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• GWAS results from Danjou et al, Nature Genetics 2015

  GWAS results in epacts format for Danjou et al, Nature Genetics 2015

  Dataset EGAD00010001722

• Batch1-2_Genotypes_PostQC

  Combined genotypes for Batch 1 and 2 after quality control. All individuals included in analyses.

  Dataset EGAD00010002127

• LOGGIC Core BioClinical Data Bank: Added clinical value of RNA-Seq in an international molecular diagnostic registry for pediatric low-grade glioma patients

  Study EGAS00001007072

• 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

• CNS and systemic relapse in DLBCL

  Microarray data for 230 DLBCL patients

  Dataset EGAD00010001909

• Germline snv g.vcf for EGAS00001004572

  Bulk Germline snv vcfs from haplotypecaller analysis in EGAS00001004572

  Dataset EGAD00001006910

• Single cell sequencing in D425

  Single cell sequencing aligned BAM files for the D425 cell line

  Dataset EGAD50000002304

• Profiling RNA Translation in Pediatric Medulloblastoma

  This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

  Study phs003446

• Sequencing to Guide Cancer Care (CanSeq)

  The overall goal of the CanSeq U01 project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project 1 are to implement and establish the feasibility of germline and somatic WES in patients with advanced solid tumors (lung and colon); to develop a framework for interpreting and reporting for exome sequencing data; to determine the proportion of patients with "actionable items" compared to existing technologies; and to report on the percentage of patients in whom unique WES findings led to a clinical action. The aims of Project 2 are to implement a production-scale platform for WES from archival (FFPE) material; to identify biologically relevant somatic and germline alterations existing in tumor/normal DNA from individual patients; to produce an evidence-based list of clinically "actionable" genetic alterations; and to develop inferential models that predict the utility of tumor genomic data within the larger clinical context. The goals of Project 3 are to describe the impact of information derived through WES on cancer patients; to test the hypothesis that patients will want to receive information about all potentially informative somatic and germline variants; to study patients' understanding of disclosed genomic information; and to describe the experiences of oncology providers as they implement WES into cancer care delivery.

  Study phs001075

• miR-200-regulated CXCL12β promotes fibroblast heterogeneity and immunosuppression in ovarian cancers

  High-grade serous epithelial ovarian cancer (HGSOC) has been recently subdivided into molecular subgroups, including the mesenchymal HGSOC associated with partial tumor-debulking surgery and poor patient survival. Consistent with stromal-related genes signatures defining mesenchymal HGSOC, we show here that stroma plays a key function in this HGSOC molecular subtype. We first highlight stromal heterogeneity in HGSOC by identifying 4 subsets of Carcinoma-Associated Fibroblast (CAF-S1-4). Mesenchymal HGSOC significantly accumulate the activated CAF-S1 subset, which exhibits immunosuppressive functions by promoting attraction, survival and activation of regulatory T-lymphocytes. The CXCL12β chemokine reliably characterizes mesenchymal HGSOC and specifically accumulates in the CAF-S1 subset through a regulation mediated by the miR-141/200a. CXCL12β promotes attraction of T-lymphocytes and is thus a key actor in CAF-S1-mediated immunosuppressive functions. In conclusion, we highlight here for the first time stromal heterogeneity and immunosuppression in mesenchymal HGSOC that could participate in the poor patient prognosis.

  Study EGAS00001002184