Resistance, rebound, and recurrence regrowth patterns in pediatric low-grade glioma treated by MAPK inhibition: A modified Delphi approach to build international consensus-based definitions-International Pediatric Low-Grade Glioma Coalition.

Pediatric low-grade glioma (pLGG) is the most common childhood brain tumor group. The natural history, when curative resection is not possible, is one of a chronic disease with periods of tumor stability and episodes of tumor progression. While there is a high overall survival rate, many patients experience significant and potentially lifelong morbidities. The majority of pLGGs have an underlying activation of the RAS/MAPK pathway due to mutational events, leading to the use of molecularly targeted therapies in clinical trials, with recent regulatory approval for the combination of BRAF and MEK inhibition for BRAFV600E mutated pLGG. Despite encouraging activity, tumor regrowth can occur during therapy due to drug resistance, off treatment as tumor recurrence, or as reported in some patients as a rapid rebound growth within 3 months of discontinuing targeted therapy. Definitions of these patterns of regrowth have not been well described in pLGG. For this reason, the International Pediatric Low-Grade Glioma Coalition, a global group of physicians and scientists, formed the Resistance, Rebound, and Recurrence (R3) working group to study resistance, rebound, and recurrence. A modified Delphi approach was undertaken to produce consensus-based definitions and recommendations for regrowth patterns in pLGG with specific reference to targeted therapies.

The Clinical Utility of a Tiered Approach to Pediatric Glioma Molecular Characterization for Resource-Limited Settings.

PURPOSE: Molecular characterization is key to optimally diagnose and manage cancer. The complexity and cost of routine genomic analysis have unfortunately limited its use and denied many patients access to precision medicine. A possible solution is to rationalize use-creating a tiered approach to testing which uses inexpensive techniques for most patients and limits expensive testing to patients with the highest needs. Here, we tested the utility of this approach to molecularly characterize pediatric glioma in a cost- and time-sensitive manner. METHODS: We used a tiered testing pipeline of immunohistochemistry (IHC), customized fusion panels or fluorescence in situ hybridization (FISH), and targeted RNA sequencing in pediatric gliomas. Two distinct diagnostic algorithms were used for low- and high-grade gliomas (LGGs and HGGs). The percentage of driver alterations identified, associated testing costs, and turnaround time (TAT) are reported. RESULTS: The tiered approach successfully characterized 96% (95 of 99) of gliomas. For 82 LGGs, IHC, targeted fusion panel or FISH, and targeted RNA sequencing solved 35% (29 of 82), 29% (24 of 82), and 30% (25 of 82) of cases, respectively. A total of 64% (53 of 82) of samples were characterized without targeted RNA sequencing. Of 17 HGG samples, 13 were characterized by IHC and four were characterized by targeted RNA sequencing. The average cost per sample was more affordable when using the tiered approach as compared with up-front targeted RNA sequencing in LGG ($405 US dollars [USD] v $745 USD) and HGGs ($282 USD v $745 USD). The average TAT per sample was also shorter using the tiered approach (10 days for LGG, 5 days for HGG v 14 days for targeted RNA sequencing). CONCLUSION: Our tiered approach molecularly characterized 96% of samples in a cost- and time-sensitive manner. Such an approach may be feasible in neuro-oncology centers worldwide, particularly in resource-limited settings.

Understanding diffuse leptomeningeal glioneuronal tumors.

INTODUCTION: Diffuse leptomeningeal glioneuronal tumors (DLGNTs) pose a rare and challenging entity within pediatric central nervous system neoplasms. Despite their rarity, DLGNTs exhibit complex clinical presentations and unique molecular characteristics, necessitating a deeper understanding of their diagnostic and therapeutic nuances. METHODS: This review synthesizes contemporary literature on DLGNT, encompassing epidemiology, clinical manifestations, pathological features, treatment strategies, prognostic markers, and future research directions. To compile the existing body of knowledge on DLGNT, a comprehensive search of relevant databases was conducted. RESULTS: DLGNT primarily affects pediatric populations but can manifest across all age groups. Its diagnosis is confounded by nonspecific clinical presentations and overlapping radiological features with other CNS neoplasms. Magnetic resonance imaging (MRI) serves as a cornerstone for DLGNT diagnosis, revealing characteristic leptomeningeal enhancement and intraparenchymal involvement. Histologically, DLGNT presents with low to moderate cellularity and exhibits molecular alterations in the MAPK/ERK signalling pathway. Optimal management of DLGNT necessitates a multidisciplinary approach encompassing surgical resection, chemotherapy, radiotherapy, and emerging targeted therapies directed against specific genetic alterations. Prognostication remains challenging, with factors such as age at diagnosis, histological subtypes, and genetic alterations influencing disease progression and treatment response. Long-term survival data are limited, underscoring the need for collaborative research efforts. CONCLUSION: Advancements in molecular profiling, targeted therapies, and international collaborations hold promise for improving DLGNT outcomes. Harnessing the collective expertise of clinicians, researchers, and patient advocates, can advance the field of DLGNT research and optimize patient care paradigms.

Pediatric-type low-grade gliomas in adolescents and young adults-challenges and emerging paradigms.

Pediatric-type low-grade glioma (PLGG) encompasses a heterogeneous group of WHO grade 1 or 2 tumors and is the most common central nervous system tumor found in children. PLGG extends beyond pediatrics, into adolescents and young adults (AYA, ages 15-40). PLGG represents 25% of all gliomas diagnosed in AYA with differences in tumor location and molecular alterations compared to children, resulting in improved outcome for AYAs. Long-term outcome is excellent, though patients may suffer significant morbidity depending on tumor location. There are differences in treatment practices with radiation used to treat PLGG in AYAs more often than in children. Most PLGG in AYA harbor an alteration in the RAS/MAPK pathway, with limited insight into response to targeted therapy in this age group. This review discusses the epidemiology, current therapeutic approaches, and challenges in the management of PLGG in AYA.

Precision immuno-oncology approach for four malignant tumors in siblings with constitutional mismatch repair deficiency syndrome.

Constitutional mismatch repair deficiency (CMMRD) is a rare syndrome characterized by an increased incidence of cancer. It is caused by biallelic germline mutations in one of the four mismatch repair genes (MMR) genes: MLH1, MSH2, MSH6, or PMS2. Accurate diagnosis accompanied by a proper molecular genetic examination plays a crucial role in cancer management and also has implications for other family members. In this report, we share the impact of the diagnosis and challenges during the clinical management of two brothers with CMMRD from a non-consanguineous family harbouring compound heterozygous variants in the PMS2 gene. Both brothers presented with different phenotypic manifestations and cancer spectrum. Treatment involving immune checkpoint inhibitors significantly contributed to prolonged survival in both patients affected by lethal gliomas. The uniform hypermutation also allowed immune-directed treatment using nivolumab for the B-cell lymphoma, thereby limiting the intensive chemotherapy exposure in this young patient who remains at risk for subsequent malignancies.

Pediatric neuropathology practice in a low- and middle-income country: capacity building through institutional twinning.

Background: Accurate and precise diagnosis is central to treating central nervous system (CNS) tumors, yet tissue diagnosis is often a neglected focus in low- and middle-income countries (LMICs). Since 2016, the WHO classification of CNS tumors has increasingly incorporated molecular biomarkers into the diagnosis of CNS tumors. While this shift to precision diagnostics promises a high degree of diagnostic accuracy and prognostic precision, it has also resulted in increasing divergence in diagnostic and management practices between LMICs and high-income countries (HICs). Pathologists and laboratory professionals in LMICs lack the proper training and tools to join the molecular diagnostic revolution. We describe the impact of a 7-year long twinning program between Canada and Pakistan on pathology services. Methods: During the study period, 141 challenging cases of pediatric CNS tumors initially diagnosed at Aga Khan University Hospital (AKUH), Karachi, were sent to the Hospital for Sick Children in Toronto, Canada (SickKids), for a second opinion. Each case received histologic review and often immunohistochemical staining and relevant molecular testing. A monthly multidisciplinary online tumor board (MDTB) was conducted to discuss the results with pathologists from both institutions in attendance. Results: Diagnostic discordance was seen in 30 cases. Expert review provided subclassification for 53 cases most notably for diffuse gliomas and medulloblastoma. Poorly differentiated tumors benefited the most from second review, mainly because of the resolving power of specialized immunohistochemical stains, NanoString, and targeted gene panel next-generation sequencing. Collaboration with expert neuropathologists led to validation of over half a dozen immunostains at AKUH facilitating diagnosis of CNS tumors. Conclusions: LMIC-HIC Institutional twinning provides much-needed training and mentorship to pathologists and can help in infrastructure development by adopting and validating new immunohistochemical stains. Persistent unresolved cases indicate that molecular techniques are indispensable in for diagnosis in a minority of cases. The development of affordable alternative molecular techniques may help with these histologically unresolved cases.

Identification of Multiclass Pediatric Low-Grade Neuroepithelial Tumor Molecular Subtype with ADC MR Imaging and Machine Learning.

BACKGROUND AND PURPOSE: Molecular biomarker identification increasingly influences the treatment planning of pediatric low-grade neuroepithelial tumors (PLGNTs). We aimed to develop and validate a radiomics-based ADC signature predictive of the molecular status of PLGNTs. MATERIALS AND METHODS: In this retrospective bi-institutional study, we searched the PACS for baseline brain MRIs from children with PLGNTs. Semiautomated tumor segmentation on ADC maps was performed using the semiautomated level tracing effect tool with 3D Slicer. Clinical variables, including age, sex, and tumor location, were collected from chart review. The molecular status of tumors was derived from biopsy. Multiclass random forests were used to predict the molecular status and fine-tuned using a grid search on the validation sets. Models were evaluated using independent and unseen test sets based on the combined data, and the area under the receiver operating characteristic curve (AUC) was calculated for the prediction of 3 classes: KIAA1549-BRAF fusion, BRAF V600E mutation, and non-BRAF cohorts. Experiments were repeated 100 times using different random data splits and model initializations to ensure reproducible results. RESULTS: Two hundred ninety-nine children from the first institution and 23 children from the second institution were included (53.6% male; mean, age 8.01 years; 51.8% supratentorial; 52.2% with KIAA1549-BRAF fusion). For the 3-class prediction using radiomics features only, the average test AUC was 0.74 (95% CI, 0.73-0.75), and using clinical features only, the average test AUC was 0.67 (95% CI, 0.66-0.68). The combination of both radiomics and clinical features improved the AUC to 0.77 (95% CI, 0.75-0.77). The diagnostic performance of the per-class test AUC was higher in identifying KIAA1549-BRAF fusion tumors among the other subgroups (AUC = 0.81 for the combined radiomics and clinical features versus 0.75 and 0.74 for BRAF V600E mutation and non-BRAF, respectively). CONCLUSIONS: ADC values of tumor segmentations have differentiative signals that can be used for training machine learning classifiers for molecular biomarker identification of PLGNTs. ADC-based pretherapeutic differentiation of the BRAF status of PLGNTs has the potential to avoid invasive tumor biopsy and enable earlier initiation of targeted therapy.

Update on Cancer Predisposition Syndromes and Surveillance Guidelines for Childhood Brain Tumors.

Tumors of the central nervous system (CNS) comprise the second most common group of neoplasms in childhood. The incidence of germline predisposition among children with brain tumors continues to grow as our knowledge on disease etiology increases. Some children with brain tumors may present with nonmalignant phenotypic features of specific syndromes (e.g., nevoid basal cell carcinoma syndrome, neurofibromatosis type 1 and type 2, DICER1 syndrome, and constitutional mismatch-repair deficiency), while others may present with a strong family history of cancer (e.g., Li-Fraumeni syndrome) or with a rare tumor commonly found in the context of germline predisposition (e.g., rhabdoid tumor predisposition syndrome). Approximately 50% of patients with a brain tumor may be the first in a family identified to have a predisposition. The past decade has witnessed a rapid expansion in our molecular understanding of CNS tumors. A significant proportion of CNS tumors are now well characterized and known to harbor specific genetic changes that can be found in the germline. Additional novel predisposition syndromes are also being described. Identification of these germline syndromes in individual patients has not only enabled cascade testing of family members and early tumor surveillance but also increasingly affected cancer management in those patients. Therefore, the AACR Cancer Predisposition Working Group chose to highlight these advances in CNS tumor predisposition and summarize and/or generate surveillance recommendations for established and more recently emerging pediatric brain tumor predisposition syndromes.

Impact of trametinib on the neuropsychological profile of NF1 patients.

PURPOSE: The use of trametinib in the treatment of pediatric low-grade gliomas (PLGG) and plexiform neurofibroma (PN) is being investigated in an ongoing multicenter phase II trial (NCT03363217). Preliminary data shows potential benefits with significant response in the majority of PLGG and PN and an overall good tolerance. Moreover, possible benefits of MEK inhibitor therapy on cognitive functioning in neurofibromatosis type 1 (NF1) were recently shown which supports the need for further evaluation. METHODS: Thirty-six patients with NF1 (age range 3-19 years) enrolled in the phase II study of trametinib underwent a neurocognitive assessment at inclusion and at completion of the 72-week treatment. Age-appropriate Wechsler Intelligence Scales and the Trail Making Test (for children over 8 years old) were administered at each assessment. Paired t-tests and Reliable Change Index (RCI) analyses were performed to investigate change in neurocognitive outcomes. Regression analyses were used to investigate the contribution of age and baseline score in the prediction of change. RESULTS: Stable performance on neurocognitive tests was revealed at a group-level using paired t-tests. Clinically significant improvements were however found on specific indexes of the Wechsler intelligence scales and Trail Making Test, using RCI analyses. No significant impact of age on cognitive change was evidenced. However, lower initial cognitive performance was associated with increased odds of presenting clinically significant improvements on neurocognitive outcomes. CONCLUSION: These preliminary results show a potential positive effect of trametinib on cognition in patients with NF1. We observed significant improvements in processing speed, visuo-motor and verbal abilities. This study demonstrates the importance of including neuropsychological evaluations into clinical trial when using MEK inhibitors for patients with NF1.

A Validated Highly Sensitive Microsatellite Instability Assay Accurately Identifies Individuals Harboring Biallelic Germline PMS2 Pathogenic Variants in Constitutional Mismatch Repair Deficiency.

BACKGROUND: Constitutional mismatch repair deficiency (CMMRD) is a rare and extraordinarily penetrant childhood-onset cancer predisposition syndrome. Genetic diagnosis is often hampered by the identification of mismatch repair (MMR) variants of unknown significance and difficulties in PMS2 analysis, the most frequently mutated gene in CMMRD. We present the validation of a robust functional tool for CMMRD diagnosis and the characterization of microsatellite instability (MSI) patterns in blood and tumors. METHODS: The highly sensitive assessment of MSI (hs-MSI) was tested on a blinded cohort of 66 blood samples and 24 CMMRD tumor samples. Hs-MSI scores were compared with low-pass genomic instability scores (LOGIC/MMRDness). The correlation of hs-MSI scores in blood with age of cancer onset and the distribution of insertion-deletion (indel) variants in microsatellites were analyzed in a series of 169 individuals (n = 68 CMMRD, n = 124 non-CMMRD). RESULTS: Hs-MSI achieved high accuracy in the identification of CMMRD in blood (sensitivity 98.5% and specificity 100%) and detected MSI in CMMRD-associated tumors. Hs-MSI had a strong positive correlation with whole low-pass genomic instability LOGIC scores (r = 0.89, P = 2.2e-15 in blood and r = 0.82, P = 7e-3 in tumors). Indel distribution identified PMS2 pathogenic variant (PV) carriers from other biallelic MMR gene PV carriers with an accuracy of 0.997. Higher hs-MSI scores correlated with younger age at diagnosis of the first tumor (r = -0.43, P = 0.011). CONCLUSIONS: Our study confirms the accuracy of the hs-MSI assay as ancillary testing for CMMRD diagnosis, which can also characterize MSI patterns in CMMRD-associated cancers. Hs-MSI is a powerful tool to pinpoint PMS2 as the affected germline gene and thus potentially personalize cancer risk.

Brain Tumor Imaging in Adolescents and Young Adults: 2021 WHO Updates for Molecular-based Tumor Types.

Published in 2021, the fifth edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) introduced new molecular criteria for tumor types that commonly occur in either pediatric or adult age groups. Adolescents and young adults (AYAs) are at the intersection of adult and pediatric care, and both pediatric-type and adult-type CNS tumors occur at that age. Mortality rates for AYAs with CNS tumors have increased by 0.6% per year for males and 1% per year for females from 2007 to 2016. To best serve patients, it is crucial that both pediatric and adult radiologists who interpret neuroimages are familiar with the various pediatric- and adult-type brain tumors and their typical imaging morphologic characteristics. Gliomas account for approximately 80% of all malignant CNS tumors in the AYA age group, with the most common types observed being diffuse astrocytic and glioneuronal tumors. Ependymomas and medulloblastomas also occur in the AYA population but are seen less frequently. Importantly, biologic behavior and progression of distinct molecular subgroups of brain tumors differ across ages. This review discusses newly added or revised gliomas in the fifth edition of the CNS WHO classification, as well as other CNS tumor types common in the AYA population.

MRI-Based End-To-End Pediatric Low-Grade Glioma Segmentation and Classification.

Purpose: MRI-based radiomics models can predict genetic markers in pediatric low-grade glioma (pLGG). These models usually require tumour segmentation, which is tedious and time consuming if done manually. We propose a deep learning (DL) model to automate tumour segmentation and build an end-to-end radiomics-based pipeline for pLGG classification. Methods: The proposed architecture is a 2-step U-Net based DL network. The first U-Net is trained on downsampled images to locate the tumour. The second U-Net is trained using image patches centred around the located tumour to produce more refined segmentations. The segmented tumour is then fed into a radiomics-based model to predict the genetic marker of the tumour. Results: Our segmentation model achieved a correlation value of over 80% for all volume-related radiomic features and an average Dice score of .795 in test cases. Feeding the auto-segmentation results into a radiomics model resulted in a mean area under the ROC curve (AUC) of .843, with 95% confidence interval (CI) [.78-.906] and .730, with 95% CI [.671-.789] on the test set for 2-class (BRAF V600E mutation BRAF fusion) and 3-class (BRAF V600E mutation BRAF fusion and Other) classification, respectively. This result was comparable to the AUC of .874, 95% CI [.829-.919] and .758, 95% CI [.724-.792] for the radiomics model trained and tested on the manual segmentations in 2-class and 3-class classification scenarios, respectively. Conclusion: The proposed end-to-end pipeline for pLGG segmentation and classification produced results comparable to manual segmentation when it was used for a radiomics-based genetic marker prediction model.

Proton Therapy Mediates Dose Reductions to Brain Structures Associated With Cognition in Children With Medulloblastoma.

PURPOSE: Emerging evidence suggests proton radiation therapy may offer cognitive sparing advantages over photon radiation therapy, yet dosimetry has not been compared previously. The purpose of this study was to examine dosimetric correlates of cognitive outcomes in children with medulloblastoma treated with proton versus photon radiation therapy. METHODS AND MATERIALS: In this retrospective, bi-institutional study, dosimetric and cognitive data from 75 patients (39 photon and 36 proton) were analyzed. Doses to brain structures were compared between treatment modalities. Linear mixed-effects models were used to create models of global IQ and cognitive domain scores. RESULTS: The mean dose and dose to 40% of the brain (D40) were 2.7 and 4.1 Gy less among proton-treated patients compared with photon-treated patients (P = .03 and .007, respectively). Mean doses to the left and right hippocampi were 11.2 Gy lower among proton-treated patients (P < .001 for both). Mean doses to the left and right temporal lobes were 6.9 and 7.1 Gy lower with proton treatment, respectively (P < .001 for both). Models of cognition found statistically significant associations between higher mean brain dose and reduced verbal comprehension, increased right temporal lobe D40 with reduced perceptual reasoning, and greater left temporal mean dose with reduced working memory. Higher brain D40 was associated with reduced processing speed and global IQ scores. CONCLUSIONS: Proton therapy reduces doses to normal brain structures compared with photon treatment. This leads to reduced cognitive decline after radiation therapy across multiple intellectual endpoints. Proton therapy should be offered to children receiving radiation for medulloblastoma.

Pediatric low-grade glioma: State-of-the-art and ongoing challenges.

The most common childhood central nervous system (CNS) tumor is pediatric low-grade glioma (pLGG), representing 30%-40% of all CNS tumors in children. Although there is high associated morbidity, tumor-related mortality is relatively rare. pLGG is now conceptualized as a chronic disease, underscoring the importance of functional outcomes and quality-of-life measures. A wealth of data has emerged about these tumors, including a better understanding of their natural history and their molecular drivers, paving the way for the use of targeted inhibitors. While these treatments have heralded tremendous promise, challenges remain about how to best optimize their use, and the long-term toxicities associated with these inhibitors remain unknown. The International Pediatric Low-Grade Glioma Coalition (iPLGGc) is a global group of physicians and scientists with expertise in pLGG focused on addressing key pLGG issues. Here, the iPLGGc provides an overview of the current state-of-the-art in pLGG, including epidemiology, histology, molecular landscape, treatment paradigms, survival outcomes, functional outcomes, imaging response, and ongoing challenges. This paper also serves as an introduction to 3 other pLGG manuscripts on (1) pLGG preclinical models, (2) consensus framework for conducting early-phase clinical trials in pLGG, and (3) pLGG resistance, rebound, and recurrence.

Increased confidence of radiomics facilitating pretherapeutic differentiation of BRAF-altered pediatric low-grade glioma.

OBJECTIVES: Currently, the BRAF status of pediatric low-grade glioma (pLGG) patients is determined through a biopsy. We established a nomogram to predict BRAF status non-invasively using clinical and radiomic factors. Additionally, we assessed an advanced thresholding method to provide only high-confidence predictions for the molecular subtype. Finally, we tested whether radiomic features provide additional predictive information for this classification task, beyond that which is embedded in the location of the tumor. METHODS: Random forest (RF) models were trained on radiomic and clinical features both separately and together, to evaluate the utility of each feature set. Instead of using the traditional single threshold technique to convert the model outputs to class predictions, we implemented a double threshold mechanism that accounted for uncertainty. Additionally, a linear model was trained and depicted graphically as a nomogram. RESULTS: The combined RF (AUC: 0.925) outperformed the RFs trained on radiomic (AUC: 0.863) or clinical (AUC: 0.889) features alone. The linear model had a comparable AUC (0.916), despite its lower complexity. Traditional thresholding produced an accuracy of 84.5%, while the double threshold approach yielded 92.2% accuracy on the 80.7% of patients with the highest confidence predictions. CONCLUSION: Models that included radiomic features outperformed, underscoring their importance for the prediction of BRAF status. A linear model performed similarly to RF but with the added benefit that it can be visualized as a nomogram, improving the explainability of the model. The double threshold technique was able to identify uncertain predictions, enhancing the clinical utility of the model. CLINICAL RELEVANCE STATEMENT: Radiomic features and tumor location are both predictive of BRAF status in pLGG patients. We show that they contain complementary information and depict the optimal model as a nomogram, which can be used as a non-invasive alternative to biopsy. KEY POINTS: • Radiomic features provide additional predictive information for the determination of the molecular subtype of pediatric low-grade gliomas patients, beyond what is embedded in the location of the tumor, which has an established relationship with genetic status. • An advanced thresholding method can help to distinguish cases where machine learning models have a high chance of being (in)correct, improving the utility of these models. • A simple linear model performs similarly to a more powerful random forest model at classifying the molecular subtype of pediatric low-grade gliomas but has the added benefit that it can be converted into a nomogram, which may facilitate clinical implementation by improving the explainability of the model.

Postoperative cerebellar mutism syndrome is an acquired Autism-like network disturbance.

BACKGROUND: Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumour surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates. METHODS: In this study, we analyzed post-operative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and paediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n=427). RESULTS: Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the paediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviours. CONCLUSIONS: Our findings indicate that CMS-associated lesions result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Dabrafenib plus Trametinib in Pediatric Glioma with BRAF V600 Mutations.

BACKGROUND: Detection of the BRAF V600E mutation in pediatric low-grade glioma has been associated with a lower response to standard chemotherapy. In previous trials, dabrafenib (both as monotherapy and in combination with trametinib) has shown efficacy in recurrent pediatric low-grade glioma with BRAF V600 mutations, findings that warrant further evaluation of this combination as first-line therapy. METHODS: In this phase 2 trial, patients with pediatric low-grade glioma with BRAF V600 mutations who were scheduled to receive first-line therapy were randomly assigned in a 2:1 ratio to receive dabrafenib plus trametinib or standard chemotherapy (carboplatin plus vincristine). The primary outcome was the independently assessed overall response (complete or partial response) according to the Response Assessment in Neuro-Oncology criteria. Also assessed were the clinical benefit (complete or partial response or stable disease for ≥24 weeks) and progression-free survival. RESULTS: A total of 110 patients underwent randomization (73 to receive dabrafenib plus trametinib and 37 to receive standard chemotherapy). At a median follow-up of 18.9 months, an overall response occurred in 47% of the patients treated with dabrafenib plus trametinib and in 11% of those treated with chemotherapy (risk ratio, 4.31; 95% confidence interval [CI], 1.7 to 11.2; P<0.001). Clinical benefit was observed in 86% of the patients receiving dabrafenib plus trametinib and in 46% receiving chemotherapy (risk ratio, 1.88; 95% CI, 1.3 to 2.7). The median progression-free survival was significantly longer with dabrafenib plus trametinib than with chemotherapy (20.1 months vs. 7.4 months; hazard ratio, 0.31; 95% CI, 0.17 to 0.55; P<0.001). Grade 3 or higher adverse events occurred in 47% of the patients receiving dabrafenib plus trametinib and in 94% of those receiving chemotherapy. CONCLUSIONS: Among pediatric patients with low-grade glioma with BRAF V600 mutations, dabrafenib plus trametinib resulted in significantly more responses, longer progression-free survival, and a better safety profile than standard chemotherapy as first-line therapy. (Funded by Novartis; ClinicalTrials.gov number, NCT02684058.).

Optimizing preclinical pediatric low-grade glioma models for meaningful clinical translation.

Pediatric low-grade gliomas (pLGGs) are the most common brain tumor in young children. While they are typically associated with good overall survival, children with these central nervous system tumors often experience chronic tumor- and therapy-related morbidities. Moreover, individuals with unresectable tumors frequently have multiple recurrences and persistent neurological symptoms. Deep molecular analyses of pLGGs reveal that they are caused by genetic alterations that converge on a single mitogenic pathway (MEK/ERK), but their growth is heavily influenced by nonneoplastic cells (neurons, T cells, microglia) in their local microenvironment. The interplay between neoplastic cell MEK/ERK pathway activation and stromal cell support necessitates the use of predictive preclinical models to identify the most promising drug candidates for clinical evaluation. As part of a series of white papers focused on pLGGs, we discuss the current status of preclinical pLGG modeling, with the goal of improving clinical translation for children with these common brain tumors.

Pakistan National Guidelines for Pediatric High-Grade Gliomas.

Pediatric high-grade glioma (pHGG) is highly malignant central nervous system tumor and constitute 10% of the pediatric gliomas. Effective treatment needs a functioning multi-disciplinary team including pediatric neuro oncologist, neurosurgeon, neuroradiologist, neuropathologist and radiation oncologist. Despite surgical resection, radiotherapy and chemotherapy, most HGG will recur resulting in early death. A significant proportion of HGG occurs in context of cancer predisposition syndromes like Constitutional Mismatch Repair Deficiency (CMMRD) also known as Biallelic Mismatch Repair Deficiency (bMMRD) characterized by high mutational burden. The incidence of HGG with CMMRD is one per million patients. bMMRD is caused by homozygous germline mutations in one of the four Mis Match Repair (MMR) genes (PMS2, MLH1, MSH2, and MSH6). The use of TMZ is now avoided in CMMRD related HGG due to its limited response and known ability to increase the accumulation of somatic mutations in these patients, increasing the risk of secondary tumors. HGG should be managed under the care of multidisciplinary team to receive optimum treatment. This is particularly important for low middle-income countries (LMIC) with limited resources like Pakistan.