PDPN marks a subset of aggressive and radiation-resistant glioblastoma cells

Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM

BACKGROUND

Previous studies have described sex-specific patient subtyping in glioblastoma. The cluster labels associated with these "legacy data" were used to train a predictive model capable of recapitulating this clustering in contemporary contexts.

METHODS

We used robust ensemble machine learning to train a model using gene microarray data to perform multi-platform predictions including RNA-seq and potentially scRNA-seq.

RESULTS

The engineered feature set was composed of many previously reported genes that are associated with patient prognosis. Interestingly, these well-known genes formed a predictive signature only for female patients, and the application of the predictive signature to male patients produced unexpected results.

CONCLUSIONS

This work demonstrates how annotated "legacy data" can be used to build robust predictive models capable of multi-target predictions across multiple platforms.

Role of Podoplanin (PDPN) in Advancing the Progression and Metastasis of Glioblastoma Multiforme (GBM)

Glioblastoma multiforme (GBM) is a malignant primary brain tumor categorized as a Grade 4 astrocytic glioma by the World Health Organization (WHO). Some of the established risk factors of GBM include inherited genetic syndromes, body mass index, alcohol consumption, use of non-steroidal anti-inflammatory drugs (NSAIDs), and therapeutic ionizing radiation. Vascular anomalies, including local and peripheral thrombosis, are common features of GBM. Podoplanin (PDPN), a ligand of the C-type lectin receptor (CLEC-2), promotes platelet activation, aggregation, venous thromboembolism (VTE), lymphatic vessel formation, and tumor metastasis in GBM patients. It is regulated by Prox1 and is expressed in developing and adult mammalian brains. It was initially identified on lymphatic endothelial cells (LECs) as the E11 antigen and on fibroblastic reticular cells (FRCs) of lymphoid organs and thymic epithelial cells as gp38. In recent research studies, its expression has been linked with prognosis in GBM. PDPN-expressing cancer cells are highly pernicious, with a mutant aptitude to form stem cells. Such cells, on colocalization to the surrounding tissues, transition from epithelial to mesenchymal cells, contributing to the malignant carcinogenesis of GBM. PDPN can be used as an independent prognostic factor in GBM, and this review provides strong preclinical and clinical evidence supporting these claims.

Exosome-transmitted podoplanin promotes tumor-associated macrophage-mediated immune tolerance in glioblastoma

AIMS

Glioblastoma is the most frequent and aggressive primary brain tumor, characterized by rapid disease course and poor treatment responsiveness. The abundance of immunosuppressive macrophages in glioblastoma challenges the efficacy of novel immunotherapy.

METHODS

Bulk RNA-seq and single-cell RNA-seq of glioma patients from public databases were comprehensively analyzed to illustrate macrophage infiltration patterns and molecular characteristics of podoplanin (PDPN). Multiplexed fluorescence immunohistochemistry staining of PDPN, GFAP, CD68, and CD163 were performed in glioma tissue microarray. The impact of PDPN on macrophage immunosuppressive polarization was investigated using a co-culture system. Bone marrow-derived macrophages (BMDMs) and OT-II T cells isolated from BALB/c and OT-II mice respectively were co-cultured to determine T-cell adherence. Pathway alterations were probed through RNA sequencing and western blot analyses.

RESULTS

Our findings demonstrated that PDPN is notably correlated with the expression of CD68 and CD163 in glioma tissues. Additionally, macrophages phagocytosing PDPN-containing EVs (EVsPDPN ) from GBM cells presented increased CD163 expression and augmented secretion of immunoregulatory cytokine (IL-6, IL-10, TNF-α, and TGF-β1). PDPN within EVs was also associated with enhanced phagocytic activity and reduced MHC II expression in macrophages, compromising CD4+ T-cell activation.

CONCLUSIONS

This investigation underscores that EVsPDPN derived from glioblastoma cells contributes to M2 macrophage-mediated immunosuppression and is a potential prognostic marker and therapeutic target in glioblastoma.

The genes significantly associated with an improved prognosis and long-term survival of glioblastoma

BACKGROUND AND PURPOSE

Glioblastoma multiforme (GBM) is the most devastating brain tumor with less than 5% of patients surviving 5 years following diagnosis. Many studies have focused on the genetics of GBM with the aim of improving the prognosis of GBM patients. We investigated specific genes whose expressions are significantly related to both the length of the overall survival and the progression-free survival in patients with GBM.

METHODS

We obtained data for 12,042 gene mRNA expressions in 525 GBM tissues from the Cancer Genome Atlas (TCGA) database. Among those genes, we identified independent genes significantly associated with the prognosis of GBM. Receiver operating characteristic (ROC) curve analysis was performed to determine the genes significant for predicting the long-term survival of patients with GBM. Bioinformatics analysis was also performed for the significant genes.

RESULTS

We identified 33 independent genes whose expressions were significantly associated with the prognosis of 525 patients with GBM. Among them, the expressions of five genes were independently associated with an improved prognosis of GBM, and the expressions of 28 genes were independently related to a poorer prognosis of GBM. The expressions of the ADAM22, ATP5C1, RAC3, SHANK1, AEBP1, C1RL, CHL1, CHST2, EFEMP2, and PGCP genes were either positively or negatively related to the long-term survival of GBM patients.

CONCLUSIONS

Using a large-scale and open database, we found genes significantly associated with both the prognosis and long-term survival of patients with GBM. We believe that our findings may contribute to improving the understanding of the mechanisms underlying GBM.