Calycosin (CA) inhibits proliferation, migration and invasion by suppression of CXCL10 signaling pathway in glioma.

Glioblastoma is the most common malignant tumor in the central nervous system and its occurrence and development is involved in various molecular abnormalities. C-X-C chemokine ligand 10 (CXCL10), an inflammatory chemokine, has been reported to be related to the pathogenesis of cancer while it has not yet been linked to glioma. Calycosin, a bioactive compound derived from Radix astragali, has demonstrated anticancer properties in several malignancies, including glioma. Nonetheless, its underlying mechanisms are not fully understood. This study explores CXCL10 as a potential therapeutic target for calycosin in the suppression of glioblastoma. We observed that CXCL10 expression correlates positively with glioma malignancy and inversely with patient prognosis, highlighting its potential as a glioblastoma treatment target. Furthermore, we found that calycosin inhibited proliferation, migration, and invasion in U87 and U251 glioma cells, and decreased CXCL10 expression in a dose-dependent manner, along with its downstream effectors such as NLRP3, NF-κB, and IL-1ß. Additionally, molecular docking experiments demonstrated that calycosin exhibits a notable binding affinity to CXCL10. Overexpression of CXCL10 counteracted the inhibitory effects of calycosin on cell proliferation, migration, and invasion, while CXCL10 knockdown enhanced these effects. Finally, we verified that calycosin inhibited glioma growth in a xenograft mouse model and downregulated CXCL10 and its downstream molecules. These findings suggest that targeting CXCL10 may be an effective strategy in glioblastoma treatment, and calycosin emerges as a potential therapeutic agent.

PRMT1 in human neoplasm: cancer biology and potential therapeutic target.

Protein arginine methyltransferase 1 (PRMT1), the predominant type I protein arginine methyltransferase, plays a crucial role in normal biological functions by catalyzing the methylation of arginine side chains, specifically monomethylarginine (MMA) and asymmetric dimethylarginine (ADMA), within proteins. Recent investigations have unveiled an association between dysregulated PRMT1 expression and the initiation and progression of tumors, significantly impacting patient prognosis, attributed to PRMT1's involvement in regulating various facets of tumor cell biology, including DNA damage repair, transcriptional and translational regulation, as well as signal transduction. In this review, we present an overview of recent advancements in PRMT1 research across different tumor types, with a specific focus on its contributions to tumor cell proliferation, metastasis, invasion, and drug resistance. Additionally, we expound on the dynamic functions of PRMT1 during distinct stages of cancer progression, elucidating its unique regulatory mechanisms within the same signaling pathway and distinguishing between its promotive and inhibitory effects. Importantly, we sought to provide a comprehensive summary and analysis of recent research progress on PRMT1 in tumors, contributing to a deeper understanding of its role in tumorigenesis, development, and potential treatment strategies.

GPR37 expression as a prognostic marker in gliomas: a bioinformatics-based analysis.

BACKGROUND: Gliomas are the most frequently diagnosed primary brain tumors, and are associated with multiple molecular aberrations during their development and progression. GPR37 is an orphan G protein-coupled receptor (GPCR) that is implicated in different physiological pathways in the brain, and has been linked to various malignancies. The aim of this study was to explore the relationship between GPR37 gene expression and the clinicopathological factors, patient prognosis, tumor-infiltrating immune cell signature GSEA and methylation levels in glioma. METHODS: We explored the diagnostic value, clinical relevance, and molecular function of GPR37 in glioma using TCGA, STRING, cBioPortal, Tumor Immunity Estimation Resource (TIMER) database and MethSurv databases. Besides, the "ssGSEA" algorithm was conducted to estimate immune cells infiltration abundance, with 'ggplot2' package visualizing the results. Immunohistochemical staining of clinical samples were used to verify the speculations of bioinformatics analysis. RESULTS: GPR37 expression was significantly higher in the glioma tissues compared to the normal brain tissues, and was linked to poor prognosis. Functional annotation of GPR37 showed enrichment of ether lipid metabolism, fat digestion and absorption, and histidine metabolism. In addition, GSEA showed that GPR37 was positively correlated to the positive regulation of macrophage derived foam cell differentiation, negative regulation of T cell receptor signaling pathway, neuroactive ligand receptor interaction, calcium signaling pathway, and negatively associated with immunoglobulin complex, immunoglobulin complex circulating, ribosome and spliceosome mediated by circulating immunoglobulin etc. TIMER2.0 and ssGSEA showed that GPR37 expression was significantly associated with the infiltration of T cells, CD8 T cell, eosinophils, macrophages, neutrophils, NK CD56dim cells, NK cells, plasmacytoid DCs (pDCs), T helper cells and T effector memory (Tem) cells. In addition, high GPR37 expression was positively correlated with increased infiltration of M2 macrophages, which in turn was associated with poor prognosis. Furthermore, GPR37 was positively correlated with various immune checkpoints (ICPs). Finally, hypomethylation of the GPR37 promoter was associated with its high expression levels and poor prognosis in glioma. CONCLUSION: GPR37 had diagnostic and prognostic value in glioma. The possible biological mechanisms of GPR37 provide novel insights into the clinical diagnosis and treatment of glioma.

Elevated LILRB1 expression predicts poor prognosis and is associated with tumor immune infiltration in patients with glioma.

BACKGROUND: Leukocyte immunoglobulin-like receptor subfamily B1 (LILRB1) is regarded as an inhibitory molecule. However, the importance of LILRB1 expression in glioma has not yet been determined. This investigation examined the immunological signature, clinicopathological importance and prognostic value of LILRB1 expression in glioma. METHODS: We used data from the UCSC XENA database, the Cancer Genome Atlas (TCGA) database, the Chinese Glioma Genome Atlas (CGGA) database, the STRING database, the MEXPRESS database and our clinical glioma samples to perform bioinformatic analysis and used vitro experiments to examine the predictive value and potential biological roles of LILRB1 in glioma. RESULTS: Higher LILRB1 expression was considerably present in the higher WHO grade glioma group and was linked to a poorer prognosis in patients with glioma. Gene set enrichment analysis (GSEA) revealed that LILRB1 was positively correlated with the JAK/STAT signaling pathway. LILRB1 combined with tumor mutational burden (TMB) and microsatellite instability (MSI) may be a promising indicator for the effectiveness of immunotherapy in patients with glioma. Increased LILRB1 expression was positively linked with the hypomethylation, M2 macrophage infiltration, immune checkpoints (ICPs) and M2 macrophage makers. Univariate and multivariate Cox regression analyses determined that increased LILRB1 expression was a standalone causal factor for glioma. Vitro experiments determined that LILRB1 positively enhanced the proliferation, migration and invasion in glioma cells. MRI images demonstrated that higher LILRB1 expression was related with larger tumor volume in patients with glioma. CONCLUSION: Dysregulation of LILRB1 in glioma is correlated with immune infiltration and is a standalone causal factor for glioma.

Lipidomics of the erythrocyte membrane and network pharmacology to explore the mechanism of mangiferin from Anemarrhenae rhizoma in treating type 2 diabetes mellitus rats.

Mangiferin, a natural C-glucoside xanthone, is one of the major bioactive ingredients derived from the dry rhizome of Anemarrhenae rhizome, which has been reported to exhibit various pharmacological effects, including anti-oxidant, anti-inflammatory, anti-fatty liver, anti-metabolic syndrome, and anti-diabetic. However, the precise molecular mechanisms underlying its impact on phospholipid metabolism in the erythrocyte membrane of type 2 diabetes mellitus (T2DM) remain unclear. The present research aimed to evaluate the effects of mangiferin on glucose and lipid metabolism in T2DM model rats and discuss the relationship between lipid metabolites and potential targets involved in the hypoglycemic effects by integrating lipidomics and network pharmacology method. After 8 consecutive weeks of treatment with mangiferin, the T2DM model rats exhibited significant improvements in several biochemical indices and cytokines, including fasting blood glucose (FBG) levels after 12 h of fasting, fasting insulin level (FINS), total cholesterol (T-CHO), triacylglycerols (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), homeostasis model assessment of insulin resistance (HMOA-IR), TNF-α and IL-6. A total of 22 differential lipid metabolites were selected from erythrocyte membrane phospholipids, which were closely associated with the processes of T2DM. These metabolites mainly belonged to glycerophospholipid metabolism and sphingolipid metabolism. Based on network pharmacology analysis, 22 genes were recognized as the potential targets of mangiferin against diabetes. Moreover, molecular docking analysis revealed that the targets of TNF, CASP3, PTGS2, MMP9, RELA, PLA2G2A, PPARA, and NOS3 could be involved in the modulation of inflammatory signaling pathways and arachidonic acid (AA) metabolism to improve IR and hyperglycemia. The combination of immunohistochemical staining and PCR showed that mangiferin could treat T2DM by regulating the expression of PPARγ protein and NF-κB mRNA expression to impact glycerophospholipids (GPs) and AA metabolism. The present study showed that mangiferin might alleviate IR and hyperglycemia of T2DM model rats via multiple targets and multiple pathways to adjust their phospholipid metabolism, which may be the underlying mechanism for mangiferin in the treatment of T2DM.

Echinacoside (ECH) suppresses proliferation, migration, and invasion of human glioblastoma cells by inhibiting Skp2-triggered epithelial-mesenchymal transition (EMT).

BACKGROUND: Echinacoside (ECH) is a phenylethanoid extracted from the stems of Cistanches salsa, an herb used in Chinese medicine formulations, and is effective against glioblastoma multiforme (GBM). Epithelial-mesenchymal transition (EMT) is the cornerstone of tumorigenesis and metastasis, and increases the malignant behavior of GBM cells. The S phase kinase-related protein 2 (skp2), an oncoprotein associated with EMT, is highly expressed in GBM and significantly associated with drug resistance, tumor grade and dismal prognosis. The aim of this study was to explore the inhibitory effects of ECH against GBM development and skp2-induced EMT. METHODS: CCK-8, EdU incorporation, transwell, colony formation and sphere formation assays were used to determine the effects of ECH on GBM cell viability, proliferation, migration and invasion in vitro. The in vivo anti-glioma effects of ECH were examined using a U87 xenograft model. The expression levels of skp2 protein, EMT-associated markers (vimentin and snail) and stemness markers (Nestin and sox2) were analyzed by immunofluorescence staining and western blotting experiments. RESULTS: ECH suppressed the proliferation, invasiveness and migration of GBM cells in vitro, as well as the growth of U87 xenograft in vivo. In addition, ECH downregulated the skp2 protein, EMT-related markers (vimentin and snail) and stemness markers (sox2 and Nestin). The inhibitory effects of ECH were augmented in the skp2-knockdown GBM cells, and reversed in cells with ectopic expression of skp2. CONCLUSION: ECH inhibits glioma development by suppressing skp2-induced EMT of GBM cells.

Neural stem cell­derived exosomes transfer miR­124­3p into cells to inhibit glioma growth by targeting FLOT2.

Currently, exosomes (EXOs) are being explored as novel drug delivery carriers with greater advantages, including crossing the blood­brain­barrier and loading drugs. The present study utilized EXOs derived from neural stem cells (NSCs) for the delivery of molecular drugs to treat gliomas. miR­124­3p was selected according to previous studies by the authors, and the effects of the delivery of miR­124­3p to glioma cells by NSC­EXOs in vitro and in vivo were evaluated. It was found that NSC­EXOs successfully delivered miR­124­3p into glioma cells, and NSC­EXOs loaded with miR­124­3p significantly inhibited glioma cell proliferation, invasion and migration. Furthermore, the delivery of miR­124­3p by NSC­EXOs suppressed flotillin 2 (FLOT2) expression by specifically binding to the 3' untranslated region of the FLOT2 gene in gliomas; subsequently, AKT1 was found to be associated with the EXO­miR­124­3p/FLOT2 pathway. Moreover, the therapeutic effects of the delivery of miR­124­3p by NSC­EXOs were confirmed in a mouse tumor xenograft model of glioma. Thus, bio­carrier NSC­EXOs loaded with miR­124­3p suppressed glioma growth via the EXO­miR­124­3p/FLOT2/AKT1 pathway. On the whole, the present study provides insight into stem cell­free molecular­targeted therapy based on bio­carrier NSC­EXOs and provides a potential strategy for the treatment of glioma.

Paeoniflorin Inhibits EMT and Angiogenesis in Human Glioblastoma via K63-Linked C-Met Polyubiquitination-Dependent Autophagic Degradation.

Epithelial-to-mesenchymal transition (EMT) and angiogenesis have emerged as two pivotal events in cancer progression. Paeoniflorin has been widely studied in experimental models and clinical trials for cancer treatment because of its anti-cancer property. However, the underlying mechanisms of paeoniflorin in EMT and angiogenesis in glioblastoma was not fully elucidated. The present study aimed to investigate whether paeoniflorin inhibits EMT and angiogenesis, which involving c-Met suppression, while exploring the potential ways of c-Met degradation. In our study, we found that paeoniflorin inhibited EMT via downregulating c-Met signaling in glioblastoma cells. Furthermore, overexpressing c-Met in glioblastoma cells abolished the effects of paeoniflorin on EMT. Moreover, paeoniflorin showed anti-angiogenic effects by suppressing cell proliferation, migration, invasion and tube formation through downregulating c-Met in human umbilical vein endothelial cells (HUVECs). And c-Met overexpression in HUVECs offset the effects of paeoniflorin on angiogenesis. Additionally, paeoniflorin induced autophagy activation involving mTOR/P70S6K/S6 signaling and promoted c-Met autophagic degradation, a process dependent on K63-linked c-Met polyubiquitination. Finally, paeoniflorin suppressed mesenchymal makers (snail, vimentin, N-cadherin) and inhibited angiogenesis via the identical mechanism in an orthotopic xenograft mouse model. The in vitro and in vivo experiments showed that paeoniflorin treatment inhibited EMT, angiogenesis and activated autophagy. What's more, for the first time, we identified c-Met may be a potential target of paeoniflorin and demonstrated paeoniflorin downregulated c-Met via K63-linked c-Met polyubiquitination-dependent autophagic degradation. Collectively, these findings indicated that paeoniflorin inhibits EMT and angiogenesis via K63-linked c-Met polyubiquitination-dependent autophagic degradation in human glioblastoma.

3BDO inhibits the proliferation, epithelial-mesenchymal transition (EMT), and stemness via suppressing survivin in human glioblastoma cells.

Background: Glioblastoma (GBM) is a tumor of the central nervous system with an extremely poor prognosis. Stemness and EMT play important roles in GBM progression. 3-benzyl-5-((2-nitrophenoxy) methyl) dihydrofuran-2(3H)-one (3BDO), an autophagy inhibitor, has been reported to exert anti-cancer activities on lung carcinoma. However, the effects of 3BDO on GBM remain unknown. Therefore, the purpose of this study was to explore the effects of 3BDO on GBM and to investigate the underlying molecular mechanisms. Method: CCK-8 experiments and clone formation assays were conducted to determine the level of cell proliferation. Transwell assay was conducted to examine cell migration and invasion abilities. Western blotting and immunofluorescence staining were used to analyze protein expression levels. A xenograft mouse model was used to evaluate the effect of 3BDO in vivo. Results: We found that 3BDO inhibited U87 and U251 cell proliferation in a dose-dependent manner. Additionally, 3BDO decreased the degree of sphere formation and levels of stemness markers (sox2, nestin, and CD133) in GSCs. 3BDO also inhibited migration and invasion abilities and suppressed EMT markers (N-cadherin, vimentin, and snail) in GBM cells. Moreover, we found that 3BDO downregulated the expression of survivin in both GBM cells (U87, U251) and GSCs. Furthermore, overexpression of survivin decreased the therapeutic effect of 3BDO on EMT, invasion, migration, and proliferation of GBM cells, as well as decreased the stemness of GSCs. Finally, we demonstrated that 3BDO could inhibit tumor growth in a tumor xenograft mouse model constructed using U87 cells. Similar to the in vitro findings, 3BDO decreased the expression of survivin, EMT makers, and the degree of stemness in vivo. Conclusions: Our results demonstrate that 3BDO can repress GBM both in vitro and in vivo via downregulating survivin-mediated stemness and EMT.

Histone deacetylase 6 promotes growth of glioblastoma through the MKK7/JNK/c-Jun signaling pathway.

Histone deacetylase 6 (HDAC6) activity contributes to the malignant proliferation, invasion, and migration of glioma cells (GCs), but the molecular mechanisms underlying the processes remains elusive. Here, we reported that HDAC6 inhibition by Ricolinostat (ACY-1215) or CAY10603 led to a remarkable decrease in the phosphorylation of c-Jun N-terminal kinase (JNK) and c-Jun, which preceded its suppressive effects on glioma cell growth. Further investigation showed that these effects resulted from HDAC6 inhibitor-induced suppression of MAPK kinase 7 (MKK7), which was identified to be critical for JNK activation and exerts the oncogenic roles in GCs. Selectively silencing HDAC6 by siRNAs had the same responses, whereas transient transfections expressing HDAC6 promoted MKK7 expression. Interestingly, by performing Q-PCR, HDAC6 inhibition did not cause a down-regulation of MKK7 mRNA level, whereas the suppressive effects on MKK7 protein can be efficiently blocked by the proteasomal inhibitor MG132. As a further test, elevating MKK7-JNK activity was sufficient to rescue HDAC6 inhibitor-mediated-suppressive effects on c-Jun activation and the malignant features. The suppression of both MKK7 expression and JNK/c-Jun activities was involved in the tumor-growth inhibitory effects induced by CAY10603 in U87-xenograft mice. Collectively, our findings provide new insights into the molecular mechanism of glioma malignancy regarding HDAC6 in the selective regulation of MKK7 expression and JNK/c-Jun activity. MKK7 protein stability critically depends on HDAC6 activity, and inhibition of HDAC6 probably presents a potential strategy for suppressing the oncogenic roles of MKK7/JNK/c-Jun axis in GCs.

Transfer Learning Based Fault Diagnosis with Missing Data Due to Multi-Rate Sampling.

Deep learning is an effective feature extraction method widely applied in fault diagnosis fields since it can extract fault features potentially involved in multi-sensor data. But different sensors equipped in the system may sample data at different sampling rates, which will inevitably result in a problem that a very small number of samples with a complete structure can be used for deep learning since the input of a deep neural network (DNN) is required to be a structurally complete sample. On the other hand, a large number of samples are required to ensure the efficiency of deep learning based fault diagnosis methods. To solve the problem that a structurally complete sample size is too small, this paper proposes a fault diagnosis framework of missing data based on transfer learning which makes full use of a large number of structurally incomplete samples. By designing suitable transfer learning mechanisms, extra useful fault features can be extracted to improve the accuracy of fault diagnosis based simply on structural complete samples. Thus, online fault diagnosis, as well as an offline learning scheme based on deep learning of multi-rate sampling data, can be developed. The efficiency of the proposed method is demonstrated by utilizing data collected from the QPZZ- II rotating machinery vibration experimental platform system.

A new clutter rejection algorithm for Doppler ultrasound.

Several strategies, known as clutter or wall Doppler filtering, were proposed to remove the strong echoes produced by stationary or slow moving tissue structures from the Doppler blood flow signal. In this study, the matching pursuit (MP) method is proposed to remove clutter components. The MP method decomposes the Doppler signal into wavelet atoms that are selected in a decreasing energy order. Thus, the high-energy clutter components are extracted first. In the present study, the pulsatile Doppler signal s(n) was simulated by a sum of random-phase sinusoids. Two types of high-amplitude clutter signals were then superimposed on s(n): time-varying low-frequency components, covering systole and early diastole, and short transient clutter signals, distributed within the whole cardiac cycle. The Doppler signals were modeled with the MP method and the most dominant atoms were subtracted from the time-domain signal s(n) until the signal-to-clutter (S/C) ratio reached a maximum. For the low-frequency clutter signal, the improvement in S/C ratio was 19.0 +/- 0.6 dB, and 72.0 +/- 4.5 atoms were required to reach this performance. For the transient clutter signal, ten atoms were required and the maximum improvement in S/C ratio was 5.5 +/- 0.5 dB. The performance of the MP method was also tested on real data recorded over the common carotid artery of a normal subject. Removing 15 atoms significantly improved the appearance of the Doppler sonogram contaminated with low-frequency clutter. Many more atoms (over 200) were required to remove transient clutter components. These results suggest the possibility of using this signal processing approach to implement clutter rejection filters on ultrasound commercial instruments.