Abstract
BACKGROUND
The molecular landscape of adult diffuse glioma has been extensively characterized by gene expression and DNA methylation profiling, but less attention has been paid to somatic ...copy number alteration (SCNA) data. This study aimed to give a rigorous, survival-focused analysis of glioma genome-wide SCNA data that builds on our previous work.
METHODS
Detailed survival analyses were conducted on the substructure of UMAP projections of all TCGA glioma (Nf1092), exclusively astrocytic glioma (Nf914), and exclusively IDH-wildtype glioma (Nf528). Results were validated with data from the Glioma Longitudinal Analysis Consortium (GLASS) (Nf224). Clinical factors such as age and MGMT methylation were tested in multivariate survival analyses.
RESULTS
A UMAP projection of TCGA glioma SCNA data generated three distinct clusters composed of entirely oligodendroglioma, predominantly IDH-mutant astrocytoma (C-IDHmut-astro), and predominantly IDH-wildtype glioma (C-IDHwt), respectively. For astrocytic tumors, cluster assignment was independently prognostic of IDH status (p< 0.001): TCGA IDH-mutant astrocytomas that clustered in C-IDHwt had poorer outcomes than their counterparts (p< 0.04) and IDH-wildtype tumors that clustered in C-IDHmut-astro fared better than those that did not (p< 0.01). The distribution of GLASS astrocytic tumors, which is skewed for better survival, supported our results in IDH-wildtype glioblastoma (p< 0.001, Fisher’s). Among four distinct subclusters of TCGA IDH-wildtype glioblastomas, the largest was significantly or marginally significantly negatively prognostic compared to each other cluster (p=0.048, p=0.059, p=0.027) and their combination (p=0.002). In the GLASS dataset, inclusion in the largest subcluster was also prognostic (p=0.013) and similar trends were observed between individual clusters (p=0.21, p=0.036, p=0.083). Furthermore, membership to the largest cluster was independently prognostic of MGMT methylation status and several published IDH-wildtype glioblastoma subtypes in the TCGA.
CONCLUSIONS
Unsupervised learning of genome-wide SCNA has prognostic implications for astrocytic glioma. SCNA cluster membership is independently prognostic of MGMT methylation status.
Abstract
BACKGROUND
Invasive brain sampling is typically necessary for reliable diagnosis and prognostication of intra-axial brain tumors but carries risk of morbidity. Liquid biopsy of proximal ...fluids may mitigate this risk. Through direct contact with the tumor microenvironment and, as an ultra-filtrate of plasma, the cerebrospinal fluid may be the ideal matrix. Reflecting the tumor phenotype, proteomic analyses are critical. Here we identified diagnostic CSF proteomic signatures and putatively novel biomarkers for glioblastoma (GBM), brain metastases (BM), and central nervous system lymphoma (CNSL).
METHODS
CSF samples were retrospectively retrieved from the Penn State Neuroscience Biorepository and profiled using shotgun proteomics and the MStern approach. Proteomic signatures were identified using machine learning classifiers and survival analyses.
RESULTS
With as little as 30 µL of CSF, 755 unique proteins were recovered across 73 samples (22 GBM, 17 BM, 14 CNSL, 20 NPH). Proteomic-based classifiers identified malignancy with area under the receiver operating characteristic (AUROC) of 0.94 and distinguished between tumor entities with AUROC ≥0.95. More clinically relevant triplex classifiers, comprised of just 3 proteins, distinguished between tumor entities with AUROC of 0.75-0.89. Novel biomarkers were identified, including GAP43, TFF3 and CACNA2D2, and characterized using single-cell RNA sequencing.
DISCUSSION
Reliable classification of intra-axial malignancies using low CSF volumes is feasible, allowing for longitudinal tumor surveillance. Based on emerging evidence, upfront implantation of CSF reservoirs in brain tumor patients warrants consideration.
Abstract
BACKGROUND
Treatment-related toxicity is common in patients with glioblastoma (GBM) receiving chemotherapy and radiotherapy (RT). Temporalis muscle thickness (TMT) is a biomarker associated ...with sarcopenia and worse clinical outcomes in GBM, however its relation to treatment toxicity is less studied. We hypothesize that TMT may predict toxicity and survival in GBM patients.
METHODS
We reviewed consecutive patients with IDH-wildtype GBM treated from 2014-2019 at a single academic center. TMT was retrospectively assessed on T1-weighted MRI scans and dichotomized based upon previously validated sex-specific cutoff values. TMT was measured on baseline MRI scan at time of diagnosis. Cox regression multivariable analysis (MVA) was used to assess survival.
RESULTS
We evaluated 351 patients with median age of 60y (range 20-94) and median follow-up of 14mo. Most patients were male (59%), baseline KPS >70 (95%), and MGMT unmethylated (55%). After maximal safe resection, most patients received standard (90%) or hypofractionated (10%) RT with concurrent systemic therapy (89%). On MVA, baseline low TMT (HR 1.93, p=0.01), age >65y, baseline KPS, and MGMT-unmethylated status were associated with worse OS. On MVA, baseline low TMT (HR 1.95, p=0.01), age >65y, MGMT-unmethylated status, and discontinuing systemic therapy were associated with worse profession-free survival (PFS). 21 patients did not complete anticipated treatment course of chemoradiation and adjuvant systemic therapy due to toxicity, primarily thrombocytopenia, associated with worse OS on MVA (HR 1.99, p< 0.01). Low TMT was associated with higher risk of stopping treatment due to adverse events (OR 5.25, p< 0.01) independent of age, sex, extent of resection, RT dose on MVA.
CONCLUSION
Baseline low TMT was associated with worse PFS and OS, and it was associated with treatment interruption due to treatment toxicity in GBM patients. While further validation is needed, TMT may help identify patients who will benefit from aggressive symptom management or treatment deintensification.
Abstract
Glioblastoma responses to immune checkpoint inhibition (ICI) are rare, and the molecular mechanisms underlying ICI responses are incompletely understood. Thus, serial glioblastoma samples ...are valuable resources for identifying biomarkers or therapeutic targets to increase the efficacy of ICI in patients with glioblastoma. We obtained paired glioblastoma samples from 7 patients who underwent sequential surgery, ICI, and eventual salvage surgery for recurrence. Patients were distinguished as ICI responders (n=3) or non-responders (n=4) based on (1) MRI evidence of tumor stability/reduction over 6+ months after ICI, or (2) pathologic evidence of predominant treatment effect at the time of salvage surgery after ICI. FFPE sections from each tumor (n=14) were stained using H&E or IHC/IF for macrophages/microglia (CD68) or T cells (CD3) and analyzed using light or fluorescence microscopy. Six regions-of-interest (ROIs) comprising viable tumor were selected neuropathologist from each sample (n=84 ROIs). ROIs were analyzed using quantitative spatial profiling of 72 proteins on the Nanostring Digital Profiler platform. Glioblastomas responding to ICI were enriched in T-cell proteins (CD3, CD4, CD8) and T-cell activation markers (CD25) at the time of salvage compared to initial surgery. Markers of MAPK signaling were suppressed in pre-ICI samples compared to post-ICI samples in responders. p-ERK was suppressed in post-ICI samples compared to pre-ICI samples in non-responders. Myeloid proteins (CD68, CD163, CD11c) were enriched in post-ICI samples compared to pre-ICI samples in non-responders. Principle components analysis revealed p-ERK and immune proteins (CD3, CD4, CD8, CD20, CD11c, CTLA4, CD68, CD45, CD56, and CD127) accounted for 62% of the variance among pre-ICI and post-ICI samples in responders. In conclusion, temporospatial protein profiling of human glioblastomas reveals molecular mechanisms and biomarkers underlying responses to immune checkpoint inhibition. These data establish a foundation for functional studies to reprogram the immunosuppressive glioblastoma microenvironment and sensitize tumors to immune checkpoint inhibition.
Abstract
This study introduces a multicontraction microfluidic channel that can differentiate glioma cells from normal glio cells. As cells pass through successive constriction channels, the ...incremental velocity and varying size profiles of the cells will be collected, reflecting their biophysical properties. The data of high-dimensional variables were analyzed , including the cell sizes, velocities, and velocity increments. The prediction value is used to represent the difference between two groups using the established classification model from high-dimensional variables. At the same time, we prepared three groups of primary tumor cells from patients with different grades of glioma to verify the efficacy of this classification method. The results show that in this microfluidic channel, the diagnostic model made of cell biophysical properties can well identify glioma cells, which gives a novel method for efficient identification of circulating tumor cells and rapid pathological diagnosis.
Abstract
BACKGROUND
Head Start 4 is a randomized clinical trial to determine whether dose-intensive tandem consolidation, compared with a single cycle, with autologous hematopoietic progenitor cell ...rescue provides a survival benefit in pediatric patients with medulloblastoma or other embryonal tumors. The trial incorporates upfront molecular subgrouping and non-mandatory, prospective blood and cerebrospinal fluid (CSF) collection. This pilot study aimed to identify exosomal non-coding RNAs (exo-ncRNAs) that might serve as novel diagnostic and/or treatment response biomarkers.
METHODS
CSF(1-2mLs) from 11 controls (non-tumor) and 27 medulloblastoma participants including 23 obtained at baseline, 22 at the end of induction, 3 post-consolidation, and 4 relapse time points, were profiled. Exosome isolation and small RNA-sequencing were performed by System Biosciences. Differential gene expression (DGE) was performed in R (DESeq2). Variations in gene expression profiles between samples were visualized using principal component analysis.
RESULTS
After limiting to ncRNAs with expression of 2 counts per million in 50% or more of the samples in each comparison, ~9,500 ncRNAs were detected. DGE analyses revealed 118 ncRNAs with log2 fold change(FC) >2 and 1 ncRNA with log2FC< -2 in baseline CSF samples compared to controls. In contrast, 11 ncRNAs(log2FC >2) and 1 ncRNA(log2FC< -2) were detected in end of induction CSF samples compared to controls. Comparing end of induction to baseline CSF samples accounting for paired samples, 0 ncRNAs(log2FC >2) and 52 ncRNAs(log2FC< -2) were detected.
CONCLUSIONS
Overall, our data indicate that exosomal small RNA-sequencing of limited CSF volumes is feasible. Differential expression and distinct clustering between tumor baseline samples compared to non-tumor controls was observed. CSF-derived exo-ncRNAs at end of induction also demonstrated “normalization” of ncRNA profiles, signifying CSF biomarkers may serve a role in diagnosis and molecular response assessment. A comprehensive analysis including multi-marker predictive model development and molecular subgrouping will be undertaken at completion of study enrollment.
Abstract
BACKGROUND
Glioblastoma is the most common and aggressive primary brain tumor in adults. Despite maximal surgical resection followed by concomitant chemo-/radiotherapy, the three-year ...survival remains less than 5%. Receptor tyrosine kinase-like orphan receptor 1 (ROR1) overexpression is associated with poor prognosis in several cancers. ROR1 therapeutics are in Phase I/II clinical trials making it an exciting novel target with translational potential to explore for glioblastoma treatment. The aim of this study was to examine the association between ROR1 mRNA expression and overall survival, by applying the WHO 2021 classification to transcriptomic glioma datasets.
METHODS
Clinical, histological, and molecular data was extracted from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Repository for Molecular Brain Neoplasia (REMBRANDT), and GSE16011 (GRAVENDEEL) projects via the GlioVis portal. Using the WHO 2021 classification, the dataset was appropriately re-classified. Only confirmed cases of astrocytoma, oligodendroglioma, or glioblastoma, and ROR1 mRNA expression data were included in the analysis, which included a total of 2,303 cases. 981 cases comprised the low-grade glioma cohort and 1322 cases were included in the high-grade glioma cohort. ROR1 mRNA expression from the four datasets was normalized within each dataset, combined, and divided into high and low expression groups. ROR1 expression and survival correlations were estimated with Kaplan-Meier survival analysis and Mantel-Cox test using GraphPad Prism v9.
RESULTS
Those with high ROR1 expression had an overall median survival of 4.5 months, as compared to 21.4 months in the low ROR1 expression cohort (p< 0.0001). High-grade gliomas had the highest ROR1 mRNA expression across the consortium when compared to the low-grade glioma cohort (p< 0.0001).
CONCLUSION
The results of this study indicate an association between overall survival in glioma and ROR1 expression. In addition, targeting ROR1 could hold translational importance for novel putative treatment in glioblastoma patients.
Abstract
BACKGROUND
In the updated 2021 WHO classification, diffuse gliomas were strictly reclassified by molecular statuses. In glioblastoma (GBM), the prognostic significance of the resection has ...been shown, but the excision rate to be achieved in the new classification has not been defined. Moreover, the correlation between the extent of resection (EOR) and the prognosis is still controversial for other gliomas.
METHODS
IDH 1/2 mutations and TERT promoter mutations were analyzed by Sanger sequencing, 1p/19q co-deletion by microsatellite or MLPA, and EGFR amplification and CDKN2A deletions by MLPA. The correlation between the resection rate and prognosis of each tumor type in the 2021/2016 WHO classification was analyzed retrospectively.
RESULTS
According to the 2021 classification, 293 patients with GBM, IDH-wild type, 68 with astrocytoma, IDH-mutant (2/3/4 22/26/20), and 58 with oligodendroglioma, IDH-mutant and 1p/19q co-deleted were identified. Based on the 2016 classification, they were diagnosed as 314 GBM, 106 astrocytoma (Gd II/III 37/69), and 59 oligodendroglioma. For GBM, IDH-wild type (2021 classification), a prolonged OS benefit was observed with >25% removal (p=0.042), whereas, more than 20% of tumor removal for patients with GBM (2016 classification) resulted in OS prolongation. EOR was a significant favorable prognostic factor for grade II/III astrocytoma by the 2016 classification, but not for astrocytoma, IDH-mutant (grade 2/3) in the 2021 classification. When analyzed only in patients with astrocytoma, IDH-mutant by the 2021 classification, EOR was not significantly prognostic, suggesting that poorer prognosis of patients with unresectable IDH-wild type astrocytomas (2016 classification) might have a negative impact on the outcome.
CONCLUSION
There was a strong correlation between EOR and prognosis in patients with GBM, and >25% removal was considered significant according to the 2021 classification. For astrocytoma in the 2021 classification, EOR did not show a prognostic significance, but further validation including grading effect is warranted.
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