Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncology

Microarray-Based DNA Methylation Profiling: Validation Considerations for Clinical Testing

Microarray-based methylation profiling has emerged as a valuable tool for refining diagnoses and revealing novel tumor subtypes, particularly in central nervous system tumors. Despite the increasing adoption of this technique in clinical genomic laboratories, no technical standards have been published in establishing minimum criteria for test validation. A working group with experience and expertise in DNA-based methylation profiling tests on central nervous system tumors collaborated to develop practical discussion points and focus on important considerations for validating this test in clinical laboratory settings. The experience in validating this methodology in a clinical setting is summarized. Specifically, the advantages and challenges associated with utilizing an in-house classifier compared with a third-party classifier are highlighted. Additionally, experiences in demonstrating the assay's sensitivity and specificity, establishing minimum sample criteria, and implementing quality control metrics are described. As methylation profiling for tumor classification expands to other tumor types and continues to evolve for various other applications, the critical considerations described here are expected to serve as a guidance for future efforts in establishing professional guidelines for this assay.

Rapid DNA methylation-based classification of pediatric brain tumors from ultrasonic aspirate specimens

BACKGROUND

Although cavitating ultrasonic aspirators are commonly used in neurosurgical procedures, the suitability of ultrasonic aspirator-derived tumor material for diagnostic procedures is still controversial. Here, we explore the feasibility of using ultrasonic aspirator-resected tumor tissue to classify otherwise discarded sample material by fast DNA methylation-based analysis using low pass nanopore whole genome sequencing.

METHODS

Ultrasonic aspirator-derived specimens from pediatric patients undergoing brain tumor resection were subjected to low-pass nanopore whole genome sequencing. DNA methylation-based classification using a neural network classifier and copy number variation analysis were performed. Tumor purity was estimated from copy number profiles. Results were compared to microarray (EPIC)-based routine neuropathological histomorphological and molecular evaluation.

RESULTS

19 samples with confirmed neuropathological diagnosis were evaluated. All samples were successfully sequenced and passed quality control for further analysis. DNA and sequencing characteristics from ultrasonic aspirator-derived specimens were comparable to routinely processed tumor tissue. Classification of both methods was concordant regarding methylation class in 17/19 (89%) cases. Application of a platform-specific threshold for nanopore-based classification ensured a specificity of 100%, whereas sensitivity was 79%. Copy number variation profiles were generated for all cases and matched EPIC results in 18/19 (95%) samples, even allowing the identification of diagnostically or therapeutically relevant genomic alterations.

CONCLUSION

Methylation-based classification of pediatric CNS tumors based on ultrasonic aspirator-reduced and otherwise discarded tissue is feasible using time- and cost-efficient nanopore sequencing.

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.

Availability and utilization of molecular testing for primary central nervous system tumors among US hospitals

Advanced molecular testing has increasingly become an integral component for accurate diagnosis of central nervous system (CNS) tumors. We sought to establish the current state of molecular testing availability and approaches for the diagnosis of CNS tumors in US hospitals that conduct high volumes of CNS tumor resections. We distributed a 16-item survey inquiring about molecular testing approaches for CNS tumors to 115 neuropathologists at US hospitals with neurosurgery residency programs. Thirty-five neuropathologists (30.4%) responded to the survey, all of whom indicated their institutions perform molecular testing on CNS tumor tissue. The most commonly offered tests were MGMT methylation profiling and next-generation sequencing. Fourteen respondents (40%) indicated that their institution is able to test for and report all of the molecular alterations included in our survey. Nine (25.7%) respondents indicated that molecular testing is performed as standard of care for all patients with resected CNS tumors. Our results suggest that even in academic hospitals with a high volume of CNS tumor resections, molecular testing for these tumors is limited. Continued initiatives are necessary to expand the availability of molecular testing for CNS tumors to ensure diagnostic accuracy and guide targeted therapy.

Electro-Optical Multiclassification Platform for Minimizing Occasional Inaccuracy in Point-of-Care Biomarker Detection

On-site diagnostic tests that accurately identify disease biomarkers lay the foundation for self-healthcare applications. However, these tests routinely rely on single-mode signals and suffer from insufficient accuracy, especially for multiplexed point-of-care tests (POCTs) within a few minutes. Here, this work develops a dual-mode multiclassification diagnostic platform that integrates an electrochemiluminescence sensor and a field-effect transistor sensor in a microfluidic chip. The microfluidic channel guides the testing samples to flow across electro-optical sensor units, which produce dual-mode readouts by detecting infectious biomarkers of tuberculosis (TB), human rhinovirus (HRV), and group B streptococcus (GBS). Then, machine-learning classifiers generate three-dimensional (3D) hyperplanes to diagnose different diseases. Dual-mode readouts derived from distinct mechanisms enhance the anti-interference ability physically, and machine-learning-aided diagnosis in high-dimensional space reduces the occasional inaccuracy mathematically. Clinical validation studies with 501 unprocessed samples indicate that the platform has an accuracy approaching 99%, higher than the 77%-93% accuracy of rapid point-of-care testing technologies at 100% statistical power (>150 clinical tests). Moreover, the diagnosis time is 5 min without a trade-off of accuracy. This work solves the occasional inaccuracy issue of rapid on-site diagnosis, endowing POCT systems with the same accuracy as laboratory tests and holding unique prospects for complicated scenes of personalized healthcare.

Current and emerging sequencing-based tools for precision cancer medicine

Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.

Feasibility and antitumour activity of the FGFR inhibitor erdafitnib in three paediatric CNS tumour patients

Alterations of the fibroblast growth factor (FGF) signalling pathway are increasingly recognized as frequent oncogenic drivers of paediatric brain tumours. We report on three patients treated with the selective FGFR1-4 inhibitor erdafitinib. Two patients were diagnosed with a posterior fossa ependymoma group A (PFA EPN) and one with a low-grade glioma (LGG), harbouring FGFR3/FGFR1 overexpression and an FGFR1 internal tandem duplication (ITD), respectively. While both EPN patients did not respond to erdafitinib treatment, the FGFR1-ITD-harbouring tumour showed a significant decrease in tumour volume and contrast enhancement throughout treatment. The tumour remained stable 6 months after treatment discontinuation.

Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice

MOTIVATION

Copy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings.

RESULTS

We present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson's correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts.

AVAILABILITY AND IMPLEMENTATION

Conumee 2.0 is available under open-source license at: https://github.com/hovestadtlab/conumee2.

Overview of modern genomic tools for diagnosis and precision therapy of childhood solid cancers

PURPOSE OF REVIEW

The application of technology and computational analyses to generate new data types from pediatric solid cancers is transforming diagnostic accuracy. This review provides an overview of such new capabilities in the pursuit of improved treatment for essentially rare and underserved diseases that are the highest cause of mortality in children over one year of age. Sophisticated ways of identifying therapeutic vulnerabilities for highly personalized treatment are presented alongside cutting-edge disease response monitoring by liquid biopsy.

RECENT FINDINGS

Precision molecular profiling data are now being combined with conventional pathology-based evaluation of pediatric cancer tissues. The resulting diagnostic information can be used to guide therapeutic decision-making, including the use of small molecule inhibitors and of immunotherapies. Integrating somatic and germline variant profiles constitutes a critical component of this emerging paradigm, as does tissue-of-origin derivation from methylation profiling, and rapid screening of potential therapies. These new approaches are poised for use in disease response and therapy resistance monitoring.

SUMMARY

The integration of clinical molecular profiling data with pathology can provide a highly precise diagnosis, identify therapeutic vulnerabilities, and monitor patient responses, providing next steps toward precision oncology for improved outcomes, including reducing lifelong treatment-related sequelae.

Molecular characteristics and improved survival prediction in a cohort of 2023 ependymomas

The diagnosis of ependymoma has moved from a purely histopathological review with limited prognostic value to an integrated diagnosis, relying heavily on molecular information. However, as the integrated approach is still novel and some molecular ependymoma subtypes are quite rare, few studies have correlated integrated pathology and clinical outcome, often focusing on small series of single molecular types. We collected data from 2023 ependymomas as classified by DNA methylation profiling, consisting of 1736 previously published and 287 unpublished methylation profiles. Methylation data and clinical information were correlated, and an integrated model was developed to predict progression-free survival. Patients with EPN-PFA, EPN-ZFTA, and EPN-MYCN tumors showed the worst outcome with 10-year overall survival rates of 56%, 62%, and 32%, respectively. EPN-PFA harbored chromosome 1q gains and/or 6q losses as markers for worse survival. In supratentorial EPN-ZFTA, a combined loss of CDKN2A and B indicated worse survival, whereas a single loss did not. Twelve out of 200 EPN-ZFTA (6%) were located in the posterior fossa, and these tumors relapsed or progressed even earlier than supratentorial tumors with a combined loss of CDKN2A/B. Patients with MPE and PF-SE, generally regarded as non-aggressive tumors, only had a 10-year progression-free survival of 59% and 65%, respectively. For the prediction of the 5-year progression-free survival, Kaplan-Meier estimators based on the molecular subtype, a Support Vector Machine based on methylation, and an integrated model based on clinical factors, CNV data, and predicted methylation scores achieved balanced accuracies of 66%, 68%, and 73%, respectively. Excluding samples with low prediction scores resulted in balanced accuracies of over 80%. In sum, our large-scale analysis of ependymomas provides robust information about molecular features and their clinical meaning. Our data are particularly relevant for rare and hardly explored tumor subtypes and seemingly benign variants that display higher recurrence rates than previously believed.

Unclassifiable CNS tumors in DNA methylation-based classification: clinical challenges and prognostic impact

DNA methylation analysis has become a powerful tool in neuropathology. Although DNA methylation-based classification usually shows high accuracy, certain samples cannot be classified and remain clinically challenging. We aimed to gain insight into these cases from a clinical perspective. To address, central nervous system (CNS) tumors were subjected to DNA methylation profiling and classified according to their calibrated score using the DKFZ brain tumor classifier (V11.4) as "≥ 0.84" (score ≥ 0.84), "0.3-0.84" (score 0.3-0.84), or "< 0.3" (score < 0.3). Histopathology, patient characteristics, DNA input amount, and tumor purity were correlated. Clinical outcome parameters were time to treatment decision, progression-free, and overall survival. In 1481 patients, the classifier identified 69 (4.6%) tumors with an unreliable score as "< 0.3". Younger age (P < 0.01) and lower tumor purity (P < 0.01) compromised accurate classification. A clinical impact was demonstrated as unclassifiable cases ("< 0.3") had a longer time to treatment decision (P < 0.0001). In a subset of glioblastomas, these cases experienced an increased time to adjuvant treatment start (P < 0.001) and unfavorable survival (P < 0.025). Although DNA methylation profiling adds an important contribution to CNS tumor diagnostics, clinicians should be aware of a potentially longer time to treatment initiation, especially in malignant brain tumors.

Measuring Progress in Precision Oncology

SUMMARY

In this issue of Cancer Discovery, Suehnholz and colleagues describe their efforts to quantify the gradual yet steady progress of precision oncology by surveying the regulatory approvals of targeted cancer therapies, and thus the actionability of corresponding molecular alterations in clinical practice, over more than 20 years. Their work also suggests a relationship between the discovery of candidate therapeutic targets through comprehensive tumor profiling and molecularly guided cancer drug development. See related article by Suehnholz et al., p. 49 (5).

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.

Germline Variants in Cancer Predisposition Genes in Pediatric Patients with Central Nervous System Tumors

Central nervous system (CNS) tumors comprise around 20% of childhood malignancies. Germline variants in cancer predisposition genes (CPGs) are found in approximately 10% of pediatric patients with CNS tumors. This study aimed to characterize variants in CPGs in pediatric patients with CNS tumors and correlate these findings with clinically relevant data. Genomic DNA was isolated from the peripheral blood of 51 pediatric patients and further analyzed by the next-generation sequencing approach. Bioinformatic analysis was done using an "in-house" gene list panel, which included 144 genes related to pediatric brain tumors, and the gene list panel Neoplasm (HP:0002664). Our study found that 27% of pediatric patients with CNS tumors have a germline variant in some of the known CPGs, like ALK, APC, CHEK2, ELP1, MLH1, MSH2, NF1, NF2 and TP53. This study represents the first comprehensive evaluation of germline variants in pediatric patients with CNS tumors in the Western Balkans region. Our results indicate the necessity of genomic research to reveal the genetic basis of pediatric CNS tumors, as well as to define targets for the application and development of innovative therapeutics that form the basis of the upcoming era of personalized medicine.

Clinical outcome of pediatric medulloblastoma patients with Li-Fraumeni syndrome

BACKGROUND

The prognosis for Li-Fraumeni syndrome (LFS) patients with medulloblastoma (MB) is poor. Comprehensive clinical data for this patient group is lacking, challenging the development of novel therapeutic strategies. Here, we present clinical and molecular data on a retrospective cohort of pediatric LFS MB patients.

METHODS

In this multinational, multicenter retrospective cohort study, LFS patients under 21 years with MB and class 5 or class 4 constitutional TP53 variants were included. TP53 mutation status, methylation subgroup, treatment, progression free- (PFS) and overall survival (OS), recurrence patterns, and incidence of subsequent neoplasms were evaluated.

RESULTS

The study evaluated 47 LFS individuals diagnosed with MB, mainly classified as DNA methylation subgroup "SHH_3" (86%). The majority (74%) of constitutional TP53 variants represented missense variants. The 2- and 5-year (y-) PFS were 36% and 20%, and 2- and 5y-OS were 53% and 23%, respectively. Patients who received postoperative radiotherapy (RT) (2y-PFS: 44%, 2y-OS: 60%) or chemotherapy before RT (2y-PFS: 32%, 2y-OS: 48%) had significantly better clinical outcome then patients who were not treated with RT (2y-PFS: 0%, 2y-OS: 25%). Patients treated according to protocols including high-intensity chemotherapy and patients who received only maintenance-type chemotherapy showed similar outcomes (2y-PFS: 42% and 35%, 2y-OS: 68% and 53%, respectively).

CONCLUSIONS

LFS MB patients have a dismal prognosis. In the presented cohort use of RT significantly increased survival rates, whereas chemotherapy intensity did not influence their clinical outcome. Prospective collection of clinical data and development of novel treatments are required to improve the outcome of LFS MB patients.

Clinical impact of molecular profiling in rare brain tumors

PURPOSE OF REVIEW

The purpose of this review is to describe the commonly used molecular diagnostics and illustrate the prognostic importance to the more accurate diagnosis that also may uncover therapeutic targets.

RECENT FINDINGS

The most recent WHO Classification of Central Nervous System Tumours (2021) lists over 100 distinct tumor types. While traditional histology continues to be an important component, molecular testing is increasingly being incorporated as requisite diagnostic criteria. Specific molecular findings such as co-deletion of the short arm of chromosome 1 (1p) and long arm of chromosome 19 (19q) now define IDH-mutant gliomas as oligodendroglioma. In recent years, DNA methylation profiling has emerged as a dynamic tool with high diagnostic accuracy. The integration of specific genetic (mutations, fusions) and epigenetic (CpG methylation) alterations has led to diagnostic refinement and the discovery of rare brain tumor types with distinct clinical outcomes. Molecular profiling is anticipated to play an increasing role in routine surgical neuropathology, although costs, access, and logistical concerns remain challenging.

SUMMARY

This review summarizes the current state of molecular testing in neuro-oncology highlighting commonly used and developing technologies, while also providing examples of new tumor types/subtypes that have emerged as a result of improved diagnostic precision.

Mouse models of pediatric high-grade gliomas with MYCN amplification reveal intratumoral heterogeneity and lineage signatures

Pediatric high-grade gliomas of the subclass MYCN (HGG-MYCN) are highly aggressive tumors frequently carrying MYCN amplifications, TP53 mutations, or both alterations. Due to their rarity, such tumors have only recently been identified as a distinct entity, and biological as well as clinical characteristics have not been addressed specifically. To gain insights into tumorigenesis and molecular profiles of these tumors, and to ultimately suggest alternative treatment options, we generated a genetically engineered mouse model by breeding hGFAP-cre::Trp53Fl/Fl::lsl-MYCN mice. All mice developed aggressive forebrain tumors early in their lifetime that mimic human HGG-MYCN regarding histology, DNA methylation, and gene expression. Single-cell RNA sequencing revealed a high intratumoral heterogeneity with neuronal and oligodendroglial lineage signatures. High-throughput drug screening using both mouse and human tumor cells finally indicated high efficacy of Doxorubicin, Irinotecan, and Etoposide as possible therapy options that children with HGG-MYCN might benefit from.

Ependymoma-like tumor with mesenchymal differentiation (ELTMD) with ZFTA:NCOA1 fusion: A diagnostic challenge

Ependymal tumors are classified based on their location, histology, and molecular characteristics. Supratentorial ependymomas (ST-EPNs) are a group of circumscribed supratentorial gliomas, which usually have pathogenic fusions involving either zinc finger translocation associated (ZFTA) (formerly C11orf95) or YAP1. A subtype of ependymoma was recently described and labeled ependymoma-like tumors with mesenchymal differentiation (ELTMDs). We describe a case of a 5-year-old boy who presented with a right frontal tumor. The diagnosis was challenging, and a correct diagnosis could only be reached after reanalysis of methylation data with a more recent version of the classifier and RNA fusion testing, which revealed ZFTA:NCOA1 (nuclear receptor coactivator 1) fusion. There are only a handful of cases of this entity, which is being reported for its rarity and the diagnostic challenge it poses.

[Pediatric brain tumors]

Pediatric central nervous system (CNS) tumors differ in their relative frequency, location, histology, biological behavior and prognosis from tumors in adults. Accurate neuropathological classification of CNS tumors is essential for therapeutic decisions and inclusion in therapy optimization studies. Tissue samples are analyzed by standardized conventional histological, immunohistological and molecular pathological methods and diagnosed according to the current World Health Organization (WHO) classification for CNS tumors (2021). By identifying characteristic genetic alterations and specific epigenetic signatures, the precision in the classification of pediatric brain tumors has significantly improved in recent years. The WHO classification allows a worldwide uniform, standardized classification of brain tumors and forms the basis for comparability of international epidemiological and clinical data. In some tumor types, such as childhood gliomas and embryonal tumors, key molecules and signaling pathways have been identified in recent years that represent starting points for new mechanism-based therapeutic modalities in the treatment of these patients.

Implementation of DNA Methylation Array Profiling in Pediatric Central Nervous System Tumors: The AIM BRAIN Project: An Australian and New Zealand Children's Haematology/Oncology Group Study

DNA methylation array profiling for classifying pediatric central nervous system (CNS) tumors is a valuable adjunct to histopathology. However, unbiased prospective and interlaboratory validation studies have been lacking. The AIM BRAIN diagnostic trial involving 11 pediatric cancer centers in Australia and New Zealand was designed to test the feasibility of routine clinical testing and ran in parallel with the Molecular Neuropathology 2.0 (MNP2.0) study at Deutsches Krebsforschungszentrum (German Cancer Research Center). CNS tumors from 269 pediatric patients were prospectively tested on Illumina EPIC arrays, including 104 cases co-enrolled on MNP2.0. Using MNP classifier versions 11b4 and 12.5, we report classifications with a probability score ≥0.90 in 176 of 265 (66.4%) and 213 of 269 (79.2%) cases, respectively. Significant diagnostic information was obtained in 130 of 176 (74%) for 11b4, and 12 of 174 (7%) classifications were discordant with histopathology. Cases prospectively co-enrolled on MNP2.0 gave concordant classifications (99%) and score thresholds (93%), demonstrating excellent test reproducibility and sensitivity. Overall, DNA methylation profiling is a robust single workflow technique with an acceptable diagnostic yield that is considerably enhanced by the extensive subgroup and copy number profile information generated by the platform. The platform has excellent test reproducibility and sensitivity and contributes significantly to CNS tumor diagnosis.

Methylation across the central dogma in health and diseases: new therapeutic strategies

The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.

Diagnostic Yield From a Nationwide Implementation of Precision Medicine for all Children With Cancer

PURPOSE

Several studies have indicated that broad genomic characterization of childhood cancer provides diagnostically and/or therapeutically relevant information in selected high-risk cases. However, the extent to which such characterization offers clinically actionable data in a prospective broadly inclusive setting remains largely unexplored.

METHODS

We implemented prospective whole-genome sequencing (WGS) of tumor and germline, complemented by whole-transcriptome sequencing (RNA-Seq) for all children diagnosed with a primary or relapsed solid malignancy in Sweden. Multidisciplinary molecular tumor boards were set up to integrate genomic data in the clinical decision process along with a medicolegal framework enabling secondary use of sequencing data for research purposes.

RESULTS

During the study's first 14 months, 118 solid tumors from 117 patients were subjected to WGS, with complementary RNA-Seq for fusion gene detection in 52 tumors. There was no significant geographic bias in patient enrollment, and the included tumor types reflected the annual national incidence of pediatric solid tumor types. Of the 112 tumors with somatic mutations, 106 (95%) exhibited alterations with a clear clinical correlation. In 46 of 118 tumors (39%), sequencing only corroborated histopathological diagnoses, while in 59 cases (50%), it contributed to additional subclassification or detection of prognostic markers. Potential treatment targets were found in 31 patients (26%), most commonly ALK mutations/fusions (n = 4), RAS/RAF/MEK/ERK pathway mutations (n = 14), FGFR1 mutations/fusions (n = 5), IDH1 mutations (n = 2), and NTRK2 gene fusions (n = 2). In one patient, the tumor diagnosis was revised based on sequencing. Clinically relevant germline variants were detected in 8 of 94 patients (8.5%).

CONCLUSION

Up-front, large-scale genomic characterization of pediatric solid malignancies provides diagnostically valuable data in the majority of patients also in a largely unselected cohort.