Dataset Information

Unlocking Bevacizumab's Potential: rCBV_max as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients.

ABSTRACT:

Background

Aberrant vascular architecture and angiogenesis are hallmarks of glioblastoma IDH-wildtype, suggesting that these tumors are suitable for antiangiogenic therapy. Bevacizumab was FDA-approved in 2009 following promising results in two clinical trials. However, its use for recurrent glioblastomas remains a subject of debate, as it does not universally improve patient survival.

Purposes

In this study, we aimed to analyze the influence of tumor vascularity on the benefit provided by BVZ and propose preoperative rCBVmax at the high angiogenic tumor habitat as a predictive biomarker to select patients who can benefit the most.

Methods

Clinical and MRI data from 106 patients with glioblastoma IDH-wildtype have been analyzed. Thirty-nine of them received BVZ, and the remaining sixty-seven did not receive a second-line treatment. The ONCOhabitats method was used to automatically calculate rCBV.

Results

We found a median survival from progression of 305 days longer for patients with moderate vascular tumors who received BVZ than those who did not receive any second-line treatment. This contrasts with patients with high-vascular tumors who only presented a median survival of 173 days longer when receiving BVZ. Furthermore, better responses to BVZ were found for the moderate-vascular group with a higher proportion of patients alive at 6, 12, 18, and 24 months after progression.

Conclusions

We propose rCBVmax as a potential biomarker to select patients who can benefit more from BVZ after tumor progression. In addition, we propose a threshold of 7.5 to stratify patients into moderate- and high-vascular groups to select the optimal second-line treatment.

SUBMITTER: Alvarez-Torres MDM

PROVIDER: S-EPMC10778147 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Unlocking Bevacizumab's Potential: rCBV<sub>max</sub> as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients.

Álvarez-Torres María Del Mar MDM Balaña Carmen C Fuster-García Elies E Puig Josep J García-Gómez Juan Miguel JM

Cancers 20231228 1

<h4>Background</h4>Aberrant vascular architecture and angiogenesis are hallmarks of glioblastoma IDH-wildtype, suggesting that these tumors are suitable for antiangiogenic therapy. Bevacizumab was FDA-approved in 2009 following promising results in two clinical trials. However, its use for recurrent glioblastomas remains a subject of debate, as it does not universally improve patient survival.<h4>Purposes</h4>In this study, we aimed to analyze the influence of tumor vascularity on the benefit pr ...[more]

PMID: 38201588

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Project description:BackgroundNF1 inactivation is associated with sensitivity to MEK inhibitor targeted therapy in low-grade and some high-grade gliomas. NF1 loss may also be a harbinger of exploitable vulnerabilities in IDH-wildtype glioblastoma (GBM). Accurate and consistent detection of NF1 loss, however, is fraught given the large gene size, challenges with complete coverage and variant calling upon sequencing, and mechanisms of mRNA and protein regulation that result in early degradation in the absence of genomic alterations. Here, we seek to perform a composite analysis for NF1 loss accounting for genomic alterations and protein expression via immunohistochemistry. We also characterize the landscape of NF1 alterations in GBM.MethodsWe assembled a single-institution, retrospective cohort of 542 IDH-wildtype GBM with somatic next generation sequencing to investigate the frequency and nature of detected NF1 alterations. We selected 69 GBMs from which to build a tissue microarray (TMA) of 44 NF1-wildtype and 25 NF1-mutant cases. We performed NF1 immunohistochemistry using two different NF1 antibodies (NFC, Sigma-Aldrich; and iNF-07E, iNFixion Bioscience) and correlated results with clinical, genomic, and other immunohistochemical features.ResultsIn our retrospective cohort, we identified 88 IDH-wildtype GBM with NF1 alterations (16%). NF1 alterations were mutually exclusive with EGFR and MDM2 alterations (p-adj < 0.001, 0.05, respectively), but co-occurred with PIK3R1 alterations (Log2(OR) = - 1.6, p-adj = 0.03). Of the 63 scorable sporadic GBMs in the TMA, 14 harbored NF1 inactivating alterations and of those, 12 (86%) demonstrated minimal NF1 immunoreactivity by NFC antibody, compared to 8 (57%) by iNF-07E antibody. Among the 42 scorable NF1-wildtype GBM in the TMA, NF1 immunostaining was minimal in 18 (43%) by NFC antibody compared to 4 (10%) by iNF-07E antibody, potentially reflecting false positives or differential protein regulation. Minimal immunoreactivity by NFC antibody was associated with decreased median overall survival (8.5 vs. 16.4 months, p = 0.011). Cox proportional hazards model correcting for prognostic variables in this subset revealed HR 3.23 (95% CI 1.29-8.06, p = 0.01) associated with decreased NF1 expression by IHC.ConclusionNF1 immunostaining may serve as a sensitive surrogate marker of NF1 genomic inactivation and a valuable extension to next-generation sequencing for defining NF1 status. Minimal NF1 immunoreactivity is a poor prognostic marker, even in IDH-wildtype glioblastoma without apparent NF1 genomic alterations, but the underlying molecular mechanism requires further investigation.

Project description:Objectives: In the present study, we aimed to determine the candidate genes that may function as biomarkers to further distinguish patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM), which are heterogeneous with respect to clinical outcomes. Materials and Methods: We selected 41 candidate genes associated with overall survival (OS) using univariate Cox regression from IDH-wildtype GBM patients based on RNA sequencing (RNAseq) expression data from the Chinese Glioma Genome Atlas (CGGA, n = 105) and The Cancer Genome Atlas (TCGA, n = 139) cohorts. Next, a seven-gene-based risk signature was formulated according to Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm in the CGGA RNAseq database as a training set, while another 525 IDH-wildtype GBM patient TCGA datasets, consisting of RNA sequencing and microarray data, were used for validation. Patient survival in the low- and high-risk groups was calculated using Kaplan-Meier survival curve analysis and the log-rank test. Uni-and multivariate Cox regression analysis was used to assess the prognosis value. Gene oncology (GO) and gene set enrichment analysis (GSEA) were performed for the functional analysis of the seven-gene-based risk signature. Results: We developed a seven-gene-based signature, which allocated each patient to a risk group (low or high). Patients in the high-risk group had dramatically shorter overall survival than their low-risk counterparts in three independent cohorts. Univariate and multivariate analysis showed that the seven-gene signature remained an independent prognostic factor. Moreover, the seven-gene risk signature exhibited a striking prognostic validity, with AUC of 78.4 and 73.9%, which was higher than for traditional "age" (53.7%, 62.4%) and "GBM sub-type" (57.7%, 52.9%) in the CGGA- and TCGA-RNAseq databases, respectively. Subsequent bioinformatics analysis predicted that the seven-gene signature was involved in the inflammatory response, immune response, cell adhesion, and apoptotic process. Conclusions: Our findings indicate that the seven-gene signature could be a potential prognostic biomarker. This study refined the current classification system of IDH-wildtype GBM and may provide a novel perspective for the research and individual therapy of IDH-wildtype GBM.

Dataset Information

Unlocking Bevacizumab's Potential: rCBV_max as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients.

Background

Purposes

Methods

Results

Conclusions

Publications

Unlocking Bevacizumab's Potential: rCBV<sub>max</sub> as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Unlocking Bevacizumab's Potential: rCBVmax as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients.

Background

Purposes

Methods

Results

Conclusions

Publications

Unlocking Bevacizumab's Potential: rCBV<sub>max</sub> as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Unlocking Bevacizumab's Potential: rCBV_max as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients.