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• Characterizing the secretome of licensed hiPSC-derived MSCs

  Although mesenchymal stromal cells (MSCs) from primary tissues have been successfully applied in the clinic, their expansion capabilities are limited and results are variable. MSCs derived from human-induced pluripotent stem cells (hiMSCs) are expected to overcome these limitations and serve as a reproducible and sustainable cell source. We have explored characteristics and therapeutic potential of hiMSCs in comparison to hBMSCs. Our data qualify hiMSCs as a promising source for cell therapy and/or cell-based therapeutic products. Additionally, the herewith generated database will add to our understanding of the mode of action of regenerative cell-based therapies and could be used to identify relevant potency markers.

  Study EGAS50000000389

• Data Access Committee for the Nichols Group at LHSC

  Dac EGAC00001002164

• MELIS-UPF - Endocrine Regulatory Genomics Lab

  DAC for accessing human data produced by the Endocrine Regulatory Genomics Lab at MELIS-UPF (Barcelona, Spain).

  Dac EGAC50000000224

• ITER-FIISC Data Access Committee (Sepsis)

  DAC for Whole-exome variant calling of individuals from the study of sepsis and acute distress respiratory syndrome in Spain.

  Dac EGAC50000000641

• CLUSTER DAC

  The DAC for CLUSTER Consortium datasets relating to JIA and healthy controls RNAseq data and their associated clinical data.

  Dac EGAC50000000426

• Single cell sequencing in D425

  Single cell sequencing aligned BAM files for the D425 cell line

  Dataset EGAD50000002304

• Oncoscan CNV FFPE SNP-arrays (Affymetrix, Thermo Fisher Scientific) for the study "Molecular profiling of EBV associated diffuse large B-cell lymphoma"

  Dataset EGAD00010002363

• ITER-FIISC Data Access Committee (WES-CIRdb)

  DAC for the data deposit of "Expanding CIRdb, a comprehensive catalog of whole-exome sequencing data of Canary Islanders".

  Dac EGAC50000000966

• Total NF1 sequence in the patients with neurofaibromatosis type1

  We analyzed whole NF1 gene region at DNA (including whole exon and intron sequences) and RNA (full length cDNA of leukocyte) level for 20 patients with neurofibromatosis type 1.

  Study JGAS000288

• Exome sequencing data, phenotypic information, and somatic mutation analysis results for 44 diagnosis-relapse DLBCL pairs

  This dataset contains exome sequencing data, phenotypic information, and somatic mutation analysis results for 44 diagnosis-relapse DLBCL pairs. Exon sequencing data were captured using the Agilent HaloPlex exon kit. bam files were obtained from illumina sequencing followed by BWA alignment.

  Dataset EGAD50000000049

• Common clonal origin of chronic myelomonocytic leukemia and B cell acute lymphoblastic leukemia in a patient with a germline CHEK2 variant

  Whole exome sequencing data obtained from sorted leukemic clones and a buccal swab as germline reference. The dataset contains raw sequencing data (paired-end reads) for 3 samples (2 leukemic, 1 buccal swab), for a total of 6 fastq files.

  Dataset EGAD00001007644

• Single-cell RNA-seq and spatial transcriptomics data of patients with sarcoidosis

  Single-cell RNA-seq and spatial transcriptomics data for 12 patients with sarcoidosis. From each patient, we analyzed skin biopsies of both lesional and non-lesional skin and we performed spatial transcriptomics for lesional skin samples. The data are provided as aligned BAM files.

  Dataset EGAD00001010020

• Determinants of Venetoclax Resistance

  The study aimed to identify genetic determinants of resistance to Venetoclax, a recently approved BCL-2 inhibitor for patients with chronic lymphocytic leukemia (CLL). Whole exome sequencing of tumor samples from 6 CLL patients relapsing on Venetoclax revealed clonal evolution when comparing pre- and post-Venetoclax samples. Genetic screens for genes involved in sensitivity to Venetoclax and investigations of resistant cell lines (including OCI-Ly1) revealed MCL-1 and regulators of cellular energy metabolism (AMPK pathway) to drive resistance to Venetoclax. Further explorations of patient samples confirmed MCL-1 expression and AMPK activation to be increased at relapse on Venetoclax.

  Study phs001875

• human CMV-specific CD8+ T cells

  In this study we established a comprehensive workflow to collect multi-omics single-cell data using a commercially available micro-well based platform. This included whole transcriptome, cell surface markers (targeted sequencing-based cell surface proteomics), T cell specificities, adaptive immune receptor repertoire (AIRR) profiles and sample multiplexing. With this technique we identified novel paired T cell receptor sequences for three prominent human CMV epitopes. In addition, we review the ability of dCODE dextramers to detect antigenspecific T cells at low frequencies by estimating sensitivities and specificities when used as reagents for single-cell multi-omics.

  Study EGAS50000000633

• Unraveling metastatic progression of breast cancer

  To reconstruct the trajectories of BC progression, we performed exome sequencing (Illumina HiSeq2000, Truseq DNA sample preparation kit v2 and Exome Enrichment Kit v2; alignement done with BWA, substitutions and indels called with GATK and DINDEL respectively) coupled to validation by Sequenom and deep re-sequencing (ongoing), as well as copy number (CN) analyses (Oncoscan, Affymetrix) on DNA from matched primary (n=1-6/pt), axillary lymph node (ALN, n=1-6 for 4 pts), local recurrence (for 1 pt) and distant metastatic (n=1-5/pt) FFPE samples obtained from an autopsy series of 10 BC pts.

  Study EGAS00001000760

• molecular profiles of serum-derived extracellular vesicles in high-grade serous ovarian cancer

  Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have response enabling interval cytoreductive surgery. Clinically useful predictive biomarkers for such distinctions are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated them with therapeutic outcomes in patients with HGSC.

  Study EGAS00001006350

• Transcriptome profiling of HNSCC treated with PD1/PDL1

  Immune checkpoint inhibitors have improved survival in several solid tumors, including head and neck squamous cell carcinoma (HNSCC). However, current use of PD-1/PD-L1 inhibitors relies on PD-L1 expression, which does not reliably predict patient response. Therefore, better predictive biomarkers are needed to identify which patients benefit from immunotherapy. Previous studies suggest that genomic and transcriptomic features may help predict treatment response. This study aims to integrate genomic, transcriptomic, and methylomic data from 31 patients with recurrent/metastatic HNSCC to identify new biomarkers of resistance to anti-PD-1/PD-L1 therapy.

  Dataset EGAD50000002506

• Integrative Analysis of Pediatric Acute Leukemia Identifies Acute Myeloid/T-Lymphoblastic Leukemia Subtype that Spans a T Lineage and Myeloid Continuum with Distinct Prognoses

  Genomic characterization of pediatric patients with acute myeloid leukemia (AML) has revealed age specific mutational spectrums, distinguishing it biologically from adult patients. While gene expression profiling signatures can differentiate subsets of pediatric AML, its clinical utility in risk stratification has remained limited.

  Study EGAS00001004701

• RNA sequencing of CD8 T cells from melanoma patients prior to and during checkpoint immunotherapy and untreated healthy controls

  We are interested in inter-individual variation in transcriptional response to immune checkpoint blockade. We have analysed poly A purified RNA expression from CD8 T cells (297 transcriptomes in total) isolated from metastatic melanoma patients (n=106) prior to and during treatment with either single agent (Pembrolizumab) or combination (Ipilimumab/ Nivolumab) immune checkpoint blockade. We compare expression at different stages of treatment and additionally contrast this with that from healthy controls (n=68).

  Dataset EGAD00001005973

• Hubrecht Organoid Technology Colon Cancer Study

  Functional screening on patient-derived organoids identifies a therapeutic bispecific antibody that triggers EGFR degradation in LGR5+ tumor cells

  Dataset EGAD00001008445

• Genomic Predictors of Response to Immune Checkpoint Therapy

  Immune checkpoint therapies, including monoclonal antibodies to programmed cell death-1 (PD-1) and cytotoxic % lymphocyte associated protein-4 (CTLA-4), yield durable clinical responses across many tumor types, including metastatic melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). However, predictors of response to these therapies in RCC are still unknown. Genomic characterization of large clinical cohorts of patients treated with anti-CTLA-4 and anti-PD-1 agents in melanoma and NSCLC have suggested that high mutational burden, high neoantigen burden, and high expression of certain genes in pre-treatment tumors may be associated with patient response to these therapies. In this study, we sought to investigate genomic predictors of response to anti-PD1 therapy in metastatic RCC in two independent clinical cohorts using whole exome and whole transcriptome sequencing.

  Study phs001493

• CIDR Estrogen Receptor Negative Breast Cancer in African American Women: DNA Methylation, Reproductive Events, and Mammary Epithelial Cell Populations

  We conducted methylation profiling of breast tumor DNA from Formalin-Fixed Paraffin-Embedded (FFPE) samples for 1,550 cases from a cohort of Black women from the Black Women’s Health Study (BWHS), the Women’s Circle of Health Study (WCHS), and from the Pathways Study using the Illumina MethylationEPIC array. We will examine differentially methylated loci (DML) between ER+ and ER- tumors, and by age at onset of breast cancer. Combining these data with previously analyzed samples (n=385), we will consider associations between reproductive risk factors and top DML by age at diagnosis and ER status, examining the complex relationships between methylation, tumor and patient characteristics, and reproductive risk factors using structural equation modeling.

  Study phs002688

• Cross-site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms of CIMAC-CIDC Network

  The Cancer Immune Monitoring and Analysis Centers (CIMACs) and the Cancer Immunologic Data Commons (CIDC)  has engaged in efforts to harmonize Whole-exome (WES) and RNA-sequencing (RNA-seq) data from three different experimental platforms (MD Anderson, NCI MoCha lab, and Broad Institute) and are using a series of developed pipelines to process the early trial samples. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the CIMACs-CIDC conducted a systematic harmonization study. DNA and RNA were centrally extracted from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) non-small cell lung carcinoma (NSCLC) tumors and distributed to three centers for WES and RNA-seq profiling

  Study phs002295

• Aberrant ERBB4-SRC Signaling as a Hallmark of Group 4 Medulloblastoma Revealed by Integrative Phosphoproteomic Profiling

  The four main medulloblastoma subgroups are characterized by distinct biology, clinicopathological features and clinical outcomes. While the WNT and SHH subgroups are characterized by clearly defined aberrant signaling of developmental pathways, the underlying biology of Group 3 and 4 remains poorly understood. Here, we delineate distinct post-translational regulation orchestrating active oncogenic signaling networks in Groups 3 and 4. Specifically, aberrant ERBB4-SRC signaling constitutes a novel hallmark feature of Group 4, with great promise as a novel oncogenic mechanism and potential vulnerability for therapeutic intervention in the most common subgroup. Altogether, this novel integrative proteogenomic landscape demonstrates the added value of proteomics and phosphoproteomics analysis to discover and exploit unexpected oncogenic mechanisms in medulloblastoma and beyond.

  Study EGAS00001002757

• Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

  Epithelial ovarian carcinoma of all subtypes has one of the worst outcomes of any human cancer. To improve our understanding of underlying biology and therapeutic possibilities in this disease, we performed whole genome sequencing, methylation, and expression analyses of a comprehensive set of 47 ovarian cancer cell lines representing different histologic tumor subtypes. Given the challenges of genomic analyses in tumors without matched normal samples, we developed novel approaches for detection of somatic alterations and used these to identify sequence, copy number, and rearrangement changes and integrated these with genome-wide epigenetic and expression alterations. Ovarian cancer cell lines had molecular changes in genes involved in cell cycle, PI3K, RAS, BRCA, chromatin regulating, and p53 pathways, and displayed global mutation and methylation changes similar to primary ovarian carcinoma. We identified alterations not previously implicated in ovarian cancer including amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and members of the TGF beta receptor pathway, including TGFBR2, SMAD3 and SMAD4, in-frame rearrangements of YAP1-MAML2 and IKZF2-ERBB4, and fusions involving MET, NF1, FBXW7 and CCND1. Integrating cell line alterations with dose-response data using three targeted therapies revealed novel molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, those with MYC amplifications to PARP inhibitor BMN673, and SMAD4 alterations to MEK inhibitor MEK162. Genome-wide analyses revealed intrachromosomal rearrangements as an improved measure of sensitivity to PARP inhibition compared to the homologous recombination defect (HRD) score. This study provides a comprehensive resource of molecular information for ovarian cancer cell line models and a pharmacogenomic platform for developing rational cancer therapeutic strategies.

  Study EGAS00001002998