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• Cross-tissue transcriptomic analysis of human secondary lymphoid organ residing ILC3 reveals a default quiescent state in the absence of inflammation

  A cross tissue transcriptional comparison of human ILC3 isolated from non-inflamed lymph nodes (LN) and spleens, inflamed tonsils and the peripheral blood (PB). Using uniform gating and high-purity cell-sorting, ILC3 were sorted as Lineage(CD3,CD19,CD34,CD14,CD94)-CD45intCD127+CRTH2-CD117+. From LN, spleen, tonsils and PB, NKp44- ILC3 were isolated and, in addition, NKp44+ ILC3 were sorted from spleen and tonsils. RNA quality was measured on a RNA 6000 Pico Kit (Agilent Technologies) using a 2100 Bioanalyzer (Agilent Technologies). 100 pg high-quality RNA was isolated and cDNA was generated using the SMART-Seq (v3) Ultra Low Input RNA Kit (Clontech) with 15 cycles of amplification. Amplified and Covaris-fragmented cDNA was quality-checked on a High Sensitivity DNA chip (Agilent Technologies) and further processed according the TruSeq Nano DNA Library Preparation Kit (Illumina). Data was processed as follows: SMARTer adapters were trimmed with cutadapt and the resulting sequences were aligned to the human RefSeq transcriptome using 14 TopHat2 (Kim et al., 2013). Normalization and quantification was performed using Cufflinks (Trapnell et al., 2012). FPKM counts were determined per gene with HTSeq-count.

  Study EGAS00001002636

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Dataset EGAD00001001356

• Genetic Discovery and Application in a Clinical Setting: Continuing a Partnership (eMERGE Phase II)

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites funded by the NHGRI to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 19,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. The eMERGE Network brings together researchers with a wide range of expertise in genomics, statistics, ethics, informatics, and clinical medicine from leading medical research institutions across the country. Each center participating in the consortium is uniquely situated to provide critical resources to this highly collaborative and productive network. Each site combines a biobank or study cohort with extensive genomic data and access to clinical data derived from electronic medical records. Sites are geographically dispersed and have diverse patient populations, including two sites focusing specifically on pediatrics. The eMERGE Network is comprised of 9 sites and one coordinating center. Each site maintains its own biorepository where DNA specimens are linked to phenotypic data contained within EMRs. Children's Hospital of Pennsylvania, PI: Hakon Hakonarson, MD, PhD Cincinnati Children's Medical Center with Boston Children's Hospital, PI: John Harley, MD, PhD - CCHMC and Ingrid Holm, MD, MPH - BCH Geisinger Health System, PI: David Carey, PhD and Marc Williams, MD Group Health Cooperative with University of Washington, PI: Eric Larson, MD, MPH - GHC and Gail Jarvik, MD, PhD - UW Marshfield Clinic with Essentia Institute of Rural Health, PI: Catherine McCarty, PhD, MPH - Essentia and Murray Brilliant, PhD - Marshfield Mayo Clinic, PI: Christopher Chute, MD, DrPH and Iftikhar Kullo, MD Icahn School of Medicine at Mount Sinai, PI: Erwin Bottinger, MD Northwestern University, PI: Rex Chisholm, PhD and Maureen Smith, MS Vanderbilt University, PI: Dan Roden, MD eMERGE Coordinating Center - Vanderbilt University, PI: Paul Harris, PhD Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of red cell indices, white blood count (WBC) differential, diabetic retinopathy, height, serum lipid levels, specifically total cholesterol, HDL (high density lipoprotein), LDL (low density lipoprotein), and triglycerides, and autoimmune hypothyroidism as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes.

  Study phs000948

• Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations

  Introduction: Tumour Mutation Burden (TMB) is a potential biomarker for immune therapies. Identifying factors that may affect TMB prediction is key to its utility as biomarker for treatment options. Here we investigated parameters that might affect TMB using cytology smears obtained from endobronchial ultrasound transbronchial needle aspiration (EBUS TBNA)-sampled malignant lymph nodes, which are often the only diagnostic samples collected in patients with advanced lung cancer. Methods: Individual Diff-Quik cytology smears were prepared for each needle pass from the same enlarged malignant mediastinal lymph nodes. DNA extracted from smears of each pass underwent sequencing using a large gene panel sequencing (TSO500, Illumina). TMB was estimated for each individual needle pass using the TSO500 Local App v. 2.0 (Illumina). Results: Twenty patients had two or more Diff-Quik smears (total 45 smears) which passed sequencing quality control. Average TMB for all smears was 8.7 ± 5.0 mutations per megabase (Mb). Sixteen of the 20 patients had paired samples with minimal differences in TMB score (average difference 1.3 ± 0.85). Paired samples from 13 patients had concordant TMB in terms of scores being below or above a threshold of 10 mutations/Mb. Samples from seven patients had discrepant TMB, with four cases in particular exhibiting an average difference of 11.3 ± 2.7 mutations/Mb. Factors affecting TMB calling involved tumour content of the samples, the amount of DNA used in sequencing as well as bone fide intra tumour heterogeneity between paired samples. Conclusions: TMB assessment is feasible from EBUS-TBNA derived Diff-Quik slides from a single needle pass. Repeated samples of one or more lymph nodes have minimal variation in TMB in most cases (80%), suggesting accuracy of the test overall. To enhance accuracy of the result, care should be taken in relation to the tumour content of the cytology smear. Further, clinicians should be aware that even slight differences in lymph node site selection could give rise to variable genomics and discrepant TMB due to tumour heterogeneity. Therefore, it would be reasonable for multi-lymph node site analysis of TMB to be performed using EBUS TBNA aspirates from different easily accessible lymph nodes. Further investigations need to determine whether these samples should be combined as one sample or tested separately.

  Study EGAS00001007484

• Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma

  Background:Malignant pleural mesothelioma (MPM) is a heterogeneous cancer. Better knowledge of molecular and cellular intra-tumor heterogeneity throughout the thoracic cavity is required to develop efficient therapies. This study focuses on molecular intra-tumor heterogeneity using the largest series to date in MPM and is the first to report on the multi-omics profiling of a substantial series of multi-site tumor samples. Methods:Intra-tumor heterogeneity was investigated in 16 patients from whom biopsies were taken at distinct anatomical sites. The paired biopsies collected from apex, side wall, costo-diaphragmatic or highest metabolic sites as well as 5 derived cell lines were screened using targeted sequencing. Whole exome sequencing, RNA sequencing, and DNA methylation were performed on a subset of the cohort for deep characterization. Molecular classification, recently defined histo-molecular gradients, and cell populations of the tumor microenvironment were assessed. Results:Sequencing analysis identified heterogeneous variants notably in NF2, a key tumor suppressor gene of mesothelial carcinogenesis. Subclonal tumor populations were shared among paired biopsies, suggesting a polyclonal dissemination of the tumor. Transcriptome analysis highlighted dysregulation of cell adhesion and extracellular matrix pathways, linked to changes in histo-molecular gradient proportions between anatomic sites. Methylome analysis revealed contribution of epigenetic mechanisms in two patients. Finally, significant changes in the expression of immune mediators and genes related to immunological synapse, as well as differential infiltration of immune populations in the tumor environment were observed and led to a switch from a hot to a cold immune profile in three patients. Conclusions:This comprehensive analysis reveals patient-dependent spatial intra-tumor heterogeneity at the genetic, transcriptomic and epigenetic levels and in the immune landscape of the tumor microenvironment. Results support

  Study EGAS00001005328

• International Multi-Center ADHD Gene Project (IMAGE) II Case Sample

  This sample represents a collection of cases across a range of sites. All of these samples were ascertained for ADHD with most meeting criteria for combined type ADHD. The collection sites span Europe and America. Further details on the source and inclusion and exclusion information can be found in Neale et al. "Case-Control Genome-Wide Association of Attention-Deficit / Hyperactivity Disorder" J Am Acad Child Adolesc Psychiatry. 2010 September; 49(9): 906-920 PMID20732627. For online access to this manuscript see: PMC2928577.

  Study phs000407

• Endometrial Cancer Association Consortium - OncoArray Genotypes

  The data come from 9 studies participating in the Endometrial Cancer Association Consortium (ECAC). ECAC data included in this dbGaP submission include OncoArray data from 4486 endometrial cancer cases genotyped at the Center for Inherited Disease Research (CIDR). Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in O'Mara et al, Identification of nine new susceptibility loci for endometrial cancer. Nature Communications (PMID:30093612).

  Study phs001885

• Genome-Wide Analysis of Aberrant Position and Sequence of Plasma DNA Fragment Ends in Patients With Cancer

  This study investigated fragmentation characteristics in plasma cell-free DNA and evaluated the relevance of such analysis for cancer diagnostics. Specifically, we performed whole genome sequencing (WGS) of healthy individuals and cancer patients, and evaluated genome-wide coverage and sequences surrounding fragment ends. This was a retrospective study of archived plasma samples. The WGS data are available through this submission. Detailed study design and findings were published in Budhraja et al. Science Translational Medicine 2023.

  Study phs003170

• Testicular large B-cell lymphoma is genetically similar to PCNSL and distinct from nodal DLBCL

  Next generation sequencing (NGS) data analyzed in Rivas-Delgado, López, et al. HemaSphere 2024. Single nucleotide variants (SNVs) and short insertions /deletions (indels) were evaluated in 42 samples using a B-cell malignancy-oriented targeted panel covering 115 genes (SureSelectXT, Agilent Technologies and sequenced in a MiSeq instrument (Illumina; 2x150bp; mean coverage of 599x). The NGS data of 39 samples is provided here. The 3 additional samples were previously published. Please, see the original publication for additional details.

  Study EGAS50000000521

• Expression quantitative trait loci influence DNA damage-induced apoptosis in cancer

  The analysis of e2QTL allows for the identification of context-specific eQTL effects (Kim-Hellmuth et al. (2017), PMID: 28814792). To evaluate how inter-individual genetic variability influences the regulation of DNA damage-induced apoptosis, we performed e2QTL analysis of CD8+ T cells from 461 healthy European participants stimulated with high doses of 5 different carcinogens. These include Methyl-methanesulfonate (MMS), tert-butyl-hydroperoxide (TBOOH), benzo(a)pyrene-7,8-diol-9,10-epoxide (BPDE), 4-hydroxycyclophosphamide (HC) and UVC radiation.

  Study EGAS50000000666