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• Robust methylation-based classification of brain tumours using nanopore sequencing

  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 implementations using hybridization microarrays are 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 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 N=382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of N = 56 cases, we find that a minimum set of 1,000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as 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), median time to results was 21.1 hours. 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.

  Study EGAS00001006540

• Out with the Java, in with the Python - new EGA data download client unveiled

  We will shortly be deprecating the Java-based download client also known as API V2. The Java client began its life at the back end of 2014, and during its time has seen many developments that have served our users well. During its tenure, the Java client enabled distribution of over 6.5 million files totalling nearly 15 petabytes of data to researchers around the globe. Recent increases in genomic and phenotypic data file sizes, the number of datasets archived in the EGA, the number of users downloading data, and the diversity of download locations has meant that at times the Java client struggled to distribute data efficiently. In response, our team of developers have built a new download client with more robust features and better functionality and reliability. Enter stage left our shiny new API V3.1! The new API V3.1 will replace both API V2 and API V3. The download client for the new API V3.1 is written in Python, and the code is openly available on Github. This Python client makes https calls to the EGA AAI (https://ega.ebi.ac.uk:8443/) and to the EGA Data API (https://ega.ebi.ac.uk:8052), both of which must be accessible from the client location. In addition to general updates to improve performance, the API V3.1 has three new features enhancing the EGA distributions services. First, requested data are now downloaded over secure https connections rather than http, meaning that data can be delivered unencrypted. Instead of separately requesting, downloading, and decrypting data using the Java client, data can now be requested and downloaded using a single command without the need for decrypting. The API V3.1 also automatically verifies each file’s unencrypted md5 after download to ensure the file has downloaded correctly. Second, the new API supports segmenting and automatic resuming. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the new resume feature, downloads - both segmented and continuous stream - will automatically resume if they encounter any errors or the connection is interrupted. These features result in both a faster and more reliable download experience. Finally, the new API V3.1 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file saving both time and storage space. The new features of the Python-based API V3.1 represent significant improvements in security, speed, reliability, and flexibility that are sure to provide a better data download experience. To take full advantage of these features, users must update to Python 3.X. Considering the changes in the data structures with the new API, the upgrade to a new version of the Python client is also mandatory. Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 -U We are excited for users to try out the new features and take advantage of the multifariously growing EGA distribution services for human biomedical omics data. If you have any questions or feedback, please email the EGA Helpdesk team. We'd love to hear from you!

  Blog new-ega-data-download-client

• A personalised medicine approach for ponatinib-resistant chronic myeloid leukaemia

  Chronic myeloid leukaemia (CML) is characterised by the presence of a fusion driver oncogene, BCR-ABL1, which is a constitutive tyrosine kinase. Tyrosine kinase inhibitors (TKIs) are the central treatment strategy for CML patients and have significantly improved survival rates, but the T315I mutation in the kinase domain of BCR-ABL1 confers resistance to all clinically approved TKIs, except ponatinib. However, compound mutations can mediate resistance even to ponatinib and remain a clinical challenge in CML therapy. Here, we investigated a ponatinib-resistant CML patient through whole genome sequencing (WGS) to identify the cause of resistance and to find alternative therapeutic targets.

  Study EGAS00001001150

• Identification_of_drug_resistance_genes_in_melanoma

  Our aim is to analyze the genome of human melanoma cell lines and short term culture from human melanoma samples in order to identify genes that confer drug resistance to clinically relevant targeted therapies. We will perform whole-exome sequencing, copy number variation analysis and methylome analysis in a collection of human melanoma cell lines and short term culture that will be then screened for drug sensitivity/resistance through a library of clinically relevant drugs and drug combinations. By the combined analysis of the genomic lesion and the drug sensitivity/resistance profile of different cell lines, we will look for genes whose mutation is associated to the sensitivity or resistance to a specific drug in different samples.

  Study EGAS00001000617

• Transcriptomic analysis of cell-of-origin CNS neuroblastoma, FOXR2 activated

  The transcription factor FOXR2 is the universal driver of childhood central nervous system neuroblastoma, FOXR2 activated (NB-FOXR2). NB-FOXR2 tumors arise exclusively in the brain hemispheres, and despite morphological similarities to other pediatric brain tumors, they are a molecularly distinct entity based on DNA methylation profiling. The cell-of-origin is unknown. Here, we profiled a cohort of rare NB-FOXR2 tumors by bulk and single-cell transcriptomics. Through systematic comparative analyses, we delineate tumor transcriptional states and candidate cell-of-origin. More broadly, we demonstrate systematic molecular profiling of childhood cancers to orient oncogenic targeting for in vivo modeling, a critical resource for the study of rare tumors and development of therapeutics.

  Study EGAS00001007247

• SEQCAP_Internation_1q_Type_2_Consortium - Agilent SureSelec

  The aim of this project is to identify rare variants in the 1q region associated with type 2 diabetes. To this end 651 case samples and 651 control samples from six populations have been pooled (pool sizes range from 27-33 individuals), and are being sequenced. The hybridization solution being used captures the exons and UTRs of genes in the 1q region.

  Dataset EGAD00001000421

• A Polygenic Score for Acute Vaso-Occlusive Pain in Pediatric Sickle Cell Disease

  Recurrent acute pain, or vaso-occlusive pain crisis (VOP), is the most common complication of sickle cell disease and correlates strongly with increased hospital visits and early mortality (PMID: 1710777). While the genetics of VOP in sickle cell patients has been studied (PMID: 29205277, 27883292, 25102390, 30079801, 22925497, 29531649, 29620434, 19468207, 20172753, 22576309, 30031848, 24136375, 27603703, 29559808), it is not fully understood.Using whole genome sequencing, we interrogated the α-thalassemia deletion -α3.7 and 133 candidate single-nucleotide polymorphisms (SNPs) across 66 genes for associations with VOP in 327 SCCRIP participants followed longitudinally over 6 years. Twenty-one SNPs in 9 loci were associated with VOP, including 3 (BCL11A, MYB, and the β-like globin gene cluster) that regulate erythrocyte fetal hemoglobin (HbF) levels and 6 (COMT, TBC1D1, KCNJ6, FAAH, NR3C1, and IL1A) that were associated previously with various pain syndromes. An unweighted PGS integrating all 21 SNPs was associated with the VOP event rate (estimate, 0.35; standard error, 0.04; P = 5.9 × 10−14) and VOP event occurrence (estimate, 0.42; standard error, 0.06; P = 4.1 × 10−13). These associations were stronger than those of any single locus. Our findings provide insights into the genetic modulation of VOP in children with SCD. More generally, we demonstrate the utility of WGS for investigating genetic contributions to the variable expression of SCD-associated morbidities.For publications, written, and/or oral presentations resulting from use of this data, please cite the following information: "The original data description for A Polygenic Score for Acute Vaso-Occlusive Pain in Pediatric Sickle Cell Disease can be found here: (Journal Citation Blood Adv. 2021 Jul 27;5(14):2839-2851) (PMID: 34283174)."

  Study phs002470

• RNA sequencing on intestinal biopsies from inflammatory bowel disease patients treated with vehicle control, MEK inhibitor, or infliximab

  By investigating an intergenic haplotype on chr21q22, independently linked to inflammatory bowel disease (IBD), ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis, we discover that the causal gene, ETS2, is a master regulator of inflammatory responses in human macrophages and delineate how the risk haplotype increases ETS2 expression. Using a database of cellular signatures, we identified drugs that could modulate this pathway. To validate the anti-inflammatory activity of one class of small molecules ex vivo, we obtained biopsies from patients with active IBD and cultured these biopsies with a selective, non-ATP competitive MEK inhibitor (PD-0325901), infliximab (positive control), or DMSO (vehicle control) for 18 hours, then performed RNA sequencing.

  Study EGAS00001007534

• Transposable Elements in FTLD-TDP and ALS-TDP

  Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease involving the rapid and progressive loss of motor neurons. While a number of inherited mutations have been identified as causing ALS, the vast majority of cases are sporadic with no family history of disease. This has led to the model that ALS may be a complex syndrome with an unknown number of causal molecular pathways. However, nearly all ALS patient tissues display aggregates of the RNA binding protein TDP-43 (TARDBP/TAR DNA-binding protein), and mutations in the gene encoding this protein are known to cause ALS. We show that one of the normal functions of TDP-43 is to bind and regulate retrotransposons, repetitive sequences in the genome that are normally silent, due in part to the function of TDP-43. Furthermore, we demonstrate that many ALS patients with TDP-43 pathology also display de-silencing of retrotransposon RNAs, consistent with a loss of normal TDP-43 function. Those ALS patients that exhibit high levels of retrotransposon expression form a distinct subset of ALS subjects that also show other correlated alterations to the transcriptome. Using unsupervised machine learning algorithms, we identified three distinct molecular subtypes from the whole genomes and transcriptomes of a large cohort of 148 ALS patient samples. The retrotransposon re-activated subset formed 20% of ALS samples; two additional groups displayed signatures of oxidative stress (61%), and glial dysfunction (19%), respectively. Together these results demonstrate that retrotransposon re-activation is common in a subset of ALS patients with TDP-43 pathology.

  Study phs001889

• CSER: Evaluating Utility and Improving Implementation of Genomic Sequencing for Pediatric Cancer Patients in the Diverse Population and Healthcare Settings of Texas: The KidsCanSeq Study

  Through this Clinical Sequencing Evidence-Generating Research (CSER) with Enhanced Diversity project we are completing a clinical study (The Texas KidsCanSeq Study) comparing the results of targeted cancer panel sequencing versus genome-scale testing in pediatric cancer patients across diverse clinical settings. We will compare the targeted pediatric cancer panel to germline whole exome sequencing (WES) of unselected childhood cancer patients. We will also compare an RNA/DNA targeted pediatric cancer panel versus WES, transcriptome sequencing and copy number array of FFPE tumor samples for the subset of patients with high-risk tumors. Exome sequencing is performed from a blood or saliva sample of the pediatric age (0-18) patient. We are building on our success completing the CSER program BASIC3 exome sequencing trial (which included 60% Hispanic and African-American patients from a single large academic center) in this large multi-institutional study of an even more diverse patient population from six pediatric oncology healthcare settings across Texas. Data from the Texas KidsCanSeq study will be submitted through the CSER Data Coordinating Center for access in NIH-supported databases.

  Study phs002378