The molecular mechanisms associated with PIN7, a protein-protein interaction network of seven pleiotropic proteins

Screening and identification of potential biomarkers and therapeutic targets for systemic sclerosis-associated interstitial lung disease

Objectives

This study aims to analyze gene expression in lung tissue and lung fibroblasts of patients with systemic sclerosis-associated interstitial lung disease (SSc-ILD) to identify potential biomarkers and therapeutic targets and to examine its possible role in the pathogenesis of SSc-ILD.

Patients and methods

We obtained datasets from Gene Expression Omnibus (GEO) database, and used Robust Rank Aggregation to calculate the co-expressed differentially-expressed-genes (DEGs) in three chips, then analyzed the function, signaling pathways and the protein-protein interaction network of the DEGs. Finally, we verified the DEGs related to SSc-ILD by three databases of Comparative Toxicogenomics Database (CTD), GENE, and DisGeNET, respectively.

Results

There were 16 co-expressed DEGs related to SSc-ILD in three GEO series, of which six genes were upregulated, and 10 genes were downregulated. The CTD included 29,936 genes related to SSc, and the GENE and DisGeNET databases had 429 genes related to SSc.

Conclusion

The results of gene differential expression analysis suggest that interleukin-6, chemokine ligand 2, intercellular adhesion molecule 1, tumor necrosis factor alpha-induced protein 3, pentraxin 3, and cartilage oligomeric matrix protein may be implicated in the pathogenesis of SSc-ILD and are expected to be potential biomarkers and therapeutic targets for SSc-ILD.

Finding New Ways How to Control BACE1

Recently, all applications of BACE1 inhibitors failed as therapeutical targets for Alzheimer´s disease (AD) due to severe side effects. Therefore, alternative ways for treatment development are a hot research topic. The present analysis investigates BACE1 protein-protein interaction networks and attempts to solve the absence of complete knowledge about pathways involving BACE1. A bioinformatics analysis matched the functions of the non-substrate interaction network with Voltage-gated potassium channels, which also appear as top priority protein nodes. Targeting BACE1 interactions with PS1 and GGA-s, blocking of BACE1 access to APP by BRI3 and RTN-s, activation of Wnt signaling and upregulation of β-catenin, and brain delivery of the extracellular domain of p75^NTR, are the main alternatives to the use of BACE 1 inhibitors highlighted by the analysis. The pathway enrichment analysis also emphasized substrates and substrate candidates with essential biological functions, which cleavage must remain controlled. They include ephrin receptors, ROBO1, ROBO2, CNTN-s, CASPR-s, CD147, CypB, TTR, APLP1/APLP2, NRXN-s, and PTPR-s. The analysis of the interaction subnetwork of BACE1 functionally related to inflammation identified a connection to three cardiomyopathies, which supports the hypothesis of the common molecular mechanisms with AD. A lot of potential shows the regulation of BACE1 activity through post-translational modifications. The interaction network of BACE1 and its phosphorylation enzyme CSNK1D functionally match the Circadian clock, p53, and Hedgehog signaling pathways. The regulation of BACE1 glycosylation could be achieved through N-acetylglucosamine transferases, α-(1→6)-fucosyltransferase, β-galactoside α-(2→6)-sialyltransferases, galactosyltransferases, and mannosidases suggested by the interaction network analysis of BACE1-MGAT3. The present analysis proposes possibilities for the alternative control of AD pathology.

Lymphoid Organ Proteomes Identify Therapeutic Efficacy Biomarkers Following the Intracavitary Administration of Curcumin in a Highly Invasive Rat Model of Peritoneal Mesothelioma

This study aimed to identify the proteomic changes produced by curcumin treatment following stimulation of the host immune system in a rat model of malignant mesothelioma. We analyzed the proteomes of secondary lymphoid organs from four normal rats, four untreated tumor-bearing rats, and four tumor-bearing rats receiving repeated intraperitoneal administrations of curcumin. Cross-comparing proteome analyses of histological sections of the spleen from the three groups first identified a list of eighty-three biomarkers of interest, thirteen of which corresponded to proteins already reported in the literature and involved in the anticancer therapeutic effects of curcumin. In a second step, comparing these data with proteomic analyses of histological sections of mesenteric lymph nodes revealed eight common biomarkers showing a similar pattern of changes in both lymphoid organs. Additional findings included a partial reduction of the increase in spleen-circulating biomarkers, a decrease in C-reactive protein and complement C3 in the spleen and lymph nodes, and an increase in lymph node purine nucleoside phosphorylase previously associated with liver immunodeficiency. Our results suggest some protein abundance changes could be related to the systemic, distant non-target antitumor effects produced by this phytochemical.

Linking TPPII to the protein interaction and signalling networks

Tripeptidyl peptidase II (TPPII) is primarily considered a house-keeping exopeptidase, which contributes to the functions of the ubiquitin-proteasome system by the maintenance of the cellular amino acid homeostasis. Although functionally well-characterised in vitro and using the mammalian cell models, less is known about the molecular mechanisms of its involvement in the signalling and metabolic pathways, which mediate its cellular functions. The present protein-protein interaction network analysis identified these mechanisms involved in the adaptive and innate immunity, the metabolism of the glucose, cancer cell growth, apoptosis, cell cycle and DNA damage responses. The interaction network constructed based on the publicly available protein-protein interaction data was extended by the application GeneMania, which was further used for the pathway enrichment, the protein function prediction and the protein node prioritisation analysis. The analysis suggested that the molecular mechanisms linked to the adaptive and innate immunity (ID, Kit receptor, BCR, IL-2 and G-CSF signalling; the regulation of NFκB), the aerobic glycolysis (ID and IL-2 signalling), tumorigenesis (TGF-β and p53 signalling; the top priority nodes MAPKs, mTOR regulation), diabetes (Kit receptor signalling; the top priority node GSK3β) and neurodegeneration (the control of mTOR and Aβ peptide degradation) are controlling the resulting TPPII interaction network. The uncharacterized interactions with two lung cancer suppressors (DOK3, DENND2D), a protein involved in the increased risk of the lung cancer in smokers (CYP1A1) and a protein implicated in asthmatic reactions (CHIA) suggest potential roles of TPPII in the lung cancer pathology. The interactions with methyltransferase CARNMT1, which modifies di- and tripeptides and the xenobiotic processing enzyme CYP1A1, are additional candidates for the breakthrough in new functions discovery of TPPII.