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• Transcriptome of (peripheral blood), from donor Sample A, replicate 1 FACS processing technical replicates

  FACS processing technical replicates

  Dataset EGAD00001010086

• Phase 1/2 Study of the Indoleamine 2,3-Dioxygenase 1 Inhibitor Linrodostat Mesylate Combined With Nivolumab or Nivolumab and Ipilimumab in Advanced Solid Tumors or Hematologic Malignancies

  Purpose: To evaluate the safety, efficacy, pharmacokinetics, pharmacodynamics, and biomarker data of linrodostat mesylate, a selective, oral indoleamine 2,3-dioxygenase 1 (IDO1) inhibitor, combined with nivolumab ± ipilimumab in advanced solid tumors and hematologic malignancies. Patients and Methods: In this phase 1/2 study, patients received once-daily (QD) linrodostat (part 1 [escalation], 25-400 mg; part 2 [expansion], 100 or 200 mg) plus nivolumab (480 mg every [Q] 4 weeks [W] or 240 mg Q2W) or triplet therapy (part 3, linrodostat 20-100 mg QD; nivolumab 360 mg Q3W or 480 mg Q4W; ipilimumab 1 mg/kg Q6W or Q8W). Endpoints included safety and efficacy (co-primary; parts 2, 3), pharmacokinetics, pharmacodynamics, biomarkers, and efficacy (part 1). Results: Fifty-five, 494, and 41 patients were enrolled in parts 1, 2, and 3, respectively. Linrodostat exposures exceeded predicted therapeutic target concentrations starting at 50 mg. Rates of grade 3/4 adverse events were 50.1%-63.4%. The maximum tolerated linrodostat dose was 200 mg; dose-limiting toxicities were primarily immune related. Responses were observed across different cohorts, study parts, and tumor types, particularly in immunotherapy-naive patients. Kynurenine decreased with linrodostat + nivolumab, regardless of response. In contrast, interferon gamma (IFN-γ) gene expression signature was associated with response; in nonmelanoma patients, a composite of low tryptophan 2,3-dioxygenase (TDO2) gene expression plus high IFN-γ signature was associated with response. Conclusions: Linrodostat + nivolumab ± ipilimumab demonstrated a manageable safety profile. Kynurenine changes supported IDO1 pathway inhibition but did not correlate with response. A composite biomarker of low TDO2 expression plus high IFN-γ gene expression may predict response to linrodostat + nivolumab.

  Study EGAS50000000710

• Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)

  Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis.

  Study phs004002

• Exome Sequencing of Chordoma Cases

  Chordoma is a rare tumor that is believed to develop from notochord remnants. We previously identified germline duplication of the TBXT gene as a major susceptibility mechanism in several chordoma families. Currently, we are using whole exome sequencing to identify additional susceptibility genes in chordoma families without TBXT duplication as well as in sporadic cases.

  Study phs001280

• The Genetic Landscape of Mutations in Burkitt Lymphoma

  Burkitt lymphoma (BL) is characterized by deregulation of MYC, but the contribution of other genetic mutations to the disease is largely unknown. We sequenced exomes of 59 BL tumors, 14 of which had paired normal tissue. Our work elucidates commonly occurring gene-coding mutations in Burkitt lymphoma and implicates ID3 as a novel tumor suppressor gene.

  Study phs000562

• Exome Sequencing of Pleuropulmonary Blastoma

  Pleuropulmonary blastoma (PPB) is a rare, aggressive pediatric cancer arising from the lung or pleural cavity. In this study, we sequenced and analyzed the exomes of 15 PPB matched tumor and normal pairs. This study is part of a larger effort to characterize pediatric cancers as part of the Slim Initiative for Genomic Medicine (SIGMA) project.

  Study phs000543

• Single cell transcriptomic profiles of advanced melanoma patients treated with checkpoint inhibitor immunotherapy

  Little is known about the resistant clones within the tumour ecosystem treated with immunotherapy. This work provides a comprehensive and integrative analysis of each individual non-responding melanoma patients, including clinical features integrated with single cell analysis, which is critical to understand features of resistance in order to improve cancer patients’ outcomes.

  Study EGAS50000000339

• CAGEKID: Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001000083

• CAGEKID: Cancer Genomics of the Kidney - Targeted Sequencing

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001007004

• Ribosome_Profiling_of_Macrophages_during_Salmonella_Infection

  The aim of this study is to assess translational changes in macrophages over a time course of Salmonella infection. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001285