Mapping Conformational Changes in the Saliva Proteome Potentially Associated with Oral Cancer Aggressiveness.

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these targets may be regulated by events that do not imply variation in protein abundance levels, we hypothesized that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients with and without lymph node metastasis. Thirty-six proteins with potential structural rearrangements were associated with clinical patient features including transketolase and its interacting partners. Moreover, N-glycosylated peptides contribute to structural rearrangements of potential diagnostic and prognostic markers. Altogether, this approach utilizes saliva proteins to search for targets for diagnosing and prognosing oral cancer and can guide the discovery of potential regulated sites beyond protein-level abundance.

Proteomics of serum-derived extracellular vesicles are associated with the severity and different clinical profiles of patients with COVID-19: An exploratory secondary analysis.

BACKGROUND AIMS: Coronavirus disease 2019 (COVID-19) is characterized by a broad spectrum of clinical manifestations with the potential to progress to multiple organ dysfunction in severe cases. Extracellular vesicles (EVs) carry a range of biological cargoes, which may be used as biomarkers of disease state. METHODS: An exploratory secondary analysis of the SARITA-2 and SARITA-1 datasets (randomized clinical trials on patients with mild and moderate/severe COVID-19) was performed. Serum-derived EVs were used for proteomic analysis to identify enriched biological processes and key proteins, thus providing insights into differences in disease severity. Serum-derived EVs were separated from patients with COVID-19 by size exclusion chromatography and nanoparticle tracking analysis was used to determine particle concentration and diameter. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was performed to identify and quantify protein signatures. Bioinformatics and multivariate statistical analysis were applied to distinguish candidate proteins associated with disease severity (mild versus moderate/severe COVID-19). RESULTS: No differences were observed in terms of the concentration and diameter of enriched EVs between mild (n = 14) and moderate/severe (n = 30) COVID-19. A total of 414 proteins were found to be present in EVs, of which 360 were shared while 48 were uniquely present in severe/moderate compared to mild COVID-19. The main biological signatures in moderate/severe COVID-19 were associated with platelet degranulation, exocytosis, complement activation, immune effector activation, and humoral immune response. Von Willebrand factor, serum amyloid A-2 protein, histone H4 and H2A type 2-C, and fibrinogen ß-chain were the most differentially expressed proteins between severity groups. CONCLUSION: Exploratory proteomic analysis of serum-derived EVs from patients with COVID-19 detected key proteins related to immune response and activation of coagulation and complement pathways, which are associated with disease severity. Our data suggest that EV proteins may be relevant biomarkers of disease state and prognosis.

Extracellular vesicles in carcinoma microenvironment.

Cancer is a significant cause of death, precluding increasing life expectancy worldwide. That is a multifactorial disease initiated by intrinsic or extrinsic factors that induce cell differentiation into cancer cells. However, cancer development, progression, and metastasis are not controlled only by cancer cells. The entire environment around these cells, named tumor microenvironment (TME), influences tumor development and spread. The tumor microenvironment is formed by cancer cells and heterogenous nonmalignant cells integrated with a complex extracellular matrix. The main cellular components of the TME are cancer-associated fibroblasts (CAFs), T lymphocytes, B cells, tumor-associated macrophages (TAMs), dendritic cells (DC), natural killer (NK) cells, tumor-associated neutrophils (TANs), Stem Cells, Endothelial Cells and their soluble secreted extracellular vesicles (EVs) that modulate cancer cells to establish and disseminate. This review provides a recent insight into the role of EVs secreted from different populations of the TME associated with the initiation and progression of carcinoma.

Typic: A Practical and Robust Tool to Rank Proteotypic Peptides for Targeted Proteomics.

The selection of a suitable proteotypic peptide remains a challenge for designing a targeted quantitative proteomics assay. Although the criteria are well-established in the literature, the selection of these peptides is often performed in a subjective and time-consuming manner. Here, we have developed a practical and semiautomated workflow implemented in an open-source program named Typic. Typic is designed to run in a command line and a graphical interface to help selecting a list of proteotypic peptides for targeted quantitation. The tool combines the input data and downloads additional data from public repositories to produce a file per protein as output. Each output file includes relevant information to the selection of proteotypic peptides organized in a table, a colored ranking of peptides according to their potential value as targets for quantitation and auxiliary plots to assist users in the task of proteotypic peptides selection. Taken together, Typic leads to a practical and straightforward data extraction from multiple data sets, allowing the identification of most suitable proteotypic peptides based on established criteria, in an unbiased and standardized manner, ultimately leading to a more robust targeted proteomics assay.

Connecting multiple microenvironment proteomes uncovers the biology in head and neck cancer.

The poor prognosis of head and neck cancer (HNC) is associated with metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision-making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identify nodal metastasis signatures in blood and saliva. We present a proteomic characterization wiring multiple sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures.

Epigenetic alterations in salivary gland tumors.

Salivary gland tumors (SGTs) comprise a heterogeneous group of benign and malignant neoplasms that exhibit significant variability in their microscopic appearance, clinical presentation, and biological behavior. The etiologic factors are unknown; however, chromosomic translocation, secondary radiation, and chemotherapy can be associated with the development of SGT. It has been indicated that epigenetic alterations can be responsible for the development and progress of these neoplasms. The epigenetic mechanisms are defined as a set of DNA changes that do not alter the sequence of nucleotide bases but alter the expression of the proteins. These alterations have been studied in the SGT, and they were associated with the development and progress of these neoplasms and may influence on SGT prognosis. Hence, we critically review the currently available data on the participation of epigenetic events on salivary gland tumors.