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.

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.

Novel Prodrug-Like Fusion Toxin with Protease-Sensitive Bioorthogonal PEGylation for Tumor Targeting

Highly potent biotoxins like Pseudomonas exotoxin A (ETA) are attractive payloads for tumor targeting. However, despite replacement of the natural cell-binding domain of ETA by tumor-selective antibodies or alternative binding proteins like designed ankyrin repeat proteins (DARPins) the therapeutic window of such fusion toxins is still limited by target-independent cellular uptake, resulting in toxicity in normal tissues. Furthermore, the strong immunogenicity of the bacterial toxin precludes repeated administration in most patients. Site-specific modification to convert ETA into a prodrug-like toxin which is reactivated specifically in the tumor, and at the same time has a longer circulation half-life and is less immunogenic, is therefore appealing. To engineer a prodrug-like fusion toxin consisting of the anti-EpCAM DARPin Ec1 and a domain I-deleted variant of ETA (ETA″), we used strain-promoted azide alkyne cycloaddition for bioorthogonal conjugation of linear or branched polyethylene glycol (PEG) polymers at defined positions within the toxin moiety. Reversibility of the shielding was provided by a designed peptide linker containing the cleavage site for the rhinovirus 3C model protease. We identified two distinct sites, one within the catalytic domain and one close to the C-terminal KDEL sequence of Ec1-ETA″, simultaneous PEGylation of which resulted in up to 1000-fold lower cytotoxicity in EpCAM-positive tumor cells. Importantly, the potency of the fusion toxin was fully restored by proteolytic unveiling. Upon systemic administration in mice, PEGylated Ec1-ETA″ was much better tolerated than Ec1-ETA″; it showed a longer circulation half-life and an almost 10-fold increased area under the curve (AUC). Our strategy of engineering prodrug-like fusion toxins by bioorthogonal veiling opens new possibilities for targeting tumors with more specificity and efficacy.

Cancer intelligence acquired (CIA): tumor glycosylation and sialylation codes dismantling antitumor defense

Aberrant glycosylation is a key feature of malignant transformation and reflects epigenetic and genetic anomalies among the multitude of molecules involved in glycan biosynthesis. Although glycan biosynthesis is not template bound, altered tumor glycosylation is not random, but associated with common glycosylation patterns. Evidence suggests that acquisition of distinct glycosylation patterns evolves from a ‘microevolutionary’ process conferring advantages in terms of tumor growth, tumor dissemination, and immune escape. Such glycosylation modifications also involve xeno- and hypersialylation. Xeno-autoantigens such as Neu5Gc-gangliosides provide potential targets for immunotherapy. Hypersialylation may display ‘enhanced self’ to escape immunosurveillance and involves several not mutually exclusive inhibitory pathways that all rely on protein–glycan interactions. A better understanding of tumor ‘glycan codes’ as deciphered by lectins, such as siglecs, selectins, C-type lectins and galectins, may lead to novel treatment strategies, not only in cancer, but also in autoimmune disease or transplantation.

Cloning, sequencing and partial functional characterization of the 5' region of the human p75 tumor necrosis factor receptor-encoding gene (TNF-R)

A 1887-bp region at the 5' flank of the human p75 tumor necrosis factor receptor (p75 TNF-R)-encoding gene was found to be active in driving expression of the luc (luciferase-encoding) reporter gene, suggesting that it contains the promoter for the receptor. Rather unexpectedly, a 1827-bp region at the 3' end of the first intron of the p75 TNF-R gene also displayed promoter activity. This activity may be artefactual, reflecting only the presence of an enhancer in this region; yet it also raises the possibility that p75 TNF-R is controlled by more than one promoter and that it encodes various forms of the receptor, or even other proteins. We present here the nucleotide sequences of the 5' flanking and intron regions. Possible implications for the transcriptional regulation of the p75 TNF-R gene are discussed.

Improved bioassay for the detection of porcine tumor necrosis factor using a homologous cell line: PK(15)

Close similarities of various physiological parameters makes the pig one of the preferred animal models for the study of human diseases, especially those involving the cardiovascular system. Unfortunately, the use of pig models to study diseases such as viral hemorrhagic fevers and endotoxic shock syndrome have been hampered by the lack of the necessary immunological tools to measure important immunoregulatory cytokines such as tumor necrosis factor (TNF). Here we describe a TNF-bioassay which is based on the porcine kidney cell line PK(15). Compared to the widely used murine fibroblastoid cell line L929, the PK(15) cell line displays a 100-1000-fold higher sensitivity for porcine TNF-alpha, a higher sensitivity for human TNF-alpha, and a slightly lower sensitivity for murine TNF-alpha. Using a PK(15) bioassay we can detect recombinant TNF-alpha as well as cytotoxic activity in the supernatants of lipopolysaccharide (LPS)-activated porcine monocytes at high dilutions. This suggests that the sensitivity of the test should permit the detection of TNF in biological specimens such as pig serum.