Comprehensive Glycoprofiling of Oral Tumors Associates N-Glycosylation With Lymph Node Metastasis and Patient Survival.

While altered protein glycosylation is regarded a trait of oral squamous cell carcinoma (OSCC), the heterogeneous and dynamic glycoproteome of tumor tissues from OSCC patients remain unmapped. To this end, we here employ an integrated multi-omics approach comprising unbiased and quantitative glycomics and glycoproteomics applied to a cohort of resected primary tumor tissues from OSCC patients with (n = 19) and without (n = 12) lymph node metastasis. While all tumor tissues displayed relatively uniform N-glycome profiles suggesting overall stable global N-glycosylation during disease progression, altered expression of six sialylated N-glycans was found to correlate with lymph node metastasis. Notably, glycoproteomics and advanced statistical analyses uncovered altered site-specific N-glycosylation revealing previously unknown associations with several clinicopathological features. Importantly, the glycomics and glycoproteomics data unveiled that comparatively high abundance of two core-fucosylated and sialylated N-glycans (Glycan 40a and Glycan 46a) and one N-glycopeptide from fibronectin were associated with low patient survival, while a relatively low abundance of N-glycopeptides from both afamin and CD59 were also associated with poor survival. This study provides insight into the complex OSCC tissue N-glycoproteome, thereby forming an important resource to further explore the underpinning disease mechanisms and uncover new prognostic glycomarkers for OSCC.

A Reductionist Approach Using Primary and Metastatic Cell-Derived Extracellular Vesicles Reveals Hub Proteins Associated with Oral Cancer Prognosis.

Oral squamous cell carcinoma (OSCC) has high mortality rates that are largely associated with lymph node metastasis. However, the molecular mechanisms that drive OSCC metastasis are unknown. Extracellular vesicles (EVs) are membrane-bound particles that play a role in intercellular communication and impact cancer development and progression. Thus, profiling EVs would be of great significance to decipher their role in OSCC metastasis. For that purpose, we used a reductionist approach to map the proteomic, miRNA, metabolomic, and lipidomic profiles of EVs derived from human primary tumor (SCC-9) cells and matched lymph node metastatic (LN1) cells. Distinct omics profiles were associated with the metastatic phenotype, including 670 proteins, 217 miRNAs, 26 metabolites, and 63 lipids differentially abundant between LN1 cell- and SCC-9 cell-derived EVs. A multi-omics integration identified 11 'hub proteins' significantly decreased at the metastatic site compared with primary tumor-derived EVs. We confirmed the validity of these findings with analysis of data from multiple public databases and found that low abundance of seven 'hub proteins' in EVs from metastatic lymph nodes (ALDH7A1, CAD, CANT1, GOT1, MTHFD1, PYGB, and SARS) is correlated with reduced survival and tumor aggressiveness in patients with cancer. In summary, this multi-omics approach identified proteins transported by EVs that are associated with metastasis and which may potentially serve as prognostic markers in OSCC.

Proteomic approaches to assist in diagnosis and prognosis of oral cancer.

Introduction: Oral squamous cell carcinoma (OSCC) ranks among the top 10 leading causes of cancer worldwide, with 5-year survival rate of about 50%, high lymph node metastasis, and relapse rates. The OSCC diagnosis, prognosis, and treatment are mostly based on the clinical TNM classification. There is an urgent need for the discovery of biomarkers and therapeutic targets to assist in the clinical decision-making process.Areas covered: We summarize proteomic studies of the OSCC tumor, immune microenvironment, potential liquid biopsy sites, and post-translational modifications trying to retrieve information in the discovery and verification or (pre)validation phases. The search strategy was based on the combination of MeSH terms and expert refinement.Expert opinion: Untargeted combined with targeted proteomics are strategies that provide reliable and reproducible quantitation of proteins and are the methods of choice of many groups worldwide. Undoubtedly, proteomics has been contributing to the understanding of OSCC progression and uncovers potential candidates as biomarker or therapeutic targets. Nevertheless, none of these targets are available in the clinical practice yet. The scientific community needs to overcome the limitations by investing in robust experimental designs to strengthen the value of the findings, leveraging the translation of knowledge, and further supporting clinical decisions.

Follistatin-related protein 1 interacting partner of Syndecan-1 promotes an aggressive phenotype on Oral Squamous cell carcinoma (OSCC) models.

Syndecans belong to the family of transmembrane heparan sulfate proteoglycans and are associated with many physiopathological processes, including oral cancer. As previously shown soluble syndecan-1 (SDC1) fragments and synthetic SDC1 peptide were able to induce cell migration in oral cancer cell lines. In order to explore the role of SDC1 in oral cancer, we have investigated SDC1 interacting partners and its functional role in oral cancer models. Here we have shown that SDC1 interacts with follistatin-related protein 1 (FSTL1) by its ectodomain (ectoSDC1) and extracellular juxtamembrane peptide (pepSDC1) and that their transcript levels can affect tumor events. Using orthotopic mouse model we identified that the knock-down for FSTL1 (shFSTL1) or for both FSTL1 and SDC1 (sh2KD) produced less aggressive and infiltrative tumors, with lower keratinization deposition, but with increased levels of epithelial-mesenchymal transition and proliferation compared to control and SDC1 knock-down. Based on cell culture assays, we suggest that the shFSTL1 effect on tumor tissues might be from significant increase of mRNA levels of Activin A (ActA) and its resceptors. This study shows for the first time two different complexes, SDC1 and FSTL1; pepSDC1 and FSTL1, exhibiting a close relationship in cell signaling events, as FSTL1 promotes a more aggressive phenotype. SIGNIFICANCE: This work contributes to the understanding of new SDC1 functions, based on the investigation of protein-protein complex formation in Oral Squamous cell carcinoma (OSCC) models. The FSTL1 identification, as an interacting partner of SDC1 ectodomain and of its derived peptide promotes molecular events that favors cancer development and progression, as highlighted by Activin A (ActA) and Epithelial-mesenchymal transition (EMT) gene expression and by changes in the phenotype of orthotopic OSCC mouse tumor tissues when SDC1-FSTL1 expression is modulated.

Comparative proteomic analysis of Xanthomonas citri ssp. citri periplasmic proteins reveals changes in cellular envelope metabolism during in vitro pathogenicity induction.

Citrus canker is a plant disease caused by Gram-negative bacteria from the genus Xanthomonas. The most virulent species is Xanthomonas citri ssp. citri (XAC), which attacks a wide range of citrus hosts. Differential proteomic analysis of the periplasm-enriched fraction was performed for XAC cells grown in pathogenicity-inducing (XAM-M) and pathogenicity-non-inducing (nutrient broth) media using two-dimensional electrophoresis combined with liquid chromatography-tandem mass spectrometry. Amongst the 40 proteins identified, transglycosylase was detected in a highly abundant spot in XAC cells grown under inducing condition. Additional up-regulated proteins related to cellular envelope metabolism included glucose-1-phosphate thymidylyltransferase, dTDP-4-dehydrorhamnose-3,5-epimerase and peptidyl-prolyl cis-trans-isomerase. Phosphoglucomutase and superoxide dismutase proteins, known to be involved in pathogenicity in other Xanthomonas species or organisms, were also detected. Western blot and quantitative real-time polymerase chain reaction analyses for transglycosylase and superoxide dismutase confirmed that these proteins were up-regulated under inducing condition, consistent with the proteomic results. Multiple spots for the 60-kDa chaperonin and glyceraldehyde-3-phosphate dehydrogenase were identified, suggesting the presence of post-translational modifications. We propose that substantial alterations in cellular envelope metabolism occur during the XAC infectious process, which are related to several aspects, from defence against reactive oxygen species to exopolysaccharide synthesis. Our results provide new candidates for virulence-related proteins, whose abundance correlates with the induction of pathogenicity and virulence genes, such as hrpD6, hrpG, hrpB7, hpa1 and hrpX. The results present new potential targets against XAC to be investigated in further functional studies.

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer.

Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor-node-metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.

Xanthomonas citri subsp. citri surface proteome by 2D-DIGE: Ferric enterobactin receptor and other outer membrane proteins potentially involved in citric host interaction.

Xanthomonas citri subsp. citri (XAC) is the causative agent of citrus canker, a disease of great economic impact around the world. Understanding the role of proteins on XAC cellular surface can provide new insights on pathogen-plant interaction. Surface proteome was performed in XAC grown in vivo (infectious) and in vitro (non-infectious) conditions, by labeling intact cells followed by cellular lysis and direct 2D-DIGE analysis. Seventy-nine differential spots were analyzed by mass spectrometry. Highest relative abundance for in vivo condition was observed for spots containing DnaK protein, 60kDa chaperonin, conserved hypothetical proteins, malate dehydrogenase, phosphomannose isomerase, and ferric enterobactin receptors. Elongation factor Tu, OmpA-related proteins, Oar proteins and some Ton-B dependent receptors were found in spots decreased in vivo. Some proteins identified on XAC's surface in infectious condition and predicted to be cytoplasmic, such as DnaK and 60KDa chaperonin, have also been previously found at cellular surface in other microorganisms. This is the first study on XAC surface proteome and results point to mediation of molecular chaperones in XAC-citrus interaction. The approach utilized here can be applied to other pathogen-host interaction systems and help to achieve new insights in bacterial pathogenicity toward promising targets of biotechnological interest. BIOLOGICAL SIGNIFICANCE: This research provides new insights for current knowledge of the Xanthomonas sp. pathogenicity. For the first time the 2D-DIGE approach was applied on intact cells to find surface proteins involved in the pathogen-plant interaction. Results point to the involvement of new surface/outer membrane proteins in the interaction between XAC and its citrus host and can provide potential targets of biotechnological interest for citrus canker control.

Machine learning-driven serum metabolomics: insights into the transition to early-stage heart failure with preserved ejection fraction

Introduction: Metabolomics has emerged as a powerful tool in providing readouts of early disease states before clinical manifestation. Here we used the predictive power of Unsupervised Hierarchical Clustering Analysis (UHCA) and Automated Machine Learning (AutoML) algorithms to identify serum metabolic panels in a population at risk of developing HFpEF. Methods: We studied 215 subjects staged as non-HF, pre-HFpEF and early-stage HFpEF(es-HFpEF). We evaluated clinical, laboratory, echocardiographic, and NMR-based metabolomics of blood serum data. UHCA and AutoML were used to explore metabolic fingerprints potentially related to clinical features or HFpEF. We used Metabolite Set Enrichment Analysis to explore biochemical pathways. Results: The UHCA identified three major patients (P) and two metabolites (M) clusters (Figure). The P clusters were associated with HFpEF stages, cardiac remodeling, diastolic dysfunction, and sex (Pearson Chi-square, p < 0.05) and M clusters with glycine and serine metabolism and urea cycle pathways (FDR-adjusted p-value < 0.002). Considering non-HFpEF and es-HFpEF groups, AUROC mean for feature subset combinations was 0.897 and the highest AUROC (0.995) combined metabolites, clinical, laboratory and echo features. Of the 64 models trained that included metabolites as input, serine (25), uridine (17), 2-oxoglutarate (14), citrate (14), 2-aminobutyrate (13) and taurine (13) were observed more frequently with feature importance value greater than zero. The metabolites with higher sum values of feature importance were serine (0.173), uridine (0.131), 2-aminobutyrate (0.123), choline (0.098) and dimethylamine (0.087). Conclusions: This study revealed characteristic metabolite profiles in the sera of patients at risk of developing HFpEF. These metabolite panels can add information for classificatory algorithms development and contribute to the understanding of HFpEF pathophysiology.

Interaction network and mass spectrometry data of Xanthomonas citri subsp. citri surface proteins from differential proteomic analysis of infectious and non-infectious cells.

Here we provide the mass-spectrometry and in silico interaction network dataset of proteins identified on our research article on surface proteomic analysis from Xanthomonas citri subsp. citri (XAC) cells grown in vivo (infectious) and in vitro (non-infectious, control) by 2D-DIGE approach. Fluorescence labeling of proteins were performed on intact cells followed by cellular lysis and labeled spots from 2D gel differing in abundance between the two conditions (ANOVA, p-value<0.05) were analyzed by a nano-electrospray tandem mass spectrometry Q-Tof Ultima API mass spectrometer (MicroMass/Waters) (LC-ESI-MS/MS). This article contains raw data of proteins detected in the 79 spots analyzed by LC-ESI-MS/MS approach and also an enrichment analysis on the resulting protein-protein interaction network performed with the Integrated Interactome System (IIS) platform and Cytoscape software. The data are supplementary to our original research article, "Xanthomonas citri subsp. citri surface proteome by 2D-DIGE: ferric enterobactin receptor and other outer membrane proteins potentially involved in citric host interaction" (Carnielli et al., 2016) [1], and raw data are available via Peptide Atlas (ftp://PASS00850:ZJ7425v@ftp.peptideatlas.org/).