Combined bulk RNA-seq and single-cell RNA-seq identifies a necroptosis-related prognostic signature associated with inhibitory immune microenvironment in glioma

DNAJC1 facilitates glioblastoma progression by promoting extracellular matrix reorganization and macrophage infiltration

BACKGROUND

Glioblastoma (GBM) is a high-grade and heterogeneous subtype of glioma that presents a substantial challenge to human health, characterized by a poor prognosis and low survival rates. Despite its known involvement in regulating leukemia and melanoma, the function and mechanism of DNAJC1 in GBM remain poorly understood.

METHODS

Utilizing data from the TCGA, CGGA, and GEO databases, we investigated the expression pattern of DNAJC1 and its correlation with clinical characteristics in GBM specimens. Loss-of-function experiments were conducted to explore the impact of DNAJC1 on GBM cell lines, with co-culture experiments assessing macrophage infiltration and functional marker expression.

RESULTS

Our analysis demonstrated frequent overexpression of DNAJC1 in GBM, significantly associated with various clinical characteristics including WHO grade, IDH status, chromosome 1p/19q codeletion, and histological type. Moreover, Kaplan‒Meier and ROC analyses revealed DNAJC1 as a negative prognostic predictor and a promising diagnostic biomarker for GBM patients. Functional studies indicated that silencing DNAJC1 impeded cell proliferation and migration, induced cell cycle arrest, and enhanced apoptosis. Mechanistically, DNAJC1 was implicated in stimulating extracellular matrix reorganization, triggering the epithelial-mesenchymal transition (EMT) process, and initiating immunosuppressive macrophage infiltration.

CONCLUSIONS

Our findings underscore the pivotal role of DNAJC1 in GBM pathogenesis, suggesting its potential as a diagnostic and therapeutic target for this challenging disease.

Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach

Background

In the central nervous system, glioma is the most common malignant tumor, and patients have a poor prognosis. Identification of novel marker genes and establishment of prognostic models are important for early diagnosis and prognosis determination.

Methods

Download glioma data from the CGGA and TCG databases. Application of bioinformatics to analyze the impact of CYBB on the clinicopathological characteristics, immunological features and prognosis of gliomas. Using single-cell sequencing data from 7 glioblastoma patients in the CGGA database, the role of CYBB in the tumor microenvironment was analyzed. In addition, a prognostic model was constructed based on CYBB high and low differentially expressed genes and mitochondrial genes.

Results

The expression of CYBB is closely related to various clinical features, immune cell infiltration level, immune checkpoint and survival time of patients. A 10-gene prediction model was constructed based on the differentially expressed genes of low and high CYBB and mitochondria-related genes. Glioma patients with higher risk scores had significantly lower survival probabilities. Receiver operating characteristic curves and nomograms were plotted over time to show the predictive accuracy and predictive value of the 10-gene prognostic model.

Conclusions

Our study shows that CYBB is strongly correlated with clinical characteristics features and prognosis of glioma patients, and can be used as a potential therapeutic target. Prognostic models based on CYBB and mitochondrial genes have good performance in predicting prognosis of glioma patients.

Integrated analysis of necroptosis related gene signature to predict clinical outcomes, immune status and drug sensitivity in lower grade Glioma

Background

The treatment of lower grade gliomas (LGG) is currently the most challenging dilemma in the management of intracranial tumors. Necroptosis is a type of programmed cell death that is closely associated with tumor progression, However, the role of necroptosis related genes in LGG is not yet well elucidated.

Methods

Online databases were used to obtain gene expression and clinical information. After gene differential expression analysis, a risk score model based on prognostic differentially expressed necroptosis-related genes (DENGs) were constructed to predict prognosis for LGG patients. The validity of the risk score model was then assessed with Kaplan-Meier survival curve. The prognostic DENGs included in the risk score model were then subjected to gene expression analysis, functional enrichment analysis, consensus clustering analysis, and single cell sequencing analysis. Finally, we investigated the correlation of the risk score and immune infiltration in LGG tumor microenvironment and drug sensitivity for LGG patients in different risk groups.

Results

A survival risk score model was constructed based on seven prognostic DENGs, which demonstrated satisfactory performance in predicting the prognosis of LGG patients. According to functional enrichment analyses, these seven DENGs may play a regulatory role in LGG tumorigenesis through several immune and metabolic pathways. LGG patients could be categorized into two clusters with distinct prognosis and clinicopathologic characteristics based on the expression of seven DENGs. Single-cell sequencing analysis demonstrated that the DENG signature was differentially expressed in various types of cells in LGG and may play a vital role in oncogenesis. Additionally, drug sensitivity analysis suggested that the seven-gene signature could guide clinical medication for LGG patients.

Conclusion

Our study developed a reliable necroptosis-related signature to predict the prognosis of LGG patients. This gene signature may also help estimate immune status and anti-cancer drug sensitivity in LGG patients. Our findings may pave the way to enhance our understanding of necroptosis in LGG.

Identification and Validation of a Prognostic Signature Derived from the Cancer Stem Cells for Oral Squamous Cell Carcinoma

The progression and metastasis of oral squamous cell carcinoma (OSCC) are highly influenced by cancer stem cells (CSCs) due to their unique self-renewal and plasticity. In this study, data were obtained from a single-cell RNA-sequencing dataset (GSE172577) in the GEO database, and LASSO-Cox regression analysis was performed on 1344 CSCs-related genes to establish a six-gene prognostic signature (6-GPS) consisting of ADM, POLR1D, PTGR1, RPL35A, PGK1, and P4HA1. High-risk scores were significantly associated with unfavorable survival outcomes, and these features were thoroughly validated in the ICGC. The results of nomograms, calibration plots, and ROC curves confirmed the good prognostic accuracy of 6-GPS for OSCC. Additionally, the knockdown of ADM or POLR1D genes may significantly inhibit the proliferation, migration, and invasion of OSCC cells through the JAK/HIF-1 pathway. Furthermore, cell-cycle arrest occurred in the G1 phase by suppressing Cyclin D1. In summary, 6-GPS may play a crucial role in the occurrence and development of OSCC and has the potential to be developed further as a diagnostic, therapeutic, and prognostic tool for OSCC.

AKIP1 accelerates glioblastoma progression through stabilizing EGFR expression

A Kinase Interacting Protein 1 (AKIP1) is found to be overexpressed in a variety of human cancers and associated with patients' worse prognosis. Several studies have established AKIP1's malignant functions in tumor metastasis, angiogenesis, and chemoradiotherapy resistance. However, the mechanism of AKIP1 involved in accelerating glioblastoma (GBM) progression remains unknown. Here, we showed that the expression of AKIP1 was positively correlated with the glioma pathological grades. Down-regulating AKIP1 greatly impaired the proliferation, colony formation, and tumorigenicity of GBM cells. In terms of the mechanism, AKIP1 cooperates with transcriptional factor Yin Yang 1 (YY1)-mediated Heat Shock Protein 90 Alpha Family Class A Member 1 (HSP90AA1) transcriptional activation, enhancing the stability of Epidermal Growth Factor Receptor (EGFR). YY1 was identified as a potential transcriptional factor of HSP90AA1 and directly interacts with AKIP1. The overexpression of HSP90α significantly reversed AKIP1 depletion incurred EGFR instability and the blocked cell proliferation. Moreover, we further investigated the interacted pattern between EGFR and HSP90α. These findings established that AKIP1 acted as a critical oncogenic factor in GBM and uncovered a novel regulatory mechanism in EGFR aberrant expression.

Pyroptosis, ferroptosis, and autophagy cross-talk in glioblastoma opens up new avenues for glioblastoma treatment

Glioma is a common primary tumor of the central nervous system (CNS), with glioblastoma multiforme (GBM) being the most malignant, aggressive, and drug resistant. Most drugs are designed to induce cancer cell death, either directly or indirectly, but malignant tumor cells can always evade death and continue to proliferate, resulting in a poor prognosis for patients. This reflects our limited understanding of the complex regulatory network that cancer cells utilize to avoid death. In addition to classical apoptosis, pyroptosis, ferroptosis, and autophagy are recognized as key cell death modalities that play significant roles in tumor progression. Various inducers or inhibitors have been discovered to target the related molecules in these pathways, and some of them have already been translated into clinical treatment. In this review, we summarized recent advances in the molecular mechanisms of inducing or inhibiting pyroptosis, ferroptosis, or autophagy in GBM, which are important for treatment or drug tolerance. We also discussed their links with apoptosis to better understand the mutual regulatory network among different cell death processes. Video Abstract.