A Comprehensive Pan-cancer Analysis of the Biological Immunomodulatory Function and Clinical Value of CD27.

Background: CD27 is an immunological checkpoint gene, plays a critical function inInhibition or activation of cancer immunity. The CD27/CD27L axis is its pathway of action. Therefore, our goal was to examine the predictive role of CD27 in the clinical prognosis of 33 cancer types and its functions in cancer progression, as well as explore the link between pan-cancer CD27 gene expression and immune infiltration. Methods: By comprehensive use of datasets and methods from TCGA, cBioPortal, GTEx, HPA, KM-plotter, Spearman, CellMinerTM, R packages and RT-qPCR, we delved deeper into the potential impact of the CD27 on cancer development. These include expression differences, immune infiltration, matrix infiltration, gene mutations, DNA methylation, signaling pathways, TMB, MSI, and prognosis. Also, we explored CD27 interactions with different drugs. Results: The results showed that, mutated CD27 was highly expressed in most cancers. The CD27 showed strong diagnostic value in 4 cancers and marked a positive prognosis for CESC, intracervical adenocarcinoma, HNSC, and endometrial cancer, and a poor prognosis for UVM. In addition, CD27 affects multiple immune and inflammatory signaling pathways and is positively correlated with immune cell infiltration, T cell differentiation, macrophage M1 polarization, stromal infiltration, and drug sensitivity. DNA methylation is involved in CD27 expression in cancer. Conclusion: CD27, which is mutated in cancers and appears widely highly expressed and altered tumor immune invasion and stromal invasion by affecting multiple immune-related and inflammation signaling pathways, plays a significant role in CESC, HNSC, UCEC and UVM, and may be used as a therapeutic target for related cancers.

Targeting MAGI2-AS3-modulated Akt-dependent ATP-binding cassette transporters as a possible strategy to reverse temozolomide resistance in temozolomide-resistant glioblastoma cells.

Drug resistance is a major impediment to the successful treatment of glioma. This study aimed to elucidate the effects and mechanisms of the long noncoding RNA membrane-associated guanylate kinase inverted-2 antisense RNA 3 (MAGI2-AS3) on temozolomide (TMZ) resistance in glioma cells. MAGI2-AS3 expression in TMZ-resistant glioblastoma (GBM) cells was analyzed using the Gene Expression Omnibus data set GSE113510 and quantitative real-time PCR (qRT-PCR). Cell viability and TMZ half-maximal inhibitory concentration values were determined using the MTT assay. Apoptosis and cell cycle distribution were evaluated using flow cytometry. The expression of multidrug resistance 1 (MDR1), ATP-binding cassette superfamily G member 2 (ABCG2), protein kinase B (Akt), and phosphorylated Akt was detected using qRT-PCR and/or western blot analysis. MAGI2-AS3 was expressed at low levels in TMZ-resistant GBM cells relative to that in their parental cells. MAGI2-AS3 re-expression alleviated TMZ resistance in TMZ-resistant GBM cells. MAGI2-AS3 overexpression also accelerated TMZ-induced apoptosis and G2/M phase arrest. Mechanistically, MAGI2-AS3 overexpression reduced MDR1 and ABCG2 expression and inhibited the Akt pathway, whereas Akt overexpression abrogated the reduction in MDR1 and ABCG2 expression induced by MAGI2-AS3. Moreover, activation of the Akt pathway inhibited the effects of MAGI2-AS3 on TMZ resistance. MAGI2-AS3 inhibited tumor growth and enhanced the suppressive effect of TMZ on glioma tumorigenesis in vivo. In conclusion, MAGI2-AS3 reverses TMZ resistance in glioma cells by inactivating the Akt pathway.

Machine learning versus regression for prediction of sporadic pancreatic cancer.

BACKGROUND/OBJECTIVES: There is currently no widely accepted approach to identify patients at increased risk for sporadic pancreatic cancer (PC). We aimed to compare the performance of two machine-learning models with a regression-based model in predicting pancreatic ductal adenocarcinoma (PDAC), the most common form of PC. METHODS: This retrospective cohort study consisted of patients 50-84 years of age enrolled in either Kaiser Permanente Southern California (KPSC, model training, internal validation) or the Veterans Affairs (VA, external testing) between 2008 and 2017. The performance of random survival forests (RSF) and eXtreme gradient boosting (XGB) models were compared to that of COX proportional hazards regression (COX). Heterogeneity of the three models were assessed. RESULTS: The KPSC and the VA cohorts consisted of 1.8 and 2.7 million patients with 1792 and 4582 incident PDAC cases within 18 months, respectively. Predictors selected into all three models included age, abdominal pain, weight change, and glycated hemoglobin (A1c). Additionally, RSF selected change in alanine transaminase (ALT), whereas the XGB and COX selected the rate of change in ALT. The COX model appeared to have lower AUC (KPSC: 0.737, 95% CI 0.710-0.764; VA: 0.706, 0.699-0.714), compared to those of RSF (KPSC: 0.767, 0.744-0.791; VA: 0.731, 0.724-0.739) and XGB (KPSC: 0.779, 0.755-0.802; VA: 0.742, 0.735-0.750). Among patients with top 5% predicted risk from all three models (N = 29,663), 117 developed PDAC, of which RSF, XGB and COX captured 84 (9 unique), 87 (4 unique), 87 (19 unique) cases, respectively. CONCLUSIONS: The three models complement each other, but each has unique contributions.

Derivation and External Validation of Machine Learning-Based Model for Detection of Pancreatic Cancer.

INTRODUCTION: There is currently no widely accepted approach to screening for pancreatic cancer (PC). We aimed to develop and validate a risk prediction model for pancreatic ductal adenocarcinoma (PDAC), the most common form of PC, across 2 health systems using electronic health records. METHODS: This retrospective cohort study consisted of patients aged 50-84 years having at least 1 clinic-based visit over a 10-year study period at Kaiser Permanente Southern California (model training, internal validation) and the Veterans Affairs (VA, external testing). Random survival forests models were built to identify the most relevant predictors from >500 variables and to predict risk of PDAC within 18 months of cohort entry. RESULTS: The Kaiser Permanente Southern California cohort consisted of 1.8 million patients (mean age 61.6) with 1,792 PDAC cases. The 18-month incidence rate of PDAC was 0.77 (95% confidence interval 0.73-0.80)/1,000 person-years. The final main model contained age, abdominal pain, weight change, HbA1c, and alanine transaminase change (c-index: mean = 0.77, SD = 0.02; calibration test: P value 0.4, SD 0.3). The final early detection model comprised the same features as those selected by the main model except for abdominal pain (c-index: 0.77 and SD 0.4; calibration test: P value 0.3 and SD 0.3). The VA testing cohort consisted of 2.7 million patients (mean age 66.1) with an 18-month incidence rate of 1.27 (1.23-1.30)/1,000 person-years. The recalibrated main and early detection models based on VA testing data sets achieved a mean c-index of 0.71 (SD 0.002) and 0.68 (SD 0.003), respectively. DISCUSSION: Using widely available parameters in electronic health records, we developed and externally validated parsimonious machine learning-based models for detection of PC. These models may be suitable for real-time clinical application.

TSPO knockdown attenuates OGD/R-induced neuroinflammation and neural apoptosis by decreasing NLRP3 inflammasome activity through PPARγ pathway.

Ischemic stroke is a cerebrovascular disease which is related to brain function loss induced by cerebral ischemia. Translocator protein (TSPO) is an important regulator in inflammatory diseases, while its role in ischemic stroke remains largely unknown. This research aimed to explore the role and action mechanism of TSPO in oxygen-glucose deprivation/reperfusion (OGD/R)-induced neuron cell damage. The differentially expressed genes in ischemic stroke were predicted using GSE140275 dataset, DisGeNet, and GeneCards databases. Differentiated SH-SY5Y cells and primary neurons were subjected to transfection, and stimulated with OGD/R or MCC950 (NLRP3 inhibitor). Proteins were detected by western blotting and ELISA. Cell apoptosis was evaluated through CCK-8, caspase-3 activity and TUNEL assays. TSPO was upregulated in ischemic stroke and in SH-SY5Y cells and primary neurons after OGD/R treatment. TSPO silencing attenuated OGD/R-induced inflammation and apoptosis by decreasing NLRP3 inflammasome activity. TSPO downregulation increased PPARγ expression and decreased HMGB1 expression in OGD/R-treated cells, which was reversed by silencing PPARγ. PPARγ knockdown abolished the effect of TSPO silence on NLRP3 inflammasome activity, inflammation, and cell apoptosis in OGD/R-treated cells, while PPARγ overexpression alleviated OGD/R-induced injury in SH-SY5Y cells. In conclusion, TSPO knockdown attenuates neuroinflammation and neural apoptosis by decreasing NLRP3 inflammasome activity through PPARγ pathway.

Cardamonin attenuates cerebral ischemia/reperfusion injury by activating the HIF-1α/VEGFA pathway.

Cardamonin is a chalcone with neuroprotective activity. The aim of our study was to explore the functions and mechanism of action of cardamonin in ischemic stroke. Oxygen-glucose deprivation and reperfusion (OGD/R)-induced human brain microvascular endothelial cells (HBMECs) and middle cerebral artery occlusion (MCAO) mouse model were utilized to mimic ischemic stroke. Cell viability was analyzed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide. Permeability was investigated via fluorescein isothiocyanate-dextran assay. Apoptosis was detected by TdT-Mediated dUTP Nick End Labeling staining. Hypoxia-inducible factor (HIF)-1α and vascular endothelial growth factor A (VEGFA) protein levels were measured using Western blotting. Brain injury was evaluated by 2,3,5-triphenyltetrazolium chloride staining, neurological score and brain water content. The 37 overlapping targets of ischemic stroke and cardamonin were predicted to be associated with the HIF-1/VEGFA signaling. Cardamonin alleviated OGD/R-induced viability reduction and increase of permeability and apoptosis in HBMECs. Cardamonin increased OGD/R-induced activation of the HIF-1α/VEGFA pathway. Inhibition of the HIF-1α/VEGFA signaling using inhibitor relieved the effect of cardamonin on cell viability, permeability and apoptosis in HBMECs under OGD/R. Cardamonin mitigated brain injury and promoted activation of the HIF-1α/VEGFA signaling in MCAO-treated mice. Overall, cardamonin protected against OGD/R-induced HBMEC damage and MACO-induced brain injury through activating the HIF-1α/VEGFA pathway.

Fraxetin suppresses reactive oxygen species-dependent autophagy by the PI3K/Akt pathway to inhibit isoflurane-induced neurotoxicity in hippocampal neuronal cells.

Isoflurane, a common volatile anesthetic, has been widely used to provide general anesthesia in operations. However, exposure to isoflurane may cause widespread neurotoxicity in the developing animal brain. Fraxetin, a natural coumarin derivative extracted from the bark of Fraxinus rhynchophylla, possesses versatile pharmacological properties including anti-oxidative, anti-inflammatory, and neuroprotective effects. However, the effect and action mechanism of fraxetin on neurotoxicity induced by isoflurane are unknown. Reactive oxygen species (ROS) generation, cell viability, lactate dehydrogenase (LDH) release, and apoptosis were estimated by 2',7'-dichlorofluorescin-diacetate (DCFH-DA) staining, MTT, LDH release, and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end-labeling (TUNEL) staining assays, respectively. The protein levels of light chain 3 (LC3)-I, LC3-II, p62, protein kinase B (Akt), and phosphorylated Akt (p-Akt) were detected by western blot analysis. Isoflurane induced ROS, LDH release, apoptosis, and autophagy, but inhibited the viability in HT22 cells, which were overturned by fraxetin or ROS scavenger N-acetyl-L-cysteine. Fraxetin suppressed isoflurane-induced PI3K/Akt inactivation in HT22 cells. PI3K/Akt inactivation by LY294002 resisted the effects of fraxetin on isoflurane-induced autophagy and autophagy-modulated neurotoxicity in HT22 cells. In conclusion, fraxetin suppressed ROS-dependent autophagy by activating the PI3K/Akt pathway to inhibit isoflurane-induced neurotoxicity in hippocampal neuronal cells.

KIAA0101 knockdown inhibits glioma progression and glycolysis by inactivating the PI3K/AKT/mTOR pathway.

KIAA0101, a proliferating cell nuclear antigen (PCNA)-associated factor, is reported to be overexpressed and identified as an oncogene in several human malignancies. The purpose of this study is to determine the function and possible mechanism of KIAA0101 in glioma progression. KIAA0101 expression in glioma patients was analyzed by GSE50161 and GEPIA datasets. Kaplan-Meier survival analysis was used to evaluate the survival distributions. KIAA0101 expression in glioma cells were detected by qRT-PCR and western blot analyses. The function of KIAA0101 was investigated using MTT, flow cytometry, caspase-3 activity, and Transwell assays. Additionally, glycolytic flux was determined by measuring extracellular acidification rate (ECAR), glucose consumption, lactate production, and adenosine triphosphate (ATP) level. The changes of phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway were detected by western blot analysis. Results showed that KIAA0101 was upregulated in glioma tissues and cells. High KIAA0101 expression predicted a poor prognosis in glioma patients. KIAA0101 depletion impeded cell proliferation, migration, and invasion and triggered apoptosis in glioma cells. KIAA0101 silencing reduced the ECAR, glucose consumption, lactate production, and ATP level in glioma cells, suggesting that KIAA0101 knockdown inhibited glycolysis in glioma cells. Mechanistically, KIAA0101 knockdown inhibited the PI3K/AKT/mTOR pathway. In conclusion, KIAA0101 silencing inhibited glioma progression and glycolysis by inactivating the PI3K/AKT/mTOR pathway.