| 1. |
- Enroth, Stefan, et al.
(författare)
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Cancer associated epigenetic transitions identified by genome-wide histone methylation binding profiles in human colorectal cancer samples and paired normal mucosa
- 2011
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Ingår i: BMC Cancer. - : BioMed Central. - 1471-2407. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Despite their well-established functional roles, histone modifications have received less attention than DNA methylation in the cancer field. In order to evaluate their importance in colorectal cancer (CRC), we generated the first genome-wide histone modification profiles in paired normal colon mucosa and tumor samples.METHODS: Chromatin immunoprecipitation and microarray hybridization (ChIP-chip) was used to identify promoters enriched for histone H3 trimethylated on lysine 4 (H3K4me3) and lysine 27 (H3K27me3) in paired normal colon mucosa and tumor samples from two CRC patients and for the CRC cell line HT29.RESULTS: By comparing histone modification patterns in normal mucosa and tumors, we found that alterations predicted to have major functional consequences were quite rare. Furthermore, when normal or tumor tissue samples were compared to HT29, high similarities were observed for H3K4me3. However, the differences found for H3K27me3, which is important in determining cellular identity, indicates that cell lines do not represent optimal tissue models. Finally, using public expression data, we uncovered previously unknown changes in CRC expression patterns. Genes positive for H3K4me3 in normal and/or tumor samples, which are typically already active in normal mucosa, became hyperactivated in tumors, while genes with H3K27me3 in normal and/or tumor samples and which are expressed at low levels in normal mucosa, became hypersilenced in tumors.CONCLUSIONS: Genome wide histone modification profiles can be used to find epigenetic aberrations in genes associated with cancer. This strategy gives further insights into the epigenetic contribution to the oncogenic process and may identify new biomarkers.
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| 2. |
- Hvidsten, Torgeir R, et al.
(författare)
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A comprehensive analysis of the structure-function relationship in proteins based on local structure similarity
- 2009
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 4:7, s. e6266-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Sequence similarity to characterized proteins provides testable functional hypotheses for less than 50% of the proteins identified by genome sequencing projects. With structural genomics it is believed that structural similarities may give functional hypotheses for many of the remaining proteins. METHODOLOGY/PRINCIPAL FINDINGS: We provide a systematic analysis of the structure-function relationship in proteins using the novel concept of local descriptors of protein structure. A local descriptor is a small substructure of a protein which includes both short- and long-range interactions. We employ a library of commonly reoccurring local descriptors general enough to assemble most existing protein structures. We then model the relationship between these local shapes and Gene Ontology using rule-based learning. Our IF-THEN rule model offers legible, high resolution descriptions that combine local substructures and is able to discriminate functions even for functionally versatile folds such as the frequently occurring TIM barrel and Rossmann fold. By evaluating the predictive performance of the model, we provide a comprehensive quantification of the structure-function relationship based only on local structure similarity. Our findings are, among others, that conserved structure is a stronger prerequisite for enzymatic activity than for binding specificity, and that structure-based predictions complement sequence-based predictions. The model is capable of generating correct hypotheses, as confirmed by a literature study, even when no significant sequence similarity to characterized proteins exists. CONCLUSIONS/SIGNIFICANCE: Our approach offers a new and complete description and quantification of the structure-function relationship in proteins. By demonstrating how our predictions offer higher sensitivity than using global structure, and complement the use of sequence, we show that the presented ideas could advance the development of meta-servers in function prediction.
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| 3. |
- Rada-Iglesias, A., et al.
(författare)
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Histone H3 lysine 27 trimethylation in adult differentiated colon associated to cancer DNA hypermethylation
- 2009
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Ingår i: Epigenetics. - 1559-2294. ; 4:2, s. 107-13
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Tidskriftsartikel (refereegranskat)abstract
- DNA hypermethylation of gene promoters is a common epigenetic alteration occurring in cancer cells. However, little is known about the mechanisms instructing these cancer-specific DNA hypermethylation events. Recent reports have suggested that genes bound by polycomb/Histone H3 lysine 27 trimethylation (H3K27me3) in embryonic stem (ES) cells are frequent targets for cancer-specific DNA hypermethylation. This polycomb-premarking is assumed to be restrained to ES cells, even though almost no polycomb/H3K27me3 binding profiles are available for differentiated tissues. We generated H3K27me3 profiles in human normal colon and they significantly overlapped with those of ES cells and genes hypermethylated in colorectal cancer (CRC). Moreover, colon H3K27me3 was more restricted to genes hypermethylated in CRC, while ES H3K27me3 was also common in genes hypermethylated in other tumors. Therefore, the suggested polycomb pre-marking of genes for cancer DNA hypermethylation is not necessarily limited to ES or early precursor cells but can occur later in differentiated tissues.
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| 4. |
- Stratmann, Svea, 1989-, et al.
(författare)
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Genomic characterization of relapsed acute myeloid leukemia reveals novel putative therapeutic targets
- 2021
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Ingår i: Blood Advances. - : American Society of Hematology. - 2473-9529 .- 2473-9537. ; 5:3, s. 900-912
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Tidskriftsartikel (refereegranskat)abstract
- Relapse is the leading cause of death of adult and pediatric patients with acute myeloid leukemia (AML). Numerous studies have helped to elucidate the complex mutational landscape at diagnosis of AML, leading to improved risk stratification and new therapeutic options. However, multi-whole-genome studies of adult and pediatric AML at relapse are necessary for further advances. To this end, we performed whole-genome and whole-exome sequencing analyses of longitudinal diagnosis, relapse, and/or primary resistant specimens from 48 adult and 25 pediatric patients with AML. We identified mutations recurrently gained at relapse in ARID1A and CSF1R, both of which represent potentially actionable therapeutic alternatives. Further, we report specific differences in the mutational spectrum between adult vs pediatric relapsed AML, with MGA and H3F3A p.Lys28Met mutations recurrently found at relapse in adults, whereas internal tandem duplications in UBTF were identified solely in children. Finally, our study revealed recurrent mutations in IKZF1, KANSL1, and NIPBL at relapse. All of the mentioned genes have either never been reported at diagnosis in de novo AML or have been reported at low frequency, suggesting important roles for these alterations predominantly in disease progression and/or resistance to therapy. Our findings shed further light on the complexity of relapsed AML and identified previously unappreciated alterations that may lead to improved outcomes through personalized medicine.
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| 5. |
- Stratmann, Svea, 1989-, et al.
(författare)
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Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression
- 2022
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Ingår i: Blood Advances. - : American Society of Hematology. - 2473-9529 .- 2473-9537. ; 6:1, s. 152-164
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Tidskriftsartikel (refereegranskat)abstract
- Numerous studies have been performed over the last decade to exploit the complexity of genomic and transcriptomic lesions driving the initiation of acute myeloid leukemia (AML). These studies have helped improve risk classification and treatment options. Detailed molecular characterization of longitudinal AML samples is sparse, however; meanwhile, relapse and therapy resistance represent the main challenges in AML care. To this end, we performed transcriptome-wide RNA sequencing of longitudinal diagnosis, relapse, and/or primary resistant samples from 47 adult and 23 pediatric AML patients with known mutational background. Gene expression analysis revealed the association of short event-free survival with overexpression of GLI2 and IL1R1, as well as downregulation of ST18. Moreover, CR1 downregulation and DPEP1 upregulation were associated with AML relapse both in adults and children. Finally, machine learning–based and network-based analysis identified overexpressed CD6 and downregulated INSR as highly copredictive genes depicting important relapse-associated characteristics among adult patients with AML. Our findings highlight the importance of a tumor-promoting inflammatory environment in leukemia progression, as indicated by several of the herein identified differentially expressed genes. Together, this knowledge provides the foundation for novel personalized drug targets and has the potential to maximize the benefit of current treatments to improve cure rates in AML. ß 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.
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| 6. |
- Torabi Moghadam, Behrooz, 1982-, et al.
(författare)
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PiiL : visualization of DNA methylation and gene expression data in gene pathways
- 2017
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date. To study the complex interplay between methylation status, cellular programs, and the resulting phenotypes, we present PiiL, an interactive gene expression pathway browser, facilitating analyses through an integrated view of methylation and expression on multiple levels.Results: PiiL allows for specific hypothesis testing by quickly assessing pathways or gene networks, where the data is projected onto pathways that can be downloaded directly from the online KEGG database. PiiL provides a comprehensive set of analysis features that allow for quick and specific pattern searches. Individual CpG sites and their impact on host gene expression, as well as the impact on other genes present in the regulatory network, can be examined. To exemplify the power of this approach, we analyzed two types of brain tumors, Glioblastoma multiform and lower grade gliomas.Conclusion: At a glance, we could confirm earlier findings that the predominant methylation and expression patterns separate perfectly by mutations in the IDH genes, rather than by histology. We could also infer the IDH mutation status for samples for which the genotype was not known. By applying different filtering methods, we show that a subset of CpG sites exhibits consistent methylation patterns, and that the status of sites affect the expression of key regulator genes, as well as other genes located downstream in the same pathways.PiiL is implemented in Java with focus on a user-friendly graphical interface. The source code is available under the GPL license from https://github.com/behroozt/PiiL.git.
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| 7. |
- Wabnik, Krzysztof, et al.
(författare)
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Gene expression trends and protein features effectively complement each other in gene function prediction
- 2009
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 25:3, s. 322-330
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Genome-scale 'omics' data constitute a potentially rich source of information about biological systems and their function. There is a plethora of tools and methods available to mine omics data. However, the diversity and complexity of different omics data types is a stumbling block for multi-data integration, hence there is a dire need for additional methods to exploit potential synergy from integrated orthogonal data. Rough Sets provide an efficient means to use complex information in classification approaches. Here, we set out to explore the possibilities of Rough Sets to incorporate diverse information sources in a functional classification of unknown genes. RESULTS: We explored the use of Rough Sets for a novel data integration strategy where gene expression data, protein features and Gene Ontology (GO) annotations were combined to describe general and biologically relevant patterns represented by If-Then rules. The descriptive rules were used to predict the function of unknown genes in Arabidopsis thaliana and Schizosaccharomyces pombe. The If-Then rule models showed success rates of up to 0.89 (discriminative and predictive power for both modeled organisms); whereas, models built solely of one data type (protein features or gene expression data) yielded success rates varying from 0.68 to 0.78. Our models were applied to generate classifications for many unknown genes, of which a sizeable number were confirmed either by PubMed literature reports or electronically interfered annotations. Finally, we studied cell cycle protein-protein interactions derived from both tandem affinity purification experiments and in silico experiments in the BioGRID interactome database and found strong experimental evidence for the predictions generated by our models. The results show that our approach can be used to build very robust models that create synergy from integrating gene expression data and protein features. AVAILABILITY: The Rough Set-based method is implemented in the Rosetta toolkit kernel version 1.0.1 available at: http://rosetta.lcb.uu.se/
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