Deregulation of desmosomal proteins and extracellular matrix proteases in odontogenic keratocyst.

OBJECTIVE: Odontogenic keratocyst (OKC) is a benign lesion that tends to recur after surgical treatment. In an attempt to clarify the molecular basis underlining the OKC pathobiology, we aimed to analyze its proteomic profile. MATERIALS AND METHODS: We compared the proteomic profiles of five OKC and matched normal oral mucosa by using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Then, we performed enrichment analysis and a literature search for the immunoexpression of the proteomics targets. RESULTS: We identified 1,150 proteins and 72 differently expressed proteins (log2 fold change ≥ 1.5; p < .05). Twenty-seven peptides were exclusively detected in the OKC samples. We found 35 enriched pathways related to cell differentiation and tissue architecture, including keratinocyte differentiation, keratinization, desmosome, and extracellular matrix (ECM) organization and degradation. The immunoexpression information of 11 out of 50 proteins identified in the enriched pathways was obtained. We found the downregulation of four desmosomal proteins (JUP, PKP1, PKP3, and PPL) and upregulation of ECM proteases (MMP-2, MMP-9, and cathepsins). CONCLUSIONS: Proteomic analysis strengthened the notion that OKC cells have a similar proteomic profile to oral keratinocytes. Contextual investigation of the differentially expressed proteins revealed the deregulation of desmosome proteins and ECM degradation as important alterations in OKC pathobiology.

PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries.

BACKGROUND: Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation. RESULTS: To help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer. CONCLUSIONS: PESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador/