Proteins inform survival-based differences in patients with glioblastoma

Extracellular vesicles secreted by 3D tumor organoids are enriched for immune regulatory signaling biomolecules compared to conventional 2D glioblastoma cell systems

Background

Newer 3D culturing approaches are a promising way to better mimic the in vivo tumor microenvironment and to study the interactions between the heterogeneous cell populations of glioblastoma multiforme. Like many other tumors, glioblastoma uses extracellular vesicles as an intercellular communication system to prepare surrounding tissue for invasive tumor growth. However, little is known about the effects of 3D culture on extracellular vesicles. The aim of this study was to comprehensively characterize extracellular vesicles in 3D organoid models and compare them to conventional 2D cell culture systems.

Methods

Primary glioblastoma cells were cultured as 2D and 3D organoid models. Extracellular vesicles were obtained by precipitation and immunoaffinity, with the latter allowing targeted isolation of the CD9/CD63/CD81 vesicle subpopulation. Comprehensive vesicle characterization was performed and miRNA expression profiles were generated by smallRNA-sequencing. In silico analysis of differentially regulated miRNAs was performed to identify mRNA targets and corresponding signaling pathways. The tumor cell media and extracellular vesicle proteome were analyzed by high-resolution mass spectrometry.

Results

We observed an increased concentration of extracellular vesicles in 3D organoid cultures. Differential gene expression analysis further revealed the regulation of twelve miRNAs in 3D tumor organoid cultures (with nine miRNAs down and three miRNAs upregulated). MiR-23a-3p, known to be involved in glioblastoma invasion, was significantly increased in 3D. MiR-7-5p, which counteracts glioblastoma malignancy, was significantly decreased. Moreover, we identified four miRNAs (miR-323a-3p, miR-382-5p, miR-370-3p, miR-134-5p) located within the DLK1-DIO3 domain, a cancer-associated genomic region, suggesting a possible importance of this region in glioblastoma progression. Overrepresentation analysis identified alterations of extracellular vesicle cargo in 3D organoids, including representation of several miRNA targets and proteins primarily implicated in the immune response.

Conclusion

Our results show that 3D glioblastoma organoid models secrete extracellular vesicles with an altered cargo compared to corresponding conventional 2D cultures. Extracellular vesicles from 3D cultures were found to contain signaling molecules associated with the immune regulatory signaling pathways and as such could potentially change the surrounding microenvironment towards tumor progression and immunosuppressive conditions. These findings suggest the use of 3D glioblastoma models for further clinical biomarker studies as well as investigation of new therapeutic options.

SETMAR Shorter Isoform: A New Prognostic Factor in Glioblastoma

Recent evidence suggests that the chimeric protein SETMAR is a factor of interest in cancer, especially in glioblastoma. However, little is known about the expression of this protein in glioblastoma tissues, and no study has been done to assess if SETMAR could be a prognostic and/or diagnostic marker of glioblastoma. We analyzed protein extracts of 47 glioblastoma samples coming from a local and a national cohort of patients. From the local cohort, we obtained localized biopsies from the central necrosis area, the tumor, and the perilesional brain. From the French Glioblastoma Biobank (FGB), we obtained three types of samples: from the same tumors before and after treatment, from long survivors, and from very short survivors. We studied the correlations between SETMAR amounts, clinical profiles of patients and other associated proteins (PTN, snRNP70 and OLIG2). In glioblastoma tissues, the shorter isoform of SETMAR (S-SETMAR) was predominant over the full-length isoform (FL-SETMAR), and the expression of both SETMAR variants was higher in the tumor compared to the perilesional tissues. Data from the FGB showed that SETMAR amounts were not different between the initial tumors and tumor relapses after treatment. These data also showed a trend toward higher amounts of S-SETMAR in long survivors. In localized biopsies, we found a positive correlation between good prognosis and large amounts of S-SETMAR in the perilesional area. This is the main result presented here: survival in Glioblastoma is correlated with amounts of S-SETMAR in perilesional brain, which should be considered as a new relevant prognosis marker.

A Prognostic Model for Glioblastoma Patients Treated With Standard Therapy Based on a Prospective Cohort of Consecutive Non-Selected Patients From a Single Institution

Background

Glioblastoma patients administered standard therapies, comprising maximal surgical resection, radiation therapy with concomitant and adjuvant temozolomide, have a variable prognosis with a median overall survival of 15–16 months and a 2-year overall survival of 30%. The aim of this study was to develop a prognostic nomogram for overall survival for glioblastoma patients treated with standard therapy outside clinical trials.

Methods

The study included 680 consecutive, non-selected glioblastoma patients administered standard therapy as primary treatment between the years 2005 and 2016 at Rigshospitalet, Copenhagen, Denmark. The prognostic model was generated employing multivariate Cox regression analysis modeling overall survival.

Results

The following poor prognostic factors were included in the final prognostic model for overall survival: Age (10-year increase: HR = 1.18, 95% CI: 1.08–1.28, p < 0.001), ECOG performance status (PS) 1 vs. 0 (HR = 1.30, 95% CI: 1.07–1.57, p = 0.007), PS 2 vs. 0 (HR = 2.99, 95% CI: 1.99–4.50, p < 0.001), corticosteroid use (HR = 1.42, 95% CI: 1.18–1.70, p < 0.001), multifocal disease (HR = 1.63, 95% CI: 1.25–2.13, p < 0.001), biopsy vs. resection (HR = 1.35, 95% CI: 1.04–1.72, p = 0.02), un-methylated promoter of the MGMT (O⁶-methylguanine-DNA methyltransferase) gene (HR = 1.71, 95% CI: 1.42–2.04, p < 0.001). The model was validated internally and had a concordance index of 0.65.

Conclusion

A nomogram for overall survival was established. This model can be used for risk stratification and treatment planning, as well as improve enrollment criteria for clinical trials.

Large-Scale Phosphoproteomic Study of Arabidopsis Membrane Proteins Reveals Early Signaling Events in Response to Cold

Cold stress is one of the major factors limiting global crop production. For survival at low temperatures, plants need to sense temperature changes in the surrounding environment. How plants sense and respond to the earliest drop in temperature is still not clearly understood. The plasma membrane and its adjacent extracellular and cytoplasmic sites are the first checkpoints for sensing temperature changes and the subsequent events, such as signal generation and solute transport. To understand how plants respond to early cold exposure, we used a mass spectrometry-based phosphoproteomic method to study the temporal changes in protein phosphorylation events in Arabidopsis membranes during 5 to 60 min of cold exposure. The results revealed that brief cold exposures led to rapid phosphorylation changes in the proteins involved in cellular ion homeostasis, solute and protein transport, cytoskeleton organization, vesical trafficking, protein modification, and signal transduction processes. The phosphorylation motif and kinase-substrate network analysis also revealed that multiple protein kinases, including RLKs, MAPKs, CDPKs, and their substrates, could be involved in early cold signaling. Taken together, our results provide a first look at the cold-responsive phosphoproteome changes of Arabidopsis membrane proteins that can be a significant resource to understand how plants respond to an early temperature drop.