A publicly available dataset of liver cancer-derived organoids is analysed herein using the seqCAT package, demonstrating that the organoids are genetically stable. A previously known liver cancer-related mutation is additionally shown to be present in a sample though it was not listed in the original publication. Differences between DNA- and RNA-based variant calls in this dataset are also analysed revealing a high median concordance of 97.5%.
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| 23. |
- Fasterius, Erik, 1987-, et al.
(författare)
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Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer
- 2019
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Ingår i: Scientific Reports. - : NATURE PUBLISHING GROUP. - 2045-2322. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 24. |
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| 25. |
- Forslund, Kristoffer, 1980-
(författare)
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The relationship between orthology, protein domain architecture and protein function
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Lacking experimental data, protein function is often predicted from evolutionary and protein structure theory. Under the 'domain grammar' hypothesis the function of a protein follows from the domains it encodes. Under the 'orthology conjecture', orthologs, related through species formation, are expected to be more functionally similar than paralogs, which are homologs in the same or different species descended from a gene duplication event. However, these assumptions have not thus far been systematically evaluated. To test the 'domain grammar' hypothesis, we built models for predicting function from the domain combinations present in a protein, and demonstrated that multi-domain combinations imply functions that the individual domains do not. We also developed a novel gene-tree based method for reconstructing the evolutionary histories of domain architectures, to search for cases of architectures that have arisen multiple times in parallel, and found this to be more common than previously reported. To test the 'orthology conjecture', we first benchmarked methods for homology inference under the obfuscating influence of low-complexity regions, in order to improve the InParanoid orthology inference algorithm. InParanoid was then used to test the relative conservation of functionally relevant properties between orthologs and paralogs at various evolutionary distances, including intron positions, domain architectures, and Gene Ontology functional annotations. We found an increased conservation of domain architectures in orthologs relative to paralogs, in support of the 'orthology conjecture' and the 'domain grammar' hypotheses acting in tandem. However, equivalent analysis of Gene Ontology functional conservation yielded spurious results, which may be an artifact of species-specific annotation biases in functional annotation databases. I discuss possible ways of circumventing this bias so the 'orthology conjecture' can be tested more conclusively.
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| 26. |
- Johansson, Camilla, et al.
(författare)
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Identification of Gene-Therapy Responsive Blood Biomarkers for Duchenne Muscular Dystrophy
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- IntroductionAssessing muscle dystrophin expression systemically is important for understanding the effect of dystrophin-restoring therapies in Duchenne muscular dystrophy (DMD). Many potential blood biomarkers have been identified in DMD patients which are either more or less abundant in blood samples compared to healthy individuals and that have been shown to change with disease progression or respond to pharmacological treatment. In this study, it was suggested that a panel of such blood biomarker candidates could be used to monitor dystrophin rescue in microdystrophin therapies. MethodsPlasma samples from mdx mice treated with the microdystrophin therapy SGT-001 were analysed with an antibody suspension bead array consisting of 87 antibodies targeting 83 proteins previously identified as biomarker candidates for DMD. Each sample was assayed at two different plasma dilutions to cover a broader concentration range. Median fluorescent intensities (MFI) for each antibody were correlated to dystrophin expression in muscle tissue, as measured by immunohistochemistry and Western blot. 13 targets were selected and validated in a DMD and Becker muscular dystrophy (BMD) longitudinal natural history cohort using a suspension bead array. Results10 proteins were found significantly elevated in untreated mdx mice compared to C57 wild-type mice and 10 were found to correlate with dystrophin expression (Spearman’s correlation, FDR < 0.05) upon gene transfer. Abundance of TTN, ADSSL1, LONP1, OTUD5, MYL3 as well as DMD protein were associated with dystrophin expression in BMD patients. Of these, MYL3 and ADSSL1 had different abundance in DMD compared to healthy individuals, and MYL3 also displayed different age trajectories between DMD and BMD patients. DiscussionThe ten proteins identified in mouse plasma are related to muscle contraction (ADSSL1, ASAH1, CA3, MYL3, TTN), microtubule formation (TPI1), and protein degradation (PSMA2, OTUD4, LONP1). Of these, MYL3 and ADSSL1 showed the most promise as a dystrophin monitoring biomarker in patient samples.
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| 27. |
- Johansson, Camilla, et al.
(författare)
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Monitoring Biomarker Study in Becker Muscular Dystrophy using Data Independent Acquisition LC-MS/MS
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Becker muscular dystrophy (BMD) is a rare and heterogenous form of dystrophinopathy caused by reduced expression of altered dystrophin protein. Gene therapies and exon-skipping therapies for the more severe form of dystrophinopathy, Duchenne muscular dystrophy (DMD), assumes that by promoting partial dystrophin expression in DMD patients, their disease progression could be reduced. Several studies have identified potential progression biomarkers for DMD and hypothesised in their usefulness in monitoring pharmacodynamic response in gene-therapy clinical trials. However, knowledge of progression changes of blood proteome in BMD is lacking. In this study, we aimed at exploring differences in proteomic changes between DMD and BMD in a prospective longitudinal 4-year study as well as explore what proteins relate to functional performance in BMD patients. Serum from 48 BMD patients and 19 DMD patients were analysed using Data Independent Acquisition Tandem Mass Spectrometry (DIA-MS). Linear mixed effects models identified 17 proteins with altered longitudinal signatures between DMD and BMD, among these CKM, PKM and ALDOA. Furthermore, bikunin (product of AMBP gene), C3 and IGHG2 were found related to functional performance in BMD patients.
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| 28. |
- Johansson, Camilla, 1993-, et al.
(författare)
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Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers
- 2023
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Ingår i: Clinical Proteomics. - : Springer Nature. - 1542-6416 .- 1559-0275. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundMolecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools.MethodsTwo technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS).ResultsFive, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml.ConclusionsThese results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.
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| 29. |
- Johansson, Camilla, 1993-
(författare)
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Proteomic strategies for blood biomarker development in rare dystrophinopathies
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are two rare genetic disorders of the family dystrophinopathy. They are both caused by the lack of, or reduced production of, the protein dystrophin. Due to abnormal dystrophin expression, patients experience progressive loss of muscle mass and cardio-, respiratory- and sometimes cognitive complications. DMD is the more severe form of dystrophinopathy, which manifests in young children and leads to wheelchair confinement in early teens followed by bed confinement and a shortened life expectancy. Dystrophin expression is absent or at less than 3% in DMD patients, often due to frame-shift mutations which cause protein expression to stop pre-maturely. BMD patients, on the other hand, display a higher but variable expression of dystrophin, often with large internal truncations. This partial expression results in a milder phenotype than DMD with sometimes unaffected life expectancies compared to healthy individuals. In the past decade, there has been substantial research into therapies aiming at increasing dystrophin expression in DMD patients and thereby prolonging ambulation, with the first gene-therapy gaining regulatory approval from the U.S. Food and Drug Administration (FDA) in June 2023. Current regulatory approvals for treatments of DMD patients have relied on dystrophin quantification in muscle biopsies as a biomarker and surrogate endpoint to predict a possible benefit from treatment, but these tests require repeated collection of muscle biopsies. Biomarkers are biochemical or physiological laboratory tests that measure a biological processes or condition. There is a need for monitoring biomarkers in dystrophinopathies, as well as biomarkers which can be used to predict outcome in clinical trials. As patients are often young children, it is important to develop biomarkers from less invasive and more readily available biological samples than muscle biopsies, such as blood or urine.In this thesis, we have used affinity proteomics and mass spectrometry to identify and validate biomarkers for monitoring disease progression in DMD and BMD patients from serum or plasma. The overall aim has been to identify biomarkers capable of distinguishing between patients with different levels of dystrophin expression and rates of disease progression in order to suggest gene-therapy pharmacodynamic biomarkers. In Paper I, we used suspension bead array (SBA) technology to identify biomarker candidates which reflect disease progression in DMD. Ten proteins were identified as related to disease progression. The ten biomarker candidates identified in Paper I were further analytically validated in Paper II using two orthogonal and absolute quantitative methods, parallel reaction monitoring mass spectrometry (PRM-MS) and sandwich immunoassays, which resulted in five analytically validated disease monitoring biomarkers for DMD (CA3, MYL3, LDHB, COL1A1 and FGG).Dystrophin-restoring therapies build on the hypothesis that increasing expression of internally deleted dystrophin reduces disease severity. In BMD patients, partial expression of short dystrophin molecules results in a milder phenotype than in DMD patients lacking expression of dystrophin. However, there are some differences in the nature of disease progression between DMD and BMD. In Paper III, we used Data Independent Acquisition Mass Spectrometry (DIA-MS) to study proteomic similarities and differences between DMD and BMD disease progression. This study revealed some discrepancies between disease progression biomarker candidates in the two related disorders.In Paper IV, we searched for blood biomarkers capable of reflecting changes in dystrophin expression during gene-therapy clinical trials. We identified ten proteins which correlated with dystrophin or microdystrophin expression in DMD mouse models. Out of these ten proteins, we identified that myosin light chain 3 (MYL3) declined steeper over time in dystrophinopathy patients with low or no dystrophin expression compared to patients with higher dystrophin expression. Two more biomarkers were identified in Paper IV as potentially related to dystrophin expression in muscle biopsies from both mouse models and patients. These were titin (TTN) and, interestingly, serum leakage of dystrophin. The possible presence of dystrophin in blood has not been well studied, and only one prior publication suggests that dystrophin may be a biomarker for DMD. Many DMD therapies currently in clinical trials aims at restoring dystrophin production and for those trials, the possibility of monitoring dystrophin leakage into blood could provide valuable information on therapeutic efficacy. In Paper V, we designed a proof-of-principle study to explore if dystrophin in blood can be a DMD biomarker. In conclusion, this thesis explores disease progression monitoring biomarkers and gene-therapy pharmacodynamic biomarkers for DMD and BMD. Three proteins, MYL3, TTN, and serum levels of dystrophin, are here suggested as possible gene-therapy pharmacodynamic biomarkers.
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| 30. |
- Kennedy, S. A., et al.
(författare)
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Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D
- 2020
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how oncogenic mutations impact these interactions and their functions at a network-level scale is poorly understood. Here, we analyze how a common oncogenic KRAS mutation (KRASG13D) affects PPIN structure and function of the Epidermal Growth Factor Receptor (EGFR) network in colorectal cancer (CRC) cells. Mapping >6000 PPIs shows that this network is extensively rewired in cells expressing transforming levels of KRASG13D (mtKRAS). The factors driving PPIN rewiring are multifactorial including changes in protein expression and phosphorylation. Mathematical modelling also suggests that the binding dynamics of low and high affinity KRAS interactors contribute to rewiring. PPIN rewiring substantially alters the composition of protein complexes, signal flow, transcriptional regulation, and cellular phenotype. These changes are validated by targeted and global experimental analysis. Importantly, genetic alterations in the most extensively rewired PPIN nodes occur frequently in CRC and are prognostic of poor patient outcomes.
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