“…The AJUBA protein has been implicated in the development of several human cancers. It is known that this protein participates in the assembly of countless protein complexes and is involved in several cellular biological processes, such as the repression of gene transcription, cell–cell adhesion, mitosis, differentiation, proliferation and cell migration [ 38 ]. Previous studies have shown that the AJUBA protein promotes colorectal cancer cell growth by suppressing the JAK1/STAT1/IFIT2 network and activating N-cadherin expression through interaction with Twist in colorectal cancer cells [ 39 , 40 ].…”
Gastric cancer (GC) is a highly heterogeneous, complex disease and the fifth most common cancer worldwide (about 1 million cases and 784,000 deaths worldwide in 2018). GC has a poor prognosis (the 5-year survival rate is less than 20%), but there is an effort to find genes highly expressed during tumor establishment and use the related proteins as targets to find new anticancer molecules. Data were collected from the Gene Expression Omnibus (GEO) bank to obtain three dataset matrices analyzing gastric tumor tissue versus normal gastric tissue and involving microarray analysis performed using the GPL570 platform and different sources. The data were analyzed using the GEPIA tool for differential expression and KMPlot for survival analysis. For more robustness, GC data from the TCGA database were used to corroborate the analysis of data from GEO. The genes found in in silico analysis in both GEO and TCGA were confirmed in several lines of GC cells by RT-qPCR. The AlphaFold Protein Structure Database was used to find the corresponding proteins. Then, a structure-based virtual screening was performed to find molecules, and docking analysis was performed using the DockThor server. Our in silico and RT-qPCR analysis results confirmed the high expression of the AJUBA, CD80 and NOLC1 genes in GC lines. Thus, the corresponding proteins were used in SBVS analysis. There were three molecules, one molecule for each target, MCULE-2386589557-0-6, MCULE-9178344200-0-1 and MCULE-5881513100-0-29. All molecules had favorable pharmacokinetic, pharmacodynamic and toxicological properties. Molecular docking analysis revealed that the molecules interact with proteins in critical sites for their activity. Using a virtual screening approach, a molecular docking study was performed for proteins encoded by genes that play important roles in cellular functions for carcinogenesis. Combining a systematic collection of public microarray data with a comparative meta-profiling, RT-qPCR, SBVS and molecular docking analysis provided a suitable approach for finding genes involved in GC and working with the corresponding proteins to search for new molecules with anticancer properties.
“…The AJUBA protein has been implicated in the development of several human cancers. It is known that this protein participates in the assembly of countless protein complexes and is involved in several cellular biological processes, such as the repression of gene transcription, cell–cell adhesion, mitosis, differentiation, proliferation and cell migration [ 38 ]. Previous studies have shown that the AJUBA protein promotes colorectal cancer cell growth by suppressing the JAK1/STAT1/IFIT2 network and activating N-cadherin expression through interaction with Twist in colorectal cancer cells [ 39 , 40 ].…”
Gastric cancer (GC) is a highly heterogeneous, complex disease and the fifth most common cancer worldwide (about 1 million cases and 784,000 deaths worldwide in 2018). GC has a poor prognosis (the 5-year survival rate is less than 20%), but there is an effort to find genes highly expressed during tumor establishment and use the related proteins as targets to find new anticancer molecules. Data were collected from the Gene Expression Omnibus (GEO) bank to obtain three dataset matrices analyzing gastric tumor tissue versus normal gastric tissue and involving microarray analysis performed using the GPL570 platform and different sources. The data were analyzed using the GEPIA tool for differential expression and KMPlot for survival analysis. For more robustness, GC data from the TCGA database were used to corroborate the analysis of data from GEO. The genes found in in silico analysis in both GEO and TCGA were confirmed in several lines of GC cells by RT-qPCR. The AlphaFold Protein Structure Database was used to find the corresponding proteins. Then, a structure-based virtual screening was performed to find molecules, and docking analysis was performed using the DockThor server. Our in silico and RT-qPCR analysis results confirmed the high expression of the AJUBA, CD80 and NOLC1 genes in GC lines. Thus, the corresponding proteins were used in SBVS analysis. There were three molecules, one molecule for each target, MCULE-2386589557-0-6, MCULE-9178344200-0-1 and MCULE-5881513100-0-29. All molecules had favorable pharmacokinetic, pharmacodynamic and toxicological properties. Molecular docking analysis revealed that the molecules interact with proteins in critical sites for their activity. Using a virtual screening approach, a molecular docking study was performed for proteins encoded by genes that play important roles in cellular functions for carcinogenesis. Combining a systematic collection of public microarray data with a comparative meta-profiling, RT-qPCR, SBVS and molecular docking analysis provided a suitable approach for finding genes involved in GC and working with the corresponding proteins to search for new molecules with anticancer properties.
“…When SERPINA5 or serpin proteins are overexpressed using lentivirus in HEK293 cells, the resulting EVs display efficacy by influencing the intended pathways as designed by the researchers (Fig. 3 C) [ 57 , 58 ]. Similarly, there are studies that the Tat protein and low-density lipoprotein receptor (Ldlr) protein were transfected into HEK293T cells using lipofectamine instead of lentivirus to functionalize EVs.…”
Section: Engineering Methods Of Ev and Applications For Regenerative ...mentioning
confidence: 99%
“… Engineered materials Method Targeting cell Ref. 1 PDGFR-RVG, hnRNPA2B1expressed/mirSilencer lentivirus HEK293T [ 51 ] 2 RVG/BDNF lentivirus HEK293T [ 52 ] 3 SERPINA5 protein lentivirus HEK293 [ 57 ] 4 Serpin protein lentivirus HEK293 [ 58 ] 5 miR-146a lentivirus PMSC [ 56 ] 6 miR-214-3p lentivirus UCMSC [ 55 ] 7 miR-133-3p lentivirus UCMSC [ 54 ] 8 Tat protein Lipofectamine HEK293T [ 59 ] 9 Ldlr mRNA Lipofectamine HEK293T [ 60 ] 10 Protein drug (srIkB) Effectene Transfection Reagent HEK293T [ 61 ] 11 Protein drug (srIkB) Effectene Transfection Reagent HEK293T [ 62 ] 12 Protein drug (srIkB) Effectene Transfection Reagent HEK293T [ 63 ] Fig. 3 Gene editing approaches for EV engineering.…”
Section: Engineering Methods Of Ev and Applications For Regenerative ...mentioning
Extracellular vesicles (EVs) are nanosized particles that are released from cells and reflect the characteristics of the mother cell. Recently, the EVs have been used in several types of studies across many different fields. In the field of EV research, multiple cell culture and EV isolation techniques have been highlighted in importance. Various strategies, including exclusive component culture media, three-dimensional (3D) cultures, and hypoxic conditions, have been proposed for the cell culture to control function of the EVs. Ultracentrifugation, ultrafiltration, precipitation, and tangential flow filtration (TFF) have been utilized for EV isolation. Although isolated EVs have their own functionalities, several researchers are trying to functionalize EVs by applying various engineering approaches. Gene editing, exogenous, endogenous, and hybridization methods are the four well-known types of EV functionalization strategies. EV engineered through these processes has been applied in the field of regenerative medicine, including kidney diseases, osteoarthritis, rheumatoid arthritis, nervous system-related diseases, and others. In this review, it was focused on engineering approaches for EV functionalization and their applications in regenerative medicine.Graphical Abstract
“…Song et al detected Serpin family A member 5 (SERPINA5) protein levels in plasma EVs. It was found that circulating plasma levels of the extracellular vesicles of SERPINA5 were elevated in EC patients, SERPINA5 expression was reduced in EC patients with distant metastases, and low SERPINA5 expression indicated poor survival [ 82 ]. Zhou et al compared plasma from healthy subjects and EC patients and found that the extracellular vesicles of miR-15a-5p, miR-106b-5p, and miR107 were significantly upregulated in the plasma of EC patients compared to healthy subjects.…”
Section: Progress In the Treatment Of Evs In Ecmentioning
confidence: 99%
“…In addition, the extracellular vesicular SERPINA5 protein hindered tumor growth and metastasis in xenograft models. Thus, the SERPINA5 EVs may be a new strategy for treating metastatic EC [ 82 ]. Wang et al found that upregulation of miR-192-5p by TAMs-derived EVs inhibited the IRAK1/NF-kB signaling pathway, effectively promoting apoptosis and impeding EMT in EC cells, thereby inhibiting EC progression.…”
Section: Progress In the Treatment Of Evs In Ecmentioning
Ovarian, cervical, and endometrial cancer are the three most common gynecological malignancies that seriously threaten women’s health. With the development of molecular biology technology, immunotherapy and targeted therapy for gynecologic tumors are being carried out in clinical treatment. Extracellular vesicles are nanosized; they exist in various body fluids and play an essential role in intercellular communication and in the regulation of various biological process. Several studies have shown that extracellular vesicles are important targets in gynecologic cancer treatment as they promote tumor growth, progression, angiogenesis, metastasis, chemoresistance, and immune system escape. This article reviews the progress of research into extracellular vesicles in common gynecologic tumors and discusses the role of extracellular vesicles in gynecologic tumor treatment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
