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• Genetics of Glucose Regulation in Gestation and Growth (Gen3G) Cohort - Placenta Transcriptomics RNA Sequencing

  The overarching goals of Genetics of Glucose regulation in Gestation and Growth (Gen3G) are to increase our understanding of biological, environmental, and genetic determinants of glucose regulation during pregnancy and their impact on fetal/child development. Gen3G is a prospective cohort study: we initially recruited 1,024 pregnant women between 2010-2013 at Blood Sampling in Pregnancy Clinic during the first trimester of pregnancy (median 9 weeks of gestation) in Sherbrooke, Québec, Canada. We assessed 898 pregnant women at second trimester (median 26 weeks of gestation), when participants completed a 75g oral glucose tolerance test (OGTT) as clinically indicated for screening of gestational diabetes mellitus (GDM). We collected data for 854 mother-child dyads at delivery (from medical records), in addition to placenta and/or cord blood samples in majority of newborns.The overall goal of the grant that supported data that is included in this dbGaP submission was to discover novel placental factors that regulate glucose metabolism in pregnancy and predict GDM by conducting genome-wide transcriptomics (RNA and miRNA) in carefully collected placenta samples from Gen3G.

  Study phs003151

• Blood-based monitoring of relapsed/refractory cHL patients predict responses to PD-1 blockade treatment

  Hodgkin lymphoma (cHL) patients are uniquely susceptible to treatment with programmed cell death-1 (PD-1) treatment. However, monitoring with FDG-PET/CT, the current response detection standard, is challenging. Here, we address the potential applicability of tissue biomarkers and blood-based biomarkers in PD-1 treated cHL patients. We evaluated 9p24.1/PD-L1/PD-L2 alterations, and expression of PD-L1 and antigen presentation molecules (HLA class I/II) in 9 tissue biopsies of 4 patients. In addition, we assessed circulating tumor DNA (ctDNA), extracellular vesicle associated miRNAs (EV-miRNAs), soluble PD-L1 and serum TARC (sTARC) in 26 longitudinal blood samples of these patients during PD-1 treatment. We found that the predictive power of tissue biomarkers is dependent on the timing of the biopsy . The dynamics of blood-based biomarkers: sTARC, EV-miRNAs and ctDNA corresponded well immunotherapy treatment response. Therefore, blood-based biomarkers are promising monitoring strategies in PD-1 treated cHL patients and should be further explored in clinical trials or observational studies.

  Study EGAS00001005894

• Single-cell RNA-seq of celiac disease-specific plasma cells

  Disease-specific plasma cells (PCs) reactive with transglutaminase 2 (TG2) or deamidated gluten peptides (DGP) are abundant in celiac disease (CeD) gut lesions. Their contribution toward CeD pathogenesis is unclear. We assessed expression of markers associated with PC longevity in 15 untreated and 26 treated CeD patients in addition to 13 non-CeD controls, and performed RNA-sequencing with clonal inference and transcriptomic analysis of 3251 single PCs. We observed antigen-dependent V-gene selection and stereotypic antibodies. Generation of recombinant DGP-specific antibodies revealed a key role of a heavy-chain residue that displays polymorphism, suggesting that immunoglobulin gene polymorphisms may influence CeD-specific antibody responses. We identified transcriptional differences between CeD-specific vs non-disease-specific PCs and between short-lived vs long-lived PCs. The short-lived CD19+CD45+ phenotype dominated in untreated and short-term-treated CeD, in particular among disease-specific PCs but also in the general PC population. Thus, the disease lesion of untreated CeD is characterized by massive accumulation of short-lived PCs that are not only directed against disease-specific antigens.

  Study EGAS00001004623

• Single-cell RNA sequencing of 16 NPM1 mutated AML patients

  This dataset contains paired-end fastq files for single-cell RNA-seq of 16 NPM1 mutated AML patients. 19 fastq pairs are included, with two samples split into two lanes and a second (technical) replicate for one patient. Libraries were constructed using 10x Genomics Chromium Next GEM Single cell 3’ v3.1 and sequencing was performed using Illumina NovaSeq6000.

  Dataset EGAD50000000478

• RNU2-2 splicing signature RNA-Seq

  This dataset is composed of RNA-Seq samples: 49 controls which are probands without snRNA rare variants and 19 affected probands with either monoallelic or biallelic variants in RNU2-2. RNA was extracted from short-term lymphocytes cultures. RNA-Seq libraries were obtained by hybrid capture of fragmented cDNA with RNA probes from exome v8 (Agilent)

  Dataset EGAD50000002045

• Whole Exome Sequencing of Mixed Histology Lung Cancer

  We conducted whole-exome sequencing (WES) and microarray profiling on 19 micro-dissected tumor regions of different histologic subtypes from 9 patients with lung cancers of mixed histologic patterns including 6 LUAD, 6 LCNEC, 3 SCLC, 3 LUSC, and one poorly differentiated NSCLC-NOS.

  Dataset EGAD00001007076

• scRNA-seq from brain metastasis micorenvironment and cerebrospinal fluid

  A total of 9 brain metastasis were sequenced. For 6/9 a matched cerebrospinal fluid sample, prior to surgery and in two cases after surgery (+1 month from surgery) and after treatment (+3 month) were collected. Single-cell gene expression was produced using the Chromium Single Cell 5’ Library and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD00001006452

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 5)

  Whole genome sequencing data of 19 high-grade serous carcinoma (HGSC) patients (47 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010029

• IMCISION DNAseq

  Whole-exome sequencing of 32 primary head and neck squamous cell carcinoma samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy. DNA quantity used: 50ng. Library Preparation Kit: Twist Human Core Exome Plus (Twist Bioscience). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ.

  Dataset EGAD00001008139

• Longitudinal Immune Dynamics of Mild COVID-19 Define Signatures of Recovery and Persistence

  SARS-CoV-2 has infected over 160 million and caused more than 3 million deaths to date. Most individuals (>80%) have mild symptoms and recover in the outpatient setting, but detailed studies of immune responses have focused primarily on moderate to severe COVID-19. We deeply profiled the longitudinal immune response in individuals with mild COVID beginning with early time points post-infection (1-15 days) and proceeding through convalescence to >100 days after symptom onset. We correlated data from single cell analyses of peripheral blood cells, serum proteomics, virus-specific cellular and humoral immune responses, and clinical metadata. Acute infection was characterized by vigorous coordinated innate and adaptive activation, including an early cellular and proteomic signature that correlated with the amplitude of virus-specific humoral responses after day 30. We characterized signals associated with recovery and convalescence to define a new signature of inflammatory cytokines, gene expression, and chromatin accessibility that persists in individuals with post-acute sequelae of SARS-CoV-2 infection (PASC).

  Study phs002576