Proteomics and Proteogenomics Approaches for Oral Diseases

Association between an Anti-Inflammatory Dietary Score and Periodontitis-Evidence from the Population-Based Hamburg City Health Study

While the effects of dietary patterns on cardiovascular risk and diabetes have been well studied, the evidence is scarce as to which diet has the greatest anti-inflammatory potential and how dietary patterns are associated with periodontitis. In the Hamburg City Health Study (HCHS), we developed an anti-inflammatory dietary score using a data-driven approach based on the relationship of relevant selected food groups with inflammatory biomarkers (hsCRP and IL-6). The aim of this cross-sectional study was to evaluate the association between the anti-inflammatory dietary score and the incidence of periodontitis in Hamburg, Germany. A total of n = 5642 participants fit the required inclusion criteria and were selected for analysis. Periodontal disease was assessed using probing depth, gingival recession, and bleeding on probing. Dietary intake was measured using a food frequency questionnaire (FFQ). A self-developed anti-inflammatory dietary score served as the key explanatory variable. Higher scores reflected lower inflammatory processes (measured through the biomarkers hsCRP and IL-6). Several covariates were included in the regression analysis. Regressions revealed that a higher anti-inflammatory dietary score was significantly associated with lower odds to be affected by periodontal disease in an unadjusted model (OR 0.86, 95% CI 0.82-0.89, p < 0.001) and in an adjusted model (age, sex, smoking, diabetes, hypertension, and physical activity) (OR 0.93, 95% CI 0.89-0.98, p = 0.003). Our study demonstrated a significant inverse association between an anti-inflammatory dietary score and periodontitis. Individuals with higher intake of proinflammatory nutrition should be specifically addressed to avoid periodontitis.

Identification of potential biomarkers and analysis of prognostic values in head and neck squamous cell carcinoma by bioinformatics analysis

The purpose of this study was to find disease-associated genes and potential mechanisms in head and neck squamous cell carcinoma (HNSCC) with deoxyribonucleic acid microarrays. The gene expression profiles of GSE6791 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were obtained with packages in R language and STRING constructed protein–protein interaction (PPI) network of the DEGs with combined score >0.8. Subsequently, module analysis of the PPI network was performed by Molecular Complex Detection plugin and functions and pathways of the hub gene in subnetwork were studied. Finally, overall survival analysis of hub genes was verified in TCGA HNSCC cohort. A total of 811 DEGs were obtained, which were mainly enriched in the terms related to extracellular matrix (ECM)–receptor interaction, ECM structural constituent, and ECM organization. A PPI network was constructed, consisting of 401 nodes and 1,254 edges and 15 hub genes with high degrees in the network. High expression of 4 genes of the 15 genes was associated with poor OS of patients in HNSCC, including PSMA7, ITGA6, ITGB4, and APP. Two significant modules were detected from the PPI network, and the enriched functions and pathways included proteasome, ECM organization, and ECM–receptor interaction. In conclusion, we propose that PSMA7, ITGA6, ITGB4, and APP may be further explored as potential biomarkers to aid HNSCC diagnosis and treatment.

Proteogenomic studies on cancer drug resistance: towards biomarker discovery and target identification

INTRODUCTION

Chemoresistance is a major obstacle for current cancer treatment. Proteogenomics is a powerful multi-omics research field that uses customized protein sequence databases generated by genomic and transcriptomic information to identify novel genes (e.g. noncoding, mutation and fusion genes) from mass spectrometry-based proteomic data. By identifying aberrations that are differentially expressed between tumor and normal pairs, this approach can also be applied to validate protein variants in cancer, which may reveal the response to drug treatment. Areas covered: In this review, we will present recent advances in proteogenomic investigations of cancer drug resistance with an emphasis on integrative proteogenomic pipelines and the biomarker discovery which contributes to achieving the goal of using precision/personalized medicine for cancer treatment. Expert commentary: The discovery and comprehensive understanding of potential biomarkers help identify the cohort of patients who may benefit from particular treatments, and will assist real-time clinical decision-making to maximize therapeutic efficacy and minimize adverse effects. With the development of MS-based proteomics and NGS-based sequencing, a growing number of proteogenomic tools are being developed specifically to investigate cancer drug resistance.

Identification of potential therapeutic target genes, key miRNAs and mechanisms in oral lichen planus by bioinformatics analysis

The study aimed to identify the potential target genes and key miRNAs as well as to explore the underlying mechanisms in the pathogenesis of oral lichen planus (OLP) by bioinformatics analysis. The microarray data of GSE38617 were downloaded from Gene Expression Omnibus (GEO) database. A total of 7 OLP and 7 normal samples were used to identify the differentially expressed genes (DEGs) and miRNAs. The DEGs were then performed functional enrichment analyses. Furthermore, DEG-miRNA network and miRNA-function network were constructed by Cytoscape software. Total 1758 DEGs (598 up- and 1160 down-regulated genes) and 40 miRNAs (17 up- and 23 down-regulated miRNAs) were selected. The up-regulated genes were related to nuclear factor-Kappa B (NF-κB) signaling pathway, while down-regulated genes were mainly enriched in the function of ribosome. Tumor necrosis factor (TNF), caspase recruitment domain family, member 11 (CARD11) and mitochondrial ribosomal protein (MRP) genes were identified in these functions. In addition, miR-302 was a hub node in DEG-miRNA network and regulated cyclin D1 (CCND1). MiR-548a-2 was the key miRNA in miRNA-function network by regulating multiple functions including ribosomal function. The NF-κB signaling pathway and ribosome function may be the pathogenic mechanisms of OLP. The genes such as TNF, CARD11, MRP genes and CCND1 may be potential therapeutic target genes in OLP. MiR-548a-2 and miR-302 may play important roles in OLP development.

Quartz-Crystal Microbalance (QCM) for Public Health: An Overview of Its Applications

Nanobiotechnologies, from the convergence of nanotechnology and molecular biology and postgenomics medicine, play a major role in the field of public health. This overview summarizes the potentiality of piezoelectric sensors, and in particular, of quartz-crystal microbalance (QCM), a physical nanogram-sensitive device. QCM enables the rapid, real time, on-site detection of pathogens with an enormous burden in public health, such as influenza and other respiratory viruses, hepatitis B virus (HBV), and drug-resistant bacteria, among others. Further, it allows to detect food allergens, food-borne pathogens, such as Escherichia coli and Salmonella typhimurium, and food chemical contaminants, as well as water-borne microorganisms and environmental contaminants. Moreover, QCM holds promises in early cancer detection and screening of new antiblastic drugs. Applications for monitoring biohazards, for assuring homeland security, and preventing bioterrorism are also discussed.

Quantitative and Systems-Based Approaches for Deciphering Bacterial Membrane Interactome and Gene Function

High-throughput genomic and proteomic methods provide a concise description of the molecular constituents of a cell, whereas systems biology strives to understand the way these components function as a whole. Recent developments, such as genome editing technologies and protein epitope-tagging coupled with high-sensitivity mass-spectrometry, allow systemic studies to be performed at an unprecedented scale. Available methods can be successfully applied to various goals, both expanding fundamental knowledge and solving applied problems. In this review, we discuss the present state and future of bacterial cell envelope interactomics, with a specific focus on host-pathogen interactions and drug target discovery. Both experimental and computational methods will be outlined together with examples of their practical implementation.

A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases

OBJECTIVE

In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network.

METHODS

The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes.

RESULTS

Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved.

CONCLUSIONS

Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database.

CLINICAL RELEVANCE

The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.