SLC7A11 promotes EMT and metastasis in invasive pituitary neuroendocrine tumors by activating the PI3K/AKT signaling pathway.

Invasive pituitary neuroendocrine tumors (PitNETs) are the most prevalent types of intracranial and neuroendocrine tumors. Their aggressive growth and difficulty in complete resection result in a high recurrence rate. Cystine transporter solute carrier family 7 member 11 (SLC7A11) is overexpressed in various cancers, which contributes to tumor growth, progression, and metastasis by promoting cystine uptake and glutathione biosynthesis. We identified SLC7A11 as an invasive biomarker based on three Gene Expression Omnibus cohorts. This study aimed to investigate the role of SLC7A11 in invasive PitNETs. Cell proliferation was assessed using CCK-8 and colony formation assays, while cell apoptosis was estimated with flow cytometry. Wound healing assays and transwell assays were utilized to evaluate migration and invasion ability. Our findings demonstrated that SLC7A11 was markedly upregulated in invasive PitNETs, and was associated with the invasiveness of PitNETs. Knockdown of SLC7A11 could largely suppress tumor cell proliferation, migration, and invasion, while inducing apoptosis. Furthermore, SLC7A11 depletion was implicated in regulating epithelial-mesenchymal transition and inactivating the PI3K/AKT signaling pathway. These insights suggest SLC7A11 as a potential therapeutic target for invasive PitNETs.

Investigation of cuproptosis regulator-mediated modification patterns and SLC30A7 function in GBM.

BACKGROUND: Copper-dependent controlled cell death (cuproptosis) is a novel cell death modality that is distinct from known cell death mechanisms. Nonetheless, the potential role of the cuproptosis regulator in tumour microenvironment (TME) of GBM remains unknown. METHODS: Based on 13 widely recognised cuproptosis regulators, the cuproptosis regulation patterns and the biological characteristics of each pattern were comprehensively assessed in GBMs. Machine learning strategies were used to construct a CupScore to quantify the cuproptosis regulation patterns of individual tumours. A PPI network was constructed to predict core-associated genes of cuproptosis regulators. The function of the novel cuproptosis regulators SLC30A7 was examined by in vitro and in vivo experiment. RESULTS: We identified three distinct cuproptosis regulation patterns, including immune activation, metabolic activation, and immunometabolic double deletion patterns. The CupScore was shown to predict the abundance of tumour inflammation, molecular subtype, stromal activity, gene variation, signalling pathways, and patient prognosis. The low CupScore subtype was characterised by immune activation, isocitrate dehydrogenase mutations, sensitivity to chemotherapy, and clinical benefits. The high CupScore subtype was characterised by activation of the stroma and metabolism and poor survival. Novel cuproptosis regulator SLC30A7 knockdown inhibited the cuproptosi via JAK2/STAT3/ATP7A pathway in GBM. CONCLUSION: Cuproptosis regulators have been shown to play a vital role in TME complexity. Constructing CupScores were trained to evaluate the regulation patterns of cuproptosis in individual tumours. The novel cuproptosis-related genes SLC30A7 was involved in regulation the tumorigenicity of GBM cell via JAK2/STAT3/ATP7A pathway in vitro and in vivo.

Identification of vaccine candidates against rhodococcus equi by combining pangenome analysis with a reverse vaccinology approach.

Rhodococcus equi (R. equi) is a zoonotic opportunistic pathogen that can cause life-threatening infections. The rapid evolution of multidrug-resistant R. equi and the fact that there is no currently licensed effective vaccine against R. equi warrant the need for vaccine development. Reverse vaccinology (RV), which involves screening a pathogen's entire genome and proteome using various web-based prediction tools, is considered one of the most effective approaches for identifying vaccine candidates. Here, we performed a pangenome analysis to determine the core proteins of R. equi. We then used the RV approach to examine the subcellular localization, host and gut flora homology, antigenicity, transmembrane helices, physicochemical properties, and immunogenicity of the core proteins to select potential vaccine candidates. The vaccine candidates were then subjected to epitope mapping to predict the exposed antigenic epitopes that possess the ability to bind with major histocompatibility complex I/II (MHC I/II) molecules. These vaccine candidates and epitopes will form a library of elements for the development of a polyvalent or universal vaccine against R. equi. Sixteen R. equi complete proteomes were found to contain 6,238 protein families, and the core proteins consisted of 3,969 protein families (∼63.63% of the pangenome), reflecting a low degree of intraspecies genomic variability. From the pool of core proteins, 483 nonhost homologous membrane and extracellular proteins were screened, and 12 vaccine candidates were finally identified according to their antigenicity, physicochemical properties and other factors. These included four cell wall/membrane/envelope biogenesis proteins; four amino acid transport and metabolism proteins; one cell cycle control, cell division and chromosome partitioning protein; one carbohydrate transport and metabolism protein; one secondary metabolite biosynthesis, transport and catabolism protein; and one defense mechanism protein. All 12 vaccine candidates have an experimentally validated 3D structure available in the protein data bank (PDB). Epitope mapping of the candidates showed that 16 MHC I epitopes and 13 MHC II epitopes with the strongest immunogenicity were exposed on the protein surface, indicating that they could be used to develop a polypeptide vaccine. Thus, we utilized an analytical strategy that combines pangenome analysis and RV to generate a peptide antigen library that simplifies the development of multivalent or universal vaccines against R. equi and can be applied to the development of other vaccines.

Establishment of predictive nomogram and web-based survival risk calculator for malignant pleural mesothelioma: A SEER database analysis.

Background: Malignant pleural mesothelioma (MPM) is an uncommon condition with limited available therapies and dismal prognoses. The purpose of this work was to create a multivariate clinical prognostic nomogram and a web-based survival risk calculator to forecast patients' prognoses. Methods: Using a randomization process, training and validation groups were created for a retrospective cohort study that examined the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 for individuals diagnosed with MPM (7:3 ratio). Overall survival (OS) and cancer-specific survival (CSS) were the primary endpoints. Clinical traits linked to OS and CSS were identified using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, which was also utilized to develop nomogram survival models and online survival risk calculators. By charting the receiver operating characteristic (ROC), consistency index (C-index), calibration curve, and decision curve analysis (DCA), the model's performance was assessed. The nomogram was used to classify patients into various risk categories, and the Kaplan-Meier method was used to examine each risk group's survival rate. Results: The prognostic model comprised a total of 1978 patients. For the total group, the median OS and CSS were 10 (9.4-10.5) and 11 (9.4-12.6) months, respectively. As independent factors for OS and CSS, age, gender, insurance, histology, T stage, M stage, surgery, and chemotherapy were chosen. The calibration graphs demonstrated good concordance. In the training and validation groups, the C-indices for OS and CSS were 0.729, 0.717, 0.711, and 0.721, respectively. Our nomogram produced a greater clinical net benefit than the AJCC 7th edition, according to DCA and ROC analysis. According to the cut-off values of 171 for OS and 189 for CSS of the total scores from our nomogram, patients were classified into two risk groups. The P-value < 0.001 on the Kaplan-Meier plot revealed a significant difference in survival between the two patient groups. Conclusions: Patient survival in MPM was correctly predicted by the risk evaluation model. This will support clinicians in the practice of individualized medicine.

CCR5 as a Prognostic Factor in Lower-Grade Glioma is Involved in the Remodeling of the Tumor Microenvironment.

Background: Lower-grade gliomas (LGGs) carry a high risk of malignant transformation, leading to severe neurologic deterioration and ultimately, death. The tumor microenvironment (TME) plays an essential role in tumor maintenance, progression, and immunotherapy resistance. Therefore, the LGG TME deserves comprehensive exploration for a novel therapeutic target. Methods: The ESTIMATE algorithm was used to estimate infiltrating stromal and immune cells of LGG patients obtained from the Cancer Genome Atlas (TCGA) database. Kaplan-Meier analysis was performed to classify survival differences. TME-related differentially expressed genes were identified between the low- and high-immune/stromal groups. Hub genes were screened by constructing protein-protein interaction networks and performing the Cox regression analysis. Differential analysis, survival analysis, gene set enrichment analysis, and clinical relevance analysis specific to hub genes were evaluated by using the TCGA and the Chinese Glioma Genome Atlas datasets, and the results were validated by qRT-PCR, Western blotting, and immunohistochemistry in tissues from LGG patients. Results: The immune and stromal components in TME were negatively related to patient prognosis. Differentially expressed genes sharing immune score and stromal score were mainly involved in the immune response. C-C chemokine receptor type 5 (CCR5), as only a hub gene, was significantly higher in LGG patients than normal patients and negatively correlated with the prognosis of patients. High-expression CCR5 was positively related to immune-related and tumor progression pathways. CCR5 protein expression was higher in LGG with isocitrate dehydrogenase wildtype. Validated results showed that CCR5 was upregulated in LGG tissues at mRNA and protein levels and could affect immune cell infiltration. These results suggested that CCR5 was a potential indicator for the status of TME. Conclusion: Glioma cells remodel the immune microenvironment through the high expression of CCR5 and lead to a poor prognosis in patients with LGG. The inhibition of CCR5 may contribute to the efficacy of LGG immunotherapy.

Effectiveness Comparisons of Drug Therapy on Chronic Subdural Hematoma Recurrence: A Bayesian Network Meta-Analysis and Systematic Review.

Objectives: We aim to compare the effectiveness of different drug treatments in improving recurrence in patients with chronic subdural hematoma (CSDH). Methods: Eligible randomized controlled trials (RCTs) and prospective trials were searched in PubMed, Cochrane Library, and Embase, from database inception to December 2021. After the available studies following inclusion and exclusion criteria were screened, the main outcome measures were strictly extracted. Taking the random-effects model, dichotomous data were determined and extracted by odds ratio (OR) with 95% credible interval (CrI), and a surface under the cumulative ranking curve (SUCRA) was generated to calculate the ranking probability of comparative effectiveness among each drug intervention. Moreover, we used the node-splitting model to evaluate inconsistency between direct and indirect comparisons of our network meta-analysis (NMA). Funnel plots were used to evaluate publication bias. Results: From the 318 articles found during initial citation screening, 11 RCTs and 3 prospective trials (n = 3,456 participants) were ultimately included in our study. Our NMA results illustrated that atorvastatin + dexamethasone (ATO+DXM) (OR = 0.06, 95% CrI 0.01, 0.89) was the most effective intervention to improve recurrence in patients with CSDH (SUCRA = 89.40%, 95% CrI 0.29, 1.00). Four drug interventions [ATO+DXM (OR = 0.06, 95% CrI 0.01, 0.89), DXM (OR = 0.18, 95% CrI 0.07, 0.41), tranexamic acid (TXA) (OR = 0.26, 95% CrI 0.07, 0.41), and ATO (OR = 0.41, 95% CrI 0.12, 0.90)] achieved statistical significance in improving recurrence in CSDH patients compared with the placebo (PLB) or standard neurosurgical treatment (SNT) group. Conclusion: Our NMA showed that ATO+DXM, DXM, ATO, and TXA had definite efficacy in improving recurrence in CSDH patients. Among them, ATO+DXM is the best intervention for improving recurrence in patients with CSDH in this particular population. Multicenter rigorous designed prospective randomized trials are still needed to evaluate the role of various drug interventions in improving neurological function or outcome. Systematic Review Registration: (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=299491), identifier (CRD 42022299491).

Diffusion-weighted imaging lesions after endovascular treatment of cerebral aneurysms: A network meta-analysis.

Background: Thromboembolism is one of the common complications in endovascular treatments including coiling alone, stent-assisted coiling (SAC), balloon-assisted coiling (BAC), and flow-diverting (FD) stents. Such treatments are widely used in intracranial aneurysms (IAs), which usually present as positive lesions in diffusion-weighted imaging (DWI). Whether these adjunctive techniques increase postprocedural DWI-positive lesions after endovascular treatment remains unclear. Methods: A thorough electronic search for the literature published in English between January 2000 and October 2022 was conducted on PubMed, Medline, and EMBASE. Eighteen studies (3 cohort studies and 15 case-control studies) involving 1,843 patients with unruptured IAs (UIAs) were included. We performed a frequentist framework network meta-analysis (NMA) to compare the rank risks of cerebral thromboembolism of the above four endovascular treatments. The incoherence test was used to analyze the statistical disagreement between direct and indirect evidence. Funnel plots were used to analyze publication bias. Results: The incidences of DWI lesions in patients who received FD stents, SAC, BAC, and coiling alone were 66.1% (109/165), 37.6% (299/795), 31.1% (236/759), and 25.6% (236/921). The incidence of DWI lesions in patients who received FD stents was higher than that in patients who received SAC [OR: 2.40; 95% CI (1.15, 5.00), P < 0.05], BAC [OR: 2.62; 95% CI (1.19, 5.77), P < 0.05], or coiling alone [OR: 2.77; 95% CI (1.26, 6.07), P < 0.05]. The incoherence test showed preferable consistency in this NMA. No obvious publication bias was found in the funnel plot. Conclusion: FD stent placement brings more ischemic lesions identified by DWI than any other procedures for patients with UIA. The characteristics of FD stents may result in a high incidence of DWI lesions.

A Novel Immune and Stroma Related Prognostic Marker for Invasive Breast Cancer in Tumor Microenvironment: A TCGA Based Study.

Background: Breast cancer (BC) is the most frequent cancer in women. The tumor microenvironment (TME), consisting of blood vessels, immune cells, fibroblasts, and extracellular matrix, plays a pivotal role in tumorigenesis and progression. Increasing evidence has emphasized the importance of TME, especially the immune components, in patients with BC. Nevertheless, we still lack a deep understanding of the correlation between tumor invasion and TME status. Methods: Transcriptome and clinical data were retrieved from The Cancer Genome Atlas (TCGA) database. ESTIMATE algorithm was applied for quantifying stromal and immune scores. Then we screened out the differentially expressed genes (DEGs) through the intersection analysis. Furthermore, the establishment of protein-protein interaction (PPI) network and univariate COX regression analysis were utilized to determine the core genes in DEGs. In addition, we also performed Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis to distinguish the function of crucial gene expression and the proportion of tumor-infiltrating immune cells (TICs), respectively. Results: A total of 1178 samples (112 normal samples and 1066 tumor samples) were extracted from TCGA for calculation, and 226 DEGs were obtained from this assessment. Further intersection analysis revealed eight key genes, including ITK, CD3E, CCL19, CD2, SH2D1A, CD5, SLAMF6, SPN, which were proven to correlate with BC status. Moreover, ITK was picked out for further study. The results illustrated that high expression of BC patients had a more prolonged overall survival (OS) time than ITK low expression BC patients (p = 0.009), and ITK expression also presented the statistical significance in age, TNM staging, tumor size classification, and metastasis classification. Additionally, GSEA and CIBERSORT analysis indicated that ITK expression had an association with immune activity in TME. Conclusion: ITK may be a potential indicator for prognosis prediction in patients with BC, and its biological behavior may promote our understanding of the molecular mechanism of tumor progression and targeted therapy.

Identification of Immune-Related lncRNA Prognostic Signature and Molecular Subtypes for Glioblastoma.

Background: Glioblastoma multiforme (GBM) is extensively genetically and transcriptionally heterogeneous, which poses challenges for classification and management. Long noncoding RNAs (lncRNAs) play a critical role in the development and progression of GBM, especially in tumor-associated immune processes. Therefore, it is necessary to develop an immune-related lncRNAs (irlncRNAs) signature. Methods: Univariate and multivariate Cox regression analyses were utilized to construct a prognostic model. GBM-specific CeRNA and PPI network was constructed to predict lncRNAs targets and evaluate the interactions of immune mRNAs translated proteins. GO and KEGG pathway analyses were used to show the biological functions and pathways of CeRNA network-related immunity genes. Consensus Cluster Plus analysis was used for GBM gene clustering. Then, we evaluated GBM subtype-specific prognostic values, clinical characteristics, genes and pathways, immune infiltration access single cell RNA-seq data, and chemotherapeutics efficacy. The hub genes were finally validated. Results: A total of 17 prognostically related irlncRNAs were screened to build a prognostic model signature based on six key irlncRNAs. Based on GBM-specific CeRNAs and enrichment analysis, PLAU was predicted as a target of lncRNA-H19 and mainly enriched in the malignant related pathways. GBM subtype-A displayed the most favorable prognosis, high proportion of genes (IDH1, ATRX, and EGFR) mutation, chemoradiotherapy, and low risk and was characterized by low expression of four high-risk lncRNAs (H19, HOTAIRM1, AGAP2-AS1, and AC002456.1) and one mRNA KRT8. GSs with poor survival were mainly infiltrated by mesenchymal stem cells (MSCs) and astrocyte, and were more sensitive to gefitinib and roscovitine. Among GSs, three hub genes KRT8, NGFR, and TCEA3, were screened and validated to potentially play feasible oncogenic roles in GBM. Conclusion: Construction of lncRNAs risk model and identification of GBM subtypes based on 17 irlncRNAs, which suggesting that irlncRNAs had the promising potential for clinical immunotherapy of GBM.

Construction of Novel Methylation-Driven Gene Model and Investigation of PARVB Function in Glioblastoma.

BACKGROUND: Glioblastoma multiforme (GBM) is characterized by widespread genetic and transcriptional heterogeneity. Aberrant DNA methylation plays a vital role in GBM progression by regulating gene expression. However, little is known about the role of methylation and its association with prognosis in GBM. Our aim was to explore DNA methylation-driven genes (DMDGs) and provide evidence for survival prediction and individualized treatment of GBM patients. METHODS: Use of the MethylMix R package identified DMDGs in GBM. The prognostic signature of DMDGs based on the risk score was constructed by multivariate Cox regression analysis. Receiver operating characteristics (ROC) curve and C-index were applied to assess the predictive performance of the DMDG prognostic signature. The predictive ability of the multigene signature model was validated in TCGA and CGGA cohorts. Finally, the role of DMDG ß-Parvin (PARVB) was explored in vitro. RESULTS: The prognostic signature of DMDGs was constructed based on six genes (MDK, NMNAT3, PDPN, PARVB, SERPINB1, and UPP1). The low-risk cohort had significantly better survival than the high-risk cohort (p < 0.001). The area under the curve of the ROC of the six-gene signature was 0.832, 0.927, and 0.980 within 1, 2, and 3 years, respectively. The C-index of 0.704 indicated superior specificity and sensitivity. The six-gene model has been demonstrated to be an independent prognostic factor for GBM. In addition, joint survival analysis indicated that the MDK, NMNAT3, PARVB, SERPINB1, and UPP1 genes were significantly associated with prognosis and therapeutic targets for GBM. Importantly, our DMDG prognostic model was more suitable and accurate for low-grade gliomas. Finally, we verified that PARVB induced epithelial-mesenchymal transition partially through the JAK2/STAT3 pathway, which in turn promoted GBM cell proliferation, migration, and invasion. CONCLUSION: This study demonstrated the potential value of the prognostic signature of DMDGs and provided important bioinformatic and potential therapeutic target data to facilitate individualized treatment for GBM, and to elucidate the specific mechanism by which PARVB promotes GBM progression.

Effectiveness comparisons of drug therapies for postoperative aneurysmal subarachnoid hemorrhage patients: network meta­analysis and systematic review.

OBJECTIVE: To compare the effectiveness of various drug interventions in improving the clinical outcome of postoperative patients after aneurysmal subarachnoid hemorrhage (aSAH) and assist in determining the drugs of definite curative effect in improving clinical prognosis. METHODS: Eligible Randomized Controlled Trials (RCTs) were searched in databases of PubMed, EMBASE, and Cochrane Library (inception to Sep 2020). Glasgow Outcome Scale (GOS) score, Extended Glasgow Outcome Scale (GOSE) score or modified Rankin Scale (mRS) score was used as the main outcome measurements to evaluate the efficacy of various drugs in improving the clinical outcomes of postoperative patients with aSAH. The network meta-analysis (NMA) was conducted based on a random-effects model, dichotomous variables were determined by using odds ratio (OR) with 95% confidence interval (CI), and a surface under the cumulative ranking curve (SUCRA) was generated to estimate the ranking probability of comparative effectiveness among different drug therapies. RESULTS: From the 493 of initial citation screening, forty-four RCTs (n = 10,626 participants) were eventually included in our analysis. Our NMA results showed that cilostazol (OR = 3.35,95%CI = 1.50,7.51) was the best intervention to improve the clinical outcome of patients (SUCRA = 87.29%, 95%CrI 0.07-0.46). Compared with the placebo group, only two drug interventions [nimodipine (OR = 1.61, 95%CI 1.01,2.57) and cilostazol (OR = 3.35, 95%CI 1.50, 7.51)] achieved significant statistical significance in improving the clinical outcome of patients. CONCLUSIONS: Both nimodipine and cilostazol have exact curative effect to improve the outcome of postoperative patients with aSAH, and cilostazol may be the best drug to improve the outcome of patients after aSAH operation. Our study provides implications for future studies that, the combination of two or more drugs with relative safety and potential benefits (e.g., nimodipine and cilostazol) may improve the clinical outcome of patients more effectively.

Aberrant miRNAs Regulate the Biological Hallmarks of Glioblastoma.

GBM is the highest incidence in primary intracranial malignancy, and it remains poor prognosis even though the patient is gave standard treatment. Despite decades of intense research, the complex biology of GBM remains elusive. In view of eight hallmarks of cancer which were proposed in 2011, studies related to the eight biological capabilities in GBM have made great progress. From these studies, it can be inferred that miRs, as a mode of post-transcriptional regulation, are involved in regulating these malignant biological hallmarks of GBM. Herein, we discuss state-of-the-art research on how aberrant miRs modulate the eight hallmarks of GBM. The upregulation of 'oncomiRs' or the genetic loss of tumor suppressor miRs is associated with these eight biological capabilities acquired during GBM formation. Furthermore, we also discuss the applicable clinical potential of these research results. MiRs may aid in the diagnosis and prognosis of GBM. Moreover, miRs are also therapeutic targets of GBM. These studies will develop and improve precision medicine for GBM in the future.