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• Efficacy of Bitter Taste Blockers on Flavor Acceptance in a Human Population

  The goal of this project is to determine variation in human bitter perception and the effectiveness of bitter blockers in individuals of different genotypes. The project is based on the parent project titled "Efficacy of bitter taste blockers on flavor acceptance in pediatric population", which addresses how bitter taste perception affects medication compliance. As a part of the parent project, mothers and their children were recruited from the general population of metropolitan Philadelphia through print and internet media as well as from a database of past research participants. Adults (mothers) were evaluated in the laboratory for bitter taste perception for a variety of "Generally Recognized As Safe" (GRAS) bitter compounds using the general Labeled Magnitude Scale (gLMS) which allows subjects to rate sensory intensity. Mothers were also evaluated for perception of the liquid formulation of the drug KaletraTM, a recommended 1st line treatment for infants with HIV infection, whose taste is rejected by some children and accepted well by others. DNA samples from mothers were genotyped as a part of this study to identify (1) novel genes associated with human bitter perception and (2) the ability of compounds to block bitterness.

  Study phs000839

• Development and first-in-human CAR T therapy targeting the pathognomonic MiT-fusion driven protein GPNMB

  Summary: CAR T therapy for solid tumors is constrained by the scarcity of safe, uniformly expressed cell-surface targets. Here we identify GPNMB, a MiT fusion-driven protein, as highly, homogeneously, and stably expressed in primary and relapsed translocation-positive alveolar soft part sarcoma (ASPS) and renal cell carcinoma (tRCC). We develop a GPNMB-directed CAR T cell product, GCAR1, which demonstrates potent activity against patient-matched cells, organoids and xenograft models. In a first-in-human treatment of two patients with relapsed/refractory, metastatic ASPS, GCAR1 is well tolerated and induces stable disease for up to 6 months, accompanied by resolution of many non-target lesions. GCAR1 T cells expand in peripheral blood as a polyclonal population and remain detectable for up to 6 months. Spatial transcriptomics identify multiple immunosuppressive niches adjacent to T cells infiltrating treatment-resistant lesions; biological PDL1 blockade or PD1 and TIGIT double knockout overcomes this resistance and shows synergistic activity with GCAR1 in xenograft models. Taken together, these data provide clinical proof-of-concept for treating solid tumors with CAR T cells targeting a surface antigen driven by an oncogenic gene fusion.

  Study EGAS50000001696

• WGS datasets of pediatric glioblastoma

  WGS with linked reads of pediatric glioblastoma. For each patient, blood and tumor tissue were sequenced. For two patients, we also provide sequencing data for the blood of their parents.

  Dataset EGAD00001005212

• DIPG WES and RNA-Seq

  We characterised H3K27M-mutant diffuse intrinsic pontine glioma (DIPG, n=21) and RNA-Seq (n=26 DIPG, 12 normal brain)

  Dataset EGAD00001006450

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• RNA-seq and scRNA/TCR-seq data for publication: "Pharmacological inhibition of nonsense-mediated mRNA decay enhances anti-tumour immunity"

  PDFs RNA-seq and scRNA/TCR-seq data for Pharmacologic inhibition of nonsense-mediated mRNA decay enhances anti-tumour immunity

  Dataset EGAD50000001720

• WES of melanoma tumours prior to combined immune checkpoint blockade treatment.

  Paired melanoma tumor and normal (PBMC) WES data from a cohort of 26 patients subsequently treated with combined immune checkpoint blockade.

  Dataset EGAD00001005941

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• BLUEPRINT release January 2015, DNase-Hypersensitivity for monocyte

  DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001185

• BLUEPRINT September 2016, ATAC-seq for bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002710

• Duplex sequencing of 26 genes

  Buccal samples and paired esophageal epithelium were obtained using the three sizes of swabs and endoscopic biopsy, respectively. Forty samples from 10 subjects were analyzed via duplex sequencing. This dataset contains bam files that were mapped to the GRCh37 reference genome.

  Dataset EGAD50000000998

• WGS

  Whole Genome Sequencing

  Dataset EGAD00001001120

• Somatic mutations in twin breast cancers (2019-04-03)

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004890

• L1 Retrotransposon sequencing in Cocaine Use Disorder - Study 1

  Cocaine Use Disorder (CUD) is a global public health problem, with no effective pharmacotherapies. While CUD is marked by high heritability, discovery of variants associated with risk for CUD has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from medial prefrontal cortex NeuN+ neuronal nuclei from 25 CUD cases and 26 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001966

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 26 patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Study EGAS50000000146

• BLUEPRINT September 2016, ATAC-seq Mantle Cell Lymphoma from venous blood, on Genome GRCh38

  ATAC-seq data for 5 sample(s) Mantle Cell Lymphoma from venous blood, on Genome GRCh38. 5 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002918

• BLUEPRINT September 2016, ATAC-seq Chronic Lymphocytic Leukemia from venous blood, on Genome GRCh38

  ATAC-seq data for 106 sample(s) Chronic Lymphocytic Leukemia from venous blood, on Genome GRCh38. 111 run(s), 109 experiment(s), 109 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002916

• BLUEPRINT release January 2015, DNase-Hypersensitivity for Acute myeloid leukemia

  DNase-Hypersensitivity data for 1 Acute myeloid leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001190

• BLUEPRINT September 2016, ATAC-seq for tonsil, on Genome GRCh38

  ATAC-seq data for 7 sample(s) from tonsil, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002708

• BLUEPRINT September 2016, ATAC-seq for osteoclast from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for osteoclast from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002907

• BLUEPRINT September 2016, ATAC-seq Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002920

• BLUEPRINT September 2016, ATAC-seq for plasma cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for plasma cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002912

• BLUEPRINT September 2016, ATAC-seq for naive B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from tonsil, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002903

• BLUEPRINT release August 2015, DNase-Hypersensitivity for monocyte, on genome GRCh38

  DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001560

• BLUEPRINT release January 2015, RNA-Seq for monocyte

  RNA-Seq data for 8 monocyte sample(s). 8 run(s), 8 experiment(s), 8 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001191

• BLUEPRINT release January 2015, DNase-Hypersensitivity for macrophage

  DNase-Hypersensitivity data for 14 macrophage sample(s). 18 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001198

• BLUEPRINT release August 2014, DNase-Hypersensitivity for macrophage

  DNase-Hypersensitivity data for 1 macrophage sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001000931

• Hepatitis C Antiviral Long-term Treatment Against Cirrhosis (HALT-C)

  Reprinted from http://www.haltctrial.org/ Purpose The Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial is a randomized controlled trial designed to evaluate the safety and efficacy of long-term use of pegylated interferon for the treatment of chronic hepatitis C in patients who failed to respond to previous interferon therapy. The HALT-C Trial was developed to determine whether prolonged interferon therapy altered histological and clinical outcomes in a group of patients who had failed to eradicate hepatitis C virus with previous interferon treatment. Study Hypotheses In patients with chronic hepatitis C and bridging fibrosis who failed to eradicate the virus with previous interferon therapy, long-term treatment with interferon is safe and can prevent progression to cirrhosis. In patients with cirrhosis secondary to chronic hepatitis C who failed to eradicate the virus with previous interferon therapy, long-term treatment with interferon is safe and can reduce the risks of hepatic decompensation or of hepatocellular carcinoma. Study Design 1145 patients with chronic HCV and advanced hepatic fibrosis (Ishak stage 3-6) who failed to respond to previous treatment with interferon were enrolled at 10 clinical centers and entered into a Lead-in phase. They were treated with a combination of pegylated interferon (Pegasys®, Hoffmann-La Roche) 180 µg/week and ribavirin (1000-1200 mg/day) for 24 weeks. Patients who had no detectable HCV-RNA at week 20 continued on combination therapy until week 48. 662 patients who did not clear virus were randomly assigned at week 24 to either continue treatment with pegylated interferon alone (90 µg/week) for an additional 42 months, or to have treatment discontinued. All patients were followed at 3-month intervals following randomization. Liver biopsy was performed at baseline and after 1.5 and 3.5 years of treatment. Because of slower than expected enrollment and the approval by the FDA of peginterferon alfa-2b after the start of the trial, we modified the study protocol in three ways. First, criteria for admission to the trial were liberalized to allow patients to enter the trial with lower platelet and white blood cell counts than had been initially considered safe or tolerable. Second, 151 Lead-in patients and those continuing on therapy after 24 weeks who demonstrated return of viremia during or after their 48-week treatment period (called "Breakthrough" or "Relapse" patients, respectively) were allowed to return to enter the randomized trial. Third, 237 patients treated with peginterferon alfa-2b (or with peginterferon alfa-2a in licensing trials) outside the HALT-C Trial who in other respects met all study criteria, having received the equivalent of Trial Lead-in period therapy, were allowed to enter the long-term trial as "Express" patients. A total 1050 patients were randomized. Those patients who completed Month 48 were offered an "extended follow-up (observation only)" until October 2009. These visits will primarily be to identify outcome events, and to provide information to patients concerning the current status of the trial. Some questionnaires, blood tests, and an ultrasonogram will be performed. Quarterly (every 3 months) Interval history of complications, adverse events Current medications Brief physical examination Laboratory tests: liver panel, CBC, INR, AFP Child-Pugh Score Stored serum Annual Complete physical examination Ultrasound of liver 1.5 years (M24 visit, middle of study) Liver biopsy: formalin fixed histology, frozen liver tissue (subset of patients) 3.5 years (M48, end of study) Liver biopsy: formalin fixed histology, frozen liver tissue (subset of patients) Endoscopy: evaluate esophageal varices and portal hypertension After Month 48 Observation only (no treatment) to determine clinical outcomes Clinic visit every 6 months with current medications, brief PE, liver panel, CBC, AFP, stored Serum Ultrasound of liver every 6 months Outcome Variables Primary outcome variables to be assessed in the two groups of patients include: Development of cirrhosis on liver biopsy (progression of Ishak fibrosis score by 2 points or more) Development of hepatic decompensation, as shown by: Sustained increase in the Child-Turcotte-Pugh score to 7 points or higher Variceal hemorrhage Ascites Spontaneous bacterial peritonitis Hepatic encephalopathy Development of hepatocellular carcinoma Death Secondary outcomes include quality of life, serious adverse events, events requiring dose reductions, and development of presumed hepatocellular carcinoma.

  Study phs000430

• Atezolizumab Plus Personalized Neoantigen Vaccination in Patients with Urothelial Cancer: a Phase 1 Trial

  This is a phase 1 single center clinical trial evaluating a multi-peptide personalized neoantigen vaccine, PGV001, in combination with atezolizumab for patients with urothelial cancer. Patients were enrolled in either the adjuvant or metastatic setting. Those in the adjuvant setting included patients considered high risk of recurrence (pathological stage ypT2-T4 or ypN+ for those treated with prior neoadjuvant chemotherapy or pT3-T4 or pN+ for those not treated with prior neoadjuvant chemotherapy). Those in the metastatic setting included patients progressing after prior chemotherapy or those with at least stable disease after chemotherapy treated as “switch maintenance” therapy. The primary endpoint was feasibility (including the number of neoantigens identified per patient, vaccine production time, the proportion of patients consenting to the vaccine development phase for whom a vaccine product was prepared, and the proportion of patients eligible for the treatment phase who completed the priming cycle 1 of PGV001 plus atezolizumab) and safety. Secondary endpoints included the objective response rate, progression-free survival or disease-free survival, overall survival, and immunomodulatory effects of treatment. Urothelial tumor tissue and normal tissue or peripheral blood specimens were utilized for DNA sequencing. HLA typing was performed utilizing genomic DNA isolated from whole blood, and RNA sequencing was performed utilizing tumor tissue specimens. Neoantigen prediction and final selection for incorporation into the vaccine was determined by the OpenVax computational pipeline. 12 patients were initially enrolled into the vaccine development phase and 10 patients initiated the treatment phase. PGV001 was administered with poly-ICLC and tetanus peptide on subsequent days for up to 10 doses, including an initial priming cycle 1. Atezolizumab was administered every 3 weeks for up to 1 year in the adjuvant setting or 2 years in the metastatic setting. The vaccine was feasible and safe, the median vaccine production time was 20.3 weeks, and 100% of patients that initiated the treatment phase completed the priming cycle. The most common treatment-related adverse events were local grade 1 injection site reactions, fever, and fatigue. Three of the 4 patients in the adjuvant setting remained disease-free at median follow-up of 39.5 months. There was a 40% objective response rate among patients with measurable disease in the metastatic setting. The single patient treated as “switch maintenance” therapy remained with no evidence of disease at 39.4 month follow-up. All patients demonstrated on-treatment neoantigen-specific T cell reactivity, as measured by ELISPOT and flow cytometry assays. Overall, PGV001 plus atezolizumab was feasible, safe, and warrants further investigation. Whole exome sequencing from tumor tissue and normal tissue or whole blood specimens and RNA sequencing from tumor tissue specimens will be available through dbGaP.

  Study phs003922

• Chromatin accessibility in human monocyte differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 26 samples.

  Dataset EGAD00001006601

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002922

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002921

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002919

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002917

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002914

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002913

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002909

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002905

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for naive B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002902

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002901

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002900

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002899

• BLUEPRINT release August 2015, RNA-Seq for Multiple myeloma, on genome GRCh38

  RNA-Seq data for 11 Multiple myeloma sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001471

• BLUEPRINT release August 2015, DNase-Hypersensitivity for Acute Myeloid Leukemia, on genome GRCh38

  DNase-Hypersensitivity data for 1 Acute Myeloid Leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001549

• BLUEPRINT release January 2015, DNase-Hypersensitivity for inflammatory macrophage

  DNase-Hypersensitivity data for 2 inflammatory macrophage sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001193

• BLUEPRINT release August 2015, RNA-Seq for monocyte, on genome GRCh38

  RNA-Seq data for 4 monocyte sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001572