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.

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 aetiology increases. Some children with brain tumors may present with non-malignant 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 increasingly has also impacted 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.

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.

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.

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.

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.

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.

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.

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.).

Efficacy of Nivolumab in Pediatric Cancers with High Mutation Burden and Mismatch Repair Deficiency.

PURPOSE: Checkpoint inhibitors have limited efficacy for children with unselected solid and brain tumors. We report the first prospective pediatric trial (NCT02992964) using nivolumab exclusively for refractory nonhematologic cancers harboring tumor mutation burden (TMB) ≥5 mutations/megabase (mut/Mb) and/or mismatch repair deficiency (MMRD). PATIENTS AND METHODS: Twenty patients were screened, and 10 were ultimately included in the response cohort of whom nine had TMB >10 mut/Mb (three initially eligible based on MMRD) and one patient had TMB between 5 and 10 mut/Mb. RESULTS: Delayed immune responses contributed to best overall response of 50%, improving on initial objective responses (20%) and leading to 2-year overall survival (OS) of 50% [95% confidence interval (CI), 27-93]. Four children, including three with refractory malignant gliomas are in complete remission at a median follow-up of 37 months (range, 32.4-60), culminating in 2-year OS of 43% (95% CI, 18.2-100). Biomarker analyses confirmed benefit in children with germline MMRD, microsatellite instability, higher activated and lower regulatory circulating T cells. Stochastic mutation accumulation driven by underlying germline MMRD impacted the tumor microenvironment, contributing to delayed responses. No benefit was observed in the single patient with an MMR-proficient tumor and TMB 7.4 mut/Mb. CONCLUSIONS: Nivolumab resulted in durable responses and prolonged survival for the first time in a pediatric trial of refractory hypermutated cancers including malignant gliomas. Novel biomarkers identified here need to be translated rapidly to clinical care to identify children who can benefit from checkpoint inhibitors, including upfront management of cancer. See related commentary by Mardis, p. 4701.

Diagnostic classification of childhood cancer using multiscale transcriptomics.

The causes of pediatric cancers' distinctiveness compared to adult-onset tumors of the same type are not completely clear and not fully explained by their genomes. In this study, we used an optimized multilevel RNA clustering approach to derive molecular definitions for most childhood cancers. Applying this method to 13,313 transcriptomes, we constructed a pediatric cancer atlas to explore age-associated changes. Tumor entities were sometimes unexpectedly grouped due to common lineages, drivers or stemness profiles. Some established entities were divided into subgroups that predicted outcome better than current diagnostic approaches. These definitions account for inter-tumoral and intra-tumoral heterogeneity and have the potential of enabling reproducible, quantifiable diagnostics. As a whole, childhood tumors had more transcriptional diversity than adult tumors, maintaining greater expression flexibility. To apply these insights, we designed an ensemble convolutional neural network classifier. We show that this tool was able to match or clarify the diagnosis for 85% of childhood tumors in a prospective cohort. If further validated, this framework could be extended to derive molecular definitions for all cancer types.

Single-strand mismatch and damage patterns revealed by single-molecule DNA sequencing.

Mutations accumulate in the genome of every cell of the body throughout life, causing cancer and other genetic diseases1-4. Almost all of these mosaic mutations begin as nucleotide mismatches or damage in only one of the two strands of the DNA prior to becoming double-strand mutations if unrepaired or misrepaired5. However, current DNA sequencing technologies cannot resolve these initial single-strand events. Here, we developed a single-molecule, long-read sequencing method that achieves single-molecule fidelity for single-base substitutions when present in either one or both strands of the DNA. It also detects single-strand cytosine deamination events, a common type of DNA damage. We profiled 110 samples from diverse tissues, including from individuals with cancer-predisposition syndromes, and define the first single-strand mismatch and damage signatures. We find correspondences between these single-strand signatures and known double-strand mutational signatures, which resolves the identity of the initiating lesions. Tumors deficient in both mismatch repair and replicative polymerase proofreading show distinct single-strand mismatch patterns compared to samples deficient in only polymerase proofreading. In the mitochondrial genome, our findings support a mutagenic mechanism occurring primarily during replication. Since the double-strand DNA mutations interrogated by prior studies are only the endpoint of the mutation process, our approach to detect the initiating single-strand events at single-molecule resolution will enable new studies of how mutations arise in a variety of contexts, especially in cancer and aging.

Using comprehensive genomic and functional analyses for resolving genotype-phenotype mismatches in children with suspected CMMRD in Lebanon: an IRRDC study.

Constitutional mismatch repair deficiency (CMMRD) is an aggressive and highly penetrant cancer predisposition syndrome. Because of its variable clinical presentation and phenotypical overlap with neurofibromatosis, timely diagnosis remains challenging, especially in countries with limited resources. Since current tests are either difficult to implement or interpret or both we used a novel and relatively inexpensive functional genomic assay (LOGIC) which has been recently reported to have high sensitivity and specificity in diagnosing CMMRD. Here we report the clinical and molecular characteristics of nine patients diagnosed with cancer and suspected to have CMMRD and highlight the challenges with variant interpretation and immunohistochemical analysis that led to an uncertain interpretation of genetic findings in 6 of the 9 patients. Using LOGIC, we were able to confirm the diagnosis of CMMRD in 7 and likely exclude it in 2 patients, resolving ambiguous result interpretation. LOGIC also enabled predictive testing of asymptomatic siblings for early diagnosis and implementation of surveillance. This study highlights the varied manifestations and practical limitations of current diagnostic criteria for CMMRD, and the importance of international collaboration for implementing robust and low-cost functional assays for resolving diagnostic challenges.

Insult to Short-Range White Matter Connectivity in Childhood Brain Tumor Survivors.

PURPOSE: Children treated for brain tumors are at an increased risk for cognitive impairments due to the effect of radiation therapy on developing white matter (WM). Although damage to long-range WM is well documented in pediatric brain tumor survivors, the effect of radiation therapy on short-range WM remains unelucidated. We sought to clarify whether radiation treatment affects short-range WM by completing a virtual dissection of these connections and comparing their microstructural properties between brain tumor survivors and typically developing children. METHODS AND MATERIALS: T1-weighted and diffusion-weighted magnetic resonance images were acquired for 26 brain tumor survivors and 26 typically developing children. Short-range WM was delineated using a novel, whole-brain approach. A random forest classifier was used to identify short-range connections with the largest differences in microstructure between patients and typically developing children. RESULTS: The random forest classifier identified differences in short-range WM microstructure across the brain with an accuracy of 87.5%. Nine connections showed the largest differences in short-range WM between patients and typically developing children. For these connections, fractional anisotropy and axial diffusivity were significantly lower in patients. Short-range connections in the posterior fossa were disproportionately affected, suggesting that greater radiation exposure to the posterior fossa was more injurious to short-range WM. Lower craniospinal radiation dose did not predict reduced toxicity to short-range WM. CONCLUSIONS: Our findings indicate that treatment for medulloblastoma resulted in changes in short-range WM in patients. Lower fractional anisotropy and axial diffusivity may reflect altered microstructural organization and coherence of these connections, especially in the posterior fossa. Short-range WM may be especially sensitive to the effect of craniospinal radiation therapy, resulting in compromise to these connections regardless of dose.