Citations

Abstract Tumor-related epilepsy (TRE) is a frequent and major consequence of brain tumors. Management of TRE is required throughout the course of disease and a deep understanding of diagnosis and treatment is key to improving quality of life. Gross total resection is favored from both an oncologic and epilepsy perspective. Shared mechanisms of tumor growth and epilepsy exist, and emerging data will provide better targeted therapy options. Initial treatment with antiseizure medications (ASM) in conjunction with surgery and/or chemoradiotherapy is typical. The first choice of ASM is critical to optimize seizure control and tolerability considering the effects of the tumor itself. These agents carry a potential for drug–drug interactions and therefore knowledge of mechanisms of action and interactions is needed. A review of adverse effects is necessary to guide ASM adjustments and decision-making. This review highlights the essential aspects of diagnosis and treatment of TRE with ASMs, surgery, chemotherapy, and radiotherapy while indicating areas of uncertainty. Future studies should consider the use of a standardized method of seizure tracking and incorporating seizure outcomes as a primary endpoint of tumor treatment trials.

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.

PURPOSE Pancreatic cancer (PC) carries a poor prognosis with high rates of unresectable/metastatic disease at diagnosis, recurrence after resection, and few systemic therapy options. Deficient mismatch repair (dMMR)/high microsatellite instability (MSI-H) PCs demonstrated uncharacteristically poor outcomes in KEYNOTE-158, evaluating pembrolizumab in MSI-H solid tumors. Our study aggregates the Mayo Clinic experience with dMMR/MSI-H PCs, characterizing the clinical, molecular, and treatment response patterns with a focus on response to immune checkpoint inhibitors (ICIs). METHODS Retrospective data were collected from the electronic medical record from December 2009 to February 2023. Patients were included if they had a pathologically confirmed pancreatic malignancy and had (1) deficient expression of mismatch repair (MMR) proteins by tumor immunohistochemistry, (2) pathogenic mutation of MMR genes on genomic sequencing, and/or (3) MSI-H by polymerase chain reaction. RESULTS Thirty-two patients were identified for inclusion, with all stages of disease represented. Sixteen of these patients underwent surgery or chemoradiotherapy. Of these patients, uncharacteristically favorable responses were seen, with a recurrence rate of only 19% (n = 3) despite a median follow-up of 25 months. In the palliative setting, excellent responses to ICI were seen, with overall response rate (ORR) of 75% (20% complete response). Median time to disease progression was not reached. Response rates to cytotoxic chemotherapy in the palliative setting were poor, with 30% ORR and median time to progression of 4 months. We observed a high rate of discrepancy between MMR and MSI testing methods, representing 19% of the entire cohort and 26% of evaluable cases. CONCLUSION Our data argue for the preferential use of ICI over cytotoxic chemotherapy in any patient with dMMR/MSI-H PC requiring systemic therapy, including in the metastatic and adjuvant/neoadjuvant settings.

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

Abstract Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both symbolic and statistical methods, as well as highlight the need for federated annotation and evaluation to resolve several pitfalls encountered in the course of these efforts.

Abstract The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve the 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. Informed by data from a cohort of glioblastoma patients and other evaluations of RANO criteria that allowed evaluation of features of the different criteria, we propose updates to the RANO criteria (RANO 2.0). 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 an option. 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.

Abstract Patients with relapsed/refractory (R/R) classical Hodgkin lymphoma (cHL) for whom autologous hematopoietic cell transplantation (auto-HCT) had failed experienced frequent and durable responses to nivolumab in the phase 2 CheckMate 205 trial. We present updated results (median follow-up, ∼5 years). Patients with R/R cHL who were brentuximab vedotin (BV)–naive (cohort A), received BV after auto-HCT (cohort B), or received BV before and/or after auto-HCT (cohort C) were administered with nivolumab 3 mg/kg IV every 2 weeks until progression or unacceptable toxicity. Patients in cohort C with complete remission (CR) for 1 year could discontinue nivolumab and resume upon relapse. Among 243 patients (cohort A, n = 63; B, n = 80; and C, n = 100), the objective response rate (ORR) was 71.2% (95% confidence interval [CI], 65.1-76.8); the CR rate was 21.4% (95% CI, 16.4-27.1). Median duration of response, CR, and partial remission were 18.2 (95% CI, 14.7-26.1), 30.3, and 13.5 months, respectively. Median progression-free survival was 15.1 months (95% CI, 11.3-18.5). Median overall survival (OS) was not reached; OS at 5 years was 71.4% (95% CI, 64.8-77.1). In cohort C, all 3 patients who discontinued in CR and were subsequently re-treated achieved objective response. No new or unexpected safety signals were identified. This 5-year follow-up of CheckMate 205 demonstrated favorable OS and confirmed efficacy and safety of nivolumab in R/R cHL after auto-HCT failure. Results suggest patients may discontinue treatment after persistent CR and reinitiate upon progression. This trial was registered at www.clinicaltrials.gov as #NCT02181713.