Integrated profiling identifies ferredoxin 1 as an immune-related biomarker of malignant phenotype in glioma.

Background: Glioma, a highly resistant and recurrent type of central nervous system tumor, poses a significant challenge in terms of effective drug treatments and its associated mortality rates. Despite the discovery of Ferredoxin 1 (FDX1) as a crucial participant in cuproptosis, an innovative mechanism of cellular demise, its precise implications for glioma prognosis and tumor immune infiltration remain inadequately elucidated. Methods: To analyze pan-cancer data, we employed multiple public databases. Gene expression evaluation was performed using tissue microarray (TMA) and single-cell sequencing data. Furthermore, four different approaches were employed to assess the prognostic importance of FDX1 in glioma. We conducted the analysis of differential expression genes (DEGs) and Gene Set Enrichment Analysis (GSEA) to identify immune-related predictive signaling pathways. Somatic mutations were assessed using Tumor Mutation Burden (TMB) and waterfall plots. Immune cell infiltration was evaluated with five different algorithms. Furthermore, we performed in vitro investigations to evaluate the biological roles of FDX1 in glioma. Results: Glioma samples exhibited upregulation of FDX1, which in turn predicted poor prognosis and was positively associated with unfavorable clinicopathological characteristics. Notably, the top four enriched signaling pathways were immune-related, and the discovery revealed a connection between the expression of FDX1 and the frequency of mutations or the TMB. The FDX1_high group exhibited heightened infiltration of immune cells, and there existed a direct association between the expression of FDX1 and the regulation of immune checkpoint. In vitro experiments demonstrated that FDX1 knockdown reduced proliferation, migration, invasion and transition from G2 to M phase in glioma cells. Conclusion: In glioma, FDX1 demonstrated a positive association with the advancement of malignancy and changes in the infiltration of immune cells.

A prognostic signature based on snoRNA predicts the overall survival of lower-grade glioma patients.

Introduction: Small nucleolar RNAs (snoRNAs) are a group of non-coding RNAs enriched in the nucleus which direct post-transcriptional modifications of rRNAs, snRNAs and other molecules. Recent studies have suggested that snoRNAs have a significant role in tumor oncogenesis and can be served as prognostic markers for predicting the overall survival of tumor patients. Methods: We screened 122 survival-related snoRNAs from public databases and eventually selected 7 snoRNAs that were most relevant to the prognosis of lower-grade glioma (LGG) patients for the establishment of the 7-snoRNA prognostic signature. Further, we combined clinical characteristics related to the prognosis of glioma patients and the 7-snoRNA prognostic signature to construct a nomogram. Results: The prognostic model displayed greater predictive power in both validation set and stratification analysis. Results of enrichment analysis revealed that these snoRNAs mainly participated in the post-transcriptional process such as RNA splicing, metabolism and modifications. In addition, 7-snoRNA prognostic signature were positively correlated with immune scores and expression levels of multiple immune checkpoint molecules, which can be used as potential biomarkers for immunotherapy prediction. From the results of bioinformatics analysis, we inferred that SNORD88C has a major role in the development of glioma, and then performed in vitro experiments to validate it. The results revealed that SNORD88C could promote the proliferation, invasion and migration of glioma cells. Discussion: We established a 7-snoRNA prognostic signature and nomogram that can be applied to evaluate the survival of LGG patients with good sensitivity and specificity. In addition, SNORD88C could promote the proliferation, migration and invasion of glioma cells and is involved in a variety of biological processes related to DNA and RNA.

The research landscape of immunology research in spinal cord injury from 2012 to 2022.

Background: Spinal cord injury (SCI) is defined as traumatic damage to the spinal cord, affecting over three million patients worldwide, and there is still no treatment for the injured spinal cord itself. In recent years, immunology research on SCI has been published in various journals. Methods: To systematically analyze the research hotspots and dynamic scientific developments of immunology research in SCI, we conducted a bibliometric and knowledge map analysis to help researchers gain a global perspective in this research field. Results: The bibliometric study we completed included 1788 English-language papers published in 553 journals by 8861 authors from 1901 institutions in 66 countries/regions. Based on the references and keyword analysis, researchers in the past 10 years have mainly focused on the research directions of "monocyte chemoattractor protein 1," "nitric oxide," "pain," and "nitric oxide synthase" related to immunological research in SCI. However, with the development of other new directions such as "extracellular vesicles" (2019-2022), "Regenerative medicine" (2019-2022), "stromal cells" (2018-2022), "motor recovery" (2019-2022), and "glial activation" (2019-2022). Researchers prefer to study the application of regenerative strategies in SCI, the mechanism of extracellular vesicles in the development of SCI, the activation of spinal glial cells in SCI, and the pathways of motor recovery. This bibliometric analysis of immunology research in SCI summarizes the current status of this research field. The relationship between extracellular vesicles, regenerative medicine, stromal cells, motor recovery, and glial activation is currently a major research frontier. Further research and cooperation worldwide need to be enhanced. Conclusion: We believe that our research can help researchers quickly grasp the current hotspot of immunology research in SCI and determine a new direction for future research.

ChatGPT encounters multiple opportunities and challenges in neurosurgery.

BACKGROUND: ChatGPT, powered by the GPT model and Transformer architecture, has demonstrated remarkable performance in the domains of medicine and healthcare, providing customized and informative responses. In our study, we investigated the potential of ChatGPT in the field of neurosurgery, focusing on its applications at the patient, neurosurgery student/resident, and neurosurgeon levels. METHOD: The authors conducted inquiries with ChatGPT from the viewpoints of patients, neurosurgery students/residents, and neurosurgeons, covering a range of topics, such as disease diagnosis, treatment options, prognosis, rehabilitation, and patient care. The authors also explored concepts related to neurosurgery, including fundamental principles and clinical aspects, as well as tools and techniques to enhance the skills of neurosurgery students/residents. Additionally, the authors examined disease-specific medical interventions and the decision-making processes involved in clinical practice. RESULTS: The authors received individual responses from ChatGPT, but they tended to be shallow and repetitive, lacking depth and personalization. Furthermore, ChatGPT may struggle to discern a patient's emotional state, hindering the establishment of rapport and the delivery of appropriate care. The language used in the medical field is influenced by technical and cultural factors, and biases in the training data can result in skewed or inaccurate responses. Additionally, ChatGPT's limitations include the inability to conduct physical examinations or interpret diagnostic images, potentially overlooking complex details and individual nuances in each patient's case. Moreover, its absence in the surgical setting limits its practical utility. CONCLUSION: Although ChatGPT is a powerful language model, it cannot substitute for the expertise and experience of trained medical professionals. It lacks the capability to perform physical examinations, make diagnoses, administer treatments, establish trust, provide emotional support, and assist in the recovery process. Moreover, the implementation of Artificial Intelligence in healthcare necessitates careful consideration of legal and ethical concerns. While recognizing the potential of ChatGPT, additional training with comprehensive data is necessary to fully maximize its capabilities.

Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas.

Background: Immunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG). Materials and methods: We identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation. Results: 32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells. Conclusion: We established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy.

miR-33b in human cancer: Mechanistic and clinical perspectives.

The microRNAs (miRNAs), an extensive class of small noncoding RNAs (∼22 nucleotides), have been shown to have critical functions in various biological processes during development. miR-33b (or hsa-miR-33b) is down-regulated in cancer of multiple systems. Notably, at least 27 protein-coding genes can be targeted by miR-33b. miR-33b regulates the cell cycle, cell proliferation, various metabolism pathways, epithelial-mesenchymal transition (EMT), cancer cell invasion and migration, etc. In prostate cancer, Cullin 4B (CUL4B) can be recruited to the promoter to inhibit the expression of miR-33b. In gastric cancer, the hypermethylation of the CpG island regulated the expression of miR-33b. Besides, miR-33b could be negatively regulated by 7 competing-endogenous RNAs (ceRNAs), which are all long non-coding RNAs (lncRNAs). There are at least 4 signaling pathways, including NF-κB, MAP8, Notch1, and Wnt/ß-catenin signaling pathways, which could be regulated partially by miR-33b. Additionally, low expression of miR-33b was associated with clinicopathology and prognosis in cancer patients. In addition, the aberrant expression of miR-33b was connected with the resistance of cancer cells to 5 anticancer drugs (cisplatin, docetaxel, bortezomib, paclitaxel, and daunorubicin). Importantly, our work systematically summarizes the aberrant expression of miR-33b in various neoplastic diseases and the effect of its downregulation on the biological behavior of cancer cells. Furthermore, this review focuses on recent advances in understanding the molecular regulation mechanisms of miR-33b. Moreso, the relationship between the miR-33b expression levels and the clinicopathological data and prognosis of tumor patients was summarized for the first time. Overall, we suggest that the current studies of miR-33b are insufficient but provide potential hints and direction for future miR-33b-related research.

Leveraging a gene signature associated with disulfidptosis identified by machine learning to forecast clinical outcomes, immunological heterogeneities, and potential therapeutic targets within lower-grade glioma.

Background: Disulfidptosis, a newly defined type of programmed cell death, has emerged as a significant regulatory process in the development and advancement of malignant tumors, such as lower-grade glioma (LGG). Nevertheless, the precise biological mechanisms behind disulfidptosis in LGG are yet to be revealed, considering the limited research conducted in this field. Methods: We obtained LGG data from the TCGA and CGGA databases and performed comprehensive weighted co-expression network analysis, single-sample gene set enrichment analysis, and transcriptome differential expression analyses. We discovered nine genes associated with disulfidptosis by employing machine learning methods like Cox regression, LASSO regression, and SVM-RFE. These were later used to build a predictive model for patients with LGG. To confirm the expression level, functional role, and impact on disulfidptosis of ABI3, the pivotal gene of the model, validation experiments were carried out in vitro. Results: The developed prognostic model successfully categorized LGG patients into two distinct risk groups: high and low. There was a noticeable difference in the time the groups survived, which was statistically significant. The model's predictive accuracy was substantiated through two independent external validation cohorts. Additional evaluations of the immune microenvironment and the potential for immunotherapy indicated that this risk classification could function as a practical roadmap for LGG treatment using immune-based therapies. Cellular experiments demonstrated that suppressing the crucial ABI3 gene in the predictive model significantly reduced the migratory and invasive abilities of both SHG44 and U251 cell lines while also triggering cytoskeletal retraction and increased cell pseudopodia. Conclusion: The research suggests that the prognostic pattern relying on genes linked to disulfidptosis can provide valuable insights into the clinical outcomes, tumor characteristics, and immune alterations in patients with LGG. This could pave the way for early interventions and suggests that ABI3 might be a potential therapeutic target for disulfidptosis.

The role of lncRNA just proximal to XIST (JPX) in human disease phenotypes and RNA methylation: The novel biomarker and therapeutic target potential.

Increasing evidence suggests that long non-coding RNAs (lncRNAs) are closely related to the initialization and development of human diseases. lncRNA just proximal to XIST (JPX), as a newly identified lncRNA, has been reported to be aberrantly expressed and associated with pathophysiological traits in numerous diseases, particularly cancers. More importantly, JPX has been proven to play important roles in various biological functions, including cell proliferation, migration, invasion, apoptosis, chemoresistance, and differentiation. In addition, we discuss the diverse molecular mechanisms and correlation with RNA methylation of JPX in several cancers. In this Review, we summarize current studies on JPX's roles in diseases and its potential application as a biomarker for both diagnoses and prognoses and a therapeutic target in human diseases.

A practical and economical method for frontal sinus reconstruction after frontal craniotomy: A single-center experience with 140 patients.

Background: Frontal sinus exposure is a common consequence of frontal craniotomy. Cerebrospinal fluid leakage and infection are the major postoperative complications that may occur as a result of the open frontal sinus. The successful filling of the open frontal sinus provides an approach to prevent significant complications caused by frontal sinus exposure. Objective: This article describes a new technique to reconstruct the exposed frontal sinus cavity with the combined application of gelatin sponge and a vascularized pericranial flap. Methods: A total of 140 patients underwent frontal sinus reconstruction using gelfoam and vascularized pericranial flaps from 2016 to 2021. Gelatin sponge was used to fill the frontal sinus, and a vascularized pericranial flap was used to cover the frontal sinus when the bone flap was retracted. Results: Postoperative cerebrospinal fluid leakage and infection did not occur in any patient. Conclusion: Our results validated the effectiveness of our technique in the prevention of exposed frontal sinus-related postoperative complications.

Development of an Immune-Related LncRNA Prognostic Signature for Glioma.

INTRODUCTION: Glioma is the most common primary cancer of the central nervous system with dismal prognosis. Long noncoding RNAs (lncRNAs) have been discovered to play key roles in tumorigenesis in various cancers, including glioma. Because of the relevance between immune infiltrating and clinical outcome of glioma, identifying immune-related lncRNAs is urgent for better personalized management. MATERIALS AND METHODS: Single-sample gene set enrichment analysis (ssGSEA) was applied to estimate immune infiltration, and glioma samples were divided into high immune cell infiltration group and low immune cell infiltration group. After screening differentially expressed lncRNAs in two immune groups, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune-related prognostic signature. Additionally, we explored the correlation between immune infiltration and the prognostic signature. RESULTS: A total of 653 samples were appropriate for further analyses, and 10 lncRNAs were identified as immune-related lncRNAs in glioma. After univariate Cox regression and LASSO Cox regression analysis, six lncRNAs were identified to construct a prognostic signature for glioma, which could be taken as independent prognostic factors in both univariate and multivariate Cox regression analyses. Moreover, risk score was significantly correlated with all the 29 immune-related checkpoint expression (p < 0.05) in ssGSEA except neutrophils (p = 0.43). CONCLUSION: The study constructed an immune-related prognostic signature for glioma, which contributed to improve clinical outcome prediction and guide immunotherapy.

METTL7B is a novel prognostic biomarker of lower-grade glioma based on pan-cancer analysis.

Methyltransferase-like 7B (METTL7B) is a member of the methyltransferase-like protein family that plays an important role in the development and progression of tumors. However, its prognostic value and the correlation of METTL7B expression and tumor immunity in some cancers remain unclear. By analyzing online data, we found that METTL7B is abnormally overexpressed in multiple human tumors and plays an important role in the overall survival (OS) of patients with 8 cancer types and disease-free survival (DFS) of patients with 5 cancer types. Remarkably, METTL7B expression was positively correlated with the OS and DFS of patients with lower-grade glioma (LGG). In addition, a positive correlation between METTL7B expression and immune cell infiltration in LGG was observed. Moreover, we identified a strong correlation between METTL7B expression and immune checkpoint gene expression in kidney chromophobe (KICH), LGG and pheochromocytoma and paraganglioma (PCPG). Furthermore, METTL7B was involved in the extracellular matrix (ECM) and immune-related pathways in LGGs. Finally, in vitro experiments showed that knockdown of METTL7B inhibited the growth, migration, invasion and the epithelial-mesenchymal transition (EMT) of LGG cells. METTL7B expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in LGG.