MYCN amplification drives one in six cases of neuroblastoma. The supernumerary gene copies are commonly found on highly rearranged, extrachromosomal circular DNA (ecDNA). The exact amplicon structure has not been described thus far and the functional relevance of its rearrangements is unknown. Here, we analyze the MYCN amplicon structure using short-read and Nanopore sequencing and its chromatin landscape using ChIP-seq, ATAC-seq and Hi-C. This reveals two distinct classes of amplicons which explain the regulatory requirements for MYCN overexpression. The first class always co-amplifies a proximal enhancer driven by the noradrenergic core regulatory circuit (CRC). The second class of MYCN amplicons is characterized by high structural complexity, lacks key local enhancers, and instead contains distal chromosomal fragments harboring CRC-driven enhancers. Thus, ectopic enhancer hijacking can compensate for the loss of local gene regulatory elements and explains a large component of the structural diversity observed in MYCN amplification.

Background Brain tumor surgery must balance the benefit of maximal resection against the risk of inflicting severe damage. The impact of increased resection is diagnosis specific. However, the precise diagnosis is typically uncertain at surgery due to limitations of imaging and intraoperative histomorphological methods. Novel and accurate strategies for brain tumor classification are necessary to support personalized intraoperative neurosurgical treatment decisions. Here, we describe a fast and cost-efficient workflow for intraoperative classification of brain tumors based on DNA methylation profiles generated by low coverage nanopore sequencing and machine learning algorithms. Methods We evaluated six independent cohorts containing 105 patients, including 50 pediatric and 55 adult patients. Ultra-low coverage whole genome sequencing was performed on nanopore flow cells. Data was analyzed using copy number variation and ad hoc random forest classifier for the genome-wide methylation-based classification of the tumor. Results Concordant classification was obtained between nanopore DNA methylation analysis and a full neuropathological evaluation in 93 of 105 (89%) cases. The analysis demonstrated correct diagnosis in 6/6 cases where frozen section evaluation was inconclusive. Results could be returned to the operating room at a median of 97 minutes (range 91-161 minutes). Precise classification of the tumor entity and subtype would have supported modification of the surgical strategy in 12 out of 20 patients evaluated intraoperatively. Conclusion Intraoperative nanopore sequencing combined with machine learning diagnostics was robust, sensitive, and rapid. This strategy allowed DNA methylation-based classification of the tumor to be returned to the surgeon within a timeframe that supports intraoperative decision-making.

Background DNA methylation‐based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro‐oncology. However, current implementation using hybridisation microarrays is time consuming and costly. We recently reported on shallow nanopore whole‐genome sequencing for rapid and cost‐effective generation of genome‐wide 5‐methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows us to discriminate a wide spectrum of primary brain tumours. Results Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on 382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of 55 cases, we found that a minimum set of 1000 random CpG features is sufficient for high‐confidence classification by ad hoc random forests. We implemented score recalibration as a confidence measure for interpretation in a clinical context and empirically determined a platform‐specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut‐off to an independent validation series (n = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100% specificity. Cross‐lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), the median time to results was 21.1 h. Conclusions In conclusion, nanopore sequencing allows robust and rapid methylation‐based classification across the full spectrum of brain tumours. Platform‐specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

MYCN amplification drives one in six cases of neuroblastoma. The supernumerary gene copies are commonly found on highly rearranged, extrachromosomal circular DNA. The exact amplicon structure has not been described thus far and the functional relevance of its rearrangements is unknown. Here, we analyzed the MYCN amplicon structure and its chromatin landscape. This revealed two distinct classes of amplicons which explain the regulatory requirements for MYCN overexpression. The first class always co-amplified a proximal enhancer driven by the noradrenergic core regulatory circuit (CRC). The second class of MYCN amplicons was characterized by high structural complexity, lacked key local enhancers, and instead contained distal chromosomal fragments, which harbored CRC-driven enhancers. Thus, ectopic enhancer hijacking can compensate for the loss of local gene regulatory elements and explains a large component of the structural diversity observed in MYCN amplification.

Background Cavitating ultrasonic aspirator (CUSA) devices are commonly used in neurosurgical procedures to carefully debulk tumor from adjacent healthy brain tissue. Here, we explore the feasibility of using ultrasonic minced tumor tissue to classify otherwise discarded sample material by DNA methylation according to the respective World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) using low pass nanopore whole genome sequencing. Material and Methods 21 ultrasonic aspirated specimens from patients undergoing surgery in the department of pediatric neurosurgery at the Charité-Universitätsmedizin Berlin with either newly diagnosed cerebral lesions or pre-treated lesions were processed by nanopore sequencing to generate copy number profiles and ad-hoc random forest classification. Results were compared to microarray-based routine profiling. Tumor purity was assessed. Results In 19/21 (90.5 %) samples the minimum amount of 1,000 CpG sites were sequenced. In 20/21 (95.2 %) cases copy number variation profiles could be generated and matched microarray derived copy number profiles, allowing for identification of diagnostically or therapeutically relevant pathognomonic alterations. 12/17 (70.6 %) samples were concordantly classified to the corresponding microarray-based diagnosis by routine neuropathological workup. Applying recently defined thresholds for nanopore-based classification resulted in sensitivity of 64.7 % and specificity of 100 %. Conclusion CUSA referred sample material of pediatric brain tumors allows for methylation-based classification according to the respective WHO classification of CNS tumors with acceptable sensitivity and high specificity. Hereby, a promising opportunity for accurate classification of pediatric brain tumors by a time- and cost-efficient advanced molecular technique is offered using otherwise discarded tumor tissue.