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- Nyström, Hanna, 1980-
(författare)
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Stromal collagens in colorectal cancer and in colorectal liver metastases : tumour biological implications and a source for novel tumour markers
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality. About 50 % of patients with CRC will develop subsequent liver metastases (CLM). The survival for untreated CLM is only a few months and liver resection provides the only chance for a lasting cure. It is therefore essential to detect CLM early, enabling successful surgical resection and achieving a long-term cure. There are no optimal tumour markers for CRC or CLM. The best marker available is Carcinoembryonic Antigen (CEA), a marker found elevated in about 50-60% of patients with CLM, but also in many other conditions. The main focus of cancer research has been on the malignant cancer cell. However, a tumour consists of more than cancer cells. A major part of all solid tumours is made up by the stroma. The tumour stroma is defined as the non-malignant cells of a tumour such as fibroblasts, the cells of the vascular and immune systems as well as the extracellular matrix (ECM). The basement membrane (BM) is a specialized form of the ECM in which type IV collagen is the major protein component. All epithelial cells need a contact to the BM and the definition of an invasive cancer is the degradation of the BM and the spread of cancer cells beyond this structure. Different metastatic growth patterns of CLM have previously been described, namely the desmoplastic, pushing and replacement type of CLM. These differ in their stromal reaction in the border, which separates the tumour from the normal liver. In this thesis the tumour stroma of CRC and CLM is studied with a special emphasis on stromal collagens. The aim is to investigate whether stromal collagens/ circulating type IV collagen can be used as tumour markers for CRC and CLM, and to compare this to the conventional marker CEA. The circulating type IV collagen level is also measured in liver metastases from other primary tumours than CRC. Furthermore, the differences between the stroma of a primary CRC that metastasizes to the liver when compared to a CRC that never spreads are analysed. Additionally, the metastatic growth pattern of CLM is studied in relation to the primary tumour, stromal components and survival. We also sought out to find whether CRC cell lines possess the trait to produce ECM proteins endogenously, and in response to a normal liver stroma in a novel organotypic model for CLM.Methods: Expression patterns of type I, III and IV collagen were studied by immunofluorescence (IF), chemical staining and immunohistochemistry (IHC) in normal colorectal tissue, normal liver, CRC, CLM, benign liver lesions and in liver metastases of other origin than CRC. Circulating plasma levels of type IV collagen were analysed in healthy controls, patients with CRC (T stage I-III) and in patients with CLM. Samples were analysed at the time of diagnosis, during and after oncological and surgical treatment and at the time of relapsing or progressive disease. Additionally, circulating levels were analysed in patients with benign liver lesions and in liver metastases of other origin than CRC. The metastatic growth pattern of CLM was classified according to earlier descriptions. CRC cell lines were studied regarding their production of type IV collagen. The growth, invasiveness and stromal production in CRC cell lines were also investigated in a new organotypic model for CLM using human liver specimens.Results: Circulating type IV collagen levels are increased in patients with CLM and other epithelial-derived liver metastases, and is found normal in patients with primary CRC (stage I-III), with liver metastases from tumours of non-epithelial origin, benign liver lesions and in healthy controls. The type IV collagen levels in patients with CLM reflect the tumour burden in the liver, decreases in response to therapy and is found increased in progressive or relapsing disease. The combination of circulating type IV collagen and CEA increased the sensitivity and specificity for detecting CLM. Livermetastatic CRC displayed an increased stromal production when compared to non-metastatic CRC, with an increased type IV collagen expression in the direct vicinity of the CRC cells. The earlier described growth patterns of CLM were verified, with the pushing type of CLM associated with a short survival and poor outcome. Furthermore, CRC cell lines possess the trait of endogenously producing type IV collagen. The novel organotypic liver model revealed that CRC cell lines grown in the context of normal liver stroma, devoid of other cells, does not elicit a desmoplastic reaction.Conclusion: Circulating type IV collagen is a promising tumour marker for CLM, where the levels reflect the hepatic tumour burden and can detect disease relapse after liver surgery. The combination of the tumour markers CEA and type IV collagen is superior to CEA alone. The stromal composition of primary CRC predicts the risk of subsequent CLM and the metastatic growth pattern of CLM is related to survival.
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| 2. |
- Sandström, Malin, 1980-, et al.
(författare)
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A Bulb Model Implementing Fuzzy Coding of Odor Concentration
- 2009
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Ingår i: Olfaction and Electronic Nose. - : AIP. - 9780735406742 ; , s. 159-162
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Konferensbidrag (refereegranskat)abstract
- It is commonly accepted that the olfactory bulb (OB) codes for odor quality by specific patterns of activated glomeruli. However, no such consensus has been reached for how the OB codes for odor concentration. We have constructed a model of the olfactory bulb which is able to generate a "fuzzy code" for odor concentration, while still coding for odor identity and showing synchronization of active mitral cells. The fuzzy code arises from competitive inhibition in the glomerular layer of the model. Fuzzy concentration coding could explain how the OB might encode odor concentration while still encoding odor quality according to the consensus view above.
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| 3. |
- Sandström, Malin, 1980-
(författare)
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Computational Modelling of Early Olfactory Processing
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Chemical sensing is believed to be the oldest sensory ability. The chemical senses, olfaction and gustation, developed to detect and analyze information in the form of air- or waterborne chemicals, to find food and mates, and to avoid danger. The organization of the olfactory system follows the same principles in almost all living animals, insects as well as mammals. Likely, the similarities are due to parallel evolution – the same type of organisation seems to have arisen more than once. Therefore, the olfactory system is often assumed to be close to optimally designed for its tasks.Paradoxically, the workings of the olfactory system are not yet well known,although several milestone discoveries have been made during the last decades. The most well-known is probably the disovery of the olfactory receptor gene family,announced in 1991 by Linda Buck and Richard Axel. For this and subsequent work, they were awarded a Nobel Prize Award in 2004. This achievement has been of immense value for both experimentalists and theorists, and forms the basis of the current understanding of olfaction. The olfactory system has long been a focus for scientific interest within several fields, both experimental and theoretical, and it has often been used asa model system. And ever since the field of computational neuroscience was founded, the functions of the olfactory system have been investigated through computational modelling. In this thesis, I present several approaches to biologically realistic computational models of parts of the olfactory system, with an emphasis on the earlier stages of the vertebrate olfactory system – olfactory receptor neurons (ORNs) and the olfactory bulb (OB). I have investigated the behaviour of the enzyme CaMKII, which is known to be critical for olfactory adaptation (suppression of constant odour stimuli) in the ORN, using a biochemical model. By constructing several OB models of different size, I have shown that the size of the OB network has an impact on its ability to process noisy information. Taking into account the reported variability of geometrical, electrical and receptor-dependent neuronal characteristics, I have been able to model the frequency response of a population of ORNs. I have used this model to find the key properties that govern most of the ORN population’s response, and investigated some of the possible implications of these key properties in subsequent studies of the ORN population and the OB – what we call the fuzzy concentration coding hypothesis.
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| 4. |
- Sandström, Malin, 1980-
(författare)
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Early Information Processing in the Vertebrate Olfactory System : A Computational Study
- 2007
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The olfactory system is believed to be the oldest sensory system. It developed to detect and analyse chemical information in the form of odours, and its organisation follows the same principles in almost all living animals - insects as well as mammals. Likely, the similarities are due to parallel evolution - the same type of organisation has arisen more than once. Therefore, the olfactory system is often assumed to be close to optimally designed for its tasks. Paradoxically, the workings of the olfactory system are not yet well known, although several milestone discoveries have been made during the last decades. The most well-known is probably the disovery of the olfactory receptor gene family, announced in 1991 by Linda Buck and Richard Axel. For this and subsequent work, they were awarded a Nobel Prize Award in 2004. This achievement has been of immense value for both experimentalists and theorists, and forms the basis of the current understanding of olfaction. The olfactory system has long been a focus for scientific interest, both experimental and theoretical. Ever since the field of computational neuroscience was founded, the functions of the olfactory system have been investigated through computational modelling. In this thesis, I present the basis of a biologically realistic model of the olfactory system. Our goal is to be able to represent the whole olfactory system. We are not there yet, but we have some of the necessary building blocks; a model of the input from the olfactory receptor neuron population and a model of the olfactory bulb. Taking into account the reported variability of geometrical, electrical and receptor-dependent neuronal characteristics, we have been able to model the frequency response of a population of olfactory receptor neurons. By constructing several olfactory bulb models of different size, we have shown that the size of the bulb network has an impact on its ability to process noisy information. We have also, through biochemical modelling, investigated the behaviour of the enzyme CaMKII which is known to be critical for early olfactory adaptation (suppression of constant odour stimuli).
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| 5. |
- Sandström, Malin, 1980-, et al.
(författare)
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Modeling the response of a population of olfactory receptor neurons to an odorant
- 2009
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Ingår i: Journal of Computational Neuroscience. - : Springer Science and Business Media LLC. - 0929-5313 .- 1573-6873. ; 27:3, s. 337-355
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Tidskriftsartikel (refereegranskat)abstract
- We modeled the firing rate of populations of olfactory receptor neurons (ORNs) responding to an odorant at different concentrations. Two cases were considered: a population of ORNs that all express the same olfactory receptor (OR), and a population that expresses many different ORs. To take into account ORN variability, we replaced single parameter values in a biophysical ORN model with values drawn from statistical distributions, chosen to correspond to experimental data. For ORNs expressing the same OR, we found that the distributions of firing frequencies are Gaussian at all concentrations, with larger mean and standard deviation at higher concentrations. For a population expressing different ORs, the distribution of firing frequencies can be described as the superposition of a Gaussian distribution and a lognormal distribution. Distributions of maximum value and dynamic range of spiking frequencies in the simulated ORN population were similar to experimental results.
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