Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis.

AIM: Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgently needed. METHODS: GSE54129 and GSE26942 datasets were downloaded from Gene Expression Omnibus (GEO) database to detect differentially expressed genes (DEGs). Then, gene set enrichment analyses and protein-protein interactions were investigated. Afterward, ten hub genes were identified from the constructed network of DEGs. Then, the expression of hub genes in GC was validated. Performing survival analysis, the prognostic value of each hub gene in GC samples was investigated. Finally, the databases were used to predict microRNAs that could regulate the hub genes. Eventually, top miRNAs with more interactions with the list of hub genes were introduced. RESULTS: In total, 203 overlapping DEGs were identified between both datasets. The main enriched KEGG pathway was "Protein digestion and absorption." The most significant identified GO terms included "primary alcohol metabolic process," "basal part of cell," and "extracellular matrix structural constituent conferring tensile strength." Identified hub modules were COL1A1, COL1A2, TIMP1, SPP1, COL5A2, THBS2, COL4A1, MUC6, CXCL8, and BGN. The overexpression of seven hub genes was associated with overall survival. Moreover, among the list of selected miRNAs, hsa-miR-27a-3, hsa-miR-941, hsa-miR-129-2-3p, and hsa-miR-1-3p, were introduced as top miRNAs targeting more than five hub genes. CONCLUSIONS: The present study identified ten genes associated with GC, which may help discover novel prognostic and diagnostic biomarkers as well as therapeutic targets for GC. Our results may advance the understanding of GC occurrence and progression.

An update in the applications of exosomes in cancer theranostics: from research to clinical trials.

Exosomes are nanosized extracellular vesicles secreted by nearly all viable cells following the fusing of multivesicular bodies and the plasma membrane and discharged into the encircling bodily fluids. Exosomes can transport cell-specific components from the source cell to the target cell. Given the enormous potential of exosomes as non-invasive diagnostic biomarkers and therapeutic nanovehicles. Lately, accumulated evidence has demonstrated that exosomes serve an important role in prognosis, diagnosis, and even treatment strategies. While several reviews have collective information on the biomedical application of exosomes, a comprehensive review incorporating updated and improved methodologies for beneficial applications of such vesicles in cancer theranostics is indispensable. In the current review, we first provided a comprehensive review of the introduction of exosomes, featuring their discovery, separation, characterization, function, biogenesis, secretion. The implications of exosomes as promising nanovehicles for drug and gene delivery, application of exosome inhibitors in the management of cancers, completed and ongoing clinical trials on the biological relevance of exosomes are then discussed in detail. As the field of exosome research grows, a better understanding of the subcellular parts and mechanisms involved in exosome secretion and targeting of specific cells will help figure out what their exact physiological functions are in the body.

An updated overview and classification of bioinformatics tools for MicroRNA analysis, which one to choose?

The term 'MicroRNA' (miRNA) refers to a class of small endogenous non-coding RNAs (ncRNAs) regenerated from hairpin transcripts. Recent studies reveal miRNAs' regulatory involvement in essential biological processes through translational repression or mRNA degradation. Recently, there is a growing body of literature focusing on the importance of miRNAs and their functions. In this respect, several databases have been developed to manage the dispersed data produced. Therefore, it is necessary to know the parameters and characteristics of each database to benefit their data. Besides, selecting the correct database is of great importance to scientists who do not have enough experience in this field. A comprehensive classification along with an explanation of the information contained in each database leads to facilitating access to these resources. In this regard, we have classified relevant databases into several categories, including miRNA sequencing and annotation, validated/predicted miRNA targets, disease-related miRNA, SNP in miRNA sequence or target site, miRNA-related pathways, or gene ontology, and mRNA-miRNA interactions. Hence, this review introduces available miRNA databases and presents a convenient overview to inform researchers of different backgrounds to find suitable miRNA-related bioinformatics web tools and relevant information rapidly.