The PTEN-associated immune prognostic signature reveals the landscape of the tumor microenvironment in glioblastoma

Immunogenic cell death genes in single-cell and transcriptome analyses perspectives from a prognostic model of cervical cancer

Background

The role of immunogenic cell death (ICD) in cervical cancer (CESC) is not well understood. This study sought to investigate the significance of ICD in CESC and to establish an ICDRs prognostic model to improve immunotherapy efficacy for patients with cervical cancer.

Methods

ICD-associated genes were screened at the single-cell and transcriptome levels based on AddModuleScore, single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network (WGCNA) analysis. Immunogenic cell death-related features (ICDRs) were constructed using multiple machine algorithms, and ICDRs were evaluated in training and validation sets to provide quantitative tools for predicting prognosis in clinical practice. Predictive models were used to risk subgroups for response to immunotherapy, as well as drug sensitivity. Finally, the expression of ICD-related genes was verified by RT-qPCR.

Results

Through an integrated analysis of single-cell data, transcriptomic profiling, and computational modeling, seven ICD-related genes were identified as highly prognostic for CESC patients. Multivariate analysis demonstrated that low-risk patients had significantly better overall survival compared to high-risk patients, confirming the model as an independent prognostic tool. Assessments of the tumor microenvironment (TME), mutation characteristics, and drug sensitivity within ICDRs risk subgroups indicated a stronger immunotherapy response in the low-risk group.

Identification of Prognostic Genes Related to Cell Senescence and Lipid Metabolism in Glioblastoma Based on Transcriptome and Single-Cell RNA-Seq Data

Glioblastoma (GBM) is the most aggressive primary brain cancer, with poor prognosis due to its aggressive behavior and high heterogeneity. This study aimed to identify cellular senescence (CS) and lipid metabolism (LM)-related prognostic genes to improve GBM prognosis and treatment. Transcriptome and scRNA-seq data, CS-associated genes (CSAGs), and LM-related genes (LMRGs) were acquired from public databases. Prognostic genes were identified by intersecting CSAGs, LMRGs, and differentially expressed genes (DEGs), followed by WGCNA and univariate Cox regression. A risk model and nomogram were constructed. Analyses covered clinicopathological features, immune microenvironment, somatic mutations, and drug sensitivity. GBM scRNA-seq data identified key cells and prognostic gene expression. SOCS1 and PHB2 were identified as prognostic markers, contributing to the construction of a robust risk model with excellent predictive ability. High-risk group (HRG) patients had poorer survival, higher immune and stromal scores, and distinct somatic mutation profiles. Drug sensitivity analysis revealed significant differences in IC50 values. In microglia differentiation, SOCS1 and PHB2 showed dynamic expression patterns. These findings provide new strategies for GBM prognosis and treatment.

Genes to therapy: a comprehensive literature review of whole-exome sequencing in neurology and neurosurgery

Whole-exome sequencing (WES), a ground-breaking technology, has emerged as a linchpin in neurology and neurosurgery, offering a comprehensive elucidation of the genetic landscape of various neurological disorders. This transformative methodology concentrates on the exonic portions of DNA, which constitute approximately 1% of the human genome, thus facilitating an expedited and efficient sequencing process. WES has been instrumental in advancing our understanding of neurodegenerative diseases, neuro-oncology, cerebrovascular disorders, and epilepsy by revealing rare variants and novel mutations and providing intricate insights into their genetic complexities. This has been achieved while maintaining a substantial diagnostic yield, thereby offering novel perspectives on the pathophysiology and personalized management of these conditions. The utilization of WES boasts several advantages over alternative genetic sequencing methodologies, including cost-effectiveness, reduced incidental findings, simplified analysis and interpretation process, and reduced computational demands. However, despite its benefits, there are challenges, such as the interpretation of variants of unknown significance, cost considerations, and limited accessibility in resource-constrained settings. Additionally, ethical, legal, and social concerns are raised, particularly in the context of incidental findings and patient consent. As we look to the future, the integration of WES with other omics-based approaches could help revolutionize the field of personalized medicine through its implications in predictive models and the development of targeted therapeutic strategies, marking a significant stride toward more effective and clinically oriented solutions.

Research progress on the role of PTEN deletion or mutation in the immune microenvironment of glioblastoma

Recent advances in immunotherapy represent a breakthrough in solid tumor treatment but the existing data indicate that immunotherapy is not effective in improving the survival time of patients with glioblastoma. The tumor microenvironment (TME) exerts a series of inhibitory effects on immune effector cells, which limits the clinical application of immunotherapy. Growing evidence shows that phosphate and tension homology deleted on chromosome ten (PTEN) plays an essential role in TME immunosuppression of glioblastoma. Emerging evidence also indicates that targeting PTEN can improve the anti-tumor immunity in TME and enhance the immunotherapy effect, highlighting the potential of PTEN as a promising therapeutic target. This review summarizes the function and specific upstream and downstream targets of PTEN-associated immune cells in glioblastoma TME, providing potential drug targets and therapeutic options for glioblastoma.

A Synopsis of Biomarkers in Glioblastoma: Past and Present

Accounting for 48% of malignant brain tumors in adults, glioblastoma has been of great interest in the last decades, especially in the biomolecular and neurosurgical fields, due to its incurable nature and notable neurological morbidity. The major advancements in neurosurgical technologies have positively influenced the extent of safe tumoral resection, while the latest progress in the biomolecular field of GBM has uncovered new potential therapeutical targets. Although GBM currently has no curative therapy, recent progress has been made in the management of this disease, both from surgical and molecular perspectives. The main current therapeutic approach is multimodal and consists of neurosurgical intervention, radiotherapy, and chemotherapy, mostly with temozolomide. Although most patients will develop treatment resistance and tumor recurrence after surgical removal, biomolecular advancements regarding GBM have contributed to a better understanding of this pathology and its therapeutic management. Over the past few decades, specific biomarkers have been discovered that have helped predict prognosis and treatment responses and contributed to improvements in survival rates.

Advancements in Image-Based Models for High-Grade Gliomas Might Be Accelerated

The first half of 2022 saw the publication of several major research advances in image-based models and artificial intelligence applications to optimize treatment strategies for high-grade gliomas, the deadliest brain tumors. We review them and discuss the barriers that delay their entry into clinical practice; particularly, the small sample size and the heterogeneity of the study designs and methodologies used. We will also write about the poor and late palliation that patients suffering from high-grade glioma can count on at the end of life, as well as the current legislative instruments, with particular reference to Italy. We suggest measures to accelerate the gradual progress in image-based models and end of life care for patients with high-grade glioma.

Investigating the effects of PTEN mutations on cGAS-STING pathway in glioblastoma tumours

BACKGROUND

PTEN is a tumour suppressor gene and well-known for being frequently mutated in several cancer types. Loss of immunogenicity can also be attributed to PTEN loss, because of its role in establishing the tumour microenvironment. Therefore, this study aimed to represent the link between PTEN and cGAS-STING activity, a key mediator of inflammation, in tumour samples of glioblastoma patients.

METHODS

Tumour samples of 36 glioblastoma patients were collected. After DNA isolation, all coding regions of PTEN were sequenced and analysed. PTEN expression status was also evaluated by qRT-PCR, western blot, and immunohistochemical methods. Interferon-stimulated gene expressions, cGAMP activity, CD8 infiltration, and Granzyme B expression levels were determined especially for the evaluation of cGAS-STING activity and immunogenicity.

RESULTS

Mutant PTEN patients had significantly lower PTEN expression, both at mRNA and protein levels. Decreased STING, IRF3, NF-KB1, and RELA mRNA expressions were also found in patients with mutant PTEN. Immunohistochemistry staining of PTEN displayed expressional loss in 38.1% of the patients. Besides, patients with PTEN loss had considerably lower amounts of IFNB and IFIT2 mRNA expressions. Furthermore, CD8 infiltration, cGAMP, and Granzyme B levels were reduced in the PTEN loss group.

CONCLUSION

This study reveals the immunosuppressive effects of PTEN loss in glioblastoma tumours via the cGAS-STING pathway. Therefore, determining the PTEN status in tumours is of great importance, like in situations when considering the treatment of glioblastoma patients with immunotherapeutic agents.