Hereditary diffuse gastric cancer therapeutic roadmap: current and novel approaches in a nutshell.

Hereditary diffuse gastric cancer (HDGC) is a rare malignancy characterized by autosomal dominant inheritance of pathological variants of the CDH1 gene encoding E-cadherin, which is involved in cell-cell adhesion, maintenance of epithelial architecture, tumor suppression, and regulation of intracellular signaling pathways. Late-stage recognition of HDGC is typically associated with a poor clinical outcome due to its metastatic potential and risk of lobular breast cancer (LBC) development. The American College of Gastroenterology issued guidelines to evaluate HDGC, test for CDH1 genetic variants, and recommend prophylactic gastrectomy for carriers of CDH1 mutations. If surgery is not pursued, endoscopy is a surveillance alternative, although it carries a limited ability to detect malignant foci. As part of clinical research efforts, novel endoscopy advances are currently studied, and a center of excellence for HDGC was created for a comprehensive multidisciplinary team approach. Within this review, we cover current conventional treatment modalities such as gastrectomy and chemotherapy, as the mainstay treatments, in addition to Pembrolizumab, an immune checkpoint inhibitor, as the last therapeutic resort. We also shed light on novel and promising approaches with emphasis on immunotherapy to treat HDGC. We further break down the therapeutic paradigms to utilize molecular tools, antibodies against checkpoint inhibitors, TGF-ß and tyrosine kinase inhibitors, cell-based adoptive therapies, and oncolytic viral therapies. We aim to expand the understanding on how to modulate the tumor microenvironment to tip the balance towards an anti-tumor phenotype, prevent metastasis of the primary disease, and potentially alter the therapeutic landscape for HDGC.

ePath: an online database towards comprehensive essential gene annotation for prokaryotes.

Experimental techniques for identification of essential genes (EGs) in prokaryotes are usually expensive, time-consuming and sometimes unrealistic. Emerging in silico methods provide alternative methods for EG prediction, but often possess limitations including heavy computational requirements and lack of biological explanation. Here we propose a new computational algorithm for EG prediction in prokaryotes with an online database (ePath) for quick access to the EG prediction results of over 4,000 prokaryotes ( https://www.pubapps.vcu.edu/epath/ ). In ePath, gene essentiality is linked to biological functions annotated by KEGG Ortholog (KO). Two new scoring systems, namely, E_score and P_score, are proposed for each KO as the EG evaluation criteria. E_score represents appearance and essentiality of a given KO in existing experimental results of gene essentiality, while P_score denotes gene essentiality based on the principle that a gene is essential if it plays a role in genetic information processing, cell envelope maintenance or energy production. The new EG prediction algorithm shows prediction accuracy ranging from 75% to 91% based on validation from five new experimental studies on EG identification. Our overall goal with ePath is to provide a comprehensive and reliable reference for gene essentiality annotation, facilitating the study of those prokaryotes without experimentally derived gene essentiality information.

Bioinformatics Workflow for Gonococcal Proteomics.

High-throughput quantitative proteomics unravels secrets of Neisseria gonorrhoeae biology by profiling proteome responses to environmental and endogenous cues and opens translational research paths through identification of vaccine candidates, drug targets/virulence factors, and biomarkers. Bioinformatics tools and databases are indispensable for downstream analysis of proteomic datasets to generate biologically meaningful outcomes. In this chapter, we present a workflow for proteomic data analysis with emphasis on publicly available resources, software systems, and tools that predict protein subcellular localization (CELLO, PSORTb v3.0, SOSUI-GramN, SignalP 4.1, LipoP 1.0, TMHMM 2.0) and functional annotation (EggNOG-mapper 4.5.1., DAVID v6.8, and KEGG) of N. gonorrhoeae proteins. This computational step-by-step procedure may help to foster new hypotheses and to provide insights into the structure-function relationship of proteins.

Quantitative Proteomics of the 2016 WHO Neisseria gonorrhoeae Reference Strains Surveys Vaccine Candidates and Antimicrobial Resistance Determinants.

The sexually transmitted disease gonorrhea (causative agent: Neisseria gonorrhoeae) remains an urgent public health threat globally because of its reproductive health repercussions, high incidence, widespread antimicrobial resistance (AMR), and absence of a vaccine. To mine gonorrhea antigens and enhance our understanding of gonococcal AMR at the proteome level, we performed the first large-scale proteomic profiling of a diverse panel (n = 15) of gonococcal strains, including the 2016 World Health Organization (WHO) reference strains. These strains show all existing AMR profiles - established through phenotypic characterization and reference genome publication - and are intended for quality assurance in laboratory investigations. Herein, these isolates were subjected to subcellular fractionation and labeling with tandem mass tags coupled to mass spectrometry and multi-combinatorial bioinformatics. Our analyses detected 904 and 723 common proteins in cell envelope and cytoplasmic subproteomes, respectively. We identified nine novel gonorrhea vaccine candidates. Expression and conservation of new and previously selected antigens were investigated. In addition, established gonococcal AMR determinants were evaluated for the first time using quantitative proteomics. Six new proteins, WHO_F_00238, WHO_F_00635c, WHO_F_00745, WHO_F_01139, WHO_F_01144c, and WHO_F_01126, were differentially expressed in all strains, suggesting that they represent global proteomic AMR markers, indicate a predisposition toward developing or compensating gonococcal AMR, and/or act as new antimicrobial targets. Finally, phenotypic clustering based on the isolates' defined antibiograms and common differentially expressed proteins yielded seven matching clusters between established and proteome-derived AMR signatures. Together, our investigations provide a reference proteomics data bank for gonococcal vaccine and AMR research endeavors, which enables microbiological, clinical, or epidemiological projects and enhances the utility of the WHO reference strains.

Identification and antibacterial resistance of bacteria isolated from poultry.

Food-borne infections are among the prominent health hazards. Antibacterial agents (ABA) are usually administered to poultry in Lebanon as antibiotic growth promoters (AGP), which might lead to the dissemination of resistant bacterial strains. The aims of this study were to isolate potential food borne pathogens from poultry and investigate an association between AGP usage and antibacterial resistance (ABR). Isolates were obtained from the culture of cloacae swabs and identified. Escherichia coli was the predominant isolate. There was a significant association between the use of tetracycline and gentamicin as AGP and the number of E. coli isolates resistant to these ABA.