Glioblastoma multiforme (GBM) is the deadliest, most heterogeneous, and most common brain cancer in adults. Not only is there an urgent need to identify efficacious therapeutics, but there is also a great need to pair these therapeutics with biomarkers that can help tailor treatment to the right patient populations. We built patient drug response models by integrating patient tumor transcriptome data with high-throughput cell line drug screening data as well as Bayesian networks to infer relationships between patient gene expression and drug response. Through these discovery pipelines, we identified agents of interest for GBM to be effective across five independent patient cohorts and in a mouse avatar model: among them are a number of MEK inhibitors (MEKis). We also predicted phosphoglycerate dehydrogenase enzyme (PHGDH) gene expression levels to be causally associated with MEKi efficacy, where knockdown of this gene increased tumor sensitivity to MEKi and overexpression led to MEKi resistance. Overall, our work demonstrated the power of integrating computational approaches. In doing so, we quickly nominated several drugs with varying known mechanisms of action that can efficaciously target GBM. By simultaneously identifying biomarkers with these drugs, we also provide tools to select the right patient populations for subsequent evaluation.

Background: The application of immunotherapy for pediatric CNS malignancies has been limited by the poorly understood immune landscape in this context. The aim of this study was to uncover the mechanisms of immune suppression common among pediatric brain tumors. Methods: We apply an immunologic clustering algorithm validated by The Cancer Genome Atlas Project to an independent pediatric CNS transcriptomic dataset. Within the clusters, the mechanisms of immunosuppression are explored via tumor microenvironment deconvolution and survival analyses to identify relevant immunosuppressive genes with translational relevance. Results: High-grade diseases fall predominantly within an immunosuppressive subtype (C4) that independently lowers overall survival time and where common immune checkpoints (e.g., PDL1, CTLA4) are less relevant. Instead, we identify several alternative immunomodulatory targets with relevance across histologic diseases. Specifically, we show how the mechanism of EZH2 inhibition to enhance tumor immunogenicity in vitro via the upregulation of MHC class 1 is applicable to a pediatric CNS oncologic context. Meanwhile, we identify that the C3 (inflammatory) immune subtype is more common in low-grade diseases and find that immune checkpoint inhibition may be an effective way to curb progression for this subset. Conclusions: Three predominant immunologic clusters are identified across pediatric brain tumors. Among high-risk diseases, the predominant immune cluster is associated with recurrent immunomodulatory genes that influence immune infiltrate, including a subset that impacts survival across histologies.

Robert T Galvin, MD, Cynthia Zheng, Garrett Fitzpatrick, MD, Colleen L Forster, Carolina Sandoval-Garcia, MD, Daniel Guillaume, MD, Ahmed Elbermawy, MD, Andrew

Background: It is not known whether temporal changes in childhood cancer therapy have reduced risk of subsequent malignant neoplasms of the central nervous system (CNS), a frequently fatal late effect of cancer therapy. Methods: Five-year survivors of primary childhood cancers diagnosed between 1970 and 1999 in the Childhood Cancer Survivor Study with CNS subsequent malignant neoplasms were identified. Cumulative incidence rates and standardized incidence ratios were compared among survivors diagnosed between 1970-1979 (n = 6223), 1980-1989 (n = 9680), and 1990-1999 (n = 8999). Multivariable models assessed risk factors for CNS subsequent malignant neoplasms. Results: A total of 157 CNS subsequent malignant neoplasms (1970s, 52; 1980s, 63; 1990s, 42) were identified, excluding meningiomas, which were most often malignant gliomas. The proportion of survivors receiving any cranial radiotherapy exposure was reduced over time (1970s, 77.0%; 1980s, 54.3%; 1990s, 33.9%), while the proportion receiving more than 35 Gy cranial radiotherapy showed a smaller reduction (11.4%, 10.8%, and 8.5%, respectively). Twenty-year cumulative incidence and standardized incidence ratios for CNS subsequent malignant neoplasms by treatment decade were 0.32% (95% confidence interval = 0.18% to 0.46%) and 6.6 (95% CI = 5.0 to 8.7); 0.55% (95% CI = 0.41% to 0.70%) and 8.3 (95% CI = 6.6 to 10.4); and 0.43% (95% CI = 0.31% to 0.55%) and 9.2 (95% CI = 7.0 to 12.0), respectively, with no statistically significant decreases between eras. Multivariable analyses showed increased risk for cranial radiotherapy dose levels more than 10 Gy and for primary diagnoses of medulloblastoma and/or primitive neuro-ectodermal tumor (hazard ratio [HR] = 18.7, 95% CI = 9.2 to 37.9) and astrocytoma (HR = 10.1, 95% CI = 5.3 to 19.5). Three-year cumulative incidence of death after CNS subsequent malignant neoplasms, by treatment decade, were 76%, 74%, and 73%, respectively. Conclusion: CNS subsequent malignant neoplasm incidence has not decreased despite fewer survivors exposed to CNS-directed radiotherapy. CNS subsequent malignant neoplasm remains a substantial source of mortality for affected patients.

Purpose: Knowledge of prognostic factors and long-term survival in patients with diffuse hemispheric glioma, H3 G34–mutant (DHG, H3 G34), remains limited in this tumor with a poor prognosis. Experimental Design: This retrospective, multi-institutional study investigated prognostic variables for patients with DHG, H3 G34, and their association with progression-free survival (PFS) and overall survival (OS). Uni- and multivariable Cox proportional hazard models were applied with multiple imputed datasets. Results: A total of 153 patients (142 G34R, 9 G34V, 2 via DNA methylation) were included. The median age at diagnosis was 17 years (range, 2–45). Initial gross/near total resection (GTR/NTR) was achieved in 43% of patients. Radiation was given in 91% (85% focal irradiation), and initial chemotherapy was given in 87% [70% temozolomide-based (TMZ), 25% TMZ/lomustine, 5% non-TMZ]. Median OS was 24 months [interquartile range (IQR), 22–28] with a median PFS of 14 months (IQR, 12–19). Twelve patients (8%) were found to be long-term survivors (≥5 years). Exploratory multivariable analysis showed that adjuvant radiotherapy [HR, 0.076; 95% confidence interval (CI), 0.033–0.17] and achieving GTR/NTR compared with < NTR (HR, 0.51; 95% CI, 0.33–0.78) were associated with improved PFS. Multivariable analysis showed improved OS with increasing age at diagnosis (HR, 0.70; 95% CI, 0.57–0.87), initial radiotherapy (HR, 0.38; 95% CI, 0.15–0.96), and initial GTR/NTR compared with < NTR (HR, 0.60; 95% CI, 0.37–0.97). Conclusions: This cohort highlights prognostic factors for patients with DHG, H3 G34, and describes relapse patterns and therapy approaches. Clinical trials and prospective registries are needed to improve outcomes.