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• Transcriptional mechanisms of resistance to anti-PD-1 therapy

  Purpose: To explore factors associated with response and resistance to anti-PD-1 therapy, we analyzed multiple disease sites at autopsy in a patient with widely metastatic melanoma who had a heterogeneous response.Materials and Methods: Twenty-six melanoma specimens (four pre-mortem, 22 post-mortem) were subjected to whole-exome sequencing. Candidate immunologic markers and gene expression were assessed in ten cutaneous metastases showing response or progression during therapy.Results: The melanoma was driven by biallelic inactivation of NF1. All lesions had highly concordant mutational profiles and copy number alterations, indicating linear clonal evolution. Expression of candidate immunologic markers was similar in responding and progressing lesions. However, progressing cutaneous metastases were associated with over-expression of genes associated with extracellular matrix and neutrophil function.Conclusions: Although mutational and immunologic differences have been proposed as the primary determinants of heterogeneous response/resistance to targeted therapies and immunotherapies, respectively, differential lesional gene expression profiles may also dictate anti-PD-1 outcomes.

  Study EGAS00001002195

• Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements

  Sparse profiling of CpG methylation in blood by microarrays have identified epigenetic links to common diseases. We apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (Ntotal ~400), providing high-resolution methylation profiling (>1.3M CpGs) at regulatory elements. We link methylation to cardiometabolic risk through associations to circulating plasma lipid levels and identify lipid-associated CpGs with unique localization patterns in regulatory elements. We show distinct features of tissue-specific versus tissue-independent lipid-linked regulatory regions by contrasting with parallel assessments in ~800 independent adipose tissue and blood samples from the general population. We follow-up on adipose-specific regulatory regions under (1) genetic and (2) epigenetic (environmental) regulation via integrational studies. Overall, the comprehensive sequencing of regulatory element methylomes reveals a rich landscape of functional variants linked genetically as well as epigenetically to plasma lipid traits.

  Study EGAS00001003415

• WGS data for HGSC patient derived organoids and matching tumor and normal samples (Wennerberg)

  Sequencing data of 10 high-grade serous carcinoma (HGSC) patients (58 samples including blood derived normal samples as germline controls, fresh frozen tissue samples as tissue controls and organoids) sequenced with HiSeq X Ten / BGISEQ-500 / MGISEQ-2000.

  Dataset EGAD00001010019

• Fecal WMS UC sequencing data

  Fecal WMS data from NCT02749630 ulcerative colitis patients. Stool samples were collected at screening as well as on day 64 and prepared for whole metagenomic sequencing.

  Dataset EGAD00001008817

• Human lung cell atlas 10x and SS2 sequencing data (3 of 3)

  Contains FASTQs for cells from 20 10x channels across 2 NovaSeq runs, 42 384-well plates across 6 NovaSeq runs, and 12 96-well plates across 4 NextSeq runs.

  Dataset EGAD00001006128

• Human lung cell atlas 10x and SS2 sequencing data (2 of 3)

  Contains FASTQs for cells from 20 10x channels across 2 NovaSeq runs, 42 384-well plates across 6 NovaSeq runs, and 12 96-well plates across 4 NextSeq runs.

  Dataset EGAD00001006127

• Human lung cell atlas 10x and SS2 sequencing data (1 of 3)

  Contains FASTQs for cells from 20 10x channels across 2 NovaSeq runs, 42 384-well plates across 6 NovaSeq runs, and 12 96-well plates across 4 NextSeq runs.

  Dataset EGAD00001006126

• Sequencing data for oesophageal and related samples - Normals release 4 (RNA)

  Dataset EGAD00001004022

• BIG MS Pilot

  Testing logistics and infrastructure of molecular screening program. Core biopsies taken from invasive recurrent or metastatic breast cancer to evaluate and identify molecular traits rendering them suitable for clinical trials

  Dataset EGAD00001000870

• RNA Fusion Panel

  RNA extracted from FFPE tumour samples 368, 455, 503, and 521, sequenced using the TruSight RNA Fusion Panel

  Dataset EGAD50000000272

• ParityImmune

  Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC)

  Dataset EGAD00010001412

• RNA-Seq Medulloblastoma data

  RNA-Seq data from 12 medulloblastoma samples, all group 4 medulloblastomas. The data consists of BAM files aligned using STAR

  Dataset EGAD00001010850

• Single cell RNA-Seq of Clear Cell Sarcoma of the Kidney

  Dataset EGAD00001007498

• Myeloma XI trial data

  The dataset contains WGS and RNA-seq from Myeloma XI trial

  Dataset EGAD00001005491

• Tumor-derived exosomes modulate PD-L1 expression in monocytes

  Small RNA expression profiles of the blood plasma-derived exosomes from B-cell chronic lymphocytic leukemia patients

  Dataset EGAD00001003230

• GLASS-NL whole exome sequencing (WES) normal samples

  Whole exome sequencing (WES) data from 45 normal samples of 45 patients in the GLASS-NL trial.

  Dataset EGAD50000000582

• Paired-end RNA-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 46 paired-end RNA-seq samples from 3 patients.

  Dataset EGAD00001010290

• RNA-seq data of 196 nontumorous human breast tissue

  Transcriptome analysis of nontumorous human breast tissues. 196 cases were included in the dataset.

  Dataset EGAD00001006397

• 125 cfDNA samples from healthy patients

  BAM files corresponding to the sequencing of 125 circulating cell-free DNA from 125 healthy patients. Each sample was sequenced twice.

  Dataset EGAD00001005463

• 64 RNAseq BAMs in the HF-GBM-Tumor-Neurosphere-Xenograft study

  Whole transcriptome sequencing generated from patient, neurosphere and xenograft samples

  Dataset EGAD00001002214

• Whole genome MeDIP-seq of DNA in whole blood samples from 5yr old Swedish children (the ABIS study)

  Dataset EGAD00001001221

• WES of HCC

  WES of HCC by HiSeq 2000,total 71 samples including Hepatocellular carcinoma cell lines and nornal sample(Peripheral Blood or the adjacent tissues of cancer)

  Dataset EGAD00001001249

• Neoantigen responses to Immunotherapy in Prostate Cancer

  To determine whether antigen-specific T cell responses can be elicited following treatment with ICT in cancers that have a low TMB, a clinical trial with ipilimumab (anti-CTLA-4) was conducted in 30 patients with metastatic castration-resistant prostate cancer (CRPC). We identified 2 distinct groups of patients divided by clinical outcomes, which consisted of a cohort with Favorable and Unfavorable outcomes. Compared to the Unfavorable cohort, the patients in the Favorable cohort were more likely to have higher intratumoral CD8 T cell density and/or IFN-γ response gene signature, including five patients who had antigen-specific T cell responses that were only detectable after ipilimumab therapy. Three patients had T cell responses against tumor-associated antigens (PSMA and PAP). Importantly, two patients with a relatively low TMB had T cell responses against unique neoantigens. Collectively, our data indicate that a subset of patients with metastatic prostate cancer benefit from ICTs, particularly those who have immunological biomarkers associated with effector T cell responses. Publication: Sumit K. Subudhi, Luis Vence, Hao Zhao, Jorge Blando, Shalini S. Yadav, Qing Xiong, Alexandre Reuben, Ana Aparicio, Paul G. Corn, Brian F. Chapin, Louis L. Pisters, Patricia Troncoso, Rebecca Slack Tidwell, Peter Thall, Chang-Jiun Wu, Jianhua Zhang, Christopher L. Logothetis, Andrew Futreal, James P. Allison and Padmanee Sharma, 2020, Neoantigen responses, immune correlates, and favorable outcomes after ipilimumab treatment of patients with prostate cancer. Science Translational Medicine, 01 Apr 2020:Vol. 12, Issue 537, eaaz3577DOI: 10.1126/scitranslmed.aaz3577. https://pubmed.ncbi.nlm.nih.gov/32238575/

  Study EGAS00001004050

• B-lineage cells in coeliac disease Data Access Committee

  The DAC will be made up of: Ida Lindeman ida.lindeman@medisin.uio.no (admin) Ludvig M. Sollid l.m.sollid@medisin.uio.no Rasmus Iversen rasmus.iversen@medisin.uio.no

  Dac EGAC50000000162

• University of Michigan ALS Biorepository

  We are collaborators at the University of Michigan (Ann Arbor, MI) studying amyotrophic lateral sclerosis (ALS), employing sequencing-based approaches (e.g. bulk RNA-seq of whole blood) in case-control studies.

  Dac EGAC50000000598