Mrugała, Maciej M.

The NCCN Guidelines for Central Nervous System (CNS) Cancers focus on management of the following adult CNS cancers: glioma (WHO grade 1, WHO grade 2–3 oligodendroglioma [1p19q codeleted, IDH- mutant], WHO grade 2–4 IDH- mutant astrocytoma, WHO grade 4 glioblastoma), intracranial and spinal ependymomas, medulloblastoma, limited and extensive brain metastases, leptomeningeal metastases, non–AIDS-related primary CNS lymphomas, metastatic spine tumors, meningiomas, and primary spinal cord tumors. The information contained in the algorithms and principles of management sections in the NCCN Guidelines for CNS Cancers are designed to help clinicians navigate through the complex management of patients with CNS tumors. Several important principles guide surgical management and treatment with radiotherapy and systemic therapy for adults with brain tumors. The NCCN CNS Cancers Panel meets at least annually to review comments from reviewers within their institutions, examine relevant new data from publications and abstracts, and reevaluate and update their recommendations. These NCCN Guidelines Insights summarize the panel’s most recent recommendations regarding molecular profiling of gliomas.

AbstractNeuro-oncology encompasses a broad field focusing on an array of neoplasms, many of which can mimic several diseases. Neurologists will often be involved in the initial diagnostic evaluation and management of these patients. Their insight is central to optimizing the diagnostic yield and providing high-level clinical care. Several neuro-oncologic cases are reviewed with a goal of increasing the understanding of these diseases in a clinically relevant manner and providing updates on the contemporary thinking in the subspecialty.

Abstract Characterizing intra- and inter-tumoral heterogeneity of glioblastoma has historically relied on discrete classifications of malignant cell populations leaving immune and other cell populations, known to exist admixed with the malignant tumor cells, relatively neglected. Manifold learning algorithms can manage deconvolving multiple cell populations and are often used to track cell state transitions in single cell transcriptomics. We applied a manifold learning approach to TCGA microarray data (Nf525) and bulk transcriptomics of 134 image localized biopsies across 30 patients with primary and 9 with recurrent glioblastoma to further elucidate how to organize biopsies across a spectrum of possible tissue states. The algorithm revealed a low-dimensional manifold graph for which each biopsy lives across 3 polarizing tissue states - one that is associated with diffusely invaded brain, one that is enriched in mesenchymal genes, and one that is enriched in classical proliferative tumor signatures. We deconvolved the bulk transcriptomics of the image-localized biopsies to reveal the relative abundance of 18 malignant, immune, and other cell subpopulations in each biopsy. Overlaying the cellular decomposition onto the manifold graph visualizing the tissue state distributions revealed that transitions between states correlate with changes in cellular cohabitation composition. The tumor cellular cohabitation ecologies have the lowest diversity, as inferred by ecological measures such as Shannon entropy and evenness, at the distal poles of the graph when compared to the transitional arms. Further, we found that the relationship between imaging appearance of contrast enhancement on T1-weighted MRI and the biopsy cellular composition varies with sex and primary vs recurrent biopsy status. The limited spectrum of possible tissue states revealed by the manifold learning is suggestive of a limited continuum along which tumor and non-tumoral cell populations can cohabitate. Such a limited low-dimensional biological space may constrain the dynamics of tumor biology in a predictable manner.

Abstract Neuro-oncology fellowship trainees have varied academic backgrounds before subspecialty certification with most completing neurology residency ( > 90%) and a minority coming from medical oncology and neurosurgery programs. Given the variability in background and training of fellows, concerns about competency, particularly in prescribing chemotherapy and understanding associated toxicities, need to be addressed. Providing a metric to track and assess competency can enhance trainees’ skills and bolster confidence during a neuro-oncology fellowship. In an IRB-exempt quality improvement project, we developed a competency test that was primarily case-based and guided knowledge of treatment indications, dosing, and management of associated toxicities. All questions were created based on NCCN guidelines and linked to a quality metric from ASCO-QOPI. Question content included 1. Prescribing, 2. Prescription review 3. Planning management, 4. Communicating information, 5. Drug dose calculation skills, 6. Adverse drug reactions, 7. Drug monitoring, and 8. Data interpretation. At the start of the fellowship, trainees took a pre-assessment test with a validated Likert scale for self-efficacy/confidence. These tests were scored, and directed elements were delivered via didactics to fellows by practicing neuro-oncologist and clinical pharmacist. The same assessments were performed at 6 and 12 months. All tests were scored and compared to the level of self-efficacy/confidence. Four fellows were included in this project across two institutions. Higher level of proficiency correlated with a higher level of self-reported confidence at the pre-assessment time point. Assessment at six months revealed an improvement in test scores and associated confidence and this trend continued at fellowship completion. This metric is the first known tool to evaluate chemotherapy competency and confidence in neuro-oncology fellows. Performance and self-efficacy/confidence are positively linked. This chemotherapy competency metric can be introduced to all neuro-oncology fellowship programs and used for national certification.

Abstract Diffuse gliomas are aggressive brain tumors that lack effective therapies. Despite advances in the molecular characterization of gliomas, targeted treatments have failed to improve patient outcomes to date. Here, we employed a functional genomics approach to rapidly identify therapeutic vulnerabilities and provide a strategy to individualize patient treatment. Our process combined comprehensive genomic and transcriptomic tumor profiling, custom algorithms and visualization software for data integration, and preclinical 3-dimensional ex vivo models (mcancers) for drug screening to assess response to therapeutic agents targeting specific molecular alterations. A total of 32 cases, including 5 oligodendrogliomas (1 primary and 4 recurrent), 5 astrocytomas (1 primary and 4 recurrent), and 22 glioblastomas (5 primary and 17 recurrent), were included in the study. Immunohistochemistry and integrated genomics confirmed that mcancers maintain key molecular alterations, including mutations, chromosomal rearrangements and focal amplifications, cellularity, and heterogeneity, faithfully recapitulating the original tumor. A total of 119 single drugs and 183 combinations were tested, including a panel of 26-brain penetrant targeted agents (18 single drugs and 8 combinations) that was curated to target common glioma oncogenic pathways and was tested across all cases. A strong correlation was observed between therapeutic vulnerabilities of glioma mcancers to targeted agents (EGFR, MET, PDGFR, HDAC inhibitors, etc.) and clinical experience. Single agent activity of panel compounds in the ex vivo setting was generally poor, with only 35% mCancers exhibiting > 70% growth inhibition at Cmax. In contrast, combination strategies, especially ones including epigenetic drugs, were significantly more effective (affecting 22 out of 32 mCancers), underscoring the molecular complexity of gliomas and the need for clinical trials testing combination treatments. Our data identified a number of novel combination treatments with significant efficacy across glioma subtypes and molecular profiles, suggesting that our functional genomics pipeline can guide treatment selection and inform clinical trial enrollment for gliomas.

Abstract Tumor Treating Fields therapy (TTFields; 200 kHz) is a noninvasive, locoregional, antimitotic treatment approved for newly diagnosed glioblastoma (ndGBM), recurrent (r) GBM, malignant pleural mesothelioma, and is being investigated in additional solid tumors. Approval in GBM was based on results of the phase 3 EF-11 (TTFields monotherapy; rGBM) and EF-14 (TTFields therapy/maintenance temozolomide; ndGBM), which showed clinical benefit without an increase in adverse events (AEs). Here we review post-marketing surveillance (PMS) data from patients with brain tumors who received TTFields therapy over an 11-year period. Unsolicited PMS data from patients with brain tumors who received TTFields therapy between October 2011 and March 2022, were included. Overall 23,822 patients were included in this analysis. Most patients (72%) were from North America; 24% from Europe, Middle East and Africa, and 4% from Japan. Birth year was available for 23,784 patients; of these, the average age at treatment start was 57 years (range: 3–103). Diagnoses were ndGBM (67%), rGBM (27%), astrocytoma (WHO grade 3; 4%) and other (2%). Overall, 71% of patients reported ≥ 1 AE, with the most common being skin reaction (42%), electric (tingling) sensation (14%), heat (warmth) sensation (12%), and seizure (11%). Furthermore, 56% of patients reported AEs possibly related to TTFields therapy, with the most frequently reported being skin reaction (42%), electric sensation (14%) and heat sensation (12%), occurring underneath the arrays. Numbers and types of AEs were comparable between age and diagnosis groups. PMS data from > 23,000 patients with brain tumors show that TTFields therapy (200 kHz) is well-tolerated, consistent with the known safety profile; no new safety signals were identified. TTFields therapy is not associated with systemic toxicity; most common possibly-related AEs are localized dermatologic events that can be managed with appropriate prophylaxis and treatment strategies.

Abstract BACKGROUND In May 2022 the Food and Drug Administration approved fam-trastuzumab deruxtecan-nxki (FAM-TRAS) for adult patients with unresectable or metastatic Her-2 positive breast cancer who have received prior Her-2-based regimen and developed recurrence withing 6 months of completing therapy. Efficacy of the drug was established in the DESTINY-BreastO3 study. It has been suggested that fam-trastuzumab deruxtecan crosses blood-brain barrier, similarly to trastuzumab and another drug conjugate trastuzumab-DM1. CNS responses in patients with Her2 positive metastatic breast cancer have been reported. ERBB2 is a receptor tyrosine kinase from the family of EGFR/ERBB/HER family of kinases and its alterations can serve as a biomarker and actionable target in solid tumors. Here we present a case of CNS metastases from ERBB2 positive lung adenocarcinoma treated successfully with FAM-TRAS alone. METHODS Case report. RESULTS 50 y old man presented with a persistent cough. CT chest showed RUL nodule and peribronchial lymphadenopathy. Biopsy was positive for adenocarcinoma. Molecular testing has shown ERBB2 exon20 insertion, TP53 pathogenic variant, PDL1 positive (1%), and BRACA1 mutation. The patient had a solitary brain metastasis at the time of the initial diagnosis. He was started on FAM-TRAS and CNS response was seen while lung disease progressed. He was switched to immunotherapy but developed pneumonitis and therapy was stopped. He subsequently developed innumerable brain metastases and was restarted on FAM-TRAS. After 2 doses, dramatic response in CNS was seen with lung disease was stable. CONCLUSIONS This case demonstrates the critical importance of molecular testing in neuro-oncology in the era of novel systemic therapies, many with good blood-brain barrier penetration. Systemic therapies for brain metastases can be successfully implemented in the right clinical setting and they can allow for the deferral of radiotherapy. ERBB2 mutations can guide clinicians when choosing therapy for many solid tumors, including those with brain metastases.

Background: Combined PD-1/PD-L1 and CTLA-4 immune checkpoint inhibition for the has been shown to produce superior results in the treatment of malignant melanoma when compared to monotherapy. However, patients with intracranial disease were excluded from these studies given their poor prognosis. Objective: The objective of this study was to critically assess current evidence supporting the co-administration of PD-1/PD-L1 and CTLA-4 inhibitors in the treatment of melanoma brain metastases. Methods: The objective was addressed through the development of a critically appraised topic that included a clinical scenario, structured question, literature search strategy, critical appraisal, assessment of results, evidence summary, commentary, and bottom-line conclusions. Participants included consultant and resident neurologists, a medical librarian, clinical epidemiologists, and a content expert in the field of neuro-oncology. Results: A recent, open-label, non-comparative randomized phase II trial was selected for critical appraisal. This trial evaluated the efficacy and safety of nivolumab alone or in combination with ipilimumab in 79 adult patients with untreated, asymptomatic melanoma brain metastases. The rates of the primary outcome (intracranial response at ≥12 wk) in the primary endpoint cohort were 46% for cohort A (combination therapy) and 20% for cohort B (nivolumab monotherapy). No treatment related deaths were observed in the study. Grade 4 adverse events occurred in 9% of patients in cohort A and none in cohort B. Conclusions: Co-administration of ipilimumab and nivolumab as first-line therapy is effective in the treatment of asymptomatic melanoma brain metastases, with an acceptable safety profile.

Abstract Background Magnetic Resonance Imaging (MRI) is the mainstay for neurosurgical oncology but not for informing us about glioma biology. An obstacle to developing MR-based glioma biomarkers is the absence of rigorous correlation between MRI features and glioma biology as assessed in multi-regional biopsies, within and across patients. Methods We directly addressed this obstacle by collating a unique cohort of 202 MRI-localized biopsies from 58 patients. We define a low-dimensional transcriptional pseudotime continuum along which heterogeneous high-grade glioma (HGG) samples organize both within and across patients. Results We observe three polarized transcriptional tissue states: infiltrated brain, immune/inflammatory, and proliferative associated with patterns of cohabitation of cellular subpopulations. The states and deconvolved populations show correlation with enhancement status on T1Gd MRI. Moreover, discrete MRI habitats, regions sharing common imaging features, defined as combinations of high or low signal intensity across multiparametric MRI revealed 14 MRI habitats. We order the MRI habitats according to the average pseudotime on the transcriptional continuum. We find that MRI habitats with low pseudotime (associated with early tumor development and diffusely invaded brain tissue) localized at the periphery of the tumor whilst high pseudotime either proliferative or immune/inflammatory states were towards the core of the lesion. We find that composition of MRI habitats are impacted by MGMT status and patient sex. Conclusion This suggests that ongoing aggregation of MRI-localized biopsies may augment our projection of biology onto MRI habitats to support tracking of the evolution of cellular ecologies within and across each patient’s tumor over time. Key Points Trajectory inference of HGG samples reveals a continuum connecting three polarized tissue states reflecting transitions in cellular population ecologies and gene set enrichment Combining multiparametric MRI features into regional MRI habitats reveal clinically-distinct patterns of cell co-habitation and tissue state MGMT methylation status shifts the cellular patterns of cohabitation within MRI habitats Importance of the Study Regional heterogeneity is a defining characteristic of high-grade glioma (HGG). Mapping the transcriptomic biology of multiregionally sampled MRI-localized biopsies from high-grade gliomas onto a low-dimensional space reveals a continuum between three primary tissue states: infiltrated brain, immune/inflammatory, and proliferative. Each state is associated with distinct cell cohabitation ecologies. Transitions between the tissue states coordinate with changes in tumor composition, revealing potential direct connections between tumor biology shifts and their manifestation on clinical imaging.