| 1. |
- Ansell, Anna, et al.
(författare)
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Matrix metalloproteinase-7 and -13 expression associate to cisplatin resistance in head and neck cancer cell lines.
- 2009
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Ingår i: Oral Oncology. - : Elsevier. - 1368-8375 .- 1879-0593. ; 45:10, s. 866-871
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Tidskriftsartikel (refereegranskat)abstract
- Concomitant chemoradiotherapy is a common treatment for advanced head and neck squamous cell carcinomas (HNSCC). Cisplatin is the backbone of chemotherapy regimens used to treat HNSCC. Therefore, the aim of this study was to identify predictive markers for cisplatin treatment outcome in HNSCC. The intrinsic cisplatin sensitivity (ICS) was determined in a panel of tumour cell lines. From this panel, one sensitive and two resistant cell lines were selected for comparative transcript profiling using microarray analysis. The enrichment of Gene Ontology (GO) categories in sensitive versus resistant cell lines were assessed using the Gene Ontology Tree Machine bioinformatics tool. In total, 781 transcripts were found to be differentially expressed and 11 GO categories were enriched. Transcripts contributing to this enrichment were further analyzed using Ingenuity Pathway Analysis (IPA) for identification of key regulator genes. IPA recognized 20 key regulator genes of which five were differentially expressed in sensitive versus resistant cell lines. The mRNA level of these five genes was further assessed in a panel of 25 HNSCC cell lines using quantitative real-time PCR. Among these key regulators, MMP-7 and MMP-13 are implicated as potential biomarkers of ICS. Taken together, genome-wide transcriptional analysis identified single genes, GO categories as well as molecular networks that are differentially expressed in HNSCC cell lines with different ICS. Furthermore, two novel predictive biomarkers for cisplatin resistance, MMP-7 and MMP-13, were identified.
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| 2. |
- Farnebo, Lovisa, et al.
(författare)
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Combining factors on protein and gene level to predict radioresponse in head and neck cancer cell lines
- 2011
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Ingår i: Journal of Oral Pathology & Medicine. - : John Wiley and sons. - 0904-2512 .- 1600-0714. ; 40:10, s. 739-746
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Radiotherapy is the main therapy for head and neck squamous cell carcinoma (HNSCC); however, treatment resistance and local recurrence are significant problems, highlighting the need for predictive markers. In this study, we evaluated selected proteins, mutations, and single nucleotide polymorphisms (SNPs) involved in apoptosis, cell proliferation, and DNA repair alone or combined as predictive markers for radioresponse in 42 HNSCC cell lines. METHODS: The expression of epidermal growth factor receptor, survivin, Bax, Bcl-2, Bcl-XL, cyclooxygenase-2, and heat shock protein 70 was analyzed by ELISA. Furthermore, mutations and SNPs in the p53 gene as well as SNPs in the MDM2, XRCC1, and XRCC3 genes were analyzed for their relation to radioresponse. To enable the evaluation of the predictive value of several factors combined, each cell line was allocated points based on the number of negative points (NNP) system, and the NNP sum was correlated with radioresponse. RESULTS: Survivin was the only factor that alone was significantly correlated with the intrinsic radiosensitivity (r=0.36, p=0.02). The combination of survivin, Bax, Bcl-2, Bcl-XL, cyclooxygenase-2, and the p53 Arg72Pro polymorphism was found to most strongly correlate with radioresponse (r=0.553, p<0.001). CONCLUSION: These data indicate that the intrinsic radiosensitivity of 42 HNSCC cell lines can be predicted by a panel of factors on both the protein and gene levels. Moreover, among the investigated factors, survivin was the most promising biomarker of radioresponse.
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| 3. |
- Grafström, Roland C, et al.
(författare)
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Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from Human Cell Cultures
- 2015
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Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929 .- 2632-3559. ; 43:5, s. 325-332
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Tidskriftsartikel (refereegranskat)abstract
- This paper outlines the work for which Roland Grafström and Pekka Kohonen were awarded the 2014 Lush Science Prize. The research activities of the Grafström laboratory have, for many years, covered cancer biology studies, as well as the development and application of toxicity-predictive in vitro models to determine chemical safety. Through the integration of in silico analyses of diverse types of genomics data (transcriptomic and proteomic), their efforts have proved to fit well into the recently-developed Adverse Outcome Pathway paradigm. Genomics analysis within state-of-the-art cancer biology research and Toxicology in the 21st Century concepts share many technological tools. A key category within the Three Rs paradigm is the Replacement of animals in toxicity testing with alternative methods, such as bioinformatics-driven analyses of data obtained from human cell cultures exposed to diverse toxicants. This work was recently expanded within the pan-European SEURAT-1 project (Safety Evaluation Ultimately Replacing Animal Testing), to replace repeat-dose toxicity testing with data-rich analyses of sophisticated cell culture models. The aims and objectives of the SEURAT project have been to guide the application, analysis, interpretation and storage of 'omics' technology-derived data within the service-oriented sub-project, ToxBank. Particularly addressing the Lush Science Prize focus on the relevance of toxicity pathways, a 'data warehouse' that is under continuous expansion, coupled with the development of novel data storage and management methods for toxicology, serve to address data integration across multiple 'omics' technologies. The prize winners' guiding principles and concepts for modern knowledge management of toxicological data are summarised. The translation of basic discovery results ranged from chemical-testing and material-testing data, to information relevant to human health and environmental safety.
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| 4. |
- Hammerling, Ulf, et al.
(författare)
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Comparative hazard characterization in food toxicology
- 2009
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Ingår i: Critical reviews in food science and nutrition. - : Informa UK Limited. - 1040-8398 .- 1549-7852. ; 49:7, s. 626-669
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Forskningsöversikt (refereegranskat)abstract
- Historically, different approaches have been adopted for comparing and characterizing hazards that can be found in the very complex mixture of substances present in food. In this review a variety of prominent risk assessment models are evaluated in the context of food safety. In their current state of refinement, though, they show limited applicability for comparative hazard characterization and impact magnitude scoring of adverse effects of substances in food. Nonetheless, some existing models hold building blocks and modelling concepts that appear promising for further development and integration. Thus, a new, dedicated, and generally accepted model is needed that is capable of generating relevant "Impact Magnitude Score" (IMS) values for comparing potentially toxic substances in food. A brief outline of requirements for a model (Guided Toxicology-assessment of Health Impact; GTHI) is presented that considers "severity" (S), "duration" (D), and "proportion of population affected" (P). An important demand on such a model is to provide significantly improved food safety evaluation amenable to regulatory agencies and consumers. This review is based on a project entitled "Promoting food safety through a new integrated risk analysis approach for foods" (acronym: "SAFE FOODS") that is under the subsidy of the European Commission.
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| 5. |
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| 6. |
- Jerhammar, Fredrik, et al.
(författare)
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Identification of Key Regulator Genes Linked to Radioresistance in Head and Neck Squamous Cell Carcinoma by Bioinformatic Processing of Transcript Data
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Purpose: We analyzed basal expression patterns of cell lines with different intrinsic radiosensitivity to discover predictive markers of radiotherapy response. Experimental Design: Five head and neck squamous cell carcinoma (HNSCC) cell lines were selected for microarray analysis. Two cell lines showed high resistance to radiation, two cell lines showed an intermediate resistance and one cell line was sensitive and therefore used as reference to other cell lines. Three gene lists were generated from this analysis; one list with commonly deregulated genes in all cell lines compared to the reference and two lists with deregulated genes for the intermediate and highly resistant cell lines compared to the reference, respectively. Gene Ontology enrichment profiling and Ingenuity Pathway Analysis was applied on all gene lists. Key transcript findings were verified at the protein level by Western blot. Results: Expression analysis of the high and intermediate resistant cell lines compared to the reference resulted in approximately 1300 significantly altered transcripts, respectively; 552 transcripts were found commonly differently expressed. The deregulated transcripts enriched several GO-categories under biological process, cellular component and molecular function as well as multiple molecular networks in Ingenuity Pathway Analysis. A transcriptional profile of 28 key-regulator genes from the molecular networks was generated from the four resistant lines compared to the reference. Finally, immunoblot analysis supported deregulation at the protein level of markers implicated from the transcriptional-profile. Conclusions: Novel markers for prediction of radiation sensitivity could be proposed from bioinformatic processing of gene-expression profiles in HNSCC carcinoma cells.
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| 7. |
- Jerhammar, Fredrik, 1979-
(författare)
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Predictive Markers of Treatment Resistance in Head and Neck Squamous Cell Carcinoma
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Head and neck cancer is a common malignancy with approximately 600 000 new cases yearly. Disappointingly, the overall survival has not increased over the last decades. The concept of personalized medicine, i.e. to treat every patient with an individually planned treatment regime has gathered increased interest, but requires the establishment of novel biomarkers that can predict treatment response.The aim of this thesis is to propose novel predictive single markers or combinations of markers of response to radiation, cisplatin and cetuximab. The general methodology is to evaluate common differences of cell lines resistant to radiation, cisplatin or cetuximab compared to sensitive counterparts.In paper I, we analysed the expression of 14 proteins involved in growth control and/or apoptosis by western blot and related them to intrinsic radiosensitivity (IR) in nine cell lines. No factor had a significant correlation to IR on its own. A combination of EGFR, survivin, Bak, Smad4, and Hsp70 had the best correlation to IR (R=0.886, p=0.001). Additionally, we analysed the presence of p53 mutations in the cell lines. All cell lines had at least one missense, splice site or loss of transcript mutation. To be able to combine protein expression and presence of p53 mutations we created a system designated the number of negative points (NNP). With this system we could extract that expression of EGFR, survivin, and p53 missense or splice site mutations had the best correlation to IR (R=0.990, p<0.001).In paper II we conducted a gene expression microarray analysis of three cell lines, from which common deregulations in two cisplatin resistant cell lines was compared to a cisplatin sensitive cell line. From a bioinformatic approach of gene ontology and molecular network analysis, we defined a transcriptional profile of 20 genes. Finally, key findings were analysed in a larger panel of cell lines, where high MMP-7 expression correlated with higher cisplatin resistance.Paper III compared 4 cell lines with high IR to a radiosensitive equivalent. Using a similar bioinformatic approach as paper II, we established a transcriptional profile of 14 genes. Analysis in a larger panel of cell lines revealed that FN1 expression predicts higher IR.Paper IV establishes the cetuximab sensitivity of 35 cell lines of which 12 were resistant and five were sensitive to cetuximab. After whole genome gene copy number analysis of five cetuximab resistant and five cetuximab sensitive cell lines, and verification of key findings in a larger cell line panel, the results show that the amplification of the YAP1 gene is coupled to cetuximab resistance.In summary, this thesis proposes a number of novel markers of resistance to radiation, cisplatin, and cetuximab which could influence treatment choice in the future, following verifications in primary tumor material.
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| 8. |
- Kohonen, Pekka, et al.
(författare)
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Cancer Biology, Toxicology and Alternative Methods Development Go Hand-in-Hand
- 2014
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Ingår i: Basic & Clinical Pharmacology & Toxicology. - : Wiley. - 1742-7835 .- 1742-7843. ; 115:1, s. 50-58
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Forskningsöversikt (refereegranskat)abstract
- Toxicological research faces the challenge of integrating knowledge from diverse fields and novel technological developments generally in the biological and medical sciences. We discuss herein the fact that the multiple facets of cancer research, including discovery related to mechanisms, treatment and diagnosis, overlap many up and coming interest areas in toxicology, including the need for improved methods and analysis tools. Common to both disciplines, in vitro and in silico methods serve as alternative investigation routes to animal studies. Knowledge on cancer development helps in understanding the relevance of chemical toxicity studies in cell models, and many bioinformatics-based cancer biomarker discovery tools are also applicable to computational toxicology. Robotics-aided cell-based high throughput screening, microscale immunostaining techniques, and gene expression profiling analyses are common tools in cancer research, and when sequentially combined, form a tiered approach to structured safety evaluation of thousands of environmental agents, novel chemicals or engineered nanomaterials. Comprehensive tumour data collections in databases have been translated into clinically useful data, and this concept serves as template for computer-driven evaluation of toxicity data into meaningful results. Future “cancer research-inspired knowledge management” of toxicological data will aid the translation of basic discovery results and chemicals- and materials-testing data to information relevant to human health and environmental safety.
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| 9. |
- Lampa, Samuel, et al.
(författare)
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RDFIO : extending Semantic MediaWiki for interoperable biomedical data management
- 2017
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Ingår i: Journal of Biomedical Semantics. - : Springer Science and Business Media LLC. - 2041-1480. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Biological sciences are characterised not only by an increasing amount but also the extreme complexity of its data. This stresses the need for efficient ways of integrating these data in a coherent description of biological systems. In many cases, biological data needs organization before integration. This is not seldom a collaborative effort, and it is thus important that tools for data integration support a collaborative way of working. Wiki systems with support for structured semantic data authoring, such as Semantic MediaWiki, provide a powerful solution for collaborative editing of data combined with machine-readability, so that data can be handled in an automated fashion in any downstream analyses. Semantic MediaWiki lacks a built-in data import function though, which hinders efficient round-tripping of data between interoperable Semantic Web formats such as RDF and the internal wiki format.RESULTS: To solve this deficiency, the RDFIO suite of tools is presented, which supports importing of RDF data into Semantic MediaWiki, with metadata needed to export it again in the same RDF format, or ontology. Additionally, the new functionality enables mash-ups of automated data imports combined with manually created data presentations. The application of the suite of tools is demonstrated by importing drug discovery related data about rare diseases from Orphanet and acid dissociation constants from Wikidata. The RDFIO suite of tools is freely available for download via pharmb.io/project/rdfio .CONCLUSIONS: Through a set of biomedical demonstrators, it is demonstrated how the new functionality enables a number of usage scenarios where the interoperability of SMW and the wider Semantic Web is leveraged for biomedical data sets, to create an easy to use and flexible platform for exploring and working with biomedical data.
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| 10. |
- Lampa, Samuel, 1983-
(författare)
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Reproducible Data Analysis in Drug Discovery with Scientific Workflows and the Semantic Web
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The pharmaceutical industry is facing a research and development productivity crisis. At the same time we have access to more biological data than ever from recent advancements in high-throughput experimental methods. One suggested explanation for this apparent paradox has been that a crisis in reproducibility has affected also the reliability of datasets providing the basis for drug development. Advanced computing infrastructures can to some extent aid in this situation but also come with their own challenges, including increased technical debt and opaqueness from the many layers of technology required to perform computations and manage data. In this thesis, a number of approaches and methods for dealing with data and computations in early drug discovery in a reproducible way are developed. This has been done while striving for a high level of simplicity in their implementations, to improve understandability of the research done using them. Based on identified problems with existing tools, two workflow tools have been developed with the aim to make writing complex workflows particularly in predictive modelling more agile and flexible. One of the tools is based on the Luigi workflow framework, while the other is written from scratch in the Go language. We have applied these tools on predictive modelling problems in early drug discovery to create reproducible workflows for building predictive models, including for prediction of off-target binding in drug discovery. We have also developed a set of practical tools for working with linked data in a collaborative way, and publishing large-scale datasets in a semantic, machine-readable format on the web. These tools were applied on demonstrator use cases, and used for publishing large-scale chemical data. It is our hope that the developed tools and approaches will contribute towards practical, reproducible and understandable handling of data and computations in early drug discovery.
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