Survival prediction based on qualitative MRI diffusion signature in patients with recurrent high grade glioma treated with bevacizumab

Advanced magnetic resonance imaging to support clinical drug development for malignant glioma

Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.

A novel DNA repair-related nomogram predicts survival in low-grade gliomas

Aims

We aimed to create a tumor recurrent‐based prediction model to predict recurrence and survival in patients with low‐grade glioma.

Methods

This study enrolled 291 patients (188 in the training group and 103 in the validation group) with clinicopathological information and transcriptome sequencing data. LASSO‐COX algorithm was applied to shrink predictive factor size and build a predictive recurrent signature. GO, KEGG, and GSVA analyses were performed for function annotations of the recurrent signature. The calibration curves and C‐Index were assessed to evaluate the nomogram's performance.

Results

This study found that DNA repair functions of tumor cells were significantly enriched in recurrent low‐grade gliomas. A predictive recurrent signature, built by the LASSO‐COX algorithm, was significantly associated with overall survival and progression‐free survival in low‐grade gliomas. Moreover, function annotations analysis of the predictive recurrent signature exhibited that the signature was associated with DNA repair functions. The nomogram, combining the predictive recurrent signature and clinical prognostic predictors, showed powerful prognostic ability in the training and validation groups.

Conclusion

An individualized prediction model was created to predict 1‐, 2‐, 3‐, 5‐, and 10‐year survival and recurrent rate of patients with low‐grade glioma, which may serve as a potential tool to guide postoperative individualized care.

The MRI Features and Prognosis of Gliomas Associated With IDH1 Mutation: A Single Center Study in Southwest China

Purpose: To investigate the associations of MRI radiological features and prognosis of glioma with the status of isocitrate dehydrogenase 1 (IDH1).

Material and Methods: A total of 116 patients with gliomas were retrospectively recruited from January 2013 to December 2015. All patients were undergone routine MRI (T1WI, T2WI, T2-FLAIR) scanning and contrast-enhanced MRI T1WI before surgery. The following imaging features were included: tumor location, diameter, the pattern of growth, boundary, the degree of enhancement, mass effect, edema, cross the middle line, under the ependyma. χ² and Fisher's exact probability tests were used to determine the significance of associations between MRI features and IDH1 mutation of glioma. The survival distributions were estimated using Kaplan-Meier compared by Log-rank test. Univariate and multivariate analyses were performed using Cox regression.

Results: Gliomas with IDH1 mutant were significantly more likely to exhibit homogeneous signal intensity (p = 0.009) on non-contrast MRI protocols and less contrast enhancement (p = 0.000) on contrast enhanced T1WI. IDH1 mutant type glioma was more inclined to cross the midline to invade contralateral hemisphere (p = 0.001). The overall survival between IDH1 mutated and wild type glioma were significantly different (p = 0.000), age ≤ 40 (p = 0.003), KPS scores > 80 before operation (p = 0.000) and low grade glioma (p = 0.000).

Conclusions: Our results suggest IDH1 mutant in gliomas is more likely to exhibit homogeneous signal intensity, less contrast enhancement and more inclined to cross the midline. Patients with IDH1 mutated, age ≤ 40, KPS scores > 80 before operation and low-grade glioma may have a longer life and better prognosis.

Bevacizumab dose adjustment to improve clinical outcomes of glioblastoma

BACKGROUND

Glioblastoma (GBM) is one of the most aggressive and vascularized brain tumors in adults, with a median survival of 20.9 months. In newly diagnosed and recurrent GBM, bevacizumab demonstrated an increase in progression-free survival, but not in overall survival.

METHODS

We conducted an in silico analysis of VEGF expression, in a cohort of 1082 glioma patients. Then, to determine whether appropriate bevacizumab dose adjustment could increase the anti-angiogenic response, we used in vitro and in vivo GBM models. Additionally, we analyzed VEGFA expression in tissue, serum, and plasma in a cohort of GBM patients before and during bevacizumab treatment.

RESULTS

We identified that 20% of primary GBM did not express VEGFA suggesting that these patients would probably not respond to bevacizumab therapy as we proved in vitro and in vivo. We found that a specific dose of bevacizumab calculated based on VEGFA expression levels increases the response to treatment in cell culture and serum samples from mice bearing GBM tumors. Additionally, in a cohort of GBM patients, we observed a correlation of VEGFA levels in serum, but not in plasma, with bevacizumab treatment performance.

CONCLUSIONS

Our data suggest that bevacizumab dose adjustment could improve clinical outcomes in Glioblastoma treatment.

Reactive oxygen species metabolism-based prediction model and drug for patients with recurrent glioblastoma

Background: Tumor recurrence is the main cause of poor prognosis of GBM. Finding the characteristics of recurrent GBM that provide early warning of tumor recurrence can provide guidance for the clinical treatment of recurrent GBM.

Results: Reactive oxygen species (ROS) biosynthetic processes was significantly elevated in recurrent GBM. The recurrent risk score based on the ROS biosynthetic process was closely related to tumor purity and tumor immune functions. The quantitative risk assessment system could be used to predict the recurrence time of GBM. Gallic acid, a compound with high anti-oxidation activity and low cytotoxicity, was screened as a potential chemotherapy sensitizer for recurrent GBM.

Conclusion: The quantitative risk assessment system based on ROS biosynthetic process could be used for early warning of GBM recurrence. Combination of low-dose gallic acid and temozolomide could improve therapeutic outcomes in recurrent GBM.

Methods: A total of 663 primary and recurrent GBM samples with clinical and microarray data were included in this study. GSVA, LASSO-COX, and Kaplan-Meier survive curve were performed to construct and verify a quantitative risk assessment system for GBM recurrence prediction. An antioxidant capacity test and cell viability test were used to discover potential drugs for recurrent GBM.

The Brain Penetrating and Dual TORC1/TORC2 Inhibitor, RES529, Elicits Anti-Glioma Activity and Enhances the Therapeutic Effects of Anti-Angiogenetic Compounds in Preclinical Murine Models

Background. Glioblastoma multiforme (GBM) is a devastating disease showing a very poor prognosis. New therapeutic approaches are needed to improve survival and quality of life. GBM is a highly vascularized tumor and as such, chemotherapy and anti-angiogenic drugs have been combined for treatment. However, as treatment-induced resistance often develops, our goal was to identify and treat pathways involved in resistance to treatment to optimize the treatment strategies. Anti-angiogenetic compounds tested in preclinical and clinical settings demonstrated recurrence associated to secondary activation of the phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR pathway. Aims. Here, we determined the sensitizing effects of the small molecule and oral available dual TORC1/TORC2 dissociative inhibitor, RES529, alone or in combination with the anti-VEGF blocking antibody, bevacizumab, or the tyrosine kinase inhibitor, sunitinib, in human GBM models. Results. We observed that RES529 effectively inhibited dose-dependently the growth of GBM cells in vitro counteracting the insurgence of recurrence after bevacizumab or sunitinib administration in vivo. Combination strategies were associated with reduced tumor progression as indicated by the analysis of Time to Tumor Progression (TTP) and disease-free survival (DSF) as well as increased overall survival (OS) of tumor bearing mice. RES529 was able to reduce the in vitro migration of tumor cells and tubule formation from both brain-derived endothelial cells (angiogenesis) and tumor cells (vasculogenic mimicry). Conclusions. In summary, RES529, the first dual TORC1/TORC2 dissociative inhibitor, lacking affinity for ABCB1/ABCG2 and having good brain penetration, was active in GBM preclinical/murine models giving credence to its use in clinical trial for patients with GBM treated in association with anti-angiogenetic compounds.

Cerebral blood volume and apparent diffusion coefficient - Valuable predictors of non-response to bevacizumab treatment in patients with recurrent glioblastoma

BACKGROUND

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. The core of standard of care for newly diagnosed GBM was established in 2005 and includes maximum feasible surgical resection followed by radiation and temozolomide, with subsequent temozolomide with or without tumor-treating fields. Unfortunately, nearly all patients experience a recurrence. Bevacizumab (BV) is a commonly used second-line agent for such recurrences, but it has not been shown to impact overall survival, and short-term response is variable.

METHODS

We collected MRI perfusion and diffusion images from 54 subjects with recurrent GBM treated only with radiation and temozolomide. They were subsequently treated with BV. Using machine learning, we created a model to predict short term response (6 months) and overall survival. We set time thresholds to maximize the separation of responders/survivors versus non-responders/short survivors.

RESULTS

We were able to segregate 21 (68%) of 31 subjects into unlikely to respond categories based on Progression Free Survival at 6 months (PFS6) criteria. Twenty-two (69%) of 32 subjects could similarly be identified as unlikely to survive long using the machine learning algorithm.

CONCLUSION

With the use of machine learning techniques to evaluate imaging features derived from pre- and post-treatment multimodal MRI, it is possible to identify an important fraction of patients who are either highly unlikely to respond, or highly likely to respond. This can be helpful is selecting patients that either should or should not be treated with BV.

Early assessment of recurrent glioblastoma response to bevacizumab treatment by diffusional kurtosis imaging: a preliminary report

PURPOSE

The purpose of this preliminary study is to apply diffusional kurtosis imaging to assess the early response of recurrent glioblastoma to bevacizumab treatment.

METHODS

This prospective cohort study included 10 patients who had been diagnosed with recurrent glioblastoma and scheduled to receive bevacizumab treatment. Diffusional kurtosis images were obtained from all the patients 0-7 days before (pre-bevacizumab) and 28 days after (post-bevacizumab) initiating bevacizumab treatment. The mean, 10th, and 90th percentile values were derived from the histogram of diffusional kurtosis imaging metrics in enhancing and non-enhancing lesions, selected on post-contrast T1-weighted and fluid-attenuated inversion recovery images. Correlations of imaging measures with progression-free survival and overall survival were evaluated using Spearman's rank correlation coefficient. The significance level was set at P < 0.05.

RESULTS

Higher pre-bevacizumab non-enhancing lesion volume was correlated with poor overall survival (r = -0.65, P = 0.049). Higher post-bevacizumab mean diffusivity and axial diffusivity (D_∥, D_∥10% and D_∥90%) in non-enhancing lesions were correlated with poor progression-free survival (r = -0.73, -0.83, -0.71 and -0.85; P < 0.05). Lower post-bevacizumab axial kurtosis (K_∥10%) in non-enhancing lesions was correlated with poor progression-free survival (r = 0.81, P = 0.008).

CONCLUSIONS

This preliminary study demonstrates that diffusional kurtosis imaging metrics allow the detection of tissue changes 28 days after initiating bevacizumab treatment and that they may provide information about tumor progression.