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• Comparative transcriptome of CD34+ hematopoietic progenitors from myeloproliferative patients and control donors

  BCR-ABL-negative MPNs are related to mutations activating the JAK2/STAT pathway and occurring in hematopoietic stem cells (HSC). The most prevalent mutation is JAK2V617F. Calreticulin (CALR) and activating MPLW515 mutations are also observed in ET and PMF. Additional non-MPN mutations may be found, particularly in PMF, and can change disease phenotype or accelerate progression to myelofibrosis or leukemia. In this study, we wanted to compare the transcriptome of CD34+ progenitors from JAK2V617F postive MPN patients to the CD34+ progenitors from control donors. The patients were selected for their high JAK2V617F variant allele frequency (from 60 to 100% VAF). Peripheral blood from patients was collected in EDTA tubes. Hematopoietic progenitors (CD34+) were isolated from mononuclear cells (MNCs) by immunomagnetic enrichment (Miltenyi, Biotech) and were amplified for 5 days in serum-free medium in the presence of a cocktail of human recombinant cytokines containing EPO (1 U/mL) (Amgen Thousand Oaks, CA), TPO (20 ng/mL) (Kirin, Japan), SCF (25 ng/mL) (Biovitrum AB, Sweden), IL-3 (10 ng/mL), FLT3-L (10 ng/mL), G-CSF (20 ng/mL) and IL-6 (100 U/mL) (MiltenyiBiotec).

  Study EGAS00001005106

• PCGP Ph-like ALL

  Background: BCR-ABL1-like, or Ph-like acute lymphoblastic leukemia is characterized by a gene expression profile similar to BCR-ABL1 positive ALL, genetic alterations of lymphoid transcription factor genes, and poor outcome. Sequencing of small numbers of Ph-like ALL cases has identified genetic alterations activating kinase signaling suggesting Ph-like ALL may be amenable to treatment with tyrosine kinase inhibitors. However, the spectrum of genetic alterations in childhood and adult Ph-like ALL is incompletely understood. Methods: We performed genomic profiling of 1736 B-ALL cases and next-generation sequencing for 160 Ph-like cases. We examined the functional effects of chimeric fusion proteins in mouse cell lines. Results: The frequency of Ph-like ALL rose from 11% in children to 26% in young adults, and was associated with very poor outcome. Kinase-activating alterations were identified in 90% of Ph-like cases, most commonly fusions involving 10 kinase or cytokine receptor genes (ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B and TYK2), and mutations involving FLT3, IL7R and SH2B3. Expression of ABL1, ABL2, CSF1R and JAK2 fusions resulted in cytokine-independent proliferation of cell lines and activation of pSTAT5. Cells expressing ABL1, ABL2, CSF1R and PDGFRB fusions were sensitive to dasatinib, and JAK2 fusions to ruxolitinib. Conclusions: Ph-like ALL is characterized by a diverse range of genomic alterations that converge on a limited number of kinase signaling pathways amenable to inhibition with currently available tyrosine kinase inhibitors. Trials identifying Ph-like ALL and testing the efficacy of tyrosine kinase inhibitor therapy are warranted

  Study EGAS00001000654

• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

  Blog discover-cancer-image-europe

• Bayesian-Based Noninvasive Prenatal Diagnosis of Single-Gene Disorders

  In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases. (Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research)

  Study phs001659

• Detection of rare mutations, copy number variation, and DNA methylation in the same template DNA molecules

  The analysis of cell-free DNA (cfDNA) from plasma offers great promise for the earlier detection of cancer. At present, changes in DNA sequence, methylation, or copy number are the most sensitive ways to detect the presence of cancer. To further increase the sensitivity of such assays with limited amounts of sample, it would be useful to be able to evaluate the same template molecules for all these changes. Here we report an approach, called MethylSaferSeqS, that achieves this goal, and can be applied to any standard library preparation method suitable for massively parallel sequencing. The innovative step was to copy both strands of each DNA-barcoded molecule with a primer that allows the subsequent separation of the original strands (retaining their 5-methylcytosine residues) from the copied strands (in which the 5-methylcytosine residues are replaced with unmodified cytosine residues). The epigenetic and genetic alterations present in the DNA molecules can then be obtained from the original and copied strands, respectively. We applied this approach to plasma from 265 individuals, including 198 with cancers of the pancreas, ovary, lung and colon, and found the expected patterns of mutations, copy number alterations, and methylation. Furthermore, we could determine which original template DNA molecules were methylated and/or mutated. MethylSaferSeqS should be useful for addressing a variety of questions relating genetics and epigenetics in the future.

  Study EGAS00001006839

• PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

  Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

  Study phs000963

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

  This dataset includes raw label-free mass spectrometry proteomics data of different sinonasal tumor entities as well as normal sinonasal tissue. 72 samples were processed on a Q Exactive HF-X instrument coupled to an easy nanoLC 1200 system using one microgram of peptides and an 110 minutes gradient.

  Dataset EGAD00010002381

• Aligned Low pass whole genbome sequencing of cell free and tumour DNA from 5 patients with high grade serous ovarian cancer. Samples have been aligned to hg19 and bam files uploaded

  This is the aligned bam files of 5 patients, with sequential sampltes from patients comprising cfDNA and FFPE extracted tumour DNA

  Dataset EGAD50000001632

• A mathematical model of cell-free DNA fragment size reveals cancer-specific fragmentomic patterns

  This study aim to test a mathematical model of cfDNA length distribution across multiple biodiy flulids. It try to investigate biological mechanisms of cfDNA fragmentation and release.

  Study EGAS50000001560

• FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls.

  FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls. The POP study placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater (ThermoFisher). For each biopsy, total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. RNA-libraries were prepared from 1g of total placental RNA with the TruSeq Stranded mRNA Library Prep Kit (Illumina) which captures polyA-tailed transcripts by oligo-dT beads, then pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and Illumina HiSeq2500

  Dataset EGAD00001006304