Citations

PURPOSE The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION The revised RANO 2.0 criteria refine response assessment in gliomas.

PURPOSE The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial that uses response adaptive randomization and genomic profiling to efficiently identify novel therapies for phase III testing. Three initial experimental arms (abemaciclib [a cyclin-dependent kinase [CDK]4/6 inhibitor], neratinib [an epidermal growth factor receptor [EGFR]/human epidermal growth factor receptor 2 inhibitor], and CC-115 [a deoxyribonucleic acid–dependent protein kinase/mammalian target of rapamycin inhibitor]) were simultaneously evaluated against a common control arm. We report the results for each arm and examine the feasibility and conduct of the adaptive platform design. PATIENTS AND METHODS Patients with newly diagnosed O 6 -methylguanine–DNA methyltransferase-unmethylated glioblastoma were eligible if they had tumor genotyping to identify prespecified biomarker subpopulations of dominant glioblastoma signaling pathways (EGFR, phosphatidylinositol 3-kinase, and CDK). Initial random assignment was 1:1:1:1 between control (radiation therapy and temozolomide) and the experimental arms. Subsequent Bayesian adaptive randomization was incorporated on the basis of biomarker-specific progression-free survival (PFS) data. The primary end point was overall survival (OS), and one-sided P values are reported. The trial is registered with ClinicalTrials.gov (identifier: NCT02977780 ). RESULTS Two hundred thirty-seven patients were treated (71 control; 73 abemaciclib; 81 neratinib; 12 CC-115) in years 2017-2021. Abemaciclib and neratinib were well tolerated, but CC-115 was associated with ≥ grade 3 treatment-related toxicity in 58% of patients. PFS was significantly longer with abemaciclib (hazard ratio [HR], 0.72; 95% CI, 0.49 to 1.06; one-sided P = .046) and neratinib (HR, 0.72; 95% CI, 0.50 to 1.02; one-sided P = .033) relative to the control arm but there was no PFS benefit with CC-115 (one-sided P = .523). None of the experimental therapies demonstrated a significant OS benefit ( P > .05). CONCLUSION The INSIGhT design enabled efficient simultaneous testing of three experimental agents using a shared control arm and adaptive randomization. Two investigational arms had superior PFS compared with the control arm, but none demonstrated an OS benefit. The INSIGhT design may promote improved and more efficient therapeutic discovery in glioblastoma. New arms have been added to the trial.

Abstract Highly conserved transport protein particle (TRAPP) complexes regulate subcellular trafficking pathways. Accurate protein trafficking has been increasingly recognized to be critically important for normal development, particularly in the nervous system. Variants in most TRAPP complex subunits have been found to lead to neurodevelopmental disorders with diverse but overlapping phenotypes. We expand on limited prior reports on TRAPPC6B with detailed clinical and neuroradiologic assessments, and studies on mechanisms of disease, and new types of variants. We describe 29 additional patients from 18 independent families with biallelic variants in TRAPPC6B. We identified seven homozygous nonsense (n = 12 patients) and eight canonical splice-site variants (n = 17 patients). In addition, we identified one patient with compound heterozygous splice-site/missense variants with a milder phenotype and one patient with homozygous missense variants. Patients displayed non-progressive microcephaly, global developmental delay/intellectual disability, epilepsy and absent expressive language. Movement disorders including stereotypies, spasticity and dystonia were also observed. Brain imaging revealed reductions in cortex, cerebellum and corpus callosum size with frequent white matter hyperintensity. Volumetric measurements indicated globally diminished volume rather than specific regional losses. We identified a reduced rate of trafficking into the Golgi apparatus and Golgi fragmentation in patient-derived fibroblasts that was rescued by wild-type TRAPPC6B. Molecular studies revealed a weakened interaction between mutant TRAPPC6B (c.454C>T, p.Q152*) and its TRAPP binding partner TRAPPC3. Patient-derived fibroblasts from the TRAPPC6B (c.454C>T, p.Q152*) variant displayed reduced levels of TRAPPC6B as well as other TRAPP II complex-specific members (TRAPPC9 and TRAPPC10). Interestingly, the levels of the TRAPPC6B homologue TRAPPC6A were found to be elevated. Moreover, co-immunoprecipitation experiments showed that TRAPPC6A co-precipitates equally with TRAPP II and TRAPP III, while TRAPPC6B co-precipitates significantly more with TRAPP II, suggesting enrichment of the protein in the TRAPP II complex. This implies that variants in TRAPPC6B may preferentially affect TRAPP II functions compared to TRAPP III functions. Finally, we assessed phenotypes in a Drosophila TRAPPC6B-deficiency model. Neuronal TRAPPC6B knockdown impaired locomotion and led to wing posture defects, supporting a role for TRAPPC6B in neuromotor function. Our findings confirm the association of damaging biallelic TRAPPC6B variants with microcephaly, intellectual disability, language impairments, and epilepsy. A subset of patients also exhibited dystonia and/or spasticity with impaired ambulation. These features overlap with disorders arising from pathogenic variants in other TRAPP subunits, particularly components of the TRAPP II complex. These findings suggest that TRAPPC6B is essential for brain development and function, and TRAPP II complex activity may be particularly relevant for mediating this function.

Abstract BACKGROUND The microenvironment of glioblastoma is complex and defined in part by protumorigenic metabolic changes. Within this microenvironment, blood-brain barrier disruption is often associated with the most aggressive portions of the tumor. To date, the metabolic tumor microenvironments of enhancing, blood-brain barrier (BBB) disrupted portions of gliomas, as compared to BBB-intact tumor, remain poorly understood. Specifically, it is unclear if the associated blood-brain barrier disruption merely reflects or functionally supports tumor aggressiveness. METHODS Intra-operative high-molecular weight microdialysis was utilized under an investigational device exemption (NCT NCT04047264) to sample the extracellular metabolome of radiographically diverse regions during fifteen neurosurgical resections. The global extracellular metabolome of recovered microdialysate from contrast-enhancing and non-enhancing tumor, as well as brain adjacent to tumor, was evaluated via ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) on the Metabolon platform and assessed using enrichment and correlation analyses. RESULTS Among 162 named metabolites identified via ultra-performance liquid chromatography tandem mass spectrometry, a novel glioma-associated metabolite, guanidinoacetate (GAA), was 126.32x higher in enhancing tumor than in adjacent brain and 13.63x higher in non-enhancing tumor than brain. Forty-eight additional metabolites were 2.05-10.18x more abundant in enhancing tumor than brain, including carnitine family members and all nine large neutral amino acids. Except for GAA and 2-hydroxyglutarate in IDH-mutant gliomas, differences between non-enhancing tumor and brain microdialysate were comparatively modest and less consistent, suggesting heterogeneity in the glioma metabolic microenvironment of blood-brain barrier (BBB) intact areas as compared to BBB-disrupted portions of gliomas. Interestingly, the enhancing but not the non-enhancing glioma metabolome was significantly enriched for plasma-associated metabolites, largely comprising amino acids and carnitines. CONCLUSION Our patient-derived data suggest that the BBB-disrupted metabolome of high-grade gliomas is characterized by metabolite diffusion from circulation into the tumor microenvironment. Further studies are ongoing to determine how this alteration in the glioma extracellular metabolome impacts glioma behavior and how it could be therapeutically targeted via BBB-modulating drugs.

Abstract BACKGROUND The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time some limitations of these criteria were identified, and uncertainty emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. MATERIAL AND METHODS Informed by data from a cohort of glioblastoma patients and other evaluations of RANO criteria that allowed evaluation of features of the different criteria, the RANO working group developed updates to the RANO criteria (RANO 2.0). RESULTS Based on the 2021 WHO classification of gliomas, we recommend a standard set of criteria for both high and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the post-radiotherapy MRI, rather than the post-surgical MRI, will be used as the baseline for future comparison. Since the incidence of pseudoprogression is high in the 12 weeks following radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, is required to define tumor progression. However, confirmation scans are not mandatory after this period nor for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (2-dimensional) but volumetric measurements are an option. For IDH-wildtype glioblastoma, the non-enhancing disease will no longer be evaluated. In IDH-mutated tumors with a significant non-enhancing component, clinical trials may require evaluating both the enhancing and non-enhancing tumor components for response assessment. CONCLUSION These criteria represent a work in progress that will hopefully improve the assessment of response in glioma trials. Future updates will incorporate novel developments, advanced imaging techniques, and endpoints as they become validated.

Transplant pathology plays a critical role in ensuring that transplanted organs function properly and the immune systems of the recipients do not reject them. To improve outcomes for transplant recipients, accurate diagnosis and timely treatment are essential. Recent advances in artificial intelligence (AI)-empowered digital pathology could help monitor allograft rejection and weaning of immunosuppressive drugs. To explore the role of AI in transplant pathology, we conducted a systematic search of electronic databases from January 2010 to April 2023. The PRISMA checklist was used as a guide for screening article titles, abstracts, and full texts, and we selected articles that met our inclusion criteria. Through this search, we identified 68 articles from multiple databases. After careful screening, only 14 articles were included based on title and abstract. Our review focuses on the AI approaches applied to four transplant organs: heart, lungs, liver, and kidneys. Specifically, we found that several deep learning-based AI models have been developed to analyze digital pathology slides of biopsy specimens from transplant organs. The use of AI models could improve clinicians’ decision-making capabilities and reduce diagnostic variability. In conclusion, our review highlights the advancements and limitations of AI in transplant pathology. We believe that these AI technologies have the potential to significantly improve transplant outcomes and pave the way for future advancements in this field.

Abstract Background Bevacizumab is commonly used to manage cerebral edema associated with brain tumors. However, its long half-life poses challenges for patients requiring urgent surgery due to wound complications. We present a case of utilizing therapeutic plasma exchange (TPE) to remove bevacizumab in a patient with recurrent glioblastoma requiring urgent surgery. Methods A 58-year-old male with recurrent glioblastoma, IDH-wildtype, presented with clinical and radiographic concern for ventriculitis requiring urgent wound washout only 4 days after his last bevacizumab infusion. TPE was performed for 3 sessions after surgery using a centrifugation-based cell separator. Replacement fluids included normal serum albumin, normal saline, and fresh frozen plasma. Bevacizumab levels were quantified using an enzyme-linked immunoabsorbent assay before and after each TPE session. Results TPE effectively removed bevacizumab, enabling safe surgery without new complications. Plasma bevacizumab levels decreased from 1087.63 to 145.35 ng/mL (13.4% of original) by the end of the last TPE session. This decline is consistent with nearly 3 half-lives, which compares favorably to the expected timeline of natural decline given the 21-day half-life. Conclusions We report a complex clinical scenario of a patient requiring urgent wound washout 4 days after last bevacizumab infusion for CNS infection. Surgery was successfully performed without new complications with use of TPE to remove bevacizumab immediately following surgery. This case highlights the feasibility of this approach, which may be utilized effectively in patients requiring surgery after having recently received bevacizumab.

Abstract Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector‐based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well‐described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

AbstractThe clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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