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• The immunological characterization of expanded tumor-infiltrating lymphocytes in renal cell carcinoma patients

  In this study, we comprehensively characterized the non-expanded and expanded tumor-infiltrating lymphocytes (TILs) from treatment-naïve RCC patients, as well as the corresponding “young” TILs (pre-REP TILs) and “rapidly expanded” TILs (REP TILs) following a clinical-grade TIL production protocol. From our scRNA+TCRαβ-seq and TCRβ-seq analyses, we show that the REP protocol preferentially favors the expansion CD4+ T-cells that originate from small T-cell clones in the tumor microenvironment (TME), indicating that the large, exhausted T-cell clones in the tumor do not expand during the protocol. We further identified RCC-associated TCR motifs that were validated in multiple TCRαβ-seq and scRNA+TCRαβ-seq datasets, as well as quantified the RCC-associated TCRs from the REP protocol. Overall, the T-cells carrying the RCC-associated TCRs remained high in the tumors and corresponding pre-REP TILs, but the frequency was reduced in the REP TILs. Furthermore, the overall anti-viral TCRs remained low throughout the REP protocol. Our results provide an in-depth understanding of the origin, phenotype, and specificity of the TCRs in RCC TILs.

  Study EGAS00001006952

• Epigenomic atlas of organoid development

  To investigfate the epigenomic basis of fate decisions in the central nerveous system, we recorded a epigenomic timecourse of human brain organoid development using Cut&Tag with paired scRNA-seq. We further performed perturbation experiment inhibiting EED and profiled the response with scRNA-seq and Cut&Tag. Finally, we profiled a sample of the developing human brain using multiome sequencing and Cut&Tag. In our study, we uncover epigenomic switches during brain region diversification and show that epigenetic activation precedes gene expression during neurogenesis in organoids and in primary tissue. Lastly, we show that transcriptional repression by H3K27me3 is required to stabilize neuroectoderm induction from pluripotency.

  Study EGAS50000000155

• eMERGE Geisinger eGenomic Medicine (GeM) Abdominal Aortic Aneurysm Project (AAAP)

  A large research cohort of Geisinger Abdominal Aortic Aneurysm (AAA) patients was created by enrolling and consenting patients of the Geisinger Department of Vascular Surgery. Consented patients provide blood, serum and DNA samples for research and authorize use of data in their medical record for research. They also complete a data questionnaire that asks information about family history of AAA and other vascular diseases, as well as information on known or suspected AAA risk factors, including smoking history, body mass index, hypertension, type 2 diabetes, and atherosclerotic disease. The AAA cases are 78% male, with a mean age of 74 years; 39% have undergone surgical or endovascular repair; more than 85% or current or past smokers; approximately 20% of cases report a positive family history of AAA. Geisinger AAA patients undergo regular imaging studies, typically every 6 months, to monitor the progression of aneurysm expansion. This allows the growth rates of their aneurysm to be calculated. DNA samples from a total of 910 AAA patients were used for whole genome genotyping; these results are included in the dbGaP.

  Study phs000387

• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847

• Dataset that contains analyses of submission 6

  This is the description of analyses dataset of submission 6

  Dataset EGAD50000001107

• An analysis of humoral and cellular immune responses following COVID-19 vaccination.

  Two dose mRNA vaccination provides excellent protection against SARS-CoV-2. However, there are few data on vaccine efficacy in elderly individuals above the age of 801. Additionally, new variants of concern (VOC) with reduced sensitivity to neutralising antibodies have raised fears for vulnerable groups. Here we assessed humoral and cellular immune responses following vaccination with mRNA vaccine BNT162b22 in elderly participants prospectively recruited from the community and younger health care workers. Median age was 72 years and 51% were females amongst 140 participants. Neutralising antibody responses after the first vaccine dose diminished with increasing age, with a steep drop in participants over 80 years old. Sera from participants below and above 80 showed significantly lower neutralisation potency against B.1.1.7, B.1.351 and P.1. variants of concern as compared to wild type. Those over 80 were more likely to lack any neutralisation against VOC compared younger participants following first dose. Binding IgG and IgA antibodies were lower in the elderly, as was the frequency of SARS-CoV-2 Spike specific B- cells. We observed a trend towards lower somatic hypermutation in participants with suboptimal neutralisation, and elderly participants demonstrated clear reduction in class switched somatic hypermutation, driven by the IgA1/2 isotype. SARS-CoV-2 Spike specific T- cell IFN?? and IL-2 responses were secreted primarily by CD4 T cells, and impaired in the older age group. We conclude that the elderly are a high risk population that warrant specific measures in order to mitigate against vaccine failure, particularly where variants of concern are circulating. Specifically, the dosing interval should not be extended in this group.

  Study EGAS00001005380

• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169

• An instructive role for IL7RA in the development of human B-cell precursor leukemia

  Kinase signaling fuels growth of B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Yet its role in leukemia initiation is unclear and has not been shown in primary human hematopoietic cells. We previously described activating mutations in interleukin-7 receptor alpha (IL7RA) in poor-prognosis “ph-like” BCP-ALL. Here we show that expression of activated mutant IL7RA in human CD34+ hematopoietic cells creates a preleukemic state in transplanted NOD/LtSz-scid IL2Rγnull mice, characterized by persistence of self-renewing Pro-B cells with non-productive V(D)J gene rearrangements. Preleukemic CD34+CD10highCD19+ cells evolved to a BCP-ALL with spontaneously acquired CDKN2A deletions as commonly observed in primary human BCP-ALL. CRISPR mediated silencing of CDKN2A in primary human CD34+ cells transduced with activated IL7RA resulted in robust development of BCP-ALLs in-vivo. Thus, we demonstrate for the first time that constitutive activation of IL7RA can initiate preleukemia in primary human hematopoietic progenitors and cooperates with CDKN2A silencing in progression into BCP-ALL.

  Study EGAS00001005347

• Monitoring of leukemia clones in B-cell acute lymphoblastic leukemia at diagnosis and during treatment by single-cell DNA amplicon sequencing

  Acute lymphoblastic leukemia (ALL) is characterized by the presence of chromosomal changes, including numerical changes, translocations and deletions, which are often associated with additional single nucleotide mutations. In this study we used single-cell targeted DNA sequencing to determine the clonal heterogeneity of B-cell ALL at diagnosis and during chemotherapy treatment. With a customly designed DNA amplicon library targeting the most common mutations (in 110 genes) present in ALL, we analyzed bone marrow samples and/or blood samples from 12 B-ALL cases at diagnosis. For 4 cases where we detected multiple mutational clones at diagnosis, we also studied blood samples during the first weeks of chemotherapy treatment. This study shows that B-ALL cases with either a ETV6-RUNX1 or a BCR-ABL1 fusion have a low mutational burden, while cases with PAX5 alterations or hyperdyploidy have multiple clones at diagnosis, often with mutations in the JAK-STAT signaling pathway and the RAS signaling pathway. As expected, it can be observed that these clones disappear during treatment of the leukemia with almost no mutated cells left after two weeks of treatment.

  Study EGAS00001005029

• GATA6 expression distinguishes classical and basal-like subtypes in advanced pancreatic cancer.

  PURPOSE: To determine the impact of basal-like and classical subtypes in advanced PDAC and to explore GATA6 expression as a surrogate biomarker. EXPERIMENTAL DESIGN: Within the COMPASS trial patients proceeding to chemotherapy for advanced PDAC undergo tumour biopsy for RNA sequencing. Overall response rate (ORR) and overall survival (OS) were stratified by subtypes and according to chemotherapy received. Correlation of GATA6 with the subtypes using gene expression profiling, in situ hybridization (ISH) were explored. RESULTS: Between December 2015-May 2019, 195 patients (95%) had enough tissue for RNA sequencing; 39 (20%) were classified as basal-like and 156 (80%) as classical. RECIST response data were available for 157 patients; 29 basal-like and 128 classical where the ORR was 10% vs. 33% respectively (p=0.02). In patients with basal-like tumours treated with modified FOLFIRINOX (mFFX) (n=22) the progression rate was 60% compared to 15% in classical PDAC (p= 0.0002). Median OS in the intention to treat population (n=195) was 9.3 months for classical vs. 5.9 months for basal-like PDAC (HR 0.47 95% CI 0.32-0.69, p=0.0001). GATA6 expression by RNAseq highly correlated with the classifier (p<0.001) and ISH predicted the subtypes with sensitivity of 89% and specificity of 83%. In a multivariable analysis, GATA6 expression was prognostic (p=0.02). In exploratory analyses, basal-like tumours, could be identified by keratin 5, were more hypoxic and enriched for a T cell inflamed gene expression signature. CONCLUSIONS: The basal-like subtype is chemoresistant and can be distinguished from classical PDAC by GATA6 expression.

  Dataset EGAD00001006081