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• RNA, ATAC, ChIP datasets from Ankylosing Spondylitis patients and Healthy Controls

  This dataset consists of functional genomic data from 20 Ankylosing Spondylitis patients and 35 Healthy Controls taken from CD4+ T cells, CD8+ T cells and CD14 Monocytes. It contains 364 paired end fastq files consisting of 104 total RNA-seq samples and 116 ATAC samples, for ChIP there are 46 H3K4me3 samples, 46 H3K27ac samples and 3 H3K4me1 samples, along with 49 paired input samples. The samples were sequenced on Illumina HiSeq4000, Illumina NextSeq500 and Illumina NovaSeq 6000 platforms.

  Dataset EGAD00001008758

• Dataset for neuroendocrine_adrenal_tumor-RNA

  Rare cancer sequencing data of 145 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008862

• CHILD Study Dataset

  This data set contains the CRAM files for the samples in the CHILD cohort, sequenced on the Illumina HiSeq X platform.

  Dataset EGAD00001009710

• Whole-exome sequencing of meningiomas for integrative molecular classification.

  Exome libraries were prepared using 100ng DNA of tumor tissue or matched normal DNA. Exome capture was performed using Agilent SureSelect Human Exome Library Preparation V5 or V6 COSIMC + kits.

  Dataset EGAD00001007051

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - WGS

  Whole genome sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015469

• Type 1 Diabetes Genetics Consortium (T1DGC): ImmunoChip Study

  The Type 1 Diabetes Genetics Consortium (T1DGC) was formed to address issues of limited sample size and consistency of phenotyping that had limited genetic investigations on risk of type 1 diabetes (T1D). The T1DGC first collected affected sib pair (ASP) families from four geographic networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, T1D cases and controls were ascertained from existing and de novo collections. The T1DGC assembled 2,601 T1D ASP families and 69 Parent-T1D offspring trios, T1D cases from the UK Genetic Resource Investigating Diabetes (UKGRID, N=6,670), and controls from the British 1958 Birth Cohort (B58BC, N=6,523), the UK National Blood Services collection (NBS, N=2,893) and the NIHR Cambridge Biomedical Research Centre BioResource (CBR, N=2,846). All samples included in this series have reported or self-declared European ancestry. All DNA samples were collected after approval from relevant institutional research ethics committees. Genotyping was performed using a custom Illumina Infinium high-density genotyping array, ImmunoChip (Illumina, Inc; CA) according to manufacturer's protocols. The ImmunoChip was designed to densely genotype, using 1000 Genomes and any other available disease specific resequencing data, immune-mediated disease loci identified by common variant GWAS. The ImmunoChip Consortium selected 186 distinct loci containing markers meeting genome wide significance criteria (P<5x10-8) from twelve such diseases (autoimmune thyroid disease, ankylosing spondylitis, Crohn's disease, celiac disease, IgA deficiency, multiple sclerosis, primary biliary cirrhosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, T1D and ulcerative colitis). All 1000 Genomes Project pilot phase CEU population variants (Sept 2009 release) within 0.1cM (HapMap3 CEU) recombination blocks around each GWAS region lead marker were submitted for array design. No filtering on correlated variants (linkage disequilibrium) was applied. Additional content included regional resequencing data (submitted by several groups) as well as a small proportion of investigator-specific undisclosed content including intermediate GWAS results. After data cleaning and quality control, a total of 154,939 single nucleotide polymorphisms (SNPs) from 186 loci on ImmunoChip were scored. Case-control and family data were analyzed independently and combined by meta-analysis.

  Study phs000911

• Therapeutic Resistance to PI3K-alpha Inhibitors

  We have studied the tumor genomic evolution in a patient with metastatic breast cancer bearing an activating PIK3CA mutation. The patient was treated with the PI3Kα inhibitor BYL719 and achieved a lasting clinical response on BYL719, but eventually progressed to treatment and died shortly thereafter. A rapid autopsy was performed and a total of 14 metastatic lesions were collected for further analysis. In order to identify possible genetic determinants of acquired resistance to PI3Kα inhibition, we took a three-step approach. First, we examined both the primary tumor (before BYL719 treatment) and the new lung metastasis by whole genome sequencing (DNA from the spleen was used as a normal control). Then, we analyzed the primary tumor, lung metastasis, and the peri-aortic lesion that remained stable (responding) at the time of progression to BYL719 therapy by whole exome sequencing. Finally, to confirm and expand our findings, we sequenced the primary tumor and all the metastatic lesions to >500-fold coverage using a custom targeted deep-sequencing assay, MSK-IMPACT. Using this 3-step approach, we have demonstrated that patient’s lesion underwent parallel genetic evolution at multiple metastatic sites with different PTEN genomic alterations leading to a convergent PTEN- null phenotype resistant to PI3Kα inhibition. In order to expand our observations, we analyzed paired samples (pre-treatment and at progression) from six additional patients enrolled in the BYL719 trial. Acquired bi-allelic loss of PTEN was found in one additional patient treated with BYL719 whereas in two patients PIK3CA mutations present in the primary tumor were no longer detected at the time of progression. To functionally characterize our findings, inducible PTEN knockdown in sensitive cells resulted in resistance to BYL719, while simultaneous PI3K-p110β blockade reverted this resistance phenotype, both in cell lines and in PTEN-null xenografts derived from our patient. We conclude that parallel genetic evolution of separate sites with different PTEN genomic alterations leads to a convergent PTEN-null phenotype resistant to PI3Kα inhibition.

  Study EGAS00001000991

• Comprehensive Omics Analysis of Pediatric Solid Tumors and Establishment of a Repository for Related Biologic Studies (10C0086)

  This study (10-C-0086) collected and analyzed tumor and circulating tumor omics of pediatric and young adult patients with relapsed rhabdomyosarcoma who were co-enrolled in and receiving treatment on the interventional study 17-C-0049. We sought to describe the summary genomic findings of tumors, and report on the detection of circulating tumor DNA (ctDNA) in serial samples. Tumor tissue and blood were collected and analyzed. Tumor samples were subjected to whole exome and/or whole genome sequencing paired with RNA-Seq. Cell free DNA (cfDNA) was extracted from serially collected blood samples and sequenced. Fusion status, mutations, and IGF1R and YES1 expression from tumor samples revealed the presence of a PAX3 fusion in most samples, a number of common mutations, and universal but heterogeneous expression of IGF-1R and YES1. ctDNA was detected above the 3% threshold in a majority of patients and analysis of cfDNA demonstrated an ability to monitor tumor clonal evolution.

  Study phs003243

• Aberrant RNA-splicing (neojunctions) offers a new source for targets, and our neoantigen discovery platform (SNIPP) characterizes a novel class of clonally-expressed splicing-derived neoantigens that elicit a CD8+ T-cell-mediated tumor killing response.

  RESULTS: Our pipeline identified 789 public neojunctions, with 32 neojunctions concurrently identified in transcriptomic and proteomic glioma data and predicted to be presented by HLA-A*02:01 with high confidence. IVS and subsequent 10x VDJ scRNA-seq identified TCR clonotypes reactive against neojunctions in RPL22 (n=7) and GNAS (n=1), the latter being highly intratumorally-conserved (detected in > 90% of spatially-mapped biopsies across 17/56 patients (26.78%)). TCR-transduced T-cells demonstrated recognition and immunogenic activation against endogenously processed and presented neoantigens in multiple GBM PDX cell lines. Furthermore, IDH1-mutant oligodendroglioma samples demonstrated significantly elevated expression of neojunctions over IDH1-mutant astrocytoma and IDH1wt subtypes. Differential gene expression (DESeq2) identified decreased expression of splicing factors due to oligodendroglioma-specific co-deletion of Chromosomes 1p/19q. siRNA knockdown of these splicing factors (e.g. SF3A3, SNRPD2) in IDH1wt glioma cells resulted in significantly increased expression of corresponding neojunctions.

  Study EGAS00001007986

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the regulation of gene expression in immune cell subsets and its contribution to autoimmune diseases, Whole blood and various immune cell subsets from 119 Systemic Lupus Erythematosus (SLE), 65 Dermatomyositis & Polymyositis, 67 Systemic Sclerosis, 19 Mixed Connective Tissue Disease, 18 Sjogren's syndrome, 24 Rheumatoid Arthritis, 23 Behcet's disease, 18 Adult Onset Still���s Disease, 25 ANCA-associated Vasculitis, 16 Takayasu���s Arteritis and 141 healthy controls (C) were collected (Naive_CD4, Mem_CD4, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Th1, Th2, Th17, Tfh, NK, Naive_CD8, Mem_CD8, EM_CD8, CM_CD8, TEMRA_CD8, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, LDG, Neu). Whole genome sequencing was performed with whole blood samples. RNA-seq was performed with each immune cell subset samples. After filtering and normalization of the gene expression data, eQTL analysis was performed in each immune cell type. 15 immune cell subsets ATAC-seq was also performed in 8 SLE and HCs, each.

  Study JGAS000220