| 1. |
- Ahmed, Rafsan, et al.
(författare)
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EasyNER: A Customizable Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical Text
- 2023
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Medical research generates a large number of publications with the PubMed database already containing >35 million research articles. Integration of the knowledge scattered across this large body of literature could provide key insights into physiological mechanisms and disease processes leading to novel medical interventions. However, it is a great challenge for researchers to utilize this information in full since the scale and complexity of the data greatly surpasses human processing abilities. This becomes especially problematic in cases of extreme urgency like the COVID-19 pandemic. Automated text mining can help extract and connect information from the large body of medical research articles. The first step in text mining is typically the identification of specific classes of keywords (e.g., all protein or disease names), so called Named Entity Recognition (NER). Here we present an end-to-end pipeline for NER of typical entities found in medical research articles, including diseases, cells, chemicals, genes/proteins, and species. The pipeline can access and process large medical research article collections (PubMed, CORD-19) or raw text and incorporates a series of deep learning models fine-tuned on the HUNER corpora collection. In addition, the pipeline can perform dictionary-based NER related to COVID-19 and other medical topics. Users can also load their own NER models and dictionaries to include additional entities. The output consists of publication-ready ranked lists and graphs of detected entities and files containing the annotated texts. An associated script allows rapid inspection of the results for specific entities of interest. As model use cases, the pipeline was deployed on two collections of autophagy-related abstracts from PubMed and on the CORD19 dataset, a collection of 764 398 research article abstracts related to COVID-19.
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| 2. |
- Aits, Sonja
(författare)
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Artificial intelligence : — a vehicle or an obstacle on our path to a sustainable future?
- 2022
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Annan publikation (populärvet., debatt m.m.)abstract
- Many people and organizations across the globe work towards a sustainable future. Artificial intelligence (AI) can be a powerful tool in their efforts.AI technologies, which aim to imitate the natural intelligence of humans and animals, have made enormous progress in the past decade. AI has brought us a whole range of futuristic tools — from self-driving cars to virtual assistants, smart home appliances and self-learning robots — and enabled us to process large and complex data with unprecedented speed and accuracy. With AI advancing so rapidly and its application becoming more ubiquitous across society every day, we should carefully consider how to use it to ensure a sustainable future.
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| 3. |
- Aits, Sonja, et al.
(författare)
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HAMLET (human alpha-lactalbumin made lethal to tumor cells) triggers autophagic tumor cell death.
- 2009
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 124:5, s. 1008-1019
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Tidskriftsartikel (refereegranskat)abstract
- HAMLET, a complex of partially unfolded alpha-lactalbumin and oleic acid, kills a wide range of tumor cells. Here we propose that HAMLET causes macroautophagy in tumor cells and that this contributes to their death. Cell death was accompanied by mitochondrial damage and a reduction in the level of active mTOR and HAMLET triggered extensive cytoplasmic vacuolization and the formation of double-membrane-enclosed vesicles typical of macroautophagy. In addition, HAMLET caused a change from uniform (LC3-I) to granular (LC3-II) staining in LC3-GFP-transfected cells reflecting LC3 translocation during macroautophagy, and this was blocked by the macroautophagy inhibitor 3-methyladenine. HAMLET also caused accumulation of LC3-II detected by Western blot when lysosomal degradation was inhibited suggesting that HAMLET caused an increase in autophagic flux. To determine if macroautophagy contributed to cell death, we used RNA interference against Beclin-1 and Atg5. Suppression of Beclin-1 and Atg5 improved the survival of HAMLET-treated tumor cells and inhibited the increase in granular LC3-GFP staining. The results show that HAMLET triggers macroautophagy in tumor cells and suggest that macroautophagy contributes to HAMLET-induced tumor cell death.
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| 4. |
- Aits, Sonja
(författare)
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Mechanisms of HAMLET-induced cancer cell death
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- HAMLET, a complex of α-lactalbumin and oleic acid, preferentially kills cancer cells and is also effective in vivo. HAMLET causes apoptosis but cells die even if this pathway is inhibited. Thus, the role of autophagy, an alternative cell death pathway, was examined. During autophagy double membrane-enclosed autophagosomes form around cellular material and deliver it to the lysosomes for degradation. After HAMLET treatment, such vesicles were observed and HAMLET also increased granular LC3-GFP staining confirming autophagosome accumulation. In addition, the autophagic form of LC3 increased if lysosomal degradation was inhibited, indicating a true increase in autophagic flux. Several factors that may activate autophagy were identified, including mitochondrial damage, inhibition of the autophagy inhibitor mTOR and increased the expression of autophagy components. Inhibition of autophagy by Atg5 and Beclin-1 siRNAs reduced cell death suggesting that autophagy is an important part of the cell death programme. As autophagy can be initiated by metabolic stress and as metabolism is altered in cancer cells we investigated if HAMLET-induced cell death involves an effect on metabolism. Healthy cells, which were less sensitive to HAMLET, had lower levels of c-Myc, an important regulator of glucose metabolism, and knockdown of c-Myc in cancer cells reduced their sensitivity. In contrast, cancer cell death was enhanced by glycolysis inhibition. HAMLET was also shown to bind the glycolytic enzyme hexokinase 1 (HK1) and to reduce HK activity, ATP levels and lactate release. Also, knockdown of HK1 and the glycolysis-enhancing HIF1A sensitized cancer cells to HAMLET whereas knockdown of the glycolysis-regulating protein PFKFB1 reduced sensitivity. Finally, mass spectrometry-based analysis indicated that HAMLET has a broad impact on metabolism possibly due to binding of HK1. In an additional screen for HAMLET-binding proteins prohibitin-2, a multifunctional protein found at the same cellular sites as HAMLET, was identified. The binding was confirmed in vitro and HAMLET was shown to also bind to the related prohibitin. Co-staining for HAMLET and prohibitins revealed colocalization in the cytoplasm. In addition, nuclear staining for both prohibitins was reduced, as described in camptothecin-induced cancer cell death. Furthermore, prohibitin-2 siRNA reduced cell death after HAMLET treatment suggesting that prohibitins may play a role in HAMLET-induced cell death. Besides cell death, HAMLET also causes cancer cell detachment and α-actinin-4, which crosslinks the actin cytoskeleton and focal adhesions, was identified in a screen as a potential HAMLET target. The binding between HAMLET and α-actinins was confirmed by co-immunoprecipitation and the actin and integrin binding sites on α-actinin were identified as possible sites of HAMLET binding in a peptide binding assay. HAMLET was also shown to colocalize with α-actinin-4 in the cell periphery and to reduce its granular surface staining and intracellular trabecular staining. In addition, HAMLET altered the staining of other focal adhesion components and reduced the level of active focal adhesion kinase and ERK, which can both be regulated via focal adhesions. Healthy cells did not detach after HAMLET treatment but the detachment of cancer cells was even further enhanced by knockdown of α-actinins. In contrast, overexpression of α-actinin-4-GFP delayed blebbing and rounding up further suggesting that α-actinin is involved in HAMLET-induced detachment. In summary, this study indicates that HAMLET activates autophagy and disrupts metabolism at least partly by binding to HK1 and that these events contribute to cell death. The results also suggest that c-Myc and glycolysis are important determinants of HAMLET sensitivity. Furthermore, the study identifies prohibitins as novel HAMLET targets with a potential role in cell death and suggests that HAMLET binding to α-actinins disrupts focal adhesions leading to cell detachment.
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| 5. |
- Aits, Sonja, et al.
(författare)
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Methods to Detect Loss of Lysosomal Membrane Integrity
- 2019
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Ingår i: Autophagy : Methods and Protocols - Methods and Protocols. - New York, NY : Springer New York. - 1064-3745. - 9781493988730 ; 1880, s. 315-329
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Bokkapitel (refereegranskat)abstract
- Loss of lysosomal membrane integrity, often referred to as lysosomal membrane permeabilization (LMP), occurs in many instances of cell death either as an initiating or as an amplifying event. Currently, the best method for detecting LMP is the galectin puncta formation assay which can be used for a broad range of sample types, both fixed and live, is easy to perform, and highly sensitive. This method, which is similar to the widely used LC3 puncta formation assay for autophagy, is based on the translocation of galectins to damaged lysosomes resulting in a change from uniform to punctate staining pattern. Here, we provide protocols for the galectin puncta formation assay in fixed and live cells and for an alternative assay based on fluorescent dextran release from damaged lysosomes, which can be performed in parallel
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| 6. |
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| 7. |
- Arvidsson, Malou, et al.
(författare)
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An annotated high-content fluorescence microscopy dataset with Hoechst 33342-stained nuclei and manually labelled outlines
- 2023
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Ingår i: Data in Brief. - : Elsevier BV. - 2352-3409. ; 46
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Tidskriftsartikel (refereegranskat)abstract
- Automated detection of cell nuclei in fluorescence microscopy images is a key task in bioimage analysis. It is essential for most types of microscopy-based high-throughput drug and genomic screening and is often required in smaller scale experiments as well. To develop and evaluate algorithms and neural networks that perform instance or semantic segmentation for detecting nuclei, high quality annotated data is essential. Here we present a benchmarking dataset of fluorescence microscopy images with Hoechst 33342-stained nuclei together with annotations of nuclei, nuclear fragments and micronuclei. Images were randomly selected from an RNA interference screen with a modified U2OS osteosarcoma cell line, acquired on a Thermo Fischer CX7 high-content imaging system at 20x magnification. Labelling was performed by a single annotator and reviewed by a biomedical expert. The dataset, called Aitslab-bioimaging1, contains 50 images showing over 2000 labelled nuclear objects in total, which is sufficiently large to train well-performing neural networks for instance or semantic segmentation. The dataset is split into training, development and test set for user convenience.
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| 8. |
- Arvidsson, Malou, et al.
(författare)
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An annotated high-content fluorescence microscopy dataset with Hoechst 33342-stained nuclei and manually labelled outlines : Dataset record
- 2022
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Here we present a benchmarking dataset of fluorescence microscopy images with Hoechst 33342-stained nuclei together with annotations of nuclei, nuclear fragments and micronuclei. Images were randomly selected from an RNA interference screen with a modified U2OS osteosarcoma cell line, acquired on a Thermo Fischer CX7 high-content imaging system at 20x magnification. Labelling was performed by a single annotator and reviewed by a biomedical expert.The dataset contains 50 images showing over 2000 labelled nuclear objects in total, which is sufficiently large to train well-performing neural networks for instance or semantic segmentation. It is pre-split into training, development and test set, each in a zip file. The dataset should be referred to as Aitslab_bioimaging1. A preprint of a brief article describing the dataset is also available from zenodo (Arvidsson M, Kazemi Rashed S, Aits S. zenodo 2022, https://doi.org/10.1016/j.dib.2022.108769)
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| 9. |
- Augusto Silva, Iran, et al.
(författare)
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Deep learning for rapid and reproducible histology scoring of lung injury in a porcine model
- 2023
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Acute respiratory distress syndrome (ARDS) is a life-threatening condition with mortality rates between 30-50%. Although in vitro models replicate some aspects of ARDS, small and large animal models remain the primary research tools due to the multifactorial nature of the disease. When using these animal models, histology serves as the gold standard method to confirm lung injury and exclude other diagnoses as high-resolution chest images are often not feasible. Semi-quantitative scoring performed by independent observers is the most common form of histologic analysis in pre-clinical animal models of ARDS. Despite progress in standardizing analysis procedures, objectively comparing histological injuries remains challenging, even for highly-trained pathologists. Standardized scoring simplifies the task and allows better comparisons between research groups and across different injury models, but it is time-consuming, and interobserver variability remains a significant concern. Convolutional neural networks (CNNs), which have emerged as a key tool in image analysis, could automate this process, potentially enabling faster and more reproducible analysis. Here we explored the reproducibility of human standardized scoring for an animal model of ARDS and its suitability for training CNNs for automated scoring at the whole slide level. We found large variations between human scorers, even for pre-clinical experts and board-certified pathologies in evaluating ARDS animal models. We demonstrate that CNNs (VGG16, EfficientNetB4) are suitable for automated scoring and achieve up to 83% F1-score and 78% accuracy. Thus, CNNs for histopathological classification of acute lung injury could help reduce human variability and eliminate a time-consuming manual research task with acceptable performance.
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| 10. |
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| 11. |
- Berg, Johanna, et al.
(författare)
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OpenChart-SE: A corpus of artificial Swedish electronic health records for imagined emergency care patients written by physicians in a crowd-sourcing project
- 2023
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Electronic health records (EHRs) are a rich source of information for medical research and public health monitoring. Information systems based on EHR data could also assist in patient care and hospital management. However, much of the data in EHRs is in the form of unstructured text, which is difficult to process for analysis. Natural language processing (NLP), a form of artificial intelligence, has the potential to enable automatic extraction of information from EHRs and several NLP tools adapted to the style of clinical writing have been developed for English and other major languages. In contrast, the development of NLP tools for less widely spoken languages such as Swedish has lagged behind. A major bottleneck in the development of NLP tools is the restricted access to EHRs due to legitimate patient privacy concerns. To overcome this issue we have generated a citizen science platform for collecting artificial Swedish EHRs with the help of Swedish physicians and medical students. These artificial EHRs describe imagined but plausible emergency care patients in a style that closely resembles EHRs used in emergency departments in Sweden. In the pilot phase, we collected a first batch of 50 artificial EHRs, which has passed review by an experienced Swedish emergency care physician. We make this dataset publicly available as OpenChart-SE corpus (version 1) under an open-source license for the NLP research community. The project is now open for general participation and Swedish physicians and medical students are invited to submit EHRs on the project website (https://github.com/Aitslab/openchart-se). Additional batches of quality-controlled EHRs will be released periodically.
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| 12. |
- Gustafsson, Lotta, et al.
(författare)
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Changes in proteasome structure and function caused by HAMLET in tumor cells.
- 2009
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 4:4
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Proteasomes control the level of endogenous unfolded proteins by degrading them in the proteolytic core. Insufficient degradation due to altered protein structure or proteasome inhibition may trigger cell death. This study examined the proteasome response to HAMLET, a partially unfolded protein-lipid complex, which is internalized by tumor cells and triggers cell death. METHODOLOGY/PRINCIPAL FINDINGS: HAMLET bound directly to isolated 20S proteasomes in vitro and in tumor cells significant co-localization of HAMLET and 20S proteasomes was detected by confocal microscopy. This interaction was confirmed by co-immunoprecipitation from extracts of HAMLET-treated tumor cells. HAMLET resisted in vitro degradation by proteasomal enzymes and degradation by intact 20S proteasomes was slow compared to fatty acid-free, partially unfolded alpha-lactalbumin. After a brief activation, HAMLET inhibited proteasome activity in vitro and in parallel a change in proteasome structure occurred, with modifications of catalytic (beta1 and beta5) and structural subunits (alpha2, alpha3, alpha6 and beta3). Proteasome inhibition was confirmed in extracts from HAMLET-treated cells and there were indications of proteasome fragmentation in HAMLET-treated cells. CONCLUSIONS/SIGNIFICANCE: The results suggest that internalized HAMLET is targeted to 20S proteasomes, that the complex resists degradation, inhibits proteasome activity and perturbs proteasome structure. We speculate that perturbations of proteasome structure might contribute to the cytotoxic effects of unfolded protein complexes that invade host cells.
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| 13. |
- Hallgren, Oskar, et al.
(författare)
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Apoptosis and tumor cell death in response to HAMLET (human alpha-lactalbumin made lethal to tumor cells).
- 2008
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Ingår i: Advances in Experimental Medicine and Biology. - New York, NY : Springer New York. - 0065-2598. ; 606, s. 217-240
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Forskningsöversikt (refereegranskat)abstract
- HAMLET (human alpha-lactalbumin made lethal to tumor cells) is a molecular complex derived from human milk that kills tumor cells by a process resembling programmed cell death. The complex consists of partially unfolded alpha-lactalbumin and oleic acid, and both the protein and the fatty acid are required for cell death. HAMLET has broad antitumor activity in vitro, and its therapeutic effect has been confirmed in vivo in a human glioblastoma rat xenograft model, in patients with skin papillomas and in patients with bladder cancer. The mechanisms of tumor cell death remain unclear, however. Immediately after the encounter with tumor cells, HAMLET invades the cells and causes mitochondrial membrane depolarization, cytochrome c release, phosphatidyl serine exposure, and a low caspase response. A fraction of the cells undergoes morphological changes characteristic of apoptosis, but caspase inhibition does not rescue the cells and Bcl-2 overexpression or altered p53 status does not influence the sensitivity of tumor cells to HAMLET. HAMLET also creates a state of unfolded protein overload and activates 20S proteasomes, which contributes to cell death. In parallel, HAMLET translocates to tumor cell nuclei, where high-affinity interactions with histones cause chromatin disruption, loss of transcription, and nuclear condensation. The dying cells also show morphological changes compatible with macroautophagy, and recent studies indicate that macroautophagy is involved in the cell death response to HAMLET. The results suggest that HAMLET, like a hydra with many heads, may interact with several crucial cellular organelles, thereby activating several forms of cell death, in parallel. This complexity might underlie the rapid death response of tumor cells and the broad antitumor activity of HAMLET.
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| 14. |
- Kazemi Rashed, Salma, et al.
(författare)
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English dictionaries, gold and silver standard corpora for biomedical natural language processing related to SARS-CoV-2 and COVID-19
- 2020
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Here we present a toolbox for natural language processing tasks related to SARS-CoV-2. It comprises English dictionaries of synonyms for SARS-CoV-2 and COVID-19, a silver standard corpus generated with the dictionaries and a gold standard corpus of 10 Pubmed abstracts manually annotated for disease, virus, symptom and protein/gene terms. This toolbox is freely available on github and can be used for text analytics in a variety of settings related to the COVID-19 crisis. It will be expanded and applied in NLP tasks over the next weeks and the community is invited to contribute.
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| 15. |
- Kazemi Rashed, Salma, et al.
(författare)
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Files and code for English dictionaries, gold and silver standard corpora for biomedical natural language processing related to SARS-CoV-2 and COVID-19 : Dataset record
- 2022
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- BACKGROUNDAutomated information extraction with natural language processing (NLP) tools is required to gain systematic insights from the large number of COVID-19 publications, reports and social media posts, which far exceed human processing capabilities. A key challenge for NLP is the extensive variation in terminology used to describe medical entities, which was especially pronounced for this newly emergent disease.FINDINGSHere we present an NLP toolbox comprising very large English dictionaries of synonyms for SARS-CoV-2 (including variant names) and COVID-19, which can be used with dictionary-based NLP tools. We also present a silver standard corpus generated with the dictionaries, and a gold standard corpus, consisting of PubMed abstracts manually annotated for disease, virus, symptom, protein/gene, cell type, chemical and species terms, which can be used to train and evaluate COVID-19-related NLP tools. Code for annotation, which can be used to expand the silver standard corpus or for text mining is also included. This toolbox is freely available on Github (on https://github.com/Aitslab/corona) and here.CONCLUSIONSThe toolbox can be used for a variety of text analytics tasks related to the COVID-19 crisis and has already been used to create a COVID-19 knowledge graph, study the variability and evolution of COVID-19-related terminology and develop and benchmark text mining tools.
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| 16. |
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| 17. |
- Lindgren, David, et al.
(författare)
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Recurrent and multiple bladder tumors show conserved expression profiles.
- 2008
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Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 8:June 30
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Urothelial carcinomas originate from the epithelial cells of the inner lining of the bladder and may appear as single or as multiple synchronous tumors. Patients with urothelial carcinomas frequently show recurrences after treatment making follow-up necessary. The leading hypothesis explaining the origin of meta- and synchronous tumors assumes a monoclonal origin. However, the genetic relationship among consecutive tumors has been shown to be complex in as much as the genetic evolution does not adhere to the chronological appearance of the metachronous tumors. Consequently, genetically less evolved tumors may appear chronologically later than genetically related but more evolved tumors. METHODS: Forty-nine meta- or synchronous urothelial tumors from 22 patients were analyzed using expression profiling, conventional CGH, LOH, and mutation analyses. RESULTS: We show by CGH that partial chromosomal losses in the initial tumors may not be present in the recurring tumors, by LOH that different haplotypes may be lost and that detected regions of LOH may be smaller in recurring tumors, and that mutations present in the initial tumor may not be present in the recurring ones. In contrast we show that despite apparent genomic differences, the recurrent and multiple bladder tumors from the same patients display remarkably similar expression profiles. CONCLUSION: Our findings show that even though the vast majority of the analyzed meta- and synchronous tumors from the same patients are not likely to have originated directly from the preceding tumor they still show remarkably similar expressions profiles. The presented data suggests that an expression profile is established early in tumor development and that this profile is stable and maintained in recurring tumors.
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| 18. |
- Pettersson, Jenny, et al.
(författare)
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Can misfolded proteins be beneficial? The HAMLET case.
- 2009
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Ingår i: Annals of Medicine. - : Informa UK Limited. - 1365-2060 .- 0785-3890. ; 41, s. 162-176
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Forskningsöversikt (refereegranskat)abstract
- By changing the three-dimensional structure, a protein can attain new functions, distinct from those of the native protein. Amyloid-forming proteins are one example, in which conformational change may lead to fibril formation and, in many cases, neurodegenerative disease. We have proposed that partial unfolding provides a mechanism to generate new and useful functional variants from a given polypeptide chain. Here we present HAMLET (Human Alpha-lactalbumin Made LEthal to Tumor cells) as an example where partial unfolding and the incorporation of cofactor create a complex with new, beneficial properties. Native alpha-lactalbumin functions as a substrate specifier in lactose synthesis, but when partially unfolded the protein binds oleic acid and forms the tumoricidal HAMLET complex. When the properties of HAMLET were first described they were surprising, as protein folding intermediates and especially amyloid-forming protein intermediates had been regarded as toxic conformations, but since then structural studies have supported functional diversity arising from a change in fold. The properties of HAMLET suggest a mechanism of structure-function variation, which might help the limited number of human protein genes to generate sufficient structural diversity to meet the diverse functional demands of complex organisms.
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| 19. |
- Storm, Petter, et al.
(författare)
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Conserved features of cancer cells define their sensitivity to HAMLET-induced death; c-Myc and glycolysis.
- 2011
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Ingår i: Oncogene. - : Springer Science and Business Media LLC. - 1476-5594 .- 0950-9232. ; 30, s. 4765-4779
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Tidskriftsartikel (refereegranskat)abstract
- HAMLET is the first member of a new family of tumoricidal protein-lipid complexes that kill cancer cells broadly, while sparing healthy, differentiated cells. Many and diverse tumor cell types are sensitive to the lethal effect, suggesting that HAMLET identifies and activates conserved death pathways in cancer cells. Here, we investigated the molecular basis for the difference in sensitivity between cancer cells and healthy cells. Using a combination of small-hairpin RNA (shRNA) inhibition, proteomic and metabolomic technology, we identified the c-Myc oncogene as one essential determinant of HAMLET sensitivity. Increased c-Myc expression levels promoted sensitivity to HAMLET and shRNA knockdown of c-Myc suppressed the lethal response, suggesting that oncogenic transformation with c-Myc creates a HAMLET-sensitive phenotype. Furthermore, HAMLET sensitivity was modified by the glycolytic state of tumor cells. Glucose deprivation sensitized tumor cells to HAMLET-induced cell death and in the shRNA screen, hexokinase 1 (HK1), 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1 and hypoxia-inducible factor 1α modified HAMLET sensitivity. HK1 was shown to bind HAMLET in a protein array containing ∼8000 targets, and HK activity decreased within 15 min of HAMLET treatment, before morphological signs of tumor cell death. In parallel, HAMLET triggered rapid metabolic paralysis in carcinoma cells. Tumor cells were also shown to contain large amounts of oleic acid and its derivatives already after 15 min. The results identify HAMLET as a novel anti-cancer agent that kills tumor cells by exploiting unifying features of cancer cells such as oncogene addiction or the Warburg effect.
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| 20. |
- Trulsson, Maria, et al.
(författare)
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HAMLET Binding to α-Actinin Facilitates Tumor Cell Detachment.
- 2011
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:3
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Tidskriftsartikel (refereegranskat)abstract
- Cell adhesion is tightly regulated by specific molecular interactions and detachment from the extracellular matrix modifies proliferation and survival. HAMLET (Human Alpha-lactalbumin Made LEthal to Tumor cells) is a protein-lipid complex with tumoricidal activity that also triggers tumor cell detachment in vitro and in vivo, suggesting that molecular interactions defining detachment are perturbed in cancer cells. To identify such interactions, cell membrane extracts were used in Far-western blots and HAMLET was shown to bind α-actinins; major F-actin cross-linking proteins and focal adhesion constituents. Synthetic peptide mapping revealed that HAMLET binds to the N-terminal actin-binding domain as well as the integrin-binding domain of α-actinin-4. By co-immunoprecipitation of extracts from HAMLET-treated cancer cells, an interaction with α-actinin-1 and -4 was observed. Inhibition of α-actinin-1 and α-actinin-4 expression by siRNA transfection increased detachment, while α-actinin-4-GFP over-expression significantly delayed rounding up and detachment of tumor cells in response to HAMLET. In response to HAMLET, adherent tumor cells rounded up and detached, suggesting a loss of the actin cytoskeletal organization. These changes were accompanied by a reduction in β1 integrin staining and a decrease in FAK and ERK1/2 phosphorylation, consistent with a disruption of integrin-dependent cell adhesion signaling. Detachment per se did not increase cell death during the 22 hour experimental period, regardless of α-actinin-4 and α-actinin-1 expression levels but adherent cells with low α-actinin levels showed increased death in response to HAMLET. The results suggest that the interaction between HAMLET and α-actinins promotes tumor cell detachment. As α-actinins also associate with signaling molecules, cytoplasmic domains of transmembrane receptors and ion channels, additional α-actinin-dependent mechanisms are discussed.
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