Prognosis and Immune Landscapes in Glioblastoma Based on Gene-Signature Related to Reactive-Oxygen-Species

Immune prognostic model for glioblastoma based on the ssGSEA enrichment score

PURPOSE

Few effective immune prognostic models based on the tumor immune microenvironment (TIME) for glioblastoma have been reported. Therefore, this study aimed to construct an immune prognostic model for glioblastoma by analyzing enriched biological processes and pathways in tumors.

METHODS

A comprehensive single-sample gene set enrichment analysis (ssGSEA) of gene sets from the Molecular Signatures Database was performed using TCGA RNA sequencing data (141 glioblastoma cases). After evaluating gene sets associated with prognosis using univariable Cox regression, gene sets related to biological processes and tumor immunity in gliomas were extracted. Finally, the least absolute shrinkage and selection operator Cox regression refined the gene sets and a nomogram was constructed. The model was validated using CGGA (183 cases) and Aichi Cancer Center (42 cases) datasets.

RESULTS

The immune prognostic model consisted of three gene sets related to biological processes (sphingolipids, steroid hormones, and intermediate filaments) and one related to tumor immunity (immunosuppressive chemokine pathways involving tumor-associated microglia and macrophages). Kaplan-Meier curves for the training (TCGA) and validation (CGGA) cohorts showed significantly worse overall survival in the high-risk group compared to the low-risk group (p < 0.001 and p = 0.04, respectively). Furthermore, in silico cytometry revealed a significant increase in macrophages with immunosuppressive properties and T cells with effector functions in the high-risk group (p < 0.01) across all cohorts.

CONCLUSION

Construction of an immune prognostic model based on the TIME assessment using ssGSEA could potentially provide valuable insights into the prognosis and immune profiles of patients with glioblastoma and guide treatment strategies.

Prognostic Value of Pentraxin3 Protein Expression in Human Malignancies: A Systematic Review and Meta-Analysis

BACKGROUND/OBJECTIVES

Pentraxin 3 (PTX3), a member of the pentraxin superfamily, plays diverse roles in immunity and inflammation. Its dual role in tumorigenesis, exhibiting both protumoral and antitumoral effects, has been the subject of conflicting reports. High PTX3 expression levels in serum and tumor tissues have been associated with poor prognosis in various malignancies, suggesting its potential as a prognostic biomarker. Through this meta-analysis, we aim to comprehensively assess the prognostic significance of PTX3 protein expression in human malignancies and evaluate its potential as a pan-cancer prognostic marker.

METHODS

A systematic literature search was conducted across the PubMed, Embase, Web of Science, MEDLINE, and Cochrane Library databases. Studies were included if they assessed the association between PTX3 protein expression and overall survival (OS) in cancer patients. Hazard ratios (HRs) were pooled using a random-effects model. Subgroup analyses were performed based on the method of PTX3 assessment, and publication bias was evaluated using Egger's and Begg's tests.

RESULTS

Nine studies encompassing 1215 patients were included in the analysis. High PTX3 expression was significantly associated with poorer OS (HR = 1.89, 95% CI = 1.55-2.32, p < 0.01) with no significant heterogeneity (I2 = 0%). Subgroup analysis revealed consistent results across different assessment methods (immunohistochemistry: HR = 1.93, p < 0.01; immunoassay: HR = 1.86, p < 0.01). However, publication bias was detected (Egger's test, p = 0.03).

CONCLUSIONS

High PTX3 protein expression is associated with a poor prognosis in various malignancies, supporting its potential as a prognostic biomarker.

CRISPR/Cas9-based genome-wide screening for metastasis ability identifies FCGR1A regulating the metastatic process of ovarian cancer by targeting LSP1

BACKGROUND

Metastasis is a main cause of death from ovarian cancer (OC). Identifying key markers involved in OC metastasis can aid in the effective detection of early postoperative metastasis. However, the role of FCGR1A in OC metastasis has yet to be fully established. A genome-wide CRISPR/Cas9-based screening system was used to identify regulatory factors involved in metastasis.

METHODS

The expression of FCGR1A and LSP1 in ovarian cancer cell lines was examined by quantitative real-time polymerase chain reaction (qRT‒PCR). The functions of FCGR1A and LSP1 in OC cell migration, invasion and proliferation were determined using wound healing, Transwell invasion and CKK-8 assays. A transcription-activated library was used to identify the potential downstream genes of FCGR1A. FCGR1A expression was detected by immunohistochemistry and the immunity risk score (IRS) scores were calculated.

RESULTS

FCGR1A was upregulated in OC cells compared with normal ovarian cells. Downregulation of FCGR1A inhibited metastasis, proliferation and epithelial-mesenchymal transition (EMT) progression in OC cells in vitro and intraperitoneal metastasis in vivo. Moreover, downregulation of FCGR1A was accompanied by decreased LSP1 expression. Overexpression of LSP1 partially reversed the tumor suppressive effect of FCGR1A downregulation. Higher FCGR1A expression was related to metastasis, higher grade, higher stage, and lymph node metastasis in OC. Survival analysis suggested that the group with higher FCGR1A expression had a lower tumor-free survival rate and a lower overall survival rate than did the group with low FCGR1A expression.

CONCLUSIONS

FCGR1A enhances OC metastasis by regulating LSP1, and FCGR1A is associated with poor prognosis, suggesting that FCGR1A is a potential predictive factor for detecting early postoperative metastasis.

Harnessing the potential of nanoengineered siRNAs carriers for target responsive glioma therapy: Recent progress and future opportunities

Past scientific testimonials in the field of glioma research, the deadliest tumor among all brain cancer types with the life span of 10-15 months after diagnosis is considered as glioblastoma multiforme (GBM). Even though the availability of treatment options such as chemotherapy, radiotherapy, and surgery, are unable to completely cure GBM due to tumor microenvironment complexity, intrinsic cellular signalling, and genetic mutations which are involved in chemoresistance. The blood-brain barrier is accountable for restricting drugs entry at the tumor location and related biological challenges like endocytic degradation, short systemic circulation, and insufficient cellular penetration lead to tumor aggression and progression. The above stated challenges can be better mitigated by small interfering RNAs (siRNA) by knockdown genes responsible for tumor progression and resistance. However, siRNA encounters with challenges like inefficient cellular transfection, short circulation time, endogenous degradation, and off-target effects. The novel functionalized nanocarrier approach in conjunction with biological and chemical modification offers an intriguing potential to address challenges associated with the naked siRNA and efficiently silence STAT3, coffilin-1, EGFR, VEGF, SMO, MGMT, HAO-1, GPX-4, TfR, LDLR and galectin-1 genes in GBM tumor. This review highlights the nanoengineered siRNA carriers, their recent advancements, future perspectives, and strategies to overcome the systemic siRNA delivery challenges for glioma treatment.

ROS regulation in gliomas: implications for treatment strategies

Gliomas are one of the most common primary malignant tumours of the central nervous system (CNS), of which glioblastomas (GBMs) are the most common and destructive type. The glioma tumour microenvironment (TME) has unique characteristics, such as hypoxia, the blood-brain barrier (BBB), reactive oxygen species (ROS) and tumour neovascularization. Therefore, the traditional treatment effect is limited. As cellular oxidative metabolites, ROS not only promote the occurrence and development of gliomas but also affect immune cells in the immune microenvironment. In contrast, either too high or too low ROS levels are detrimental to the survival of glioma cells, which indicates the threshold of ROS. Therefore, an in-depth understanding of the mechanisms of ROS production and scavenging, the threshold of ROS, and the role of ROS in the glioma TME can provide new methods and strategies for glioma treatment. Current methods to increase ROS include photodynamic therapy (PDT), sonodynamic therapy (SDT), and chemodynamic therapy (CDT), etc., and methods to eliminate ROS include the ingestion of antioxidants. Increasing/scavenging ROS is potentially applicable treatment, and further studies will help to provide more effective strategies for glioma treatment.

Role of long pentraxin PTX3 in cancer

Cancer has become a leading cause of death and disease burden worldwide, closely related to rapid socioeconomic development. However, the fundamental reason is the lack of comprehensive understanding of the mechanism of cancer, accurate identification of preclinical cancer, and effective treatment of the disease. Therefore, it is particularly urgent to study specific mechanisms of cancer and develop effective prediction and treatment methods. Long Pentraxin PTX3 is a soluble pattern recognition molecule produced by various cells in inflammatory sites, which plays a role as a promoter or suppressor of cancer in multiple tumors through participating in innate immune response, neovascularization, energy metabolism, invasion, and metastasis mechanisms. Based on this, this article mainly reviews the role of PTX3 in various cancers.

Clinical and molecular analysis of cilia-associated gene signature for prognostic prediction in glioma

PURPOSE

Glioma is a highly malignant and unfavorable cancer in the brain. Recent evidence highlights the vital role of cilia-related pathways as novel regulators of glioma development. However, the prognostic potential of ciliary pathways in glioma is still ambiguous. In this study, we aim to construct a gene signature using cilia-related genes to facilitate the prognostication of glioma.

METHODS

A multi-stage approach was employed to build the ciliary gene signature for prognostication of glioma. The strategy involved the implementation of univariate, LASSO, and stepwise multivariate Cox regression analyses based on TCGA cohort, followed by independent validation in CGGA and REMBRANDT cohort. The study further revealed molecular differences at the genomic, transcriptomic, and proteomic levels between distinct groups.

RESULTS

A prognostic tool utilizing a 9-gene signature based on ciliary pathways was developed to assess the clinical outcomes of glioma patients. The risk scores generated by the signature demonstrated a negative correlation with patient survival rates. The validation of the signature in an independent cohort reinforced its prognostic capabilities. In-depth analysis uncovered distinctive molecular characteristics at the genomic, transcriptomic, and protein-interactive levels in the high- and low-risk groups. Furthermore, the gene signature was able to predict the sensitivity of glioma patients to conventional chemotherapeutic drugs.

CONCLUSION

This study has established the utility of a ciliary gene signature as a reliable prognostic predictor of glioma patient survival. Findings not only enhance our comprehension of the intricate molecular mechanisms of cilia pathways in glioma, but also hold significant clinical implications in directing chemotherapeutic strategies.