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• Whole Exome Sequencing of Diffuse Large B-Cell Lymphoma

  We performed massively parallel whole exome sequencing of 55 primary tumor samples from patients with diffuse large B cell lymphoma (DLBCL) and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, as well as in genes for which a functional role in DLBCL has not been previously suspected. Significantly mutated genes include MYD88, CARD11, EZH2, CREBBP, as well as MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO and TNFRSF14. Analysis of somatic mutations in patients with DLBCL also revealed that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, likely caused by activation-induced cytidine deaminase (AID)-mediated somatic hypermutation, and those non-synonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. We further identified genes with mutations that are likely to be functionally relevant despite being mutated at a low rate. These genes include KRAS, BRAF and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients.In order to facilitate additional in vitro and in vivo analyses of the discrete molecular clusters and associated targeted therapies in preclinical models, we also performed our subtyping analysis on 28 Diffuse Large B-Cell Lymphoma (DLBCL) cell lines. We performed whole exome sequencing (WES) on these cell lines to capture structural variants (SVs), from which we obtained full genetic characterization and segregation of these cell lines into our previously defined molecular clusters by DLBclass assignment. These analyses are available in an interactive DLBclass portal available to the public. Our data provide an unbiased view of the landscape of mutations in DLBCL. These data may point towards new targets for the treatment of DLBCL.

  Study phs000450

• RaScALL: Rapid (Ra) screening (Sc) of RNA-seq data for prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL)

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accelerated risk-stratification and therapeutic triage.

  Dataset EGAD00001009087

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. The repository includes the raw mass spectrometry-based proteomics data

  Study EGAS00001006712

• Low T cell diversity is associated with poor outcome in bladder cancer - Total RNAseq data

  T cells are crucial effector cells in the endogenous defense against cancer, yet the clinical impact of their quantity, diversity, and dynamics remains underexplored. In this study we performed total RNAseq on blood samples from 8 patients with muscle invasive bladder cancer. The goal was to compare blood T cell subtype composition between patients with low and high TCR diversity.

  Study EGAS50000000939

• NeoPAL study - RNAseq and Targeted DNA sequencing data

  This dataset is composed of 159 RNAseq data (fastq, bam and count tables) and 35 targeted DNAseq data (fastq).

  Dataset EGAD50000001490

• FFPE CRC WGS Data

  The data consists of 3 BAM files. Two of three BAMs are tumour FFPE samples (1 repaired-FFPE; 1 unrepaired-FFPE); The other BAM file is sequenced from normal colon tissue

  Dataset EGAD00001007716

• Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)

  STARNET is a genetics of RNA expression study of multiple disease-relevant tissues obtained from living patients with cardiovascular disease. Tissue samples are obtained from blood, atherosclerotic-lesion-free internal mammary artery (MAM) and atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV) during open thorax surgery of 600 coronary artery disease (CAD) patients. All patients gave written informed consent. The inclusion criterion was eligibility for coronary artery by-pass graft (CABG) surgery. Patients with other severe systemic diseases, such as active systemic inflammatory disease or cancer, were excluded. The primary clinical end points were the SYNTAX score based on the extent of coronary atherosclerosis assessed from preoperative angiograms. The STARNET patients are Caucasians (31% females); 32% had diabetes, 75% had hypertension, and 67% had hyperlipidemia; and 33% had an MI before age 60. By New York Heart Association criteria, 45% were class I, 42% class II, 9% class III, and 1% class IV. TYPES AND RNA SEQUENCING: 566 DNA genotype and 3577 RNA-seq profiles from seven tissues from 600 STARNET CABG patients passed quality control (on average 511 RNA-seq profiles/tissue). DNA was genotyped with the OmniExpress Exome array (Illumina, ~900k SNPs) and imputed to a total of 14,098,063 DNA variant calls (6,245,505 with minor allele frequency >5%). The STARNET subjects mainly overlap with Caucasian of Northern European (Finnish) descent. RNA sequencing was performed using the HighSeq2000 platform, poly-A (LIV, SKLM, VAF, SF and blood) and ribo-zero (AOR, MAM) protocols with 50-100 bp read lengths, single end to 15-30 million read depth.

  Study phs001203

• Long-term temporal stability of peripheral blood DNA methylation alterations in patients with inflammatory bowel disease.

  Introduction There is great current interest in the potential application of DNA methylation alterations in peripheral blood as biomarkers of susceptibility, progression, and treatment response in inflammatory bowel disease (IBD). To date, the intra-individual stability of peripheral blood leukocyte (PBL) methylation in IBD patients, a key consideration in biomarker development, has not been characterised. Here, we studied the long-term stability of all probes located on the Illumina HumanMethylation EPIC BeadChip array. Methods We followed a cohort of 46 adult IBD patients (36 Crohn’s disease (CD), 10 ulcerative colitis (UC), median age 44 (IQR: 27-56), 50% female) that received standard care without any intervention at the Amsterdam UMC. Paired PBL samples were collected at two time points with a median 7 (range: 2-9) years in between. Differential methylation and intra-class correlation (ICC) analyses were used to identify time-associated differences and temporally stable CpGs, respectively. Results Around 60% of all CpG loci on the EPIC array presented poor (ICC <0.50); 119,388 (≈14%) and 41,274 (≈5%) showed good (ICC ≥0.75) or excellent (ICC ≥0.90) intra-individual stability. Functional over-representation analyses of the stable methylated CpGs implicated genes involved in cell-cell signaling, adhesion and neurogenesis. Focusing on previously identified consistently differentially methylated positions indicated that 22 CD-, 11 UC-, and 24 IBD-associated loci demonstrated good stability (ICC ≥0.75) over time, where we observed a marked stability of CpG loci associated to the HLA genes. Conclusion Our data provide insight into the long-term stability of the PBL DNA methylome within an IBD context, facilitating the selection of biologically relevant and robust IBD-associated epigenetic biomarkers with increased potential for independent validation.

  Study EGAS00001006501

• Whole Exome and Transcriptome Sequencing in Sporadic ALS

  Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease, is a fatal and devastating neurodegenerative disorder that causes the progressive death of upper and lower motor neurons. Although many efforts have been done to elucidate molecular factors involved in the onset and progression of the disorder, the causes of ALS are yet unknown and undefined. Transcriptome studies, based mostly on microarrays, have revealed multiple perturbations of the motor neuron function, supporting the current idea that several cellular events contribute to the pathobiology of the disease, including mitochondrial dysfunction, enhanced apoptosis, glutamate-mediated excitotoxicity, free radical injury, protein misfolding, abnormal calcium metabolism and altered axonal transport. In the present study, we have deeply sequenced the whole transcriptome of ventral horns of the human lumbar spinal cord from matched control and ALS post-mortem donors. Whole exome sequencing from the same donors has also been performed to exclude known genetic variants associated to the familiar form of ALS. In addition, to characterize the ALS transcriptome we have sequenced the RNA fraction at low molecular weight in the same tissues and individuals. Genomic and transcriptomic reads have been generated using the Illumina HiSeq2000 sequencer.

  Study phs000747

• Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Despite druggable events in 80% of neuroblastoma patients within the Princess Máxima Center precision medicine program 'iTHER', clinical uptake of treatment recommendations has been low, and the clinical impact for individual patients remains hard to predict. This stresses the need for a method integrating genomics and transcriptomics with functional approaches into therapeutic decision making. We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake. Cell lines, NBL-PDOs and their parental tumors were characterized utilizing (lc)WGS, WES and RNAseq. Cells were exposed to a ~200 compound library, and viability was assessed using CellTiterGlo or MTT. Molecular and HTS results were transferred to the R2 platform (http://r2platform.com/pmc_nb_drugs/), in which a comprehensive suite of visualizations and analysis options were implemented. As a result, a powerful reference set of cell lines is available, reflecting distinct known pharmacologic vulnerabilities, including resistance of TP53-inactivated lines to MDM2 inhibitor idasanutlin; ALK-inhibitor sensitivity in ALK-activated lines, and sensitivity of an ATM-deleted cell line to PARP- and CHEK1-inhibitors. Novel established NBL-PDOs retained molecular features of their parental tumor and again reflected established drug sensitivities. However, HTS also identified additional therapeutic vulnerabilities in vitro, such as a striking correlation between a positive mesenchymal signature and sensitivity to BCL2-inhibitor venetoclax. Finally, we explored personalized drug sensitivities within iTHER, demonstrating HTS can support genomic and transcriptomic results, thereby strengthening the rationale for clinical uptake. Furthermore, in vitro insensitivity may avoid ineffective treatments. Lastly, novel treatment options may be identified, as indicated by sensitivity to ponatinib correlating with overexpression of RET or KIT. In conclusion, we established a dynamic publicly available dataset with detailed genomic, transcriptomic, and pharmacological annotation of classical neuroblastoma cell lines as well as NBL-PDOs, representing the heterogeneous landscape of neuroblastoma. We anticipate that in vitro drug screening will be complementary to genomic-guided precision medicine by supporting clinical decision making, thereby improving prognosis for all neuroblastoma patients in the future.

  Study EGAS00001007160