CLIP170 inhibits the metastasis and EMT of papillary thyroid cancer through the TGF-ß pathway.

Metastasis poses a significant challenge in combating tumors. Even in papillary thyroid cancer (PTC), which typically exhibits a favorable prognosis, high recurrence rates are attributed to metastasis. Cytoplasmic linker protein 170 (CLIP170) functions as a classical microtubule plus-end tracking protein (+TIP) and has shown close association with cell migration. Nevertheless, the specific impact of CLIP170 on PTC cells remains to be elucidated. Our analysis of the GEO and TCGA databases unveiled an association between CLIP170 and the progression of PTC. To explore the impact of CLIP170 on PTC cells, we conducted various assays. We evaluated its effects through CCK-8, wound healing assay, and transwell assay after knocking down CLIP170. Additionally, the influence of CLIP170 on the cellular actin structure was examined via immunofluorescence; we further investigated the molecular expressions of epithelial-mesenchymal transition (EMT) and the transforming growth factor-ß (TGF-ß) signaling pathways through Western blotting and RT-qPCR. These findings were substantiated through an in vivo nude mouse model of lung metastasis. We observed a decreased expression of CLIP170 in PTC in contrast to normal thyroid tissue. Functionally, the knockdown of CLIP170 (CLIP170KD) notably enhanced the metastatic potential and EMT of PTC cells, both in vitro and in vivo. Mechanistically, CLIP170KD triggered the activation of the TGF-ß pathway, subsequently promoting tumor cell migration, invasion, and EMT. Remarkably, the TGF-ß inhibitor LY2157299 effectively countered TGF-ß activity and significantly reversed tumor metastasis and EMT induced by CLIP170 knockdown. In summary, these findings collectively propose CLIP170 as a promising therapeutic target to mitigate metastatic tendencies in PTC.

CircRNAs in cancer therapy tolerance.

The rapidly expanding field of circular RNA (circ-RNA) research has opened new avenues in cancer diagnostics and treatment, highlighting the role of serum circRNAs as potential biomarkers for assessing tumor therapy resistance. This review comprehensively compiles existing knowledge regarding the biogenesis, function, and clinical relevance of circRNAs, emphasizing their stability, abundance, and cell type-specific expression profiles, which make them ideal candidates for noninvasive early biomarkers in cancer treatment. We explored the roles of circRNAs in oncogenesis and tumor progression and their complex interactions with patient responses to various cancer treatments, such as chemotherapy, radiotherapy, targeted therapy, and immunotherapy. Through the analysis of data from recent studies and clinical trials, we underscore the prognostic significance of serum circRNAs in predicting therapeutic outcomes, their involvement in resistance mechanisms, and their capacity to inform personalized treatment approaches. Additionally, this review addresses the obstacles inherent in circRNA research, including the need for standardized protocols for circRNA extraction and quantification and the elucidation of the clinical significance of circRNAs. Furthermore, our investigation extends to future prospects, including embedding circRNA profiling into regular clinical workflows and pioneering circRNA-based therapeutic approaches. We underscore the transformative potential of serum circRNAs in enhancing cancer diagnosis, improving the accuracy of therapy tolerance predictions, and ultimately fostering the advent of precision oncology.

A disproportionality analysis of FDA adverse event reporting system (FAERS) events for ticagrelor.

Background: Ticagrelor is a commonly used antiplatelet agent, but due to the stringent criteria for trial population inclusion and the limited sample size, its safety profile has not been fully elucidated. Method: We utilized OpenVigil 2.1 to query the FDA Adverse Event Reporting System database and retrieved reports by the generic name "ticagrelor" published between 1 October 2010 and 31 March 2023. Adverse drug events (ADEs) were classified and described according to the preferred terms and system organ classes in the Medical Dictionary of Regulatory Activity. Proportional reporting ratio (PRR), reporting odds ratio (ROR) and Bayesian Confidence Propagation Neural Network (BCPNN) were used to detect signals. Results: The number of ADE reports with ticagrelor as the primary suspect drug was 12,909. The top three ADEs were dyspnea [1824 reports, ROR 7.34, PRR 6.45, information component (IC) 2.68], chest pain (458 reports, ROR 5.43, PRR 5.27, IC 2.39), and vascular stent thrombosis (406 reports, ROR 409.53, PRR 396.68, IC 8.02). The highest ROR, 630.24, was found for "vascular stent occlusion". Cardiac arrest (137 reports, ROR 3.41, PRR 3.39, IC 1.75), atrial fibrillation (99 reports, ROR 2.05, PRR 2.04, IC 1.03), asphyxia (101 reports, ROR 23.60, PRR 23.43, IC 4.51), and rhabdomyolysis (57 reports, ROR 2.75, PRR 2.75, IC 1.45) were suspected new adverse events of ticagrelor. Conclusion: The FAERS database produced potential signals associated with ticagrelor that have not been recorded in the package inserts, such as cardiac arrest, atrial fibrillation, asphyxia, and rhabdomyolysis. Further clinical surveillance is needed to quantify and validate potential hazards associated with ticagrelor-related adverse events.

Single-cell RNA sequencing reveals the transcriptomic characteristics of peripheral blood mononuclear cells in hepatitis B vaccine non-responders.

The emergence of a vaccine against hepatitis B has proven to be an important milestone in the prevention of this disease; however, 5%-10% of vaccinated individuals do not generate an immune response to the vaccine, and its molecular mechanism has not been clarified. In this study, single-cell RNA sequencing was performed on peripheral blood mononuclear cells (PBMCs) from three volunteers with a high immune response (HR) and three with no immune response (NR) to the hepatitis B vaccine. We found that the antigen-presenting activity scores of various antigen-presenting cells, the mitogen-activated protein kinase (MAPK) pathway activity scores of naive B cells, and the cell activity scores of three types of effector T cells were significantly decreased, whereas the cytotoxicity scores of CD3highCD16lowKLRG1high natural killer T (NKT) cells were significantly increased in the NR group compared with those in the HR group. Additionally, the expression levels of some classical molecules associated with distinct signaling pathways-including HLA-B, HLA-DRB5, BLNK, BLK, IL4R, SCIMP, JUN, CEBPB, NDFIP1, and TXNIP-were significantly reduced in corresponding subsets of PBMCs from the NR group relative to those of the HR group. Furthermore, the expression of several cytotoxicity-related effector molecules, such as GNLY, NKG7, GZMB, GZMM, KLRC1, KLRD1, PRF1, CST7, and CTSW, was significantly higher in CD3highCD16lowKLRG1high NKT cells derived from non-responders. Our study provides a molecular basis for the lack of response to the hepatitis B vaccine, including defective antigen presentation, decreased T cell activity, and reduced IL-4 secretion, as well as novel insight into the role of NKT cells in the immune response to the hepatitis B vaccine.

Comparison of ischemic stroke diagnosis models based on machine learning.

Background: The incidence, prevalence, and mortality of ischemic stroke (IS) continue to rise, resulting in a serious global disease burden. The prediction models have a great value in the early prediction and diagnosis of IS. Methods: The R software was used to screen the differentially expressed genes (DEGs) of IS and control samples in the datasets GSE16561, GSE58294, and GSE37587 and analyze DEGs for enrichment analysis. The feature genes of IS were obtained by several machine learning algorithms, including the least absolute shrinkage and selector operation (LASSO) logistic regression, the support vector machine-recursive feature elimination (SVM-RFE), and the Random Forest (RF). The IS diagnostic models were constructed based on transcriptomics by machine learning and artificial neural network (ANN). Results: A total of 69 DEGs, mainly involved in immune and inflammatory responses, were identified. The pathways enriched in the IS group were complement and coagulation cascades, lysosome, PPAR signaling pathway, regulation of autophagy, and toll-like receptor signaling pathway. The feature genes selected by LASSO, SVM-RFE, and RF were 17, 10, and 12, respectively. The area under the curve (AUC) of the LASSO model in the training dataset, GSE22255, and GSE195442 was 0.969, 0.890, and 1.000. The AUC of the SVM-RFE model was 0.957, 0.805, and 1.000, respectively. The AUC of the RF model was 0.947, 0.935, and 1.000, respectively. The models have good sensitivity, specificity, and accuracy. The AUC of the LASSO+ANN, SVM-RFE+ANN, and RF+ANN models was 1.000, 0.995, and 0.997, respectively, in the training dataset. However, the AUC of LASSO+ANN, SVM-RFE+ANN, and RF+ANN models was 0.688, 0.605, and 0.619, respectively, in the GSE22255 dataset. The AUC of the LASSO+ANN and RF+ANN models was 0.740 and 0.630, respectively, in the GSE195442 dataset. In the training dataset, the sensitivity, specificity, and accuracy of the LASSO+ANN model were 1.000, 1.000, and 1.000, respectively; of the SVM-RFE+ANN model were 0.946, 0.982, and 0.964, respectively; and of the RF+ANN model were 0.964, 1.000, and 0.982, respectively. In the test datasets, the sensitivity was very satisfactory; however, the specificity and accuracy were not good. Conclusion: The LASSO, SVM-RFE, and RF models have good prediction abilities. However, the ANN model is efficient at classifying positive samples and is unsuitable at classifying negative samples.

Hypoxia-induced circular RNA hsa_circ_0008450 accelerates hepatocellular cancer progression via the miR-431/AKAP1 axis.

Hypoxia facilitates the progression of numerous cancers. Circular RNAs (circRNA) have been revealed to be involved in the process of tumors mediated by hypoxia. However, the role and molecular mechanism of circular RNA hsa_circ_0008450 (circ_0008450) in hepatocellular cancer (HCC) under hypoxic conditions has been rarely reported. Expression levels of circ_0008450, microRNA(miR)-431 and A-kinase anchor protein 1 (AKAP1) were examined using reverse transcription-quantitative PCR. Cell viability, apoptosis and glycolysis were assessed via Cell Counting Kit-8, flow cytometry and glycolysis assays, respectively. The association between circ_0008450 or AKAP1 and miR-431 was verified via dual-luciferase reporter assays. Protein levels of AKAP1 were detected by western blotting. Effect of hsa_circ_0008450 on tumor growth in vivo was confirmed by xenograft assays. Circ_0008450 was upregulated in HCC tissues and hypoxia-disposed HCC cells. Depletion of circ_0008450 suppressed tumor growth in vivo and reversed the repression of apoptosis and the acceleration of viability and glycolysis of HCC cells induced by hypoxia treatment in vitro. Notably, circ_0008450 regulated AKAP1 expression by sponging miR-431. Furthermore, miR-431 inhibition reversed the circ_0008450 silencing-mediated effects on viability, apoptosis and glycolysis in hypoxia-treated HCC cells. Additionally, AKAP1 enhancement abolished the effects of miR-431 upregulation on the viability, apoptosis and glycolysis in hypoxia-treated HCC cells. In conclusion, circ_0008450 repression mitigated the progression of HCC under hypoxia by downregulating AKAP1 via miR-431, providing a potential target for HCC treatment.

The Role of Noncoding RNAs in Gout.

Over the past decade, noncoding ribonucleic acids (ncRNAs) have been shown to have crucial functional importance in health and disease. ncRNAs have been well studied and may be involved in the development of inflammatory arthritis, including gouty arthritis. Gout is also associated with metabolic pathway disorders, such as hyperuricemia, due to disturbed purine nucleotide metabolism or excretion of uric acid through the kidney. Moreover, their presence in the circulation has led to the idea that ncRNAs might serve as biomarkers for specific disease states to guide clinical decision-making. Therefore, we summarize the emerging evidence and review the current literature on the regulatory role of miRNAs and lncRNAs in gout pathophysiology. We further discuss the opportunities and challenges of ncRNAs as new blood-based biomarkers for future studies aimed at translation into clinical applications in the diagnosis and therapy of gout.

CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 May Be Potential Therapeutic Targets for Hepatocellular Carcinoma Using Integrated Bioinformatic Analysis.

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. The abnormal expression of genes is significantly related to the occurrence of HCC. The aim of this study was to explore the differentially expressed genes (DEGs) of HCC and to provide bioinformatics basis for the occurrence, prevention and treatment of HCC. The DEGs of HCC and normal tissues in GSE102079, GSE121248, GSE84402 and GSE60502 were obtained using R language. The GO function analysis and KEGG pathway enrichment analysis of DEGs were carried out using the DAVID database. Then, the protein-protein interaction (PPI) network was constructed using the STRING database. Hub genes were screened using Cytoscape software and verified using the GEPIA, UALCAN, and Oncomine database. We used HPA database to exhibit the differences in protein level of hub genes and used LinkedOmics to reveal the relationship between candidate genes and tumor clinical features. Finally, we obtained transcription factor (TF) of hub genes using NetworkAnalyst online tool. A total of 591 overlapping up-regulated genes were identified. These genes were related to cell cycle, DNA replication, pyrimidine metabolism, and p53 signaling pathway. Additionally, the GEPIA database showed that the CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 were associated with the poor survival of HCC patients. UALCAN, Oncomine, and HPA databases and qRT-PCR confirmed that these genes were highly expressed in HCC tissues. LinkedOmics database indicated these genes were correlated with overall survival, pathologic stage, pathology T stage, race, and the age of onset. TF analysis showed that MYBL2, KDM5B, MYC, SOX2, and E2F4 were regulators to these nine hub genes. Overexpression of CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 in tumor tissues predicted poor survival in HCC. They may be potential therapeutic targets for HCC.

[Bioinformatics analysis of COL1A1 regulated by miR-129-5p as a potential therapeutic target for gastric cancer].

OBJECTIVE: To explore the pathogenesis of gastric cancer through a bioinformatic approach to provide evidence for the prevention and treatment of gastric cancer. METHODS: The differentially expressed genes (DEGs) in gastric cancer and normal gastric mucosa in GSE79973 dataset were analyzed using GEO2R online tool. GO analysis and KEGG pathway enrichment analysis of the DEGs in DAVID database were performed. The protein interaction network was constructed using STRING database, and the key genes (Hub genes) were screened and their functional modules were analyzed using Cytoscape software. The GEPIA database was used to validate the Hub genes, and the Target Scan database was used to predict the microRNAs that regulate the target genes; OncomiR was used to analyze the expressions of the microRNAs in gastric cancer tissues and their relationship with the survival outcomes of the patients. RESULTS: A total of 181 DEGs were identified in gastric cancer, and 10 hub genes were screened by the protein- protein interaction network. Functional analysis showed that these DEGs were involved mainly in protein digestion and absorption, PI3K-Akt signaling pathway, ECM-receptor interaction and platelet activation signal pathway. GEPIA database validation showed that COL1A1 was highly expressed in gastric cancer tissues and was associated with a poor prognosis of patients with gastric cancer. MiR-129-5p was found to bind to the 3'UTR of COL1A1 mRNA, and compared with that in normal tissues, miR-129-5p expression was obviously down-regulated in gastric cancer tissues, and was correlated with the prognosis of the patients. CONCLUSIONS: COL1A1 under regulation by MiR-129-5p is a potential therapeutic target for gastric cancer.

2-arachidonyl glycerol modulates astrocytic glutamine synthetase via p38 and ERK1/2 pathways.

BACKGROUND: The glutamine synthetase (GS), an astrocyte-specific enzyme, is involved in lipopolysaccharide (LPS)-induced inflammation which activates the mitogen-activated protein kinase (MAPK) signaling. Endocannabinoid 2-arachidonyl glycerol (2-AG) has been described to serve as an endogenous mediator of analgesia and neuroprotection. However, whether 2-AG can directly influence astrocytic GS and MAPK expressions remains unknown. METHODS: In the present study, the effects of 2-AG on astrocytic GS expression, p38 and ERK1/2 expression, cell viability, and apoptosis following LPS exposure were investigated. RESULTS: The results revealed that LPS exposure increased GS expression with p38 activation in the early phase and decreased GS expression with activation of ERK1/2, decrease of cell viability, and increase of apoptosis in the late phase. Inhibition of p38 reversed GS increase in the early phase while inhibition of ERK1/2 reversed GS decrease in the late phase induced by LPS exposure. 2-AG protected astrocytes from increase of apoptosis and decrease of cell viability induced by the late phase of LPS exposure. In the early phase of LPS exposure, 2-AG could suppress the increase of GS expression and activation of p38 signaling. In the late phase of LPS exposure, 2-AG could reverse the decrease of GS expression and activation of ERK1/2 induced by LPS. CONCLUSION: These findings suggest that 2-AG could maintain the GS expression in astrocytes to a relatively stable level through modulating MAPK signaling and protect astrocytes from LPS exposure.

The critical role of HMGA2 in regulation of EMT in epithelial ovarian carcinomas.

The high mobility group A2 (HMGA2), an oncofetal protein, was shown to play a role in tumor development and progression. However, the molecular and clinical role of HMGA2 in epithelial ovarian carcinomas (EOCs) is still unknown. In the present study, EOC cell line SKOV3 was subjected to in vitro assays. Here, our findings showed that HMGA2 was highly expressed in EOC cell line SKOV3. HMGA2 knockdown promoted cell apoptosis and the cleavage of caspase 3, and decreased the B cell lymphoma 2 (Bcl-2)/Bax ratio in SKOV3. Functionally, HMGA2 knockdown resulted in reduction of SKOV3 cell migration and invasion. Mechanically, HMGA2 knockdown affected the occurrence of EMT by increasing E-cadherin gene and protein expression and decreasing the gene and protein expression of N-cadherin, slug, and vimentin. At the same time, HMGA2 also repressed the expression of matrix metalloproteinase 2 (MMP2) and matrix metalloproteinase 9 (MMP9), which was consistent with the decreased invasion capacity. In conclusion, HMGA2 is associated with migration and invasiveness and regulates the progression of EMT in the development of EOC, and HMGA2 gene and protein may be a novel therapeutic target against EOC in the clinical practice.

The Critical Role of Rab31 in Cell Proliferation and Apoptosis in Cancer Progression.

Rab31, a member of the Ras superfamily, is reported to play a role in tumor development and progression. However, the detailed role of Rab31 in proliferation and apoptosis of cancer cells is still unclear. Here, we used different cell lines, such as glioblastoma, and cervical cancer, to investigate the role of Rab31 in cancer progression. We found that Rab31 promotes U87 and SiHa cell proliferation via activation of G1/S checkpoint transitions, accompanied with an increase of cyclin D1, cyclin A, and cyclin B1. Meanwhile, Rab31 inhibits U87 and SiHa cell apoptosis, and decreased the BAX and PIG3 expression, but enhanced BCL2 expression. In addition, Rab31 induces N-cadherin, Vimentin, and Snail expression, and inhibits E-cadherin expression to regulate proliferation and migration. Besides, we observed that ERK1/2 and PI3k/AKT pathways are required for Rab31-induced cell proliferation and migration. In vivo, the knockdown of Rab31 suppresses tumor mass growth. In conclusion, our data highlight the crucial role of Rab31 in cancer progression, proliferation, and apoptosis, and indicates that Rab31 may be a useful and effective target for the clinical therapy of most cancers.