Hatanpaa, Kimmo J.

Glioblastoma (GBM) is a devastating cancer with a dismal prognosis. Current treatment includes temozolomide (TMZ), which is more effective in about 50% of GBMs that have O 6 - methylguanine DNA methyltransferase ( MGMT ) promoter methylation. MGMT is a DNA repair protein that reverses TMZ-induced DNA damage. EGFR is a prime oncogene in GBM. Here, we report that EGFR inhibition induced the down-regulation of MGMT in GBM cells, revealing a previously unidentified link between EGFR signaling and response to TMZ. EGFR inhibition led to activation of two transcription factors, activator protein-1 (AP-1), which repressed MGMT transcription, and nuclear factor κB (NF-κB), which up-regulated MGMT transcription. EGFR inhibition also induced AP-1–mediated transcription of miR-616. miR-616 inhibited both MGMT translation and NF-κB activation. Thus, the overall effect of EGFR inhibition was down-regulation of MGMT expression. In addition, we provided an explanation for the prior failure of clinical trials that used concomitant EGFR tyrosine kinase inhibitors (TKIs) and TMZ. TMZ up-regulated MGMT, and concomitant treatment with EGFR TKIs and TMZ failed to down-regulate MGMT. However, pretreatment with EGFR TKIs followed by TMZ efficiently down-regulated MGMT and enhanced TMZ sensitivity in experimental models. Posttreatment tumor tissues from two clinical trials were used to validate these findings. We demonstrated that EGFR inhibitors induced down-regulation of MGMT in posttreatment resected tumor tissues from patients with GBM and the failure of EGFR inhibition to down-regulate MGMT if TMZ was used concomitantly. These data support using EGFR TKIs before TMZ treatment as a therapeutic approach in MGMT unmethylated GBM.

Abstract Background IDH-mutant astrocytomas are classified as WHO grade 4 in the presence of conventional high-grade histologic features and/or homozygous CDKN2A/B deletion in the 5th edition of the WHO Classification of Central Nervous System Tumour guidelines. However, work over the past decade has indicated a number of other molecular alterations that warrant consideration as potential prognostic markers. Methods We used univariate Kaplan-Meier and multivariate Cox proportional hazards regression analysis to evaluate the prognostic effects of homozygous CDKN2A/B deletion, CDK4 amplification, CCND2 amplification, PDGFRA amplification/mutation, PIK3R1 mutation, PIK3CA mutation, MYCN amplification, EGFR amplification/mutation, TERT promoter mutation, and grade 4 histologic features in two independent cohorts of WHO grade 2-4 IDH-mutant astrocytoma (n = 840 and n = 367). Results The presence of CDK4 amplification, CCND2 amplification, PDGFRA alteration, PIK3R1 mutation, MYCN amplification, and EGFR alteration were each associated with reduced overall survival compared to WHO grade 2/3 astrocytomas without these molecular features. 17.7% (148/837) of otherwise grade 2/3 astrocytomas had one or more of these molecular criteria, with resulting intermediate clinical outcome in terms of overall survival (median survival of 67.3-82.0 months) compared to grade 2/3 astrocytomas without these molecular features (median survival of 135.0-140.7 months) and grade 4 astrocytomas (median survival of 35.3-45.0 months). Conclusions The presence of CDK4, CCND2, PDGFRA, PIK3R1, MYCN, and EGFR alterations result in an intermediate patient survival in IDH-mutant astrocytoma. Adding these molecular alterations should be considered in future diagnostic classification systems to improve stratification of high-risk patients.

Abstract Background The isocitrate dehydrogenase (IDH) mutation status is a key molecular marker in diagnosing and treating brain tumors. Currently, it is determined via invasive tissue biopsy. Recent advances in deep learning (DL) have offered promising non-invasive alternatives for determining IDH status. However, their clinical translation is hindered by a significant gap between DL predictions and their clinical applicability. The limited transparency of many DL-networks and inadequate evaluation metrics hinders trust and adoption, as clinicians require clear and validated insights for determining IDH status. These challenges highlight the need for robust validation and measures of predictive reliability to make DL-predictions clinically actionable. Methods We developed a unique approach for non-invasive prediction of IDH status using MRI. We combine a voxel-wise-segmentation network(MC-net) with Bayesian logistic regression (BLR) to provide an IDH status and estimate confidence scores. We utilized a comprehensive dataset of 2,481 glioma cases from eight institutions. Results Our framework(MC-net + BLR) demonstrated robust performance achieving 96.4% and 95.1% classification accuracies on diverse databases, with an AUC of 0.98. The BLR was implemented exclusively on held-out test data, ensuring that the derived confidence scores are independent of the training or validation phases. The derived confidence scores showed a low Brier score of 0.0125, highlighting its superior calibration and uncertainty quantification. Conclusion The developed framework provides an IDH status and a confidence score, offering clinicians an additional layer of assurance in prediction reliability. It bridges the gap between high-performing DL models and their clinical applicability by addressing the challenges in prediction reliability. Our framework is a significant advancement in non-invasive determination of IDH-status and confidence-informed therapeutic decision-making in neuro-oncology.

Abstract Branched-chain amino acid transaminase 1 (BCAT1) is upregulated selectively in human isocitrate dehydrogenase (IDH) wildtype (WT) but not mutant glioblastoma multiforme (GBM) and promotes IDHWT GBM growth. Through a metabolic synthetic lethal screen, we report here that α-ketoglutarate (AKG) kills IDHWT GBM cells when BCAT1 protein is lost, which is reversed by reexpression of BCAT1 or supplementation with branched-chain α-ketoacids (BCKA), downstream metabolic products of BCAT1. In patient-derived IDHWT GBM tumors in vitro and in vivo, cotreatment of BCAT1 inhibitor gabapentin and AKG resulted in synthetic lethality. However, AKG failed to evoke a synthetic lethal effect with loss of BCAT2, BCKDHA, or GPT2 in IDHWT GBM cells. Mechanistically, loss of BCAT1 increased the NAD+/NADH ratio but impaired oxidative phosphorylation, mTORC1 activity, and nucleotide biosynthesis. These metabolic alterations were synergistically augmented by AKG treatment, thereby causing mitochondrial dysfunction and depletion of cellular building blocks, including ATP, nucleotides, and proteins. Partial restoration of ATP, nucleotides, proteins, and mTORC1 activity by BCKA supplementation prevented IDHWT GBM cell death conferred by the combination of BCAT1 loss and AKG. These findings define a targetable metabolic vulnerability in the most common subset of GBM that is currently incurable. Significance: Metabolic synthetic lethal screening in IDHWT glioblastoma defines a vulnerability to ΑΚG following BCAT1 loss, uncovering a therapeutic strategy to improve glioblastoma treatment. See related commentary by Meurs and Nagrath, p. 2354

Abstract Background Glioblastoma (GBM) is the most common primary malignant adult brain tumor. Temozolomide (TMZ) is the standard of care and is most effective in GBMs that lack the DNA repair protein O6-methylguanine-DNA methyltransferase (MGMT). Moreover, even initially responsive tumors develop a secondary resistance to TMZ and become untreatable. Since aberrant epidermal growth factor receptor (EGFR) signaling is widespread in GBM, EGFR inhibition has been tried in multiple clinical trials without success. We recently reported that inhibiting EGFR leads to increased secretion of tumor necrosis factor (TNF) and activation of a survival pathway in GBM. Here, we compare the efficacy of TMZ versus EGFR plus TNF inhibition in an orthotopic mouse model of GBM. Methods We use an orthotopic model to examine the efficacy of TMZ versus EGFR plus TNF inhibition in multiple subsets of GBMs, including MGMT methylated and unmethylated primary GBMs, recurrent GBMs, and GBMs rendered experimentally resistant to TMZ. Results The efficacy of the 2 treatments was similar in MGMT methylated GBMs. However, in MGMT unmethylated GBMs, a combination of EGFR plus TNF inhibition was more effective. We demonstrate that the 2 treatment approaches target distinct and non-overlapping pathways. Thus, importantly, EGFR plus TNF inhibition remains effective in TMZ-resistant recurrent GBMs and in GBMs rendered experimentally resistant to TMZ. Conclusion EGFR inhibition combined with a blunting of the accompanying TNF-driven adaptive response could be a viable therapeutic approach in MGMT unmethylated and recurrent EGFR-expressing GBMs.