Differential effects of interferon-gamma and tumor necrosis factor-alpha on Toxoplasma gondii proliferation in organotypic rat brain slice cultures.

Organotypic slice culture explants of rat cortical tissue infected with Toxoplasma gondii tachyzoites were applied as an in vitro model to investigate host-pathogen interactions in cerebral toxoplasmosis. The kinetics of parasite proliferation and the effects of interferon-gamma (IFN-gamma) and tumor necrosis factor-alpha (TNF-alpha) in infected organotypic cultures were monitored by light microscopy, transmission electron microscopy (TEM), and quantitative polymerase chain reaction (PCR) assay. As assessed by the loss of the structural integrity of the glial fibrillary acidic protein-intermediate filament network, tachyzoites infected and proliferated mainly within astrocytes, whereas neurons and microglia remained largely unaffected. Toxoplasma gondii proliferation was severely inhibited by IFN-y. However, this inhibition was not linked to tachyzoite-to-bradyzoite stage conversion. In contrast, TNF-alpha treatment resulted in a dramatically enhanced proliferation rate of the parasite. The cellular integrity in IFN-gamma-treated organotypic slice cultures was severely impaired compared with untreated and TNF-alpha-treated cultures. Thus, on infection of organotypic neuronal cultures, IFN-gamma and TNF-alpha exhibit largely detrimental effects, which could contribute to either inhibition or acceleration of parasite proliferation during cerebral toxoplasmosis.

Tissue metabolomics of hepatocellular carcinoma: Tumor energy metabolism and the role of transcriptomic classification

Hepatocellular carcinoma (HCC) is one of the commonest causes of death from cancer. A plethora of metabolomic investigations of HCC have yielded molecules in biofluids that are both up- and down-regulated but no real consensus has emerged regarding exploitable biomarkers for early detection of HCC. We report here a different approach, a combined transcriptomics and metabolomics study of energy metabolism in HCC. A panel of 31 pairs of HCC tumors and corresponding nontumor liver tissues from the same patients was investigated by gas chromatography-mass spectrometry (GCMS)-based metabolomics. HCC was characterized by ∼2-fold depletion of glucose, glycerol 3- and 2-phosphate, malate, alanine, myo-inositol, and linoleic acid. Data are consistent with a metabolic remodeling involving a 4-fold increase in glycolysis over mitochondrial oxidative phosphorylation. A second panel of 59 HCC that had been typed by transcriptomics and classified in G1 to G6 subgroups was also subjected to GCMS tissue metabolomics. No differences in glucose, lactate, alanine, glycerol 3-phosphate, malate, myo-inositol, or stearic acid tissue concentrations were found, suggesting that the Wnt/β-catenin pathway activated by CTNNB1 mutation in subgroups G5 and G6 did not exhibit specific metabolic remodeling. However, subgroup G1 had markedly reduced tissue concentrations of 1-stearoylglycerol, 1-palmitoylglycerol, and palmitic acid, suggesting that the high serum α-fetoprotein phenotype of G1, associated with the known overexpression of lipid catabolic enzymes, could be detected through metabolomics as increased lipid catabolism. Conclusion: Tissue metabolomics yielded precise biochemical information regarding HCC tumor metabolic remodeling from mitochondrial oxidation to aerobic glycolysis and the impact of molecular subtypes on this process.

Atlas-based Segmentation of Tumor-bearing Brain Images

In diagnostic neuroradiology as well as in radiation oncology and neurosurgery, there is an increasing demand for accurate segmentation of tumor-bearing brain images. Atlas-based segmentation is an appealing automatic technique thanks to its robustness and versatility. However, atlas-based segmentation of tumor-bearing brain images is challenging due to the confounding effects of the tumor in the patient image. In this article, we provide a brief background on brain tumor imaging and introduce the clinical perspective, before we categorize and review the state of the art in the current literature on atlas-based segmentation for tumor-bearing brain images. We also present selected methods and results from our own research in more detail. Finally, we conclude with a short summary and look at new developments in the field, including requirements for future routine clinical use.

Intracranial meningiomas associated with cervical syringohydromyelia in a cat

Eine dreizehnjährige, weibliche, nicht kastrierte Hauskatze wurde zur chirurgischen Therapie eines multiplen Meningeoms in der Kleintierklinik des Tierspital Bern vorgestellt. Eine leichtgradige generalisierte Ataxie wurde beobachtet, die Propriozeption war generalisiert herabgesetzt und der Drohreflex war beidseitig reduziert. Es wurden eine prä- und eine postoperative Magnetrezonanztomographie durchgeführt. Drei supratentoriale extra-axiale Raumforderungen wurden diagnostiziert. Eine vierte Masse wurde infratentorial extra-axial über der linken zerebellären Hemisphere lokalisiert. Eine Herniation des kaudoventralen Kleinhirn (Vermis) von ungefähr einem Zentimeter Länge durch das Foramen magnum wurde beobachtet. Eine zervikale Syringohydromyelie wurde als Zufallsbefund diagnostiziert. Die Meningeome wurden durch 3 Kraniotomiestellen entfernt. Zwei Jahre nach der Operation ist die Katze normal. Anhand der vorhandenen Literatur wird die tumor-assoziierte Syringohydromyelie besprochen. Die Therapie der Syringohydromyelie sollte gegen den kausalen pathologischen Prozess (z.B. intrakranieller Tumor) für die Liquorzirkulationsstörung gerichtet sein.

Interactions between Siglec-7/9 receptors and ligands influence NK cell-dependent tumor immunosurveillance

Abstract Alteration of the surface glycosylation pattern on malignant cells potentially affects tumor immunity by directly influencing interactions with glycan-binding proteins (lectins) on the surface of immunomodulatory cells. The sialic acid-binding Ig-like lectins Siglec-7 and -9 are MHC class I-independent inhibitory receptors on human NK cells that recognize sialic acid-containing carbohydrates. Here, we found that the presence of Siglec-9 defined a subset of cytotoxic NK cells with a mature phenotype and enhanced chemotactic potential. Interestingly, this Siglec-9+ NK cell population was reduced in the peripheral blood of cancer patients. Broad analysis of primary tumor samples revealed that ligands of Siglec-7 and -9 were expressed on human cancer cells of different histological types. Expression of Siglec-7 and -9 ligands was associated with susceptibility of NK cell-sensitive tumor cells and, unexpectedly, of presumably NK cell-resistant tumor cells to NK cell-mediated cytotoxicity. Together, these observations have direct implications for NK cell-based therapies and highlight the requirement to consider both MHC class I haplotype and tumor-specific glycosylation.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Interactive Segmentation of MR Images from Brain Tumor Patients

Medical doctors often do not trust the result of fully automatic segmentations because they have no possibility to make corrections if necessary. On the other hand, manual corrections can introduce a user bias. In this work, we propose to integrate the possibility for quick manual corrections into a fully automatic segmentation method for brain tumor images. This allows for necessary corrections while maintaining a high objectiveness. The underlying idea is similar to the well-known Grab-Cut algorithm, but here we combine decision forest classification with conditional random field regularization for interactive segmentation of 3D medical images. The approach has been evaluated by two different users on the BraTS2012 dataset. Accuracy and robustness improved compared to a fully automatic method and our interactive approach was ranked among the top performing methods. Time for computation including manual interaction was less than 10 minutes per patient, which makes it attractive for clinical use.

Cerebral High-grade Oligodendroglioma with Sarcomatous Transdifferentiation ("Oligosarcoma") in a Boxer Dog.

A 9-year-old Boxer dog was referred to the Veterinary Teaching Hospital of the University of Bern for a history of chronic neck pain and gait problems, which rapidly progressed to a non-ambulatory status. Magnetic resonance imaging (MRI) examination of the head revealed a large intra-axial space-occupying lesion that was divided in two portions interconnected by a thin isthmus at the level of the cerebellar tentorium. Histopathology revealed a biphasic malignant neoplasm composed of neuroepithelial and mesenchymal elements. The former displayed characteristics of conventional anaplastic oligodendroglioma involving brisk mitotic activity and glomeruloid microvascular proliferation on a background of a fibrillary round cells with "honeycomb-like" perinuclear vacuolation. Conversely, the sarcomatous moiety exhibited haphazard fascicles of spindle cells amidst an intricate mesh of pericellular basal lamina and broad bands of collagen. Both tumor cell populations immunoreacted for Olig-2 and – to a lesser extent – GFAP. In addition, the sarcomatous areas focally expressed vimentin, muscular actin, and smooth muscle actin. "Oligosarcoma" - an exquisitely uncommon pattern of oligodendroglial malignancy in humans - has not previously been reported to affect dogs, although oligodendroglioma is a common CNS tumor in this species. Whether canine oligosarcoma shares with its human counterpart not only morphological aspects, but also molecular signatures, clinical behavior and responsiveness to therapy merits further investigation. In humans, oligodendroglial differentiation tends to confer significant clinical advantage with respect to prognosis and adjuvant treatment options. The awareness of such hallmarks and the investigation of their impact on prognosis are crucial for improved therapeutical strategies in dogs.