Molecularly targeted therapies using receptor inhibitors, small molecules or monoclonal antibodies are routinely applied in oncology. Verification of target expression should be mandatory prior to initiation of therapy, yet, determining the expression status is most challenging in recurrent glioblastoma (GBM) where most patients are not eligible for second-line surgery. Because very little is known on the consistency of expression along the clinical course we here explored common drug targets in paired primary vs. recurrent GBM tissue samples. Paired surgical tissue samples were derived from a homogeneously treated cohort of 34 GBM patients. All patients received radiotherapy and temozolomide chemotherapy. Verification of common drug targets included immunohistological analysis of PDGFR-β, FGFR-2, FGFR-3, and mTOR-pathway component (phospho-mTORSer2448) as well as molecular, MLPA-based analysis of specific copy number aberrations at the gene loci of ALK, PDGFRA, VEGFR2/KDR, EGFR, MET, and FGFR1. Paired tumor tissue exhibited significant changes of expression in 9 of the 10 investigated druggable targets (90%). Only one target (FGFR1) was found “unchanged”, since dissimilar expression was observed in only one of the 34 paired tumor tissue samples. All other targets were variably expressed with an 18–56% discordance rate between primary and recurrent tissue. The high incidence of dissimilar target expression status in clinical samples from primary vs. recurrent GBM suggests clinically relevant heterogeneity along the course of disease. Molecular target expression, as determined at primary diagnosis, may not necessarily present rational treatment clues for the clinical care of recurrent GBM. Further studies need to analyze the therapeutic impact of longitudinal heterogeneity in GBM.

Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.

Despite multimodal treatment, the prognosis of patients with glioblastoma (GBM) remains poor. Previous studies showed conflicting results on the effect of antiepileptic drugs (AED) on GBM survival. We investigated the associations of different AED with overall survival (OS) and progression-free survival (PFS) in a large institutional GBM cohort (n = 872) treated January 2006 and December 2018. In addition, we performed a meta-analysis of previously published studies, including this study, to summarize the evidence on the value of AED for GBM prognosis. Of all perioperatively administered AED, only the use of levetiracetam (LEV) was associated with longer OS (median: 12.8 vs. 8.77 months, p < 0.0001) and PFS (7 vs. 4.5 months, p = 0.001). In the multivariable analysis, LEV was independently associated with longer OS (aHR = 0.74, p = 0.017) and PFS (aHR = 0.68, p = 0.008). In the meta-analysis with 5614 patients from the present and seven previously published studies, outcome benefit for OS (HR = 0.83, p = 0.02) and PFS (HR = 0.77, p = 0.02) in GBM individuals with LEV was confirmed. Perioperative treatment with LEV might improve the prognosis of GBM patients. We recommend a prospective randomized controlled trial addressing the efficacy of LEV in GBM treatment.

Purpose: Therapy resistance and fatal disease progression in glioblastoma are thought to result from the dynamics of intra-tumor heterogeneity. This study aimed at identifying and molecularly targeting tumor cells that can survive, adapt, and subclonally expand under primary therapy. Experimental Design: To identify candidate markers and to experimentally access dynamics of subclonal progression in glioblastoma, we established a discovery cohort of paired vital cell samples obtained before and after primary therapy. We further used two independent validation cohorts of paired clinical tissues to test our findings. Follow-up preclinical treatment strategies were evaluated in patient-derived xenografts. Results: We describe, in clinical samples, an archetype of rare ALDH1A1+ tumor cells that enrich and acquire AKT-mediated drug resistance in response to standard-of-care temozolomide (TMZ). Importantly, we observe that drug resistance of ALDH1A1+ cells is not intrinsic, but rather an adaptive mechanism emerging exclusively after TMZ treatment. In patient cells and xenograft models of disease, we recapitulate the enrichment of ALDH1A1+ cells under the influence of TMZ. We demonstrate that their subclonal progression is AKT-driven and can be interfered with by well-timed sequential rather than simultaneous antitumor combination strategy. Conclusions: Drug-resistant ALDH1A1+/pAKT+ subclones accumulate in patient tissues upon adaptation to TMZ therapy. These subclones may therefore represent a dynamic target in glioblastoma. Our study proposes the combination of TMZ and AKT inhibitors in a sequential treatment schedule as a rationale for future clinical investigation.

In order to minimize the risk of infections during the COVID-19 pandemic, remote video consultations (VC) experienced an upswing in most medical fields. However, telemedicine in neuro-oncology comprises unique challenges and opportunities. So far, evidence-based insights to evaluate and potentially customize current concepts are scarce. To fill this gap, we analyzed >3700 neuro-oncological consultations, of which >300 were conducted as VC per patients’ preference, in order to detect how both patient collectives distinguished from one another. Additionally, we examined patients’ reasons, suitable/less suitable encounters, VC’s benefits and disadvantages and future opportunities with an anonymized survey. Patients that participated in VC had a worse clinical condition, higher grade of malignancy, were more often diagnosed with glioblastoma and had a longer travel distance (all p < 0.01). VC were considered a fully adequate alternative to face-to-face consultations for almost all encounters that patients chose to participate in (>70%) except initial consultations. Most participants preferred to alternate between both modalities rather than participate in one alone but preferred VC over telephone consultation. VC made patients feel safer, and participants expressed interest in implementing other telemedicine modalities (e.g., apps) into neuro-oncology. VC are a promising addition to patient care in neuro-oncology. However, patients and encounters should be selected individually.