Abstract
Glioblastoma remains a highly malignant and intrinsically resistant brain tumor. Despite intensive research through which numerous potential druggable targets were identified, virtually all ...clinical trials of the past 20 years failed to improve the outcome for the vast majority of GBM patients. However, the identification of small subgroups of patients that showed an exceptional response across several trials, implies that, when selected more carefully, some GBM patients could probably still benefit from these therapies. Identifying these patients requires that suitable biomarkers are identified. In this project, we reassessed the molecular mechanisms of ten actionable compounds (selected from previously failed trials but for which exceptional responders had been observed) in a set of carefully selected patient-derived cell lines that were sensitive/resistant to the selected therapies. Moreover, to deal with tumor heterogeneity, we used a multi-omic functional precision oncology approach, combining scRNA-seq and CyTOF, to identify drug-specific biomarkers by comparing control and treated samples at single-cell resolution. By subsequently correlating the molecular signatures to eventual cytotoxicity profiles, we could identify intrinsically responsive tumor cells at the single-cell level within hours following drug exposure. Overall, this work lays the foundation for an actionable functional diagnostic assay that could help to identify eligible GBM patients in future clinical trials.
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
High-grade gliomas, the most common primary brain tumors, are highly lethal and treatment options remain limited. Despite advances in genomic technologies, there are few molecular ...biomarkers to guide precision medicine for high-grade glioma. Here, we aimed to identify the clinicogenomic features associated with its prognosis and recurrence patterns.
MATERIALS/METHODS
Our single-institution retrospective analysis included 182 patients diagnosed with high-grade gliomas who underwent next-generation sequencing targeting 82 brain tumor-relevant genes. Clinicopathological status, treatment characteristics, survival, and genomic profiles were analyzed.
RESULTS
At a median follow-up of 23 months (range, 2-229 months), 151 patients (83%) had progression or recurrences. Local and distant recurrences were observed in 132 (72.5%) and 101 (54.9%) patients, respectively. The most common genomic variants in high-grade gliomas were TP53 (42.9%), IDH1/2 (23.1%), TERT promoter (38.5%), ATRX (13.2%), H3F3A (7.1%), and SETD2 (6.0%) mutation. Regarding copy number variants, amplification of EGFR (20.9%), PDGFRA (9.9%), MYCN (2.2%) and loss of CDKN2A/2B (49.5%), PTEN (37.9%), RB1 (17.6%), and 1p19q codeletion(9.3%) were the most common copy number aberrations. On multivariate cox regression anlalysis, MYCN amplification (HR 6.08 95% CI 1.91-19.35, p = 0.002), and SETD2 mutation (HR 0.19 95% CI 0.06-0.62, p =0.06) were independent predictors of overall survival, in relation to previously established prognostic factors including age, Eastern Cooperative Oncology Group Performance Status (ECOG PS) scale, extent of resection, MGMT promoter methylation, and IDH1/2 mutation. Interestingly, MYCN amplification (HR 5.24 95% CI 1.69-16.27, p = 0.004), SETD2 mutation (HR 0.35 95% CI 0.12-0.99, p =0.048) were independent predictors of failure from distant recurrences.
CONCLUSION
The assessment of genomic characteristics in conjunction with pattern of failure for high-grade glioma aids to identify patients who are likely to benefit from personalized medicine. We identified SETD2 mutation, and MYCN as a prognostic biomarkers with potential therapeutic implications in patients with high-grade glioma.
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.
Abstract
Methylation classification is an essential component for integrative diagnosis in glioma, however, the DNA methylation classification is not always available for all the samples. We ...hypothesized that Raman spectroscopy might be suitable to predict the glioma methylome, based upon its ability to create a molecular fingerprint of the tumor and would provide biological insights into the discriminatory features. Raman Spectroscopy was used for molecular fingerprinting of the regions of interest using 1mm2 FFPE tissue spots from 45 patient samples with LGm1 to LGm6 methylation subtypes. Spectral information was then used to train a convolutional neural network (CNN), capable of detecting the glioma methylation subtypes. 70 % of the dataset was used for model training while the remaining 30% for validation. We demonstrate that Raman spectroscopy can accurately and rapidly classify gliomas according to their methylation subtype from achieved FFPE samples, as a novel way to obtain classification. For each sample we ran Ward linkage clustering with a variable number of clusters (from 2 to 7), with the majority cluster corresponding to tumor spots and the others corresponding to (various types of) non-tumor spots. The average accuracy over all samples was 90:3%, the average precision was 99:6% and the average recall was 90:2%. We show that Raman spectroscopy together with artificial intelligence can predict the methylome of glioma samples and augment the ability to classify these tumors retrospectively. The non-destructive nature of this method and the ability to be applied on FFPE samples directly, allows the histopathologist to reuse of the same slide for subsequent staining and downstream analyses.
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
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
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.
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