| 1. |
- Axelsson, Hans, 1972, et al.
(författare)
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Global Tumor RNA Expression in Early Establishment of Experimental Tumor Growth and Related Angiogenesis following Cox-Inhibition Evaluated by Microarray Analysis.
- 2007
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Ingår i: Cancer informatics. - 1176-9351. ; 3, s. 125-39
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Tidskriftsartikel (refereegranskat)abstract
- Altered expression of COX-2 and overproduction of prostaglandins, particularly prostaglandin E(2), are common in malignant tumors. Consequently, non-steroidal anti-inflammatory drugs (NSAIDs) attenuate tumor net growth, tumor related cachexia, improve appetite and prolong survival. We have also reported that COX-inhibition (indomethacin) interfered with early onset of tumor endothelial cell growth, tumor cell proliferation and apoptosis. It is however still unclear whether such effects are restricted to metabolic alterations closely related to eicosanoid pathways and corresponding regulators, or whether a whole variety of gene products are involved both up- and downstream effects of eicosanoids. Therefore, present experiments were performed by the use of an in vivo, intravital chamber technique, where micro-tumor growth and related angiogenesis were analyzed by microarray to evaluate for changes in global RNA expression caused by indomethacin treatment.Indomethacin up-regulated 351 and down-regulated 1852 genes significantly (p < 0.01); 1066 of these genes had unknown biological function. Genes with altered expression occurred on all chromosomes.Our results demonstrate that indomethacin altered expression of a large number of genes distributed among a variety of processes in the carcinogenic progression involving angiogenesis, apoptosis, cell-cycling, cell adhesion, inflammation as well as fatty acid metabolism and proteolysis. It remains a challenge to distinguish primary key alterations from secondary adaptive changes in transcription of genes altered by cyclooxygenase inhibition.
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| 2. |
- Frigyesi, Attila, et al.
(författare)
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Non-negative matrix factorization for the analysis of complex gene expression data : Identification of clinically relevant tumor subtypes
- 2008
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Ingår i: Cancer Informatics. - : SAGE Publications. - 1176-9351. ; 6, s. 275-292
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Tidskriftsartikel (refereegranskat)abstract
- Non-negative matrix factorization (NMF) is a relatively new approach to analyze gene expression data that models data by additive combinations of non-negative basis vectors (metagenes). The non-negativity constraint makes sense biologically as genes may either be expressed or not, but never show negative expression. We applied NMF to five different microarray data sets. We estimated the appropriate number metagens by comparing the residual error of NMF reconstruction of data to that of NMF reconstruction of permutated data, thus finding when a given solution contained more information than noise. This analysis also revealed that NMF could not factorize one of the data sets in a meaningful way. We used GO categories and pre defined gene sets to evaluate the biological significance of the obtained metagenes. By analyses of metagenes specific for the same GO-categories we could show that individual metagenes activated different aspects of the same biological processes. Several of the obtained metagenes correlated with tumor subtypes and tumors with characteristic chromosomal translocations, indicating that metagenes may correspond to specific disease entities. Hence, NMF extracts biological relevant structures of microarray expression data and may thus contribute to a deeper understanding of tumor behavior.
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| 3. |
- Hansson, Marie, 1979, et al.
(författare)
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Sample preparation for in vitro anallysis of iodine in thyroid tissue using x-ray fluorescence
- 2008
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Ingår i: Cancer Informatics. - 1176-9351. ; 6, s. 51-57
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Tidskriftsartikel (refereegranskat)abstract
- Iodine is enriched and stored in the thyroid gland. Due to several factors, the size of the thyroid iodine pool varies both between individuals and within individuals over time. Excess iodine as well as iodine defi ciency may promote thyroid cancer. Therefore, knowledge of iodine content and distribution within thyroid cancer tissue is of interest. X-ray fl uorescence analysis (XRF) and secondary ion mass spectrometry (SIMS) are two methods that can be used to assess iodine content in thyroid tissue. With both techniques, choice of sample preparation affects the results. Aldehyde fi xatives are required for SIMS analysis while a freezing method might be satisfactory for XRF analysis. The aims of the present study were primarily to evaluate a simple freezing technique for preserving samples for XRF analysis and also to use XRF to evaluate the effi cacy of using aldehyde fi xatives to prepare samples for SIMS analysis. Ten porcine thyroids were sectioned into four pieces that were either frozen or fi xed in formaldehyde, glutaraldehyde, or a modifi ed Karnovsky fi xative. The frozen samples were assessed for iodine content with XRF after 1 and 2 months, and the fi xed samples were analyzed for iodine content after 1 week. Freezing of untreated tissue yielded no signifi cant iodine loss, whereas fi xation with aldehydes yielded an iodine loss of 14–30%, with Karnovsky producing the least loss.
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| 4. |
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| 5. |
- Johnson, David, et al.
(författare)
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Dealing with Diversity in Computational Cancer Modeling
- 2013
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Ingår i: Cancer Informatics. - : Libertas Academica Ltd. - 1176-9351. ; 12, s. 115-124
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Tidskriftsartikel (refereegranskat)abstract
- This paper discusses the need for interconnecting computational cancer models from different sources and scales within clinically relevant scenarios to increase the accuracy of the models and speed up their clinical adaptation, validation, and eventual translation. We briefly review current interoperability efforts drawing upon our experiences with the development of in silico models for predictive oncology within a number of European Commission Virtual Physiological Human initiative projects on cancer. A clinically relevant scenario, addressing brain tumor modeling that illustrates the need for coupling models from different sources and levels of complexity, is described. General approaches to enabling interoperability using XML-based markup languages for biological modeling are reviewed, concluding with a discussion on efforts towards developing cancer-specific XML markup to couple multiple component models for predictive in silico oncology.
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| 6. |
- Johnson, David, et al.
(författare)
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Semantically Linking In Silico Cancer Models
- 2014
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Ingår i: Cancer Informatics. - 1176-9351. ; 13:S1, s. 133-143
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Tidskriftsartikel (refereegranskat)abstract
- Multiscale models are commonplace in cancer modeling, where individual models acting on different biological scales are combined within a single, cohesive modeling framework. However, model composition gives rise to challenges in understanding interfaces and interactions between them. Based on specific domain expertise, typically these computational models are developed by separate research groups using different methodologies, programming languages, and parameters. This paper introduces a graph-based model for semantically linking computational cancer models via domain graphs that can help us better understand and explore combinations of models spanning multiple biological scales. We take the data model encoded by TumorML, an XML-based markup language for storing cancer models in online repositories, and transpose its model description elements into a graph-based representation. By taking such an approach, we can link domain models, such as controlled vocabularies, taxonomic schemes, and ontologies, with cancer model descriptions to better understand and explore relationships between models. The union of these graphs creates a connected property graph that links cancer models by categorizations, by computational compatibility, and by semantic interoperability, yielding a framework in which opportunities for exploration and discovery of combinations of models become possible.
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| 7. |
- Lagerstedt, Kristina, 1976, et al.
(författare)
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Genes with relevance for early to late progression of colon carcinoma based on combined genomic and transcriptomic information from the same patients.
- 2010
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Ingår i: Cancer informatics. - 1176-9351. ; 9, s. 79-91
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Genetic and epigenetic alterations in colorectal cancer are numerous. However, it is difficult to judge whether such changes are primary or secondary to the appearance and progression of tumors. Therefore, the aim of the present study was to identify altered DNA regions with significant covariation to transcription alterations along colon cancer progression. METHODS: Tumor and normal colon tissue were obtained at primary operations from 24 patients selected by chance. DNA, RNA and microRNAs were extracted from the same biopsy material in all individuals and analyzed by oligo-nucleotide array-based comparative genomic hybridization (CGH), mRNA- and microRNA oligo-arrays. Statistical analyses were performed to assess statistical interactions (correlations, co-variations) between DNA copy number changes and significant alterations in gene and microRNA expression using appropriate parametric and non-parametric statistics. RESULTS: Main DNA alterations were located on chromosome 7, 8, 13 and 20. Tumor DNA copy number gain increased with tumor progression, significantly related to increased gene expression. Copy number loss was not observed in Dukes A tumors. There was no significant relationship between expressed genes and tumor progression across Dukes A-D tumors; and no relationship between tumor stage and the number of microRNAs with significantly altered expression. Interaction analyses identified overall 41 genes, which discriminated early Dukes A plus B tumors from late Dukes C plus D tumor; 28 of these genes remained with correlations between genomic and transcriptomic alterations in Dukes C plus D tumors and 17 in Dukes D. One microRNA (microR-663) showed interactions with DNA alterations in all Dukes A-D tumors. CONCLUSIONS: Our modeling confirms that colon cancer progression is related to genomic instability and altered gene expression. However, early invasive tumor growth seemed rather related to transcriptomic alterations, where changes in microRNA may be an early phenomenon, and less to DNA copy number changes.
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| 8. |
- Lagerstedt, Kristina, 1976, et al.
(författare)
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Tumor Genome Wide DNA Alterations Assessed by Array CGH in Patients with Poor and Excellent Survival Following Operation for Colorectal Cancer.
- 2007
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Ingår i: Cancer informatics. - 1176-9351. ; 3, s. 341-55
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Tidskriftsartikel (refereegranskat)abstract
- Genome wide DNA alterations were evaluated by array CGH in addition to RNA expression profiling in colorectal cancer from patients with excellent and poor survival following primary operations.DNA was used for CGH in BAC and cDNA arrays. Global RNA expression was determined by 44K arrays. DNA and RNA from tumor and normal colon were used from cancer patients grouped according to death, survival or Dukes A, B, C and D tumor stage. Confirmed DNA alterations in all Dukes A - D were judged relevant for carcinogenesis, while changes in Dukes C and D only were regarded relevant for tumor progression.Copy number gain was more common than loss in tumor tissue (p < 0.01). Major tumor DNA alterations occurred in chromosome 8, 13, 18 and 20, where short survival included gain in 8q and loss in 8p. Copy number gains related to tumor progression were most common on chromosome 7, 8, 19, 20, while corresponding major losses appeared in chromosome 8. Losses at chromosome 18 occurred in all Dukes stages. Normal colon tissue from cancer patients displayed gains in chromosome 19 and 20. Mathematical Vector analysis implied a number of BAC-clones in tumor DNA with genes of potential importance for death or survival.The genomic variation in colorectal cancer cells is tremendous and emphasizes that BAC array CGH is presently more powerful than available statistical models to discriminate DNA sequence information related to outcome. Present results suggest that a majority of DNA alterations observed in colorectal cancer are secondary to tumor progression. Therefore, it would require an immense work to distinguish primary from secondary DNA alterations behind colorectal cancer.
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| 9. |
- Lauss, Martin, et al.
(författare)
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Monitoring of technical variation in quantitative high-throughput datasets.
- 2013
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Ingår i: Cancer Informatics. - 1176-9351. ; 12:Sep 23, s. 193-201
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Tidskriftsartikel (refereegranskat)abstract
- High-dimensional datasets can be confounded by variation from technical sources, such as batches. Undetected batch effects can have severe consequences for the validity of a study's conclusion(s). We evaluate high-throughput RNAseq and miRNAseq as well as DNA methylation and gene expression microarray datasets, mainly from the Cancer Genome Atlas (TCGA) project, in respect to technical and biological annotations. We observe technical bias in these datasets and discuss corrective interventions. We then suggest a general procedure to control study design, detect technical bias using linear regression of principal components, correct for batch effects, and re-evaluate principal components. This procedure is implemented in the R package swamp, and as graphical user interface software. In conclusion, high-throughput platforms that generate continuous measurements are sensitive to various forms of technical bias. For such data, monitoring of technical variation is an important analysis step.
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| 10. |
- Schaal, Wesley, PhD, et al.
(författare)
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Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening
- 2022
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Ingår i: Cancer Informatics. - : Sage Publications. - 1176-9351. ; 21, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: The aim of this project was to implement long-read sequencing for BCR-ABL1 TKI resistance mutation screening in a clinical setting for patients undergoing treatment for chronic myeloid leukemia.MATERIALS AND METHODS: Processes were established for registering and transferring samples from the clinic to an academic sequencing facility for long-read sequencing. An automated analysis pipeline for detecting mutations was established, and an information system was implemented comprising features for data management, analysis and visualization. Clinical validation was performed by identifying BCR-ABL1 TKI resistance mutations by Sanger and long-read sequencing in parallel. The developed software is available as open source via GitHub at https://github.com/pharmbio/clampRESULTS: The information system enabled traceable transfer of samples from the clinic to the sequencing facility, robust and automated analysis of the long-read sequence data, and communication of results from sequence analysis in a reporting format that could be easily interpreted and acted upon by clinical experts. In a validation study, all 17 resistance mutations found by Sanger sequencing were also detected by long-read sequencing. An additional 16 mutations were found only by long-read sequencing, all of them with frequencies below the limit of detection for Sanger sequencing. The clonal distributions of co-existing mutations were automatically resolved through the long- read data analysis. After the implementation and validation, the clinical laboratory switched their routine protocol from using Sanger to long-read sequencing for this application.CONCLUSIONS: Long-read sequencing delivers results with higher sensitivity compared to Sanger sequencing and enables earlier detection of emerging TKI resistance mutations. The developed processes, analysis workflow, and software components lower barriers for adoption and could be extended to other applications.KEYWORDS: Long-read sequencing, SMRT sequencing, drug resistance, chronic myeloid leukemia, BCR-ABL1, CML, mutation screening
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| 11. |
- Stjernqvist, Susann, et al.
(författare)
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Model-integrated estimation of normal tissue contamination for cancer SNP copy number data
- 2011
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Ingår i: Cancer Informatics. - 1176-9351. ; 10, s. 159-173
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Tidskriftsartikel (refereegranskat)abstract
- SNP allelic copy number data provides intensity measurements for the two different alleles separately. We present a method that estimates the number of copies of each allele at each SNP position, using a continuous-index hidden Markov model. The method is especially suited for cancer data, since it includes the fraction of normal tissue contamination, often present when studying data from cancer tumors, into the model. The continuous-index structure takes into account the distances between the SNPs, and is thereby appropriate also when SNPs are unequally spaced. In a simulation study we show that the method performs favorably compared to previous methods even with as much as 70% normal contamination. We also provide results from applications to clinical data produced using the Affymetrix genome-wide SNP 6.0 platform.
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| 12. |
- Ulfenborg, Benjamin, et al.
(författare)
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Classification of tumor samples from expression data using decision trunks
- 2013
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Ingår i: Cancer Informatics. - : Sage Publications. - 1176-9351. ; 12, s. 53-66
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Tidskriftsartikel (refereegranskat)abstract
- We present a novel machine learning approach for the classification of cancer samples using expression data. We refer to the method as "decision trunks," since it is loosely based on decision trees, but contains several modifications designed to achieve an algorithm that: (1) produces smaller and more easily interpretable classifiers than decision trees; (2) is more robust in varying application scenarios; and (3) achieves higher classification accuracy. The decision trunk algorithm has been implemented and tested on 26 classification tasks, covering a wide range of cancer forms, experimental methods, and classification scenarios. This comprehensive evaluation indicates that the proposed algorithm performs at least as well as the current state of the art algorithms in terms of accuracy, while producing classifiers that include on average only 2-3 markers. We suggest that the resulting decision trunks have clear advantages over other classifiers due to their transparency, interpretability, and their correspondence with human decision-making and clinical testing practices. © the author(s), publisher and licensee Libertas Academica Ltd.
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