Ventricular-Subventricular Zone Contact by Glioblastoma is Not Associated with Molecular Signatures in Bulk Tumor Data.
ABSTRACT: Whether patients with glioblastoma that contacts the ventricular-subventricular zone stem cell niche (VSVZ?+?GBM) have a distinct survival profile from VSVZ?-?GBM patients independent of other known predictors or molecular profiles is unclear. Using multivariate Cox analysis to adjust survival for widely-accepted predictors, hazard ratios (HRs) for overall (OS) and progression free (PFS) survival between VSVZ?+?GBM and VSVZ?-?GBM patients were calculated in 170 single-institution patients and 254 patients included in both The Cancer Genome (TCGA) and Imaging (TCIA) atlases. An adjusted, multivariable analysis revealed that VSVZ contact was independently associated with decreased survival in both datasets. TCGA molecular data analyses revealed that VSVZ contact by GBM was independent of mutational, DNA methylation, gene expression, and protein expression signatures in the bulk tumor. Therefore, while survival of GBM patients is independently stratified by VSVZ contact, with VSVZ?+?GBM patients displaying a poor prognosis, the VSVZ?+?GBMs do not possess a distinct molecular signature at the bulk sample level. Focused examination of the interplay between the VSVZ microenvironment and subsets of GBM cells proximal to this region is warranted.
Project description:<b>Introduction: </b>The subventricular zone (SVZ) in the brain is associated with gliomagenesis and resistance to treatment in glioblastoma. In this study, we investigate the prognostic role and biological characteristics of subventricular zone (SVZ) involvement in glioblastoma.<br><br><b>Methods: </b>We analyzed T1-weighted, gadolinium-enhanced MR images of a retrospective cohort of 647 primary glioblastoma patients diagnosed between 2005-2013, and performed a multivariable Cox regression analysis to adjust the prognostic effect of SVZ involvement for clinical patient- and tumor-related factors. Protein expression patterns of a.o. markers of neural stem cellness (CD133 and GFAP-?) and (epithelial-) mesenchymal transition (NF-?B, C/EBP-? and STAT3) were determined with immunohistochemistry on tissue microarrays containing 220 of the tumors. Molecular classification and mRNA expression-based gene set enrichment analyses, miRNA expression and SNP copy number analyses were performed on fresh frozen tissue obtained from 76 tumors. Confirmatory analyses were performed on glioblastoma TCGA/TCIA data.<br><br><b>Results: </b>Involvement of the SVZ was a significant adverse prognostic factor in glioblastoma, independent of age, KPS, surgery type and postoperative treatment. Tumor volume and postoperative complications did not explain this prognostic effect. SVZ contact was associated with increased nuclear expression of the (epithelial-) mesenchymal transition markers C/EBP-? and phospho-STAT3. SVZ contact was not associated with molecular subtype, distinct gene expression patterns, or markers of stem cellness. Our main findings were confirmed in a cohort of 229 TCGA/TCIA glioblastomas.<br><br><b>Conclusion: </b>In conclusion, involvement of the SVZ is an independent prognostic factor in glioblastoma, and associates with increased expression of key markers of (epithelial-) mesenchymal transformation, but does not correlate with stem cellness, molecular subtype, or specific (mi)RNA expression patterns.
Project description:<h4>Objective</h4>To determine the relationship between survival and glioblastoma distance from the ventricular-subventricular neural stem cell niche (VSVZ).<h4>Methods</h4>502 pre-operative gadolinium-enhanced, T1-weighted MRIs with glioblastoma retrieved from an institutional dataset (n = 252) and The Cancer Imaging Atlas (n=250) were independently reviewed. The shortest distance from the tumor contrast enhancement to the nearest lateral ventricular wall, the location of the VSVZ, was measured (GBM-VSVZ<sub>Dist</sub>). The relationship of GBM-VSVZ<sub>Dist</sub> with the proportion of glioblastomas at each distance point and overall survival was explored with a Pearson's correlation and Cox regression model, respectively, adjusting for the well-established glioblastoma prognosticators.<h4>Results</h4>244/502 glioblastomas had VSVZ contact. The proportion of non-VSVZ-contacting glioblastomas correlated inversely with GBM-VSVZ<sub>Dist</sub> (partial Pearson's correlation adjusted for tumor volume R=-0.79, p=7.11x10<sup>-7</sup>). A fit of the Cox regression model adjusted for age at diagnosis, Karnofsky performance status score, post-operative treatment with temozolomide and/or radiotherapy, <i>IDH1/2</i> mutation status, <i>MGMT</i> promoter methylation status, tumor volume, and extent of resection demonstrated a significantly decreased overall survival only when glioblastoma contacted the VSVZ. Overall survival did not correlate with GBM-VSVZ<sub>Dist</sub>.<h4>Conclusions</h4>In the two independent cohorts analyzed, glioblastomas at diagnosis were found in close proximity or in contact with the VSVZ with a proportion that decreased linearly with GBM-VSVZ<sub>Dist</sub>. Patient survival was only influenced by the presence or absence of a gadolinium-enhanced glioblastoma contact with the VSVZ. These results may guide analyses to test differential effectiveness of VSVZ radiation in VSVZ-contacting and non-contacting glioblastomas and/or inform patient selection criteria in clinical trials of glioblastoma radiation.
Project description:The clinical effect of radiographic contact of glioblastoma (GBM) with neurogenic zones (NZ)-the ventricular-subventricular (VSVZ) and subgranular (SGZ) zones-and the corpus callosum (CC) remains unclear and, in the case of the SGZ, unexplored. We investigated (1) if GBM contact with a NZ correlates with decreased survival; (2) if so, whether this effect is associated with a specific NZ; and (3) if radiographic contact with or invasion of the CC by GBM is associated with decreased survival. We retrospectively identified 207 adult patients who underwent cytoreductive surgery for GBM followed by chemotherapy and/or radiation. Age, preoperative Karnofsky performance status score (KPS), and extent of resection were recorded. Preoperative MRIs were blindly analyzed to calculate tumor volume and assess its contact with VSVZ, SGZ, CC, and cortex. Overall (OS) and progression free (PFS) survivals were calculated and analyzed with multivariate Cox analyses. Among the 207 patients, 111 had GBM contacting VSVZ (VSVZ+GBMs), 23 had SGZ+GBMs, 52 had CC+GBMs, and 164 had cortex+GBMs. VSVZ+, SGZ+, and CC+?GBMs were significantly larger in size relative to their respective non-contacting controls. Multivariate Cox survival analyses revealed GBM contact with the VSVZ, but not SGZ, CC, or cortex, as an independent predictor of lower OS, PFS, and early recurrence. We hypothesize that the VSVZ niche has unique properties that contribute to GBM pathobiology in adults.
Project description:Methods:The MRI images, genetic data, and clinical data of 152 patients with GBM were analyzed. 122 patients from the TCIA dataset (training set: n = 82; validation set: n = 40) and 30 patients from local hospitals were used as an independent test dataset. Radiomics features were extracted from multiple regions of multiparameter MRI. Kaplan-Meier survival analysis was used to verify the ability of the imaging signature to predict the response of GBM patients to radiotherapy before an operation. Multivariate Cox regression including radiomics signature and preoperative clinical risk factors was used to further improve the ability to predict the overall survival (OS) of individual GBM patients, which was presented in the form of a nomogram. Results:The radiomics signature was built by eight selected features. The C-index of the radiomics signature in the TCIA and independent test cohorts was 0.703 (P < 0.001) and 0.757 (P = 0.001), respectively. Multivariate Cox regression analysis confirmed that the radiomics signature (HR: 0.290, P < 0.001), age (HR: 1.023, P = 0.01), and KPS (HR: 0.968, P < 0.001) were independent risk factors for OS in GBM patients before surgery. When the radiomics signature and preoperative clinical risk factors were combined, the radiomics nomogram further improved the performance of OS prediction in individual patients (C-index = 0.764 and 0.758 in the TCIA and test cohorts, respectively). Conclusion:This study developed a radiomics signature that can predict the response of individual GBM patients to radiotherapy and may be a new supplement for precise GBM radiotherapy.
Project description:Glioblastoma multiforme (GBM) is the most common and devastating type of primary brain tumor, with a median survival time of only 15 months. Having a clinically applicable genetic biomarker would lead to a paradigm shift in precise diagnosis, personalized therapeutic decisions, and prognostic prediction for GBM. Radiogenomic profiling connecting radiological imaging features with molecular alterations will offer a noninvasive method for genomic studies of GBM. To this end, we analyzed over 3800 glioma and GBM cases across four independent datasets. The Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases were employed for RNA-Seq analysis, whereas the Ivy Glioblastoma Atlas Project (Ivy-GAP) and The Cancer Imaging Archive (TCIA) provided clinicopathological data. The Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme (CPTAC-GBM) was used for proteomic analysis. We identified a simple three-gene transcriptome signature-SOCS3, VEGFA, and TEK-that can connect GBM's overall prognosis with genes' expression and simultaneously correlate radiographical features of perfusion imaging with SOCS3 expression levels. More importantly, the rampant development of neovascularization in GBM offers a promising target for therapeutic intervention. However, treatment with bevacizumab failed to improve overall survival. We identified SOCS3 expression levels as a potential selection marker for patients who may benefit from early initiation of angiogenesis inhibitors.
Project description:<h4>Background</h4>Several studies have established Glioblastoma Multiforme (GBM) prognostic and predictive models based on age and Karnofsky Performance Status (KPS), while very few studies evaluated the prognostic and predictive significance of preoperative MR-imaging. However, to date, there is no simple preoperative GBM classification that also correlates with a highly prognostic genomic signature. Thus, we present for the first time a biologically relevant, and clinically applicable tumor Volume, patient Age, and KPS (VAK) GBM classification that can easily and non-invasively be determined upon patient admission.<h4>Methods</h4>We quantitatively analyzed the volumes of 78 GBM patient MRIs present in The Cancer Imaging Archive (TCIA) corresponding to patients in The Cancer Genome Atlas (TCGA) with VAK annotation. The variables were then combined using a simple 3-point scoring system to form the VAK classification. A validation set (N?=?64) from both the TCGA and Rembrandt databases was used to confirm the classification. Transcription factor and genomic correlations were performed using the gene pattern suite and Ingenuity Pathway Analysis.<h4>Results</h4>VAK-A and VAK-B classes showed significant median survival differences in discovery (P?=?0.007) and validation sets (P?=?0.008). VAK-A is significantly associated with P53 activation, while VAK-B shows significant P53 inhibition. Furthermore, a molecular gene signature comprised of a total of 25 genes and microRNAs was significantly associated with the classes and predicted survival in an independent validation set (P?=?0.001). A favorable MGMT promoter methylation status resulted in a 10.5 months additional survival benefit for VAK-A compared to VAK-B patients.<h4>Conclusions</h4>The non-invasively determined VAK classification with its implication of VAK-specific molecular regulatory networks, can serve as a very robust initial prognostic tool, clinical trial selection criteria, and important step toward the refinement of genomics-based personalized therapy for GBM patients.
Project description:Glioblastoma multiforme (GBM) is the most common and devastating type of primary brain tumor, with a median survival time of only 15 months. Having a clinically applicable genetic biomarker would lead to a paradigm shift in precise diagnosis, personalized therapeutic decisions, and prognostic prediction for GBM. Radiogenomic profiling connecting radiological imaging features with molecular alterations will offer a noninvasive method for genomic studies of GBM. To this end, we analyzed over 3800 glioma and GBM cases across four independent datasets. The Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases were employed for RNA-Seq analysis, whereas the Ivy Glioblastoma Atlas Project (Ivy-GAP) and The Cancer Imaging Archive (TCIA) provided clinicopathological data. The Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme (CPTAC-GBM) was used for proteomic analysis. We identified a simple three-gene transcriptome signature-<i>SOCS3</i>, <i>VEGFA</i>, and <i>TEK</i>-that can connect GBM's overall prognosis with genes' expression and simultaneously correlate radiographical features of perfusion imaging with <i>SOCS3</i> expression levels. More importantly, the rampant development of neovascularization in GBM offers a promising target for therapeutic intervention. However, treatment with bevacizumab failed to improve overall survival. We identified <i>SOCS3</i> expression levels as a potential selection marker for patients who may benefit from early initiation of angiogenesis inhibitors.
Project description:Glioma stem cells (GSCs), a subpopulation of tumor cells, contribute to tumor heterogeneity and therapy resistance. Gene expression profiling classified glioblastoma (GBM) and GSCs into four transcriptomically-defined subtypes. Here, we determined the DNA methylation signatures in transcriptomically pre-classified GSC and GBM bulk tumors subtypes. We hypothesized that these DNA methylation signatures correlate with gene expression and are uniquely associated either with only GSCs or only GBM bulk tumors. Additional methylation signatures may be commonly associated with both GSCs and GBM bulk tumors, i.e., common to non-stem-like and stem-like tumor cell populations and correlating with the clinical prognosis of glioma patients. We analyzed Illumina 450K methylation array and expression data from a panel of 23 patient-derived GSCs. We referenced these results with The Cancer Genome Atlas (TCGA) GBM datasets to generate methylomic and transcriptomic signatures for GSCs and GBM bulk tumors of each transcriptomically pre-defined tumor subtype. Survival analyses were carried out for these signature genes using publicly available datasets, including from TCGA. We report that DNA methylation signatures in proneural and mesenchymal tumor subtypes are either unique to GSCs, unique to GBM bulk tumors, or common to both. Further, dysregulated DNA methylation correlates with gene expression and clinical prognoses. Additionally, many previously identified transcriptionally-regulated markers are also dysregulated due to DNA methylation. The subtype-specific DNA methylation signatures described in this study could be useful for refining GBM sub-classification, improving prognostic accuracy, and making therapeutic decisions.
Project description:Glioblastoma (GBM) is both the most common and the most devastating primary cancer of the central nervous system, with an expected overall survival in most patients of about 14 months. Despite extensive research, outcomes for GBM have been largely unchanged since the introduction of temozolomide in 2005. We believe that in order to achieve a breakthrough in therapeutic management, we must begin to identify subtypes of GBM, and tailor treatment to best target a particular tumor's vulnerabilities. Our group has recently produced an examination of the clinical outcomes of radiation therapy directed at tumors that contact the subventricular zone (SVZ), the 3-5 mm lateral border of the lateral ventricles that contains the largest collection of neural stem cells in the adult brain. We find that SVZ-associated tumors have worse progression free and overall survival than tumors that do not contact the SVZ, and that they exhibit unique recurrence and migration patterns. However, with minimal basic science research into SVZ-associated GBM, it is currently impossible to determine if the clinicobehavioral uniqueness of this group of tumors represents a true disease subtype from a genetic perspective. We believe that further translational research into SVZ-associated GBM is needed to establish a therapeutic profile.
Project description:Despite current strategies combining surgery, radiation, and chemotherapy, glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor in adults. Tumor location plays a key role in the prognosis of patients, with GBM tumors located in close proximity to the lateral ventricles (LVs) resulting in worse survival expectancy and higher incidence of distal recurrence. Though the reason for worse prognosis in these patients remains unknown, it may be due to proximity to the subventricular zone (SVZ) neurogenic niche contained within the lateral wall of the LVs. We present a novel rodent model to analyze the bidirectional signaling between GBM tumors and cells contained within the SVZ. Patient-derived GBM cells expressing GFP and luciferase were engrafted at locations proximal, intermediate, and distal to the LVs in immunosuppressed mice. Mice were either sacrificed after 4 weeks for immunohistochemical analysis of the tumor and SVZ or maintained for survival analysis. Analysis of the GFP+ tumor bulk revealed that GBM tumors proximal to the LV show increased levels of proliferation and tumor growth than LV-distal counterparts and is accompanied by decreased median survival. Conversely, numbers of innate proliferative cells, neural stem cells (NSCs), migratory cells and progenitors contained within the SVZ are decreased as a result of GBM proximity to the LV. These results indicate that our rodent model is able to accurately recapitulate several of the clinical aspects of LV-associated GBM, including increased tumor growth and decreased median survival. Additionally, we have found the neurogenic and cell division process of the SVZ in these adult mice is negatively influenced according to the presence and proximity of the tumor mass. This model will be invaluable for further investigation into the bidirectional signaling between GBM and the neurogenic cell populations of the SVZ.