Aim: Long-term survivors (LTS) after glioma recurrence while on bevacizumab (Bev) therapy are rarely reported in the current literature. The purpose of this case series is to confirm the existence of and describe a large cohort of recurrent glioma LTS treated with Bev (Bev-LTS). Patients & methods: We identified Bev-LTS as patients with post-Bev initiation survival times of ≥3 years among 1397 Bev treated recurrent glioma patients. Results: Among 962 grade-IV, 221 grade III, and 214 grade II Bev-treated glioma patients, we identified 28 (2.9%), 14 (6.3%) and 8 (3.7%) Bev-LTS patients, respectively. 45 Bev-LTS patients recurred on Bev, with 36 of those patients continuing therapy. Conclusion: Our study shows that a small portion of grade-IV, -III, and -II glioma patients can have long-term survival on Bev therapy even after Bev recurrence.

Background

Diffusion magnetic resonance (MR) characteristics are a predictive imaging biomarker for survival benefit in recurrent glioblastoma treated with anti-vascular endothelial growth factor (VEGF) therapy; however, its use in large volume recurrence has not been evaluated.

Objective

To determine if diffusion MR characteristics can predict survival outcomes in patients with large volume recurrent glioblastoma treated with bevacizumab or repeat resection.

Methods

A total of 32 patients with large volume (>20 cc or > 3.4 cm diameter) recurrent glioblastoma treated with bevacizumab and 35 patients treated with repeat surgery were included. Pretreatment tumor volume and apparent diffusion coefficient (ADC) histogram analysis were used to phenotype patients as having high (>1.24 μm2/ms) or low (<1.24 μm2/ms) ADCL, the mean value of the lower peak in a double Gaussian model of the ADC histogram within the contrast enhancing tumor.

Results

In bevacizumab and surgical cohorts, volume was correlated with overall survival (Bevacizumab: P = .009, HR = 1.02; Surgical: P = .006, HR = 0.96). ADCL was an independent predictor of survival in the bevacizumab cohort (P = .049, HR = 0.44), but not the surgical cohort (P = .273, HR = 0.67). There was a survival advantage of surgery over bevacizumab in patients with low ADCL (P = .036, HR = 0.43) but not in patients with high ADCL (P = .284, HR = 0.69).

Conclusion

Pretreatment diffusion MR imaging is an independent predictive biomarker for overall survival in recurrent glioblastoma with a large tumor burden. Large tumors with low ADCL have a survival benefit when treated with surgical resection, whereas large tumors with high ADCL may be best managed with bevacizumab.

Background

Targeted next-generation sequencing (NGS) is frequently obtained at the University of California, Los Angeles (UCLA) for clinical characterization of CNS tumors. In this study, we describe the diagnostic reliability of the Foundation Medicine (FM) targeted NGS platform and its ability to explore and identify tumor characteristics of prognostic significance in gliomas.

Methods

Neuro-oncology patients seen at UCLA who have received FM testing between August 2012 and March 2019 were included in this study, and all mutations from FM test reports were recorded. Initial tumor diagnoses and diagnostic markers found via standard clinical methods were obtained from pathology reports. With overall and progression-free survival data, elastic net regularized Cox regression and Cox proportional hazards models were used to determine whether any mutations of unknown significance detected by FM could predict patient outcome in glioblastoma (GBM).

Results

Six hundred and three samples tested by FM from 565 distinct patients were identified. Concordance of diagnostic markers was high between standard clinical testing methods and FM. Oligodendroglial markers detected via FM were highly correlated with 1p19q codeletion in IDH mutated gliomas. FM testing of multiple tumor samples from the same patient demonstrated temporal and spatial mutational heterogeneity. Mutations in BCORL1, ERBB4, and PALB2, which are mutations of unknown significance in GBM, were shown to be statistically significant in predicting patient outcome.

Conclusions

In our large cohort, we found that targeted NGS can both reliably and efficiently detect important diagnostic markers in CNS tumors.