Oral squamous cell carcinoma (OSCC) is one of the most frequent types of head and neck cancer. Despite the genetic and environmental risk factors, OSCC is also associated with microbial infections and/or dysbiosis. The secreted saliva serves as the chemical barrier of the oral cavity and, since OSCC can alter the protein composition of saliva, our aim was to analyze the effect of OSCC on the salivary chemical barrier proteins. Publicly available datasets regarding the analysis of salivary proteins from patients with OSCC and controls were collected and examined in order to identify differentially expressed chemical barrier proteins. Network analysis and gene ontology (GO) classification of the differentially expressed chemical barrier proteins were performed as well. One hundred and twenty-seven proteins showing different expression pattern between the OSCC and control groups were found. Protein–protein interaction networks of up- and down-regulated proteins were constructed and analyzed. The main hub proteins (IL-6, IL-1B, IL-8, TNF, APOA1, APOA2, APOB, APOC3, APOE, and HP) were identified and the enriched GO terms were examined. Our study highlighted the importance of the chemical barrier of saliva in the development of OSCC.

Background: Obesity is a major risk factor for type 2 diabetes (T2D); however, the molecular links between these conditions are not fully understood. Methods: We performed an integrative serum proteomics study on samples from 134 individuals (healthy controls, patients with obesity and/or T2D) using both data-independent (DIA) and data-dependent (DDA) liquid chromatography-mass spectrometry approaches, complemented by phosphopeptide enrichment, kinase activity prediction, network and pathway analyses to get more information on the different proteoforms involved in the pathophysiology of the diseases. Results: We identified 235 serum proteins, including 13 differentially abundant proteins (DAPs) between groups. Both obesity and T2D were characterized by activation of complement and coagulation cascades, as well as alterations in lipid metabolism. Ingenuity Pathway Analysis^® (IPA) revealed shared canonical pathways, while phosphorylation-based regulation differentiated the two conditions. Elevated hemopexin (HPX), vitronectin (VTN), kininogen-1 (KNG1) and pigment epithelium-derived factor (SERPINF1), along with decreased adiponectin (ADIPOQ) and apolipoprotein D (APOD), indicated a pro-inflammatory, pro-coagulant serum profile. Network analyses of antimicrobial and immunomodulatory peptides (AMPs) revealed strong overlaps between immune regulation and lipid metabolism. Phosphoproteomics and kinase prediction highlighted altered CK2 and AGC kinase activities in obesity, suggesting signaling-level modulation. Conclusions: Our comprehensive proteomic and phosphoproteomic profiling reveals overlapping yet distinct molecular signatures in obesity and T2D, emphasizing inflammation, complement activation and phosphorylation-driven signaling as central mechanisms that potentially contribute to disease progression and therapeutic targeting.