Molecular profiling of CD8 T cells in autochthonous melanoma identifies Maf as driver of exhaustion.

T cells infiltrating neoplasms express surface molecules typical of chronically virus-stimulated T cells, often termed "exhausted" T cells. We compared the transcriptome of "exhausted" CD8 T cells infiltrating autochthonous melanomas to those of naïve and acutely stimulated CD8 T cells. Despite strong similarities between transcriptional signatures of tumor- and virus-induced exhausted CD8 T cells, notable differences appeared. Among transcriptional regulators, Nr4a2 and Maf were highly overexpressed in tumor-exhausted T cells and significantly upregulated in CD8 T cells from human melanoma metastases. Transduction of murine tumor-specific CD8 T cells to express Maf partially reproduced the transcriptional program associated with tumor-induced exhaustion. Upon adoptive transfer, the transduced cells showed normal homeostasis but failed to accumulate in tumor-bearing hosts and developed defective anti-tumor effector responses. We further identified TGFβ and IL-6 as main inducers of Maf expression in CD8 T cells and showed that Maf-deleted tumor-specific CD8 T cells were much more potent to restrain tumor growth in vivo. Therefore, the melanoma microenvironment contributes to skewing of CD8 T cell differentiation programs, in part by TGFβ/IL-6-mediated induction of Maf.

Gene expression profiling analysis of lung adenocarcinoma

The present study screened potential genes related to lung adenocarcinoma, with the aim of further understanding disease pathogenesis. The GSE2514 dataset including 20 lung adenocarcinoma and 19 adjacent normal tissue samples from 10 patients with lung adenocarcinoma aged 45-73 years was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between the two groups were screened using the t-test. Potential gene functions were predicted using functional and pathway enrichment analysis, and protein-protein interaction (PPI) networks obtained from the STRING database were constructed with Cytoscape. Module analysis of PPI networks was performed through MCODE in Cytoscape. In total, 535 upregulated and 465 downregulated DEGs were identified. These included ATP5D, UQCRC2, UQCR11 and genes encoding nicotinamide adenine dinucleotide (NADH), which are mainly associated with mitochondrial ATP synthesis coupled electron transport, and which were enriched in the oxidative phosphorylation pathway. Other DEGs were associated with DNA replication (PRIM1, MCM3, and RNASEH2A), cell surface receptor-linked signal transduction and the enzyme-linked receptor protein signaling pathway (MAPK1, STAT3, RAF1, and JAK1), and regulation of the cytoskeleton and phosphatidylinositol signaling system (PIP5K1B, PIP5K1C, and PIP4K2B). Our findings suggest that DEGs encoding subunits of NADH, PRIM1, MCM3, MAPK1, STAT3, RAF1, and JAK1 might be associated with the development of lung adenocarcinoma.

SCAPA (Spacially Addressable Protein Array) – a Novel Protein Array for the Differential Profiling of Ligand-receptor Induced Signalling

While protein microarray technology has been successful in demonstrating its usefulness for large scale high-throughput proteome profiling, performance of antibody/antigen microarrays has been only moderately productive. Immobilization of either the capture antibodies or the protein samples on solid supports has severe drawbacks. Denaturation of the immobilized proteins as well as inconsistent orientation of antibodies/ligands on the arrays can lead to erroneous results. This has prompted a number of studies to address these challenges by immobilizing proteins on biocompatible surfaces, which has met with limited success. Our strategy relates to a multiplexed, sensitive and high-throughput method for the screening quantification of intracellular signalling proteins from a complex mixture of proteins. Each signalling protein to be monitored has its capture moiety linked to a specific oligo ‘tag’. The array involves the oligonucleotide hybridization-directed localization and identification of different signalling proteins simultaneously, in a rapid and easy manner. Antibodies have been used as the capture moieties for specific identification of each signaling protein. The method involves covalently partnering each antibody/protein molecule with a unique DNA or DNA derivatives oligonucleotide tag that directs the antibody to a unique site on the microarray due to specific hybridization with a complementary tag-probe on the array. Particular surface modifications and optimal conditions allowed high signal to noise ratio which is essential to the success of this approach.

Overview of coded light projection techniques for automatic 3D profiling

Obtaining automatic 3D profile of objects is one of the most important issues in computer vision. With this information, a large number of applications become feasible: from visual inspection of industrial parts to 3D reconstruction of the environment for mobile robots. In order to achieve 3D data, range finders can be used. Coded structured light approach is one of the most widely used techniques to retrieve 3D information of an unknown surface. An overview of the existing techniques as well as a new classification of patterns for structured light sensors is presented. This kind of systems belong to the group of active triangulation method, which are based on projecting a light pattern and imaging the illuminated scene from one or more points of view. Since the patterns are coded, correspondences between points of the image(s) and points of the projected pattern can be easily found. Once correspondences are found, a classical triangulation strategy between camera(s) and projector device leads to the reconstruction of the surface. Advantages and constraints of the different patterns are discussed

Surface Corrosion of Ti-16Si-4B Powder Alloy Implanted With Nitrogen by Plasma-Based Technique

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modification of surface properties of Ti-16Si-4B powder alloy by plasma immersion ion implantation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Transcription profiling of Prss16 (Tssp) can be used to find additional peptidase genes that are candidates for self-peptide generation in the thymus

Positive selection (PS) in the thymus involves the presentation of self-peptides that are bound to MHC class II on the surface of cortical thymus epithelial cells (cTECs). Prss16 gene corresponds to one important element regulating the PS of CD4(+) T lymphocytes, which encodes Thymus-specific serine protease (Tssp), a cTEC serine-type peptidase involved in the proteolytic generation of self-peptides. Nevertheless, additional peptidase genes participating in the generation of self-peptides need to be found. Because of its role in the mechanism of PS and its expression in cTECs, the Prss16 gene might be used as a transcriptional marker to identify new genes that share the same expression profile and that encode peptidases in the thymus. To test this hypothesis, we compared the differential thymic expression of 4,500 mRNAs of wild-type (WT) C57BL/6 mice with their respective Prss16-knockout (KO) mutants by using microarrays. From these, 223 genes were differentially expressed, of which 115 had known molecular/biological functions. Four endopeptidase genes (Casp1, Casp2, Psmb3 and Tpp2) share the same expression profile as the Prss16 gene; i.e., induced in WT and repressed in KO while one endopeptidase gene, Capns1, features opposite expression profile. The Tpp2 gene is highlighted because it encodes a serine-type endopeptidase functionally similar to the Tssp enzyme. Profiling of the KO mice featured down-regulation of Prss16, as expected, along with the genes mentioned above. Considering that the Prss16-KO mice featured impaired PS, the shared regulation of the four endopeptidase genes suggested their participation in the mechanism of self-peptide generation and PS.

Mass spectrometry-based protein profiling strategies for biomarker discovery in liver and inflammatory bowel diseases

The study of protein expression profiles for biomarker discovery in serum and in mammalian cell populations needs the continuous improvement and combination of proteins/peptides separation techniques, mass spectrometry, statistical and bioinformatic approaches. In this thesis work two different mass spectrometry-based protein profiling strategies have been developed and applied to liver and inflammatory bowel diseases (IBDs) for the discovery of new biomarkers. The first of them, based on bulk solid-phase extraction combined with matrix-assisted laser desorption/ionization - Time of Flight mass spectrometry (MALDI-TOF MS) and chemometric analysis of serum samples, was applied to the study of serum protein expression profiles both in IBDs (Crohn’s disease and ulcerative colitis) and in liver diseases (cirrhosis, hepatocellular carcinoma, viral hepatitis). The approach allowed the enrichment of serum proteins/peptides due to the high interaction surface between analytes and solid phase and the high recovery due to the elution step performed directly on the MALDI-target plate. Furthermore the use of chemometric algorithm for the selection of the variables with higher discriminant power permitted to evaluate patterns of 20-30 proteins involved in the differentiation and classification of serum samples from healthy donors and diseased patients. These proteins profiles permit to discriminate among the pathologies with an optimum classification and prediction abilities. In particular in the study of inflammatory bowel diseases, after the analysis using C18 of 129 serum samples from healthy donors and Crohn’s disease, ulcerative colitis and inflammatory controls patients, a 90.7% of classification ability and a 72.9% prediction ability were obtained. In the study of liver diseases (hepatocellular carcinoma, viral hepatitis and cirrhosis) a 80.6% of prediction ability was achieved using IDA-Cu(II) as extraction procedure. The identification of the selected proteins by MALDITOF/ TOF MS analysis or by their selective enrichment followed by enzymatic digestion and MS/MS analysis may give useful information in order to identify new biomarkers involved in the diseases. The second mass spectrometry-based protein profiling strategy developed was based on a label-free liquid chromatography electrospray ionization quadrupole - time of flight differential analysis approach (LC ESI-QTOF MS), combined with targeted MS/MS analysis of only identified differences. The strategy was used for biomarker discovery in IBDs, and in particular of Crohn’s disease. The enriched serum peptidome and the subcellular fractions of intestinal epithelial cells (IECs) from healthy donors and Crohn’s disease patients were analysed. The combining of the low molecular weight serum proteins enrichment step and the LCMS approach allowed to evaluate a pattern of peptides derived from specific exoprotease activity in the coagulation and complement activation pathways. Among these peptides, particularly interesting was the discovery of clusters of peptides from fibrinopeptide A, Apolipoprotein E and A4, and complement C3 and C4. Further studies need to be performed to evaluate the specificity of these clusters and validate the results, in order to develop a rapid serum diagnostic test. The analysis by label-free LC ESI-QTOF MS differential analysis of the subcellular fractions of IECs from Crohn’s disease patients and healthy donors permitted to find many proteins that could be involved in the inflammation process. Among them heat shock protein 70, tryptase alpha-1 precursor and proteins whose upregulation can be explained by the increased activity of IECs in Crohn’s disease were identified. Follow-up studies for the validation of the results and the in-depth investigation of the inflammation pathways involved in the disease will be performed. Both the developed mass spectrometry-based protein profiling strategies have been proved to be useful tools for the discovery of disease biomarkers that need to be validated in further studies.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

Variability in Accumulation Rates from GPR Profiling on the West Antarctic Plateau

lsochronal layers in firn detected with ground-penetrating radar (GPR) and dated using results from ice-core analyses are used to calculate accumulation rates along a 100 km across-flow profile in West Antarctica. Accumulation rates are shown to be highly variable over short distances. Elevation measurements from global positioning system surveys show that accumulation rates derived from shallow horizons correlate well with surface undulations, which implies that wind redistribution of snow is the leading cause of this variability. Temporal changes in accumulation rate over 25-185 year intervals are smoothed to along-track length scales comparable to surface undulations in order to identify trends in accumulation that are likely related to changes in climate. Results show that accumulation rates along this profile have decreased in recent decades, which is consistent with core-derived time series of annual accumulation rates measured at the two ends of the radar profile. These results suggest that temporal variability observed in accumulation-rate records from ice cores and GPR profiles can be obscured by spatial influences, although it is possible to resolve temporal signals if the effects of local topography and ice flow are quantified and removed.

Protein profiling of organic stone matrix and urine from dogs with urolithiasis

Two-thirds of the organic matrix in urinary stones consists of proteins. Their relationship to calculogenesis remains controversial with regard to their effect as inhibitors or promoters during stone formation. The purpose of the present study was to determine the differences in peptide and protein pattern between the urine of stone formers (n = 23) and control dogs (n = 12), as well as between organic matrix of different urinary stones (struvite n = 11, calcium oxalate n = 8, uric acid n = 4) using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Specific differences in protein and peptide profiles were found in the organic matrix of different mineral compositions. Characteristic differences were also found in urinary peptide and protein pattern especially in molecular masses below 20 kDa between affected and healthy dogs. Based on the obtained molecular masses they were in some cases tentatively identified as proteins that are known to be involved in stone formation in humans. The study shows that in dogs, specific-urinary peptides and proteins might be associated with urolithiasis. It indicates the importance to further characterize those proteins for possible diagnostic purposes in prognosis and therapy

Protein profiling of urine from dogs with renal disease using ProteinChip analysis

Measurement of total urinary proteins in individuals that tested positive by urinary dipstick is a typical method for assessing the presence of potentially serious renal disorders. In the absence of such overt proteinuria, however, measurement of specific urinary proteins may be useful in the diagnosis of nephropathies and may provide greater insight into the pathogenesis. The urine of 28 dogs (16 with renal disease and 12 healthy) was evaluated to determine whether specific low-molecular-weight proteins or the pattern of protein excretion could also be used as a marker of tubular dysfunction in dogs. Specific proteins were assessed by immunological methods, whereas protein profiles were determined by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (MS). In particular, changes in the excretion of retinol-binding protein (RBP) and Tamm-Horsfall protein (THP) appear to be of clinical relevance in the diagnosis of canine kidney diseases. The pattern of urinary protein and peptides revealed specific changes in abundance in dogs with renal disease at molecular masses (kD) of 11.58, 12.41, 12.60, 14.58, 20.95 (RBP), 27.85, and 65.69 (albumin). In conclusion, comparable proteins as in humans might be used as urinary markers for proximal (RBP) and distal (THP) tubular dysfunction in dogs. Surface-enhanced laser desorption/ionization time-of-flight MS is a promising tool for the study of kidney physiology and pathophysiology and might aid in the discovery of new biomarkers of renal disease.