Binding of hepatitis A virus to its cellular receptor 1 inhibits T-regulatory cell functions in humans.

BACKGROUND & AIMS: CD4+ T-regulatory (Treg) cells suppress immune responses and control self-tolerance and immunity to pathogens, cancer, and alloantigens. Most pathogens activate Treg cells to minimize immune-mediated tissue damage and prevent clearance, which promotes chronic infections. However, hepatitis A virus (HAV) temporarily inhibits Treg-cell functions. We investigated whether the interaction of HAV with its cellular receptor 1 (HAVCR1), a T-cell co-stimulatory molecule, inhibits the function of Treg cells to control HAV infection. METHODS: We studied the effects of HAV interaction with HAVCR1 on human T cells using binding, signal transduction, apoptosis, activation, suppression, cytokine production, and confocal microscopy analyses. Cytokines were analyzed in sera from 14 patients with HAV infection using bead arrays. RESULTS: Human Treg cells constitutively express HAVCR1. Binding of HAV to HAVCR1 blocked phosphorylation of Akt, prevented activation of the T-cell receptor, and inhibited function of Treg cells. At the peak viremia, patients with acute HAV infection had no Treg-cell suppression function, produced low levels of transforming growth factor-ß , which limited leukocyte recruitment and survival, and produced high levels of interleukin-22, which prevented liver damage. CONCLUSIONS: Interaction between HAV and its receptor HAVCR1 inhibits Treg-cell function, resulting in an immune imbalance that allows viral expansion with limited hepatocellular damage during early stages of infection-a characteristic of HAV pathogenesis. The mechanism by which HAV is cleared in the absence of Treg-cell function could be used as a model to develop anticancer therapies, modulate autoimmune and allergic responses, and prevent transplant rejection.

Screening of biochemical/histological changes associated to C6 glioma tumor development by FTIR/PCA imaging.

Principal components analysis (PCA) combined to Fourier transform infrared (FTIR) microspectroscopic imaging was used to screen biochemical changes associated to C6 glioma tumor from 7 to 19 days growth. Normal brain and tumor obtained at 7, 12, 19 days after C6 cell injection were used to develop a diagnostic model of brain glioma based on PCA analysis. This classification model was validated using extra-measurements on normal and tumor at 9 and 15 days post-implantation. The spatial and biochemical information obtained from FTIR/PCA maps can be used to improve the discrimination between normal and grading human glioma. The first 4 PCs which account for more than 93.6% of total spectral variance were used to construct pseudo-color scores maps and compared each map to the corresponding hematoxylin and eosin (H&E) staining. Our results reported that by correlating pseudocolor map scores with H&E staining it was possible to screen histological changes associated with tissue transformation. In fact, PC1 and PC4 were associated to the tumor, surrounding tumor and necrosis. Indeed, at day 7 after tumor implantation, FTIR investigations displayed a very small abnormal zone associated with the proliferation of C6 cells in the caudate putamen (CP). PC2 and PC3 described normal brain structures such as white matter (corpus callosum (CC) and commissura anterior (CA)) and some cortex layers (grey matter). After delipidation of the tissues, we were still able to differentiate between different tissue features based on nucleic acid and protein content. By comparing the patterns of the PC loads with the spectra of lipids extracted from white and gray matters, and DNA, we have identified some biochemical changes associated with tissue transformation. This work demonstrated that our classification model provides a successful histological classification of different brain structures.

Ex vivo and in vivo diagnosis of C6 glioblastoma development by Raman spectroscopy coupled to a microprobe.

The potential of Raman spectroscopy for ex vivo and in vivo classification of normal and glioblastoma brain tumor development was investigated. High-quality spectra of normal and tumor tissues were obtained using a portable Raman spectrometer coupled to a microprobe with a signal integration time of 5 s. Ex vivo results demonstrated that by using the biochemical information contained in the spectra, we were able to distinguish between normal brain features (white and gray matter), invasion, and tumor tissues with a classification accuracy of 100%. Differences between these features resulted from variations in their lipid signal contributions, which probably reflect differences in the level of myelinization. This finding supports the ability of in vivo Raman spectroscopy to delineate tumor margins during surgery. After implanting C6 cells in rat brain, we monitored, in vivo, the development of glioblastoma tumor from days 0 to 20 post-implantation (PI). The classification exhibited a clear separation of the data into two clusters: one cluster was associated with normal brain tissues (cortex), and the second was related to data measured from tumor evolution. The second cluster could be divided into two subclusters, one associated with tumor tissue from 4 to 13 days PI and the second related to tumor tissue from 15 to 20 days PI. Histological analysis reveals that the differences between these two subclusters are: the presence of a massive infiltration zone in the brain tissue from 4 to 13 days PI, and; a maturation of the tumor characterized by the appearance of edematous and necrotic zones, as well as a diminution in the proliferative and invasive area, from 15 days. This work demonstrates the potential of Raman spectroscopy to provide diagnostic information for the early detection of tumors in vivo.

Monitoring of biochemical changes through the c6 gliomas progression and invasion by fourier transform infrared (FTIR) imaging.

We have investigated the spatial distribution of molecular changes associated with C6 glioma progression using Fourier transform infrared (FT-IR) microspectro-imaging in order to determine spectroscopic markers for early diagnosis of tumor growth. Our results showed that at day 7 after tumor implantation, FTIR investigations displayed a very small abnormal zone associated with the proliferation of C6 cells in the caudate putamen. From this day, rats developed solid and well-circumscribed tumors and invasive areas. The volume of peritumoral areas increased rapidly until day 19. The maturation of the tumor was accompanied by a diminution in its proliferative and invasive area. The presence of necrotic areas was visible from day 15. A non-negative least-squares algorithm was used to quantify spatial distribution of molecular changes in tissues (lipids, nucleic acids, and proteins) associated with glioma progression. Compared to those in normal brain, statistical tests on fit coefficients showed that the concentrations of sphingomyelin (SMY), nucleic acids, phosphatidylserine (PS), and galactocerebroside (GalC) were significantly affected during C6 glioma development. These constituents can be used as spectroscopic markers for C6 glioma progression. Indeed, the concentration of DNA decreased significantly from tumor to invasion, to normal brain tissues, the necrotic area has higher concentrations of the Galc than other areas. The PS content was significantly higher in the peritumoral zone and decreased in the tumor zones matter.

Discriminating healthy from tumor and necrosis tissue in rat brain tissue samples by Raman spectral imaging.

The purpose of this study was to investigate molecular changes associated with glioma tissues by Raman microspectroscopy in order to develop its use in clinical practice. Spectroscopic markers obtained from C6 glioma tissues were compared to conventional histological and histochemical techniques. Cholesterol and phospholipid contents were highest in corpus callosum and decreased gradually towards the cortex surface as well as in the tumor. Two different necrotic areas have been identified: a fully necrotic zone characterized by the presence of plasma proteins and a peri-necrotic area with a high lipid content. This result was confirmed by Nile Red staining. Additionally, one structure was detected in the periphery of the tumor. Invisible with histopathological hematoxylin and eosin staining, it was revealed by immunohistochemical Ki-67 and MT1-MMP staining used to visualize the proliferative and invasive activities of glioma, respectively. Hierarchical cluster analysis on the only cluster averaged spectra showed a clear distinction between normal, tumoral, necrotic and edematous tissues. Raman microspectroscopy can discriminate between healthy and tumoral brain tissue and yield spectroscopic markers associated with the proliferative and invasive properties of glioblastoma. Development of in vivo Raman spectroscopy could thus accurately define tumor margins, identify tumor remnants, and help in the development of novel therapies for glioblastoma.

Modeling and quantifying biochemical changes in C6 tumor gliomas by Fourier transform infrared imaging.

The purpose of the study was to investigate molecular changes associated with glioma tissues using FT-IR microspectroscopic imaging (FT-IRM). A multivariate statistical analysis allowed one to successfully discriminate between normal, tumoral, peri-tumoral, and necrotic tissue structures. Structural changes were mainly related to qualitative and quantitative changes in lipid content, proteins, and nucleic acids that can be used as spectroscopic markers for this pathology. We have developed a spectroscopic model of glioma to quantify these chemical changes. The model constructed includes individual FT-IR spectra of normal and glioma brain constituents such as lipids, DNA, and proteins (measured on delipidized tissue). Modeling of FT-IR spectra yielded fit coefficients reflecting the chemical changes associated with a tumor. Our results demonstrate the ability of FT-IRM to assess the importance and distribution of each individual constituent and its variation in normal brain structures as well as in the different pathological states of glioma. We demonstrated that (i) cholesterol and phosphatidylethanolamine contributions are highest in corpus callosum and anterior commissure but decrease gradually towards the cortex surface as well as in the tumor, (ii) phosphatidylcholine contribution is highest in the cortex and decreases in the tumor, (iii) galactocerebroside is localized only in white, but not in gray matter, and decreases in the vital tumor region while the necrosis area shows a higher concentration of this cerebroside, (iv) DNA and oleic acid increase in the tumor as compared to gray matter. This approach could, in the future, contribute to enhance diagnostic accuracy, improve the grading, prognosis, and play a vital role in therapeutic strategy and monitoring.

Brain tissue characterisation by infrared imaging in a rat glioma model.

Pathological changes associated with the development of brain tumor were investigated by Fourier transform infrared microspectroscopy (FT-IRM) with high spatial resolution. Using multivariate statistical analysis and imaging, all normal brain structures were discriminated from tumor and surrounding tumor tissues. These structural changes were mainly related to qualitative and quantitative changes in lipids (tumors contain little fat) and were correlated to the degree of myelination, an important factor in several neurodegenerative disorders. Lipid concentration and composition may thus be used as spectroscopic markers to discriminate between healthy and tumor tissues. Additionally, we have identified one peculiar structure all around the tumor. This structure could be attributed to infiltrative events, such as peritumoral oedema observed during tumor development. Our results highlight the ability of FT-IRM to identify the molecular origin that gave rise to the specific changes between healthy and diseased states. Comparison between pseudo-FT-IRM maps and histological examinations (Luxol fast blue, Luxol fast blue-cresyl violet staining) showed the complementarities of both techniques for early detection of tissue abnormalities.