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• Patient 16CH

  One file of patient 16 with WGS done on Illumina HiSeq X-Ten. For research purpose and authorised user only.

  Dataset EGAD00001003440

• FFPE Normal Panel V3 Cancer Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Dataset EGAD00001001122

• Genome Sequencing of Circulating Tumor Cells for Minimally Invasive Molecular Characterization of Multiple Myeloma Pathology

  ​​Multiple Myeloma (MM) develops from well-defined precursor stages known as Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering MM (SMM); however, invasive bone marrow (BM) biopsy limits screening and monitoring strategies for patients. In this study, we enumerated circulating tumor cells (CTCs) from patients with precursor and overt diseases, and developed a novel approach, MinimuMM-seq, which enables detection of translocations and copy number abnormalities through whole-genome sequencing of highly pure CTCs. In a cohort of 51 patients, 24 with paired BM, we applied our method MinimuMM-seq and detected 100% of clinically reported BM biopsy events. The next-generation sequencing (NGS) assay could replace molecular cytogenetics by Fluorescence In Situ Hybridization (FISH) for diagnostic yield and risk classification. In 8 patients we could apply MinimuMM-seq on serially collected samples to track and monitor major clones in peripheral blood. We describe clonal evolution and shifting dynamics of subclones over time, as well as in between blood and marrow compartments. All whole-genome sequencing (WGS) data generated in this study will be made accessible through dbGaP.

  Study phs003084

• M116 Proteome Extracellular Vesicle Profiling

  For extracellular vesicles (ECV) extraction from plasma, 1M ammonium acetate was added to precipitate ECVs on ice for 45 min. Then, 100 mM ammonium acetate was added to the mixture, and ECVs were precipitated by centrifugation at 20,000g for 30 min. ECVs were washed with 50 mM ammonium bicarbonate (Sigma-Aldrich, Cat. 1066-33-7). Then, 600 µl of 1% ammonium deoxycholate (Sigma Aldrich, Cat. K2755-1MG) were added. The concentration of protein in each sample was measured using a bicinchoninic acid assay (BCA assay). Ammonium bicarbonate was used to dilute 500 µg of protein into a final volume of 500 µl. Next, dithiothreitol (Sigma-Aldrich, Cat. D9779) was added to obtain a final concentration of 20 mM, followed by iodoacetamide (Sigma-Aldrich, Cat. I6125) to a final concentration of 40 mM. Next, trypsin (Roche, Cat. RTRYP-RO) was added to the sample in a 1:25 protein ratio and incubated at 37°C overnight. Next day, formic acid (ThermoFisher Scientific, Cat. 28905) in a final concentration of 0.1% was added and extraction of proteins was done using Empore™ Solid Phase Extraction Cartridges (3M), following manufacturer’s instructions. The eluted samples were then centrifuged for 90 min. using a speed vacuum centrifuge (Thermo, RC1010), followed by snap freezing in liquid nitrogen. Then, the samples were kept in a freeze dryer (LyoDry Compact Benchtop, MechaTech) overnight. Next, the samples were reconstituted in 30 µl of 0.1% formic acid (FA) and an o-Phthaladehyde (Oparil) assay was performed to determine the concentration of each sample. After that, the sample was prepared in a concentration of 0.5 µg/µl using 0.1% FA and alcohol dehydrogenase (ADH). The samples were prepared in glass mass spectrometry vials for proteomic analysis using a Waters Synapt G2Si High-Definition Mass Spectrometry (Waters Corporation) operated by the MassLynx 4.1., 110 min. running time with 2 µl of an injection containing 1 µg of peptide. Quality controls were also run along with samples to guarantee consistency. Pooled quality controls were made from all samples, in which the samples were run at the beginning, middle and end of the mass spectrometry run. Samples were randomized before running the experiment. The proteomic data was then imported into Progenesis software 4.2 (Nonlinear Dynamic, UK) to identify and quantify peptides and proteins.

  Dataset EGAD50000001679

• Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

  The extensive primary and secondary drug resistance in many cancer types requires rational approaches to design personalized and selective combinatorial therapies that do not only show synergistic effect in overall cancer cell killing but also result in minimal toxic side effects on non-malignant cells. To address the combinatorial explosion in the number of relevant combinations, we implemented a machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA-sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory AML patient cases, each with a different genetic background, our integrated approach accurately predicted patient-specific combinations that were shown to result not only in synergistic cancer cell co-inhibition but were also capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our data-driven approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of non-malignant cells, and highlight the relevance of considering cell heterogeneity for personalized cancer therapy.

  Study EGAS00001004614

• Evaluation of the Efficacy and Safety of a Clinical Grade Human Induced Pluripotent Stem Cell-Derived Cardiomyocyte Patch: A Pre-Clinical Study

  Cardiomyocyte-derived induced pluripotent stem cells (iPSCs) may represent a promising therapeutic strategy for severely damaged myocardium. This study aimed to assess the efficacy and safety of clinical grade human iPSC-derived cardiomyocyte (hiPSC-CM) patches and conduct a pre-clinical proof-of-concept analysis.

  Study EGAS50000000188

• Genomic Sequencing of Solitary Fibrous Tumors

  Solitary fibrous tumors (SFTs) are rare mesenchymal tumors that can be benign or malignant. In this study, we sequenced and analyzed the exomes of 17 SFT matched tumor and normal pairs. This study appertains to a large endeavor to characterize cancers as part of the Slim Initiative for Genomic Medicine in the Americas (SIGMA) project.

  Study phs000568

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  This study evaluates integrated genomic models of response to immune checkpoint blockade for lung cancer patients. A computationally adjusted tumor mutation burden was combined with HLA class I genetic variation, mutational smoking signature and activating mutations in receptor tyrosine kinase genes to generate a prognostic classifier that outperforms tumor mutation burden.

  Study phs001940

• Genome Wide Association Studies in ECOG 2997 Trial

  The ECOG 2997 trial was a randomized controlled trial for patients with previously untreated CLL comparing fludarabine monotherapy to the combination of fludarabine and cyclophosphamide. The initial clinical findings of this study were published in the Journal of Clinical Oncology in 2007 (JCO 25:793-8). Additional laboratory studies have also published (JCO 25:799-804).

  Study phs000621

• Spatiotemporal Analysis of the Human Cerebellum

  We sought to characterize neural progenitors within spatially demarcated regions of the human cerebellum at a molecular level during neurogenesis. We used laser-capture microdissection to enrich for cells within the ventricular zone and subventricular zone regions of the rhombic lip, external granule cell layer and Purkinje cell layer, then performed RNA-sequencing on the enriched samples.

  Study phs001908