Construction of Molecular Subtypes and Related Prognostic and Immune Response Models Based on M2 Macrophages in Glioblastoma

Nod-like receptors: The relevant elements of glioblastoma`s prognostic puzzle

Despite considerable improvements in understanding the biology of glioblastoma (GB), it still remains the most lethal type of brain tumor in adults. The role of innate immune cells in the development of GB was recently described. In particular, the tumor-immune cell interactions are thought to be critical in enabling tumor tolerance and even protection against therapeutics. Interestingly, the GB cells express proteins belonging to the family of intracellular pattern-recognition receptors, namely the NOD-like receptors (NLRs). Their activation may trigger the formation of the inflammasome complex leading to the secretion of mature IL-1β and IL-18 and thus resulting in cell death. Intrudingly, the expression of most NLRs was found to be correlated with tumor progression and poor prognosis. We speculate that recognizing the role of NOD-like receptors in GB has the potential to improve the effectiveness of diagnostic tools and prognosis, while also encouraging the development of novel precision medicine-based therapies.

Construction and validation of a TAMRGs prognostic signature for gliomas by integrated analysis of scRNA and bulk RNA sequencing data

BACKGROUND

This study aimed to construct and validate a prognostic model based on tumor associated macrophage-related genes (TAMRGs) by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data.

METHODS

The scRNA-seq data of three inhouse glioma tissues were used to identify the tumor-associated macrophages (TAMs) marker genes, the DEGs from the The Cancer Genome Atlas (TCGA) - Genotype-Tissue Expression (GTEx) dataset were used to further select TAMs marker genes. Subsequently, a TAMRG-score was constructed by Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis in the TCGA dataset and validated in the Chinese Glioma Genome Atlas (CGGA) dataset.

RESULTS

We identified 186 TAMs marker genes, and a total of 6 optimal prognostic genes including CKS2, LITAF, CTSB, TWISTNB, PPIF and G0S2 were selected to construct a TAMRG-score. The high TAMRG-score was significantly associated with worse prognosis (log-rank test, P<0.001). Moreover, the TAMRG-score outperformed the other three models with AUC of 0.808. Immune cell infiltration, TME scores, immune checkpoints, TMB and drug susceptibility were significantly different between TAMRG-score groups. In addition, a nomogram were constructed by combing the TAMRG-score and clinical information (Age, Grade, IDH mutation and 1p19q codeletion) to predict the survival of glioma patients with AUC of 0.909 for 1-year survival.

CONCLUSION

The high TAMRG-score group was associated with a poor prognosis. A nomogram by incorporating TMARG-score could precisely predict glioma survival, and provide evidence for personalized treatment of glioma.

Identification and validation of M2 macrophage-related genes in endometriosis

Aims

M2 macrophage is believed to play an important role in the development of endometriosis. This study aimed to identify several key genes related to the M2 macrophage in endometriosis.

Method

Differential expressed genes between endometriosis and non-endometriosis were identified based on three microarray datasets from the Gene Expression Omnibus database. Gene modules significantly associated with M2 macrophage were identified from the weighted gene co-expression network analysis. Furthermore, by intersecting the differential expressed genes and M2 macrophage-associated module genes, M2 macrophage-related genes in endometriosis were identified. Functional analyses of the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes for these genes were then performed. Following, the least absolute shrinkage and selection operator, random forest, and receiver operating characteristic curves were further conducted to identify the key M2 macrophage-related genes in endometriosis. Finally, the expressions of key genes in endometriosis, as well as their correlations with M2 macrophages were verified in an independent validation cohort.

Results

Totally, 185 M2 macrophage-related genes were identified, and they were mainly enriched in functions associated with the cell cycle, oocyte maturation, and immune response. Following machine learning algorithms, eight key genes were selected in the endometriosis: PGR, OLFM4, PIP5K1B, CCNA1, BRIP1, CADM1, PRAME, and GCNT1. The eight key genes were confirmed to be negative with M2 macrophage infiltration levels. Furthermore, the expression levels of these genes were significantly lower in the middle secretory stage while relevantly higher in the proliferative stage. The validation analysis also showed similar outcomes with the above results.

Conclusion

Eight M2 macrophage-related genes were identified as potential biomarkers of endometriosis, providing novel understanding of immune cells in the endometriosis.

Downregulated ferroptosis-related gene SQLE facilitates temozolomide chemoresistance, and invasion and affects immune regulation in glioblastoma

Chemoresistance in patients with glioblastoma multiforme (GBM) is a common reason hindering the success of treatment. Recently, ferroptosis has been reported to be associated with chemoresistance in different types of cancer, while the role of ferroptosis-related genes in GBM have not been fully elucidated. This study aimed to demonstrate the roles and mechanism of ferroptosis-related genes in chemoresistance and metastasis of GBM. First, two candidate genes, squalene epoxidase (SQLE) and FANCD2, were identified to be associated with ferroptosis-related chemoresistance in GBM from three temozolomide (TMZ) therapeutic datasets and one ferroptosis-related gene dataset. Then, comprehensive bio-informatics data from different databases testified that SQLE was significantly downregulated both in GBM tissue and cells and displayed a better prognosis in GBM. Clinical data identified lower expression of SQLE was significantly associated with WHO grade and 1p/19q codeletion. Moreover, through in vitro experiments, SQLE was confirmed to suppress ERK-mediated TMZ chemoresistance and metastasis of GBM cells. The KEGG analysis of SQLE-associated co-expressed genes indicated SQLE was potentially involved in the cell cycle. Furthermore, SQLE was found to have the most significant correlations with tumor-infiltrating lymphocytes and immunomodulators. These findings highlighted that SQLE could be a potential target and a biomarker for therapy and prognosis of patients with GBM.