Kim, Michelle M.

PURPOSE Survival for patients with melanoma has recently improved. The propensity of melanoma to metastasize to the brain remains a common and serious feature of this disease. The purposes of this study were to evaluate prognostic factors for patients with newly diagnosed melanoma brain metastases (MBMs) in a large cohort treated with modern multimodal therapies, compare those results with those in prior eras, and update the Melanoma Graded Prognostic Assessment (GPA). METHODS Univariable and multivariable (MVA) analyses of prognostic factors and treatments associated with survival were performed on 1,796 patients with newly diagnosed MBM treated between January 01, 2015, and December 31, 2021, using a multi-institutional retrospective database. Multiple imputation was used to address missingness of potential predictors. Significant variables in combined MVA were used to update the Melanoma GPA. Comparisons were made with legacy cohorts. RESULTS Median survivals for cohorts A (1985-2007, n = 481), B (2006-2015, n = 823), and C (2015-2021, n = 1,796) were 6.7, 9.8, and 16.6 months and median follow-up times were 40.1, 43.6, and 48.8 months, respectively. In combined MVA, significant prognostic factors for survival were higher Karnofsky Performance Status, fewer MBMs, absence of extracranial metastases, lower serum lactate dehydrogenase, and no immunotherapy before MBM. These factors were incorporated into the updated Melanoma GPA. The combined median and 3-year survivals for patients with GPA 0-1, 1.5-2, and 2.5-4.0 were 5.4, 13.2, and 43.2 months and 12.4%, 28.8%, and 51.6%, respectively. CONCLUSION Prognostic factors have changed and survival has improved for patients with MBM but varies widely by GPA. The updated Melanoma GPA calculator (BrainMetGPA), available free online, can be used to estimate survival, individualize treatment, stratify clinical trials, guide surveillance, and augment clinical trial eligibility. Multidisciplinary treatment is essential. Trials are needed to elucidate the optimal sequencing of various therapeutic modalities.

Abstract Advances in diagnostic and treatment technology along with rapid developments in translational research may now allow the realization of precision radiotherapy. Integration of biologically informed multimodality imaging to address the spatial and temporal heterogeneity underlying treatment resistance in glioblastoma is now possible for patient care, with evidence of safety and potential benefit. Beyond their diagnostic utility, several candidate imaging biomarkers have emerged in recent early-phase clinical trials of biologically based radiotherapy, and their definitive assessment in multicenter prospective trials is already in development. In this review, the rationale for clinical implementation of candidate advanced magnetic resonance imaging and positron emission tomography imaging biomarkers to guide personalized radiotherapy, the current landscape, and future directions for integrating imaging biomarkers into radiotherapy for glioblastoma are summarized. Moving forward, response-adaptive radiotherapy using biologically informed imaging biomarkers to address emerging treatment resistance in rational combination with novel systemic therapies may ultimately permit improvements in glioblastoma outcomes and true individualization of patient care.

Abstract Patients with H3K27M-mutant diffuse midline glioma (DMG) have no proven effective therapies. ONC201 has recently demonstrated efficacy in these patients, but the mechanism behind this finding remains unknown. We assessed clinical outcomes, tumor sequencing, and tissue/cerebrospinal fluid (CSF) correlate samples from patients treated in two completed multisite clinical studies. Patients treated with ONC201 following initial radiation but prior to recurrence demonstrated a median overall survival of 21.7 months, whereas those treated after recurrence had a median overall survival of 9.3 months. Radiographic response was associated with increased expression of key tricarboxylic acid cycle–related genes in baseline tumor sequencing. ONC201 treatment increased 2-hydroxyglutarate levels in cultured H3K27M-DMG cells and patient CSF samples. This corresponded with increases in repressive H3K27me3 in vitro and in human tumors accompanied by epigenetic downregulation of cell cycle regulation and neuroglial differentiation genes. Overall, ONC201 demonstrates efficacy in H3K27M-DMG by disrupting integrated metabolic and epigenetic pathways and reversing pathognomonic H3K27me3 reduction. Significance: The clinical, radiographic, and molecular analyses included in this study demonstrate the efficacy of ONC201 in H3K27M-mutant DMG and support ONC201 as the first monotherapy to improve outcomes in H3K27M-mutant DMG beyond radiation. Mechanistically, ONC201 disrupts integrated metabolic and epigenetic pathways and reverses pathognomonic H3K27me3 reduction. This article is featured in Selected Articles from This Issue, p. 2293

Abstract Background Predictive molecular biomarkers to select optimal treatment for patients with glioblastoma and other cancers are lacking. New strategies are needed when large randomized trials with correlative molecular data are not feasible. Methods Gene signatures (GS) were developed from 31 orthotopic glioblastoma patient-derived xenografts (PDXs), treated with standard therapies, to predict benefit from radiotherapy (RT-GS), temozolomide (Chemo-GS), or the combination (ChemoRT-GS). Independent validation was performed in a heterogeneously treated clinical cohort of 502 glioblastoma patients with overall survival as the primary endpoint. Multivariate Cox analysis was used to adjust for confounding variables and evaluate interactions between signatures and treatment. Results PDX models recapitulated the clinical heterogeneity of glioblastoma patients. RT-GS, Chemo-GS, and ChemoRT-GS were correlated with benefit from treatment in the PDX models. In independent clinical validation, higher RT-GS scores were associated with increased survival only in patients receiving RT (P = 0.0031, hazard ratio [HR] = 0.78 [0.66–0.92]), higher Chemo-GS scores were associated with increased survival only in patients receiving chemotherapy (P < 0.0001, HR = 0.66 [0.55–0.8]), and higher ChemoRT-GS scores were associated with increased survival only in patients receiving ChemoRT (P = 0.0001, HR = 0.54 [0.4–0.74]). RT-GS and ChemoRT-GS had significant interactions with treatment on multivariate analysis (P = 0.0009 and 0.02, respectively), indicating that they are bona fide predictive biomarkers. Conclusions Using a novel PDX-driven methodology, we developed and validated 3 platform-independent molecular signatures that predict benefit from standard of care therapies for glioblastoma. These signatures may be useful to personalize glioblastoma treatment in the clinic and this approach may be a generalizable method to identify predictive biomarkers without resource-intensive randomized trials.