Lack of Benefit of Extending Temozolomide Treatment in Patients with High Vascular Glioblastoma with Methylated MGMT

Preoperative vascular heterogeneity based on dynamic susceptibility contrast MRI in predicting spatial pattern of locally recurrent high-grade gliomas

OBJECTIVES

To investigate if spatial recurrence pattern is associated with patient prognosis, and whether MRI vascular habitats can predict spatial pattern.

METHODS

In this retrospective study, 69 patients with locally recurrent high-grade gliomas (HGGs) were included. The cohort was divided into intra-resection cavity recurrence (ICR) and extra-resection cavity recurrence (ECR) patterns, according to the distance between the location of the recurrent tumor and the resection cavity or surgical region. Four vascular habitats, high angiogenic tumor, low angiogenic tumor, infiltrated peripheral edema, and vasogenic peripheral edema, were segmented and vascular heterogeneity parameters were analyzed. The survival and diagnostic performance under different spatial recurrence patterns were analyzed by Kaplan-Meier and ROC. A nomogram model was constructed by regression analysis and validated by bootstrapping technique.

RESULTS

Progression-free survival (PFS) and overall survival (OS) were longer for ICR (n = 32) than those for ECR (n = 37) (median PFS: 8 vs. 5 months, median OS: 17 vs. 13 months, p < 0.05). MRI vascular habitat analyses showed ECR had higher median relative cerebral blood volume (rCBVmedian) at each habitat than ICR (all p < 0.01). The rCBVmedian at IPE had good diagnostic performance (AUC: 0.727, 95%CI: 0.607, 0.828). The AUC of the nomogram based on MRI vascular habitats and clinical factors was 0.834 (95%CI: 0.726, 0.913) and was confirmed as 0.833 (95%CI: 0.830, 0.836) by bootstrapping validation.

CONCLUSIONS

The spatial pattern of locally recurrent HGGs is associated with prognosis. MRI vascular heterogeneity parameter could be used as a non-invasive imaging marker to predict spatial recurrence pattern.

CLINICAL RELEVANCE STATEMENT

Vascular heterogeneity parameters based on MRI vascular habitat analyses can non-invasively predict the spatial patterns of locally recurrent high-grade gliomas, providing a new diagnostic basis for clinicians to develop the extent of surgical resection and postoperative radiotherapy planning.

KEY POINTS

• Intra-resection cavity pattern was associated with longer progression-free survival and overall survival in locally recurrent high-grade gliomas. • Higher vascular heterogeneities in extra-resection cavity recurrence than in intra-resection cavity recurrence and the vascular heterogeneity parameters had good diagnostic performance in discriminating spatial recurrence pattern. • A nomogram model based on MRI vascular habitats and clinical factors had good performance in predicting spatial recurrence pattern.

Multimodel habitats constructed by perfusion and/or diffusion MRI predict isocitrate dehydrogenase mutation status and prognosis in high-grade gliomas

AIM

To determine whether tumour vascular and cellular heterogeneity of high-grade glioma (HGG) is predictive of isocitrate dehydrogenase (IDH) mutation status and overall survival (OS) by using tumour habitat-based analysis constructed by perfusion and/or diffusion magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Seventy-eight HGG patients that met the 2021 World Health Organization WHO Classification of Tumors of the Central Nervous System, 5th edition (WHO CNS5), were enrolled to predict IDH mutation status, of which 32 grade 4 patients with unmethylated O6-methylguanine-DNA methyltransferase (MGMT) promoter were enrolled for prognostic analysis. The deep-learning-based model nnU-Net and K-means clustering algorithm were applied to construct the Traditional Habitat, Vascular Habitat (VH), Cellular Density Habitat (DH), and their Combined Habitat (CH). Quantitative parameters were extracted and compared between IDH-mutant and IDH-wild-type patients, respectively, and the prediction potential was evaluated by receiver operating characteristic (ROC) curve analysis. OS was analysed using Kaplan-Meier survival analysis and the log-rank test.

RESULTS

Compared with IDH-mutants, median relative cerebral blood volume (rCBVmedian) values in the whole enhancing tumour (WET), VH1, VH3, CH1-4 habitats were significantly increased in IDH-wild-type HGGs (all p<0.05). Additionally, the accuracy of rCBVmedian values in CH1 outperformed other habitats in identifying IDH mutation status (p<0.001) at a cut-off value of 4.83 with AUC of 0.815. Kaplan-Meier survival analysis highlighted significant differences in OS between the populations dichotomised by the median of rCBVmedian in WET, VH1, CH1-3 habitats (all p<0.05).

CONCLUSIONS

The habitat imaging technique may improve the accuracy of predicting IDH mutation status and prognosis, and even provide a new direction for subsequent personalised precision treatment.

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

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.

Immunoexpression of p62/SQSTM1/Sequestosome‑1 in human primary and recurrent IDH1/2 wild‑type glioblastoma: A pilot study

p62/SQSTM1/Sequestosome-1 is an autophagic protein that serves a crucial role in cellular metabolism, proliferation and malignant growth. Notably, autophagy may influence the development and resistance to therapy of numerous types of human cancer. In the present pilot study, the immunohistochemical pattern of p62 was analyzed in a cohort of patients with isocitrate dehydrogenase (IDH)1/2 wild-type glioblastoma (GBM), in primary and recurrent samples, in order to verify the concordance or discordance between the primary and recurrent tumors. In addition, the association between p62, and patient outcome and O⁶-methylguanine-DNA methyltransferase (MGMT) status was assessed. The results revealed p62 immunoexpression in the nucleus and cytoplasm of neoplastic elements in 45% of primary and 55% of recurrent cases of GBM. A discordant p62 immunoreactivity was detected in 35% of cases, with a variation either with positive or negative conversion of p62 status. Statistically, p62 expression and MGMT status exhibited a significant prognostic value by univariate analysis, whereas only MGMT promoter methylation status emerged as an independent prognostic factor by multivariate analysis. Finally, the most favorable prognosis was documented when the same GBM case was positively concordant for both p62 expression and MGMT methylated status. Since little data are available regarding the association between p62 expression and MGMT in GBM, further investigations may be required to determine if new targeted therapies may be addressed against autophagy-related proteins, such as p62.

Comprehensive Analysis of Prognostic Value and Immune Infiltration of IGFBP Family Members in Glioblastoma

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults. The insulin-like growth factor-binding protein (IGFBP) family is involved in tumorigenesis and the development of multiple cancers. However, little is known about the prognostic value and regulatory mechanisms of IGFBPs in GBM. Oncomine, Gene Expression Profiling Interactive Analysis, PrognoScan, cBioPortal, LinkedOmics, TIMER, and TISIDB were used to analyze the differential expression, prognostic value, genetic alteration, biological function, and immune cell infiltration of IGFBPs in GBM. We observed that IGFBP1, IGFBP2, IGFBP3, IGFBP4, and IGFBP5 mRNA expression was significantly upregulated in patients with GBM, whereas IGFBP6 was downregulated; this difference in mRNA expression was statistically insignificant. Subsequent investigations showed that IGFBP4 and IGFBP6 mRNA levels were significantly associated with overall survival in patients with GBM. Functional Gene Ontology Annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that genes coexpressed with IGFBP4 and IGFBP6 were mainly enriched in immune-related pathways. These results were validated using the TIMER and TSMIDB databases. This study demonstrated that the IGFBP family has prognostic value in patients with GBM. IGFBP4 and IGFBP6 are two members of the IGFBP family that had the highest prognostic value; thus, they have the potential to serve as survival predictors and immunotherapeutic targets in GBM.

Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.