Search Results - EGA European Genome-Phenome Archive

Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and &gt;124,000 in silico alterations and evaluated the methodology in &gt;2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) &gt;97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p &lt; 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) &gt;99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of &lt;5% and average PPA &gt;99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited &gt;98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

Study EGAS00001005556

High-resolution testing of ctDNA dynamics predicts survival in metastatic NSCLC

One of the great challenges of therapeutic oncology is determining who might achieve survival benefit from a particular therapy. Circulating tumor DNA (ctDNA) provides real-time assessments of patient prognosis and response to treatment using a simple blood draw. While ctDNA positivity is established as a poor prognostic factor, studies on longitudinal ctDNA dynamics have been small and non-randomized, with ctDNA assessments done at disparate time points. To address this, we performed high-sensitivity longitudinal ctDNA testing in 466 patients across 5 time points (1,954 samples total) in a randomized phase III study comparing different chemotherapy-immunotherapy combinations. We leverage machine learning to jointly model multiple ctDNA metrics to predict overall survival in a training/testing framework. _ . Treatment initiation correlated with reductions in ctDNA levels, and training of our machine learning model suggests that assessment of ctDNA dynamics at C3D1 (cycle 3 day 1) of chemo-IO treatment may be optimal to predict OS. The model performs well in the hold-back test data, enabling stratification of patients with Stable Disease (SD) into high-risk vs low-intermediate-risk (HR = 3.2 [2.0-5.3], p <0.001; median 7.1 versus 22.3 months respectively); similarly, the model stratifies patients with a Partial Response (PR) (HR =3.3 [1.7-6.4], p <0.001; median 8.8 versus 28.6 months). Importantly, the model validates well in an external cohort of patients in a different treatment setting and assayed with a different ctDNA technology, in which model predictions similarly identified high-risk patients (OS HR=3.73 [1.83-7.60], logrank p=0.00012). Simulations of clinical trial scenarios employing our ctDNA model further suggest that early ctDNA testing outperforms early radiographic imaging for predicting trial outcomes (increasing the rate of ‘True Go’ decisions by 5.2 - 22.8% depending on the drug combination). Overall, we show that measuring ctDNA dynamics during the course of therapy dramatically improves patient risk stratification, and may provide a means to differentiate between competing therapies at an early time point during clinical trials.

Study EGAS00001006703

ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA

Background Liquid biopsies, and the dynamic tracking of somatic mutations within circulating tumour DNA (ctDNA) can provide insight into the dynamics of cancer evolution and the intra-tumour heterogeneity that fuels treatment resistance. However, identifying and tracking dynamic changes in somatic copy-number alterations (SCNAs), which have been associated with poor outcome and metastasis, using ctDNA is challenging. Pancreatic adenocarcinoma is a disease which has been considered to harbour early punctuated events in its evolution, leading to an early fitness peak, with minimal further subclonal evolution. Methods To interrogate the role of SCNAs in pancreatic adenocarcinoma cancer evolution, we applied whole-exome sequencing of 55 longitudinal cell-free DNA (cfDNA) samples taken from 24 patients (including 8 from whom a patient-derived xenograft (PDX) was derived) with metastatic disease prospectively recruited into a clinical trial. We developed a method, Aneuploidy in Circulating Tumour DNA (ACT-Discover), that leverages haplotype phasing of paired tumour biopsies or PDXs to identify SCNAs in cfDNA with greater sensitivity. Results SCNAs were observed within 28 of 47 evaluable cfDNA samples. Of these events, 30% could only be identified by harnessing the haplotype-aware approach leveraged in ACT-Discover. The exceptional purity of PDX tumours enabled near-complete phasing of genomic regions in allelic imbalance, highlighting an important auxiliary function of PDXs. Finally, although the classical model of pancreatic cancer evolution emphasises the importance of early, homogenous somatic events as a key requirement for cancer development, ACT-Discover identified substantial heterogeneity of SCNAs, including parallel focal and arm-level events, affecting different parental alleles within individual tumours. Indeed, ongoing acquisition of SCNAs was identified within tumours throughout the disease course, including within an untreated metastatic tumour. Conclusions This work demonstrates the power of haplotype phasing to study genomic variation in cfDNA samples and reveals undiscovered intra-tumour heterogeneity with important scientific and clinical implications. Implementation of ACT-Discover could lead to important insights from existing cohorts, or underpin future prospective studies seeking to characterise the landscape of tumour evolution through liquid biopsy.

Study EGAS00001007077

Starr County Health Studies' Genetics of Diabetes Study

An initial observation in the 1970s that Starr County, Texas, had the highest diabetes-specific mortality of any of the 254 Texas counties led to the establishment of a field office in Rio Grande City, Texas (the county seat of Starr County) and the initiation of a series of studies to understand the epidemiology and genetics of type 2 diabetes, its complications and related conditions in this predominantly (97%) Mexican American population. The field office opened in February 1981 and has operated continuously since then. During this time, three systematic surveys of the population have been conducted as well as family and longitudinal studies. Culturally sensitive diabetes education programs have been developed and implemented and also a weight loss intervention. In total, more than 23,000 Mexican American individuals have been examined with more than 200,000 aliquots of biological specimens stored. Collectively, these studies are known as the Starr County Health Studies. The present Genetics of Diabetes Study has the goal of identifying loci/alleles that underlie susceptibility to type 2 diabetes in this high risk population using genome wide markers and association testing. The study makes use of two primary resources that have been developed in order to identify 1,000 type 2 diabetes cases and 1,000 disease free controls. In the first instance we have identified a subset of unrelated cases from the total cases that we have identified. Where multiply affected sibships were available, the youngest onset case with detailed phenotyping (including assessment of diabetic retinopathy) was selected. Controls came from a recent survey to establish a representative sample of the Starr County population. Blocks were randomly selected, households on selected blocks enumerated and one individual randomly selected from each household for a detailed examination. The examination included an oral glucose tolerance test. Those included as controls are those with no prior diagnosis of diabetes and a negative oral glucose tolerance test. This collection of cases and controls provides the opportunity to identify susceptibility loci for type 2 diabetes and its complications, specifically diabetic retinopathy and albuminuria. The data set also allows the examination of impaired fasting glucose and impaired glucose tolerance. The samples are split between those born in the United States and those born in Mexico and this gives a natural contrast for examining genotype and environmental interactions. It is anticipated that the understanding that will come will lead to strategies for delaying and preventing the onset of diabetes and its complications.

Study phs000143

High density copy number analysis and whole exome sequencing of unselected chronic lymphocytic leukemia cases and of paired chronic lymphocytic leukemia and Richter Syndrome cases

Analysis of the chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational activation The pathogenesis of chronic lymphocytic leukemia (CLL), the most common leukemia in adults, is still largely unknown since the full spectrum of genetic lesions that are present in the CLL genome, and therefore the number and identity of dysregulated cellular pathways, have not been identified. By combining next-generation sequencing and copy number analysis, we show here that the typical CLL coding genome contains less than 20 clonally represented gene alterations/case, including predominantly non-silent mutations and fewer copy number aberrations. These analyses led to the discovery of several genes not previously known to be altered in CLL. While most of these genes were affected at low frequency in an expanded CLL screening cohort, mutational activation of NOTCH1, observed in 8.3% of CLL at diagnosis, was detected at significantly higher frequency during disease progression toward Richter transformation (31.0%) as well as in chemorefractory CLL (20.8%). Consistent with the association of NOTCH1 mutations with clinically aggressive forms of the disease, NOTCH1 activation at CLL diagnosis emerged as an independent predictor of poor survival. These results provide initial data on the complexity of the CLL coding genome and identify a dysregulated pathway of diagnostic and therapeutic relevance. Genetic Lesions associated with Chronic Lymphocytic Leukemia transformation to Richter Syndrome Richter syndrome (RS) derives from the rare transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, most commonly of the diffuse large B cell type (DLBCL). The molecular pathogenesis of RS is only partially understood. By combining whole-exome sequencing and copy-number analysis of 9 CLL-RS pairs and of an extended panel of 43 RS cases, we show that this aggressive disease typically arises from the predominant CLL clone by acquiring an average of ~20 genetic lesions/case. RS lesions are heterogeneous in terms of load and spectrum among patients, and include those involved in CLL progression and chemorefractoriness (TP53 disruption and NOTCH1 activation) as well as some not previously implicated in CLL or RS pathogenesis. In particular, disruption of the CDKN2A/B cell cycle regulator locus is associated with ~30% of RS cases. Finally, we report that the genomic landscape of RS is significantly different from that of de novo DLBCL, suggesting that they represent distinct disease entities. These results provide insights into RS pathogenesis, and identify dysregulated pathways of potential diagnostic and therapeutic relevance.

Study phs000364

Lineage Plasticity and Immune Cell Heterogeneity Are Coordinately Dysregulated Through Changes in FOXA1 Expression in Bladder Cancers with Squamous Differentiation

We performed whole exome sequencing (WES) of paired, macrodissected regions of urothelial carcinoma (UC), not otherwise specified (NOS-UC) and squamous differentiation (SqD) from 21 bladder tumors in which distinct and separable NOS-UC and SqD regions were present (total 42 exomes, in addition to matched normal exomes). Mean tumor mutational burden (TMB) was higher in the SqD versus the NOS-UC regions. Consistent with the higher TMB, the SqD regions also had a higher neoantigen burden than the patient-matched NOS-UC regions. The SqD regions also exhibited higher karyotypic complexity with a higher median ploidy relative to the paired NOS-UC regions. Phylogenetic analysis of the WES data confirmed that the morphologically distinct regions of all 21 tumors arose from a shared precursor with a median of 68 (range 16 – 852) non-synonymous mutations shared between the NOS-UC and SqD regions, and the overall data were indicative of early branched evolution. As whole exome sequencing did not identify a shared mutational alteration or genomic signature unique to the SqD or NOS-UC components, we therefore performed expression profiling of separable SqD and NOS-UC regions of 12 bladder tumors from the WES cohort with RNA quality sufficient for whole transcriptome RNA-sequencing (RNAseq, total of 24 regions). Based on centroid clustering analysis of expression data, all 12 regions of SqD were basal-squamous subtype based on the TCGA molecular classification schema. Notably, 8 of the NOS-UC regions were also basal-squamous subtype, with only four pairs exhibiting discordant transcriptional subtypes (three NOS-UC regions were luminal-infiltrated, one luminal-papillary). To better quantify differences in the transcriptional profiles of the paired NOS-UC and SqD regions, we used single sample gene set enrichment analysis (ssGSEA) to assess for enrichment of luminal or basal-squamous gene expression. ssGSEA analysis revealed that the SqD regions expressed higher levels of basal-squamous genes based on the BASE47 gene set and UPK/KRT gene sets; whereas the matched NOS-UC regions expressed higher levels of luminal genes. These differences in the levels of expression of basal and luminal genes were observed even in cases in which both the NOS-UC and SqD regions were basal-squamous subtype based the TCGA molecular classification schema. Exomes from eight patients in this study have previously been deposited in dbGaP: accession number phs001783 as part of the study "Exome Recapture and Sequencing of Prospectively Characterized Clinical Specimens From Cancer Patients".

Study phs002357

Converging and evolving immuno-genomic routes towards immune escape in breast cancer

Data access committe for the project: Converging and evolving immuno-genomic routes towards immune escape in breast cancer

Dac EGAC50000000074

Thoracic Patient-Derived Xenografts

Targeted capture sequencing of 341 cancer associated genes in thoracic patient-derived xenografts.

Study phs001192

TOPARP-B patient cell-free DNA WGS

Sequencing files for TOPARP-B patients as described in manuscript

Study EGAS50000000280

Exome_sequencing_Parkinson_s_disease_patients

In this project we will sequence the exomes of 250 patients with Parkinson's disease

Study EGAS00001000151

McGill EMC Release 4 in tissue "skeletal muscle tissue"

Dataset EGAD00001001288

Premalignant SOX2 in ovarian cancer patients

Whole Genome Sequencing data set for the study "Premalignant SOX2 in ovarian cancer patients"

Dataset EGAD00001002734

Exome_NanoSeq__Thyroid_

Exome NanoSeq in thyroid from a number of donors, both healthy and with pathology.

Study EGAS00001007175

Targeted_NanoSeq___Thyroid

Targeted NanoSeq in thyroid from a number of donors, both healthy and with pathology.

Study EGAS00001007647

Genome-Wide Association Study of Anorexia Nervosa (Price Foundation, Klarman Family Foundation, Center for Applied Genomics at the Children's Hospital of Philadelphia, Scripps Translational Sciences Institute Clinical Translational Science Award)

Twin studies are consistent with substantial heritability in anorexia nervosa (AN), although detecting and confirming individual risk alleles has been difficult, due to small effects of single alleles and limited samples in prior studies. Methods: 1105 AN DNA samples obtained in a multisite study and 3733 pediatric patients of normal body weight were genotyped using the Illumina 610Q chip at The Center for Applied Genomics at The Children's Hospital of Philadelphia. Cases and controls were of European ancestry. Single nucleotide polymorphism (SNP) genotypes were subjected to quality control procedures, including elimination of SNPs with: call rates < 95%, minor allele frequency < 5%, and if Hardy-Weinberg equilibrium testing yielded p < 0.0001. Samples were removed if not of European ancestry or if showing cryptic relatedness. Eight AN DNA samples were deleted for low call rate, and 51 AN samples were deleted for cryptic relatedness. The statistical program, PLINK, was used to calculate a P value for each SNP passing quality control using the Cochran-Armitage trend test. The PennCNV program was used to define copy number variation (CNV). Results: We performed a genome-wide association study (GWAS) using with 1033 AN cases and 3733 controls (genomic inflation factor = 1.08). There were 11 SNPs with P<1X10-5 [(rsID, chromosome location, nearest gene, distance to nearest gene (base-pair), P value) rs6959888, 7q21.13, ZNF804B, 0, 1.63E-06; rs17725255, 20p11.23, CSRP2BP, 39396, 1.72E-06; rs10494067, 1p13.3, NTNG1, 0, 5.83E-06; rs2383378, 14q12, AKAP6, 0, 6.41E-06; rs410644, 5q14.1, SSBP2, 40462, 6.74E-06; rs4479806, 5p14.1, CDH9, 156926, 7.79E-06; rs957788, 13q33.3, FAM155A, 0, 8.11E-06; rs830998, 2q31.1, LRP2, 0, 8.68E-06; rs6782029, 3p25.3, VGLL4, 0, 9.04E-06; rs512089, 9p21.3, ELAVL2, 47984, 9.85E-06; rs3808986, 11q24.3, APLP2, 29217, 9.92E-6]. CNV analyses were performed on 1015 AN cases and 3532 controls. Overall frequencies of common or rare CNVs were similar between cases and controls. Specific rare and large (>500 kb, <1%) CNVs of interest included deletion of a large (~1.4Mbp) region of chr13q12 found in 2 AN samples and at a 10 fold lower frequency in a large sample (72,918) of subjects containing the genes SGCG, SACS, TNFRSF19, MIPEP, PCOTH, C1QTNF9B, SPATA13, MIR2276, and C1QTNF9, and an overlapping deletion and a duplication observed in 3 AN samples overlapping the CNTN6 and CNTN4 genes. Partially overlapping ~ 30 kb duplications were seen in 12 AN cases and in 1 control at the CDC5L gene on chromosome 6. Partially overlapping deletion of the 3' half of the PSTPIP1 gene was seen in 5 AN cases and no controls. Finally, a ~ 60 kb deletion of the PLEC1 gene was observed in 5 AN cases and in none of 3532 controls. Discussion: This is the first GWAS of AN. These preliminary results are consistent with absence of a major gene effect in AN. These results are consistent with genetic risk conveyed by multiple common alleles of small effect, as well as some uncommon CNVs of potentially larger effect. None of the implicated genes has a clear role in eating behavior. It must be emphasized that these results are preliminary and an additional ~ 400 AN cases will be analyzed as time and resources permit. These results require confirmation through study of independent populations of AN women.

Study phs000679

Genome-Wide Analysis of Diffuse Large B-Cell Lymphoma (De Novo and Derived from the High Grade Transformation of Follicular Lymphoma)

Version 1. Diffuse Large B-cell Lymphoma (DLBCL) represents the most common form of B-cell non-Hodgkin Lymphoma (B-NHL), accounting for ~30% of the de novo diagnoses and also arising as a frequent clinical evolution of Follicular Lymphoma (FL). The molecular pathogenesis of DLBCL is associated with multiple genetic lesions that in part distinctly segregate with individual phenotypic subtypes, suggesting the involvement of distinct oncogenic pathways. However, the lesions identified so far likely represent only a fraction of those necessary for malignant transformation. In order to characterize the entire set of structural alterations present in the DLBCL genome, we have integrated next generation whole exome sequencing analysis of 6 DLBCL cases and genome-wide high-density SNP array analysis of 72 DLBCL cases. We report here that FL and DLBCL harbor frequent structural alterations inactivating CREBBP and, more rarely, EP300, two highly related histone and non-histone acetyltransferases (HATs) that act as transcriptional co-activators in multiple signaling pathways. Overall, ~37% of DLBCL and 36% of FL cases display genomic deletions and/or somatic point mutations that remove or inactivate the HAT coding domain of these two genes. These lesions commonly affect a single allele, suggesting that reduction in HAT dosage is important for lymphomagenesis. We demonstrate specific defects in the acetylation-mediated inactivation of the BCL6 oncoprotein and activation of the p53 tumor suppressor. These results identify CREBBP/EP300 mutations as a major pathogenic mechanism shared by common forms of B-NHL, and have direct implications for the use of drugs targeting acetylation/deacetylation mechanisms. Version 2. Follicular lymphoma (FL) is an indolent, but incurable disease that, in 30-40% of cases, undergoes transformation to an aggressive diffuse large B cell lymphoma (DLBCL). The history of clonal evolution and the mechanisms that underlie transformation to DLBCL (tFL) remain largely unknown. Using whole exome sequencing and copy number analysis of 39 tFL patients, including 12 with paired sequential FL/tFL biopsies, we show that, in most cases, FL and tFL arise by divergent evolution from a common mutated precursor cell through the acquisition of distinct genetic lesions. Mutations in epigenetic modifiers (e.g., MLL2, CREBBP, EZH2, ARID1A) and anti-apoptotic genes (BCL2, FAS) were observed in 93% (36/39) and 78% (30/39) of cases, respectively, and were invariably shared between the two disease phases, suggesting an early acquisition in the common mutated precursor. Conversely, the development of tFL is associated with deregulation of genes involved in the control of cell proliferation, cell cycle progression and DNA damage responses (CDKN2A/2B, MYC, TP53), as well as with an aberrant activity of the somatic hypermutation mechanism. Finally, we show that the genomic profile of tFL shares significant similarities with that of germinal center B-cell type de novo DLBCL, but also displays unique combinations of altered genes that may explain the dismal clinical course of tFL.Version 3. This version includes thirty-five additional de novo DLBCL samples, newly diagnosed, and their paired normal DNA from previously untreated patients, which were analyzed by whole exome sequencing (n=27T and 25N), whole genome sequencing (8T and 10N), and/or targeted HLA-next generation sequencing (n=26T/N pairs) in order to identify genetic alterations associated with loss of surface MHC-II expression.

Study phs000328

Common Fund (CF) Genotype-Tissue Expression Project (GTEx)

Lay Description The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases. GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues, and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues from the same person in such a large population as planned for GTEx. Scientific Description Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression. The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database and tissue biobank in which to study the relationship between genetic variation and gene expression and other molecular phenotypes in reference/non-diseased tissues. The ultimate resource will include approximately 960 post-mortem donors with several dozen tissues from each, a resource large enough to study both cis- and trans- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. To request biosamples, please see the Biobank page for more information. GTEx was initially funded as a 2-year pilot project by the NIH Common Fund (CF) in 2010, and has been scaled up after demonstration of feasibility. The project will collect and analyze RNA levels in many different human tissues and each donor will be characterized for germline genetic variation through dense genotyping arrays and sequencing of either whole exomes or whole genomes. By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. A subset of banked tissue samples will also be analyzed for other molecular phenotypes, such as DNA methylation, DNaseI hypersensitivity sites, and proteomics. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease. All GTEx releases since Version 5 follow the NIH Genomic Data Sharing (GDS) Policy whereby there are no restrictions on use or publication after release. Additional information about the GTEx Data Release and Publication policy can be found on the GTEx Data Portal at www.gtexportal.org.

Study phs000424

Whole Genome Scan for Pancreatic Cancer Risk in the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium (PanScan)

Within the framework of the NCI-sponsored Cohort Consortium, investigators from 12 prospective epidemiologic cohorts formed the Pancreatic Cancer Cohort Consortium in 2006. This study, also known as "PanScan", is funded by the National Cancer Institute (NCI) and involves conducting a genome-wide association study (GWAS) of common genetic variants to identify markers of susceptibility to pancreatic cancer. In 2007, the study was expanded to include 8 case-control studies. The study team includes scientists from the cohorts comprising the Consortium, the NCI and the Pancreatic Cancer Case Control Consortium (PanC4). PanScan I and II were conducted in 12 cohort studies and 8 case-control studies, leading to the discovery of four novel regions in the genome associated with risk for pancreatic adenocarcinoma. The third phase of PanScan (PanScan III) was conducted using recently identified incident pancreatic cancer cases drawn from fourteen cohorts from the cohort consortium, including nine prospective cohorts who participated in PanScan I, and five newly joined cohorts. The nine cohort studies that participated in PanScan I and had new genotyping of cases in PanScan III include ATBC, CPS-II, EPIC, HPFS, NHS, PHS, PLCO, SMWHS, and WHI; the five newly joined cohort studies include the Agricultural Health Study (AHS), the Multiethnic Cohort Study (MEC), the Melbourne Collaborative Cohort Study (MCCS), the Vitamins and Lifestyle Study (VITAL), and Selenium and Vitamin E Cancer Prevention Trial (SELECT). In addition to the cases from cohorts, we also included cases from the Gastrointestinal Cancer Clinic of Dana-Farber Cancer Institute Study (DFCI-GCC); from the University Hospital in Heidelberg, Germany, which is part of a larger European clinical case-control study (PANDoRA); and from clinic-based cases from eastern Spain (PANKRAS-II). The dbGaP datasets available include all subjects previously made available from PanScan I and II, plus 1,582 new incident pancreatic cancer cases of European descent from prospective cohorts, case-control studies or case series (genotyped as part of PanScan III). Also included are 61 pancreatic cancer cases and 67 control subjects from PanScan I as well as 173 pancreatic cancer cases from PanScan III of Asian ancestry from the Shanghai Men's and Women's Health Study (Supplemental Table 10, Wolpin et al. (Nat Genet, 2014)). The control population used in the analysis for the Wolpin et al. manuscript included cancer-free individuals from the prospective cohorts that contributed pancreatic cancer cases to PanScan III and controls from the Spanish Bladder Cancer SBC/EPICURO study that were previously genotyped using the OmniExpress, Omni 1M or Omni 2.5M SNP arrays. The data from these control subjects were posted to dbGaP under the GWAS in which they were initially genotyped and will not be made available in duplicate under this dbGaP study.The summary statistics for PanScan I-III were generated as detailed in Wolpin BM. et al., Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer, Nature Genetics 2014; 46(9):994-1000 (https://www.nature.com/articles/ng.3052), and Klein, A. et al., Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer, Nature Communications, 2018;9(1):556 (https://www.nature.com/articles/s41467-018-02942-5). The dataset includes results from an association study of 5,117 individuals diagnosed with pancreatic ductal adenocarcinoma (PDAC) and 8,845 control individuals, or a total of 13,962 subjects of European ancestry (as compared to the genotype and phenotype information under this project that includes 9,437 individuals (PanScan I and II PDAC case and control individuals and PanScan III PDAC cases only). This is due to the fact that PanScan III “borrowed” GWAS data from control individuals genotyped separately from the PanScan GWAS project and are therefore not included as raw genotypes in phs000206.v5.p3. Association analysis was performed separately for PanScan I-II and PanScan III, followed by a meta-analysis of the two datasets. Results were filtered based on a minor allele frequency (MAF) < 0.01, an imputation INFO score < 0.3 and a heterogeneity P-value < 1x10-10 leaving a total of 9,758,390 variants. Columns in the summary statistics dataset are as follows: ID: variant rsIDChr: chromosome numberPosition: position in the chromosome, genome build GRCh37/hg19MarkerName: variant identifierAllele1: reference alleleAllele2: alternative alleleFreq1: allele frequency for allele2FreqSE: standard error of the allele frequencyMinFreq: the minimal allele frequency across studiesMaxFreq: the max allele frequency across studiesEffect: effect size for allele2StdErr: standard errorP-value: meta-analysis p-valueDirection: summary of effect direction for each studyHetISq: I^2 statistic which measures heterogeneity on scale of 0-100%HetChiSq: chi-squared statistic in simple test of heterogeneityHetDf: degrees of freedom for heterogeneity statisticHetPVal: P-value for heterogeneity statistic

Study phs000206

LLDeep DAG2+ scRNA-seq in PBMCs

Single cell transcriptomics of PBMCs of 47 donors from the Lifelines Deep cohort (general population, Northern part of the Netherlands). Cells of five or six different donors were pooled together in one sample pool, resulting in eight different sample pools. In total, 28.855 cells were captured and their transcriptomes were sequenced to an average depth of 74k. Genotype data was available for each donor, which allowed us to use the Demuxlet method that uses variable SNPs between the pooled individuals to determine which cell belongs to which individual. Since genotype information is lacking of 2 individuals, the transcriptome of only 45 individuals could be retrieved.

Dataset EGAD00010001315

Enhancing OSCC Prediction: The Prognostic Power of WPOI and Tumor Budding, and the Limited Impact of Molecular Resection Margins

This dataset contains sequences with results of mutations observed in patients with oral squamous cell carcinoma. Mutations were detected by NGS in tumor tissue, tumor margins, and peripheral blood as a healthy control. Study was using a panel of 88 cancer-related genes, which were selected based on a literature search.

Study EGAS50000000074

Genomic Sequencing of Solitary Fibrous Tumors

Solitary fibrous tumors (SFTs) are rare mesenchymal tumors that can be benign or malignant. In this study, we sequenced and analyzed the exomes of 17 SFT matched tumor and normal pairs. This study appertains to a large endeavor to characterize cancers as part of the Slim Initiative for Genomic Medicine in the Americas (SIGMA) project.

Study phs000568

Drop-BS: High-Throughput Single-Cell Bisulfite Sequencing on a Microfluidic Droplet Platform

We present a high-throughput droplet-based bisulfite sequencing library preparation platform. Our protocol allows the production of a BS library of 2,000-10,000 single cells within 2 days. In addition to validation using mixed cell lines, we also used the technology to profile various cell types in mouse and human brain samples.

Study phs002123

Washington University Coronary Artery Disease Study

The genetic basis of coronary artery disease in individuals of non-European ancestry is largely unknown. The Washington University Coronary Artery Disease Study (WUCADS) recruited participants of non-European ancestry with and without coronary artery disease to address this question. Whole genome sequencing in WUCADS was performed at the McDonnell Genome Institute at Washington University.

Study phs001227

RareBliss: Rare Bipolar Loci Identification Through Sequencing Study

Bipolar disorder is a complex psychiatric disease for which few causative genes have been discovered. Targeted sequencing of bipolar cases and unaffected controls was performed to elucidate the contribution of rare variants to bipolar disorder. This study included the standard exome targets as well as genes involved in synaptic function and genes previously implicated in bipolar disorder.

Study phs001358

Whole Exome Sequencing of Six Signet Ring/Plasmacytoid Variant Bladder Tumors

In this study, six plasmacytoid bladder cancers were analyzed by whole exome sequencing. The results show loss of the CDH1 gene in every sample and correlate with E-cadherin loss of expression by immunohistochemistry. A separate validation cohort of plasmacytoid samples showed loss of E-cadherin expression by CDH1 mutation or promoter hypermethylation.

Study phs001064

DCLRE1B/Apollo germline mutations associated with renal cell carcinoma

Highlights of Bories et al. article submitted to BBA - Molecular Basis of Disease: We identified 2 germline mutations in the DCLRE1B gene encoding the Apollo protein by Whole Exome Sequencing (WES) in two families with inherited clear-cell Renal Cell Carcinoma. Our study suggests a putative link between DNA repair, telomere protection and renal oncogenesis.

Study EGAS50000000216

PDX gene expression

Investigation of the anti-tumor activity of the potent, highly selective, orally bioavailable CHK1 inhibitor (CHK1i), SRA737, in both acquired PARPi-resistant BRCA1/2 mutant and CCNE1amp high-grade serous ovarian cancer (HGSOC) models. We analyzed gene expression in five patient derived xenografts (PDX) that responded to CHK1i and three PDX that had a poor response to CHK1i.

Study EGAS50000000084

scRNA-seq dataset, RCC

scRNA-seq dataset for the study "Surgery in combination with immune checkpoint therapy as an effective treatment for patients with metastatic cancer." The dataset comprises 38 samples from 19 patients, with each pair includes a baseline (BL) sample and a post-biopsy or post-surgery sample. Each sample corresponds to an R1 (read 1) and an R2 (read 2) files (.fastq.gz) for paired reads. Beside procedure (biopsy or surgery), another important phenotype is response (PR and PD in this case, no SD for these patients), included in the description of the samples. The sequencing was performed using Illumina NovaSeq 6000 platform., as seen in the experiment description.

Dataset EGAD50000000566

Sex Differences in MAGEL2 Gene Promoter Methylation in High Functioning Autism - Trends from a Pilot Study Using Nanopore Cas9 Targeted Long Read Sequencing

Using DNA extracted from peripheral blood, Cas9-targeted nanopore DNA sequencing was used to analyze MAGEL2 gene, including its entire regulatory construct (chr15:23639316-23651466), for sequence variation and 5-methyl-cytosine (5mC) modification in a cohort of adults with HFA compared to sex- and age-matched NC.

Study EGAS50000000508

Genomic characterization of a patient with AGS and CdLS transcriptomic comparison of his monocytes against healthy and disease control samples

In this study, we describe an extreme genetic phenotype of two simultaneous genetic lesions, leading to broad alterations in immunophenotype and transcriptome. Whole Exome Sequencing and RNA-Sequencing of CD14+ monocytes was performed on the case patient, and RNA-sequencing was also performed on disease (Systemic Lupus Erythematosus) and healthy controls.

Study EGAS00001007829

Personalized Treatment of Sezary Syndrome through a CTLA4:CD28 Fusion

We sequenced two tumor and one normal whole genome libraries for a Sezary syndrome patient and also sequenced RNA libraries for each tumor. We identified a novel, highly expressed CTLA4:CD28 gene fusion that is predicted to results in a leading to stimulatory T-cell signaling in the presence of an inhibitory signal.

Study phs000773

An epidemiological study examining the relationship among food, health, and genome

We conducted a cohort-based study to investigate the association between the genetic background and diet/lifestyle in 962 healthy Japanese. We analyzed the Ebetsu cohort and some participants living in Tokyo. The SNP array (Japonica Array v2) was used for genotyping. Shotgun metagenomic sequencing of fecal microbiome and metabolome of feces and blood were analyzed.

Study JGAS000678

scRNAseq: Human liver cholangiocyte organoids capture the heterogeneity of in vivo human liver ductal epithelium

Liver ductal organoids expanded in either conventional (Huch et al., 2015) or refined medium were split and seeded either in the same medium or in DM+. They were sequenced on day 10 after splitting. Droplet-based scRNA-seq was performed using the 10x Genomics Chromium Single Cell Kit v3, and libraries were sequenced on an Illumina NovaSeq 6000 S4. Raw sequencing data were processed using Cell Ranger software (v6.0.1) with the human genome reference (hg38) and gene annotation (Ensembl 98). Dataset integration and downstream analysis were mainly performed using Seurat (v4.3.0.1) with R v4.1.3 “One Push-up”.

Dataset EGAD50000001464

RNA sequencing of genetically modified human iPSCs modeling patients with autism spectrum disorders (ASD)

We generated two genetically modified iPSC lines. In each line, a single promoter variant identified in a patient with autism spectrum disorder (ASD) was introduced by using the CRISPR/Cas9 system. These mutant lines were analyzed by RNA-seq together with control lines to assess the impact of the introduced variant.

Study JGAS000651

Comprehensive molecular and clinicopathological profiling of salivary duct carcinoma

Molecular targets and predictive biomarkers for prognosis in salivary duct carcinoma (SDC) have not fully identified. We conducted comprehensive molecular profiling to discover novel biomarkers for SDC. A total of 67 SDC samples were examined with DNA sequencing of 464 genes and transcriptome analysis in combination with the clinicopathological characteristics of the individuals.

Study JGAS000534

Clonal structure and oncogenic potential of liver cirrhosis tissues.

Hepatocellular carcinoma (HCC) recurrently develops in cirrhotic liver composed of numbers of regenerative nodules (RNs). The biologic or genetic basis of RNs for hepatocarcinogenesis remains unclear at present. Thus, to uncover the basis of cirrhotic liver for multicentric tumorigenesis, we investigated the oncogenic potential of RNs in LC tissues using multi-omics analysis.

Study JGAS000134

Transcriptome analysis of adolescents and young adults with Acute Lymphoblastic Leukemia

The primary purpose of the research is identification of novel chromosome translocations in adolescents and young adults (AYA) with Acute Lymphoblastic Leukemia (ALL). We searched for novel chromosome translocations in 99 philadelphia-chromosome negative ALL cases (including 76 AYA cases) by RNA-seq using next-generation sequencers, and have discovered some novel chromosome translocations.

Study JGAS000047

Genomic Data from Patients with Advanced Rare Cancers Treated with Pembrolizumab

Rare cancers lack effective evidence-based treatments despite contributing substantially to cancer-related mortality. The goal of this study is to identify molecular biomarkers associated with response to pembrolizumab in patients with advanced rare cancers.This dataset includes genomic profiling generated from patients enrolled in an investigator-initiated phase II basket trial of pembrolizumab.

Study EGAS50000001508

Transcriptomic Data from Patients with Advanced Rare Cancers Treated with Pembrolizumab

Rare cancers lack effective evidence-based treatments despite contributing substantially to cancer-related mortality. The goal of this study is to identify molecular biomarkers associated with response to pembrolizumab in patients with advanced rare cancers.This dataset includes transcriptomic profiling generated from patients enrolled in an investigator-initiated phase II basket trial of pembrolizumab.

Study EGAS50000001509

Single-cell genotype-to-phenotype (scG2P) data of single nuclei from cell line mixing experiment and six donors

We developed Single-cell genotype-to-phenotype (scG2P) to profile mutations in driver gene hotspots and capture mRNA targets of interest, validating this assay in a cell line mixing experiment of KYSE-270, KYSE-410, and HCT-116, and applied the assay to esophageal biopsy samples from six donors.

Study EGAS50000001429

Single Cell RNASeq for ARMS tumors

6 samples from 3 mice related to Alveolar Rhabdomysarcoma. In this study, we employ scRNA-seq to analyze ARMS tumors from a conditional mouse model of ARMS. The conditional knock-in mouse model of ARMS, in which the Pax3-Foxo1 allele is activated in the skeletal muscle cell lineage via Myf6Cre (Myf6CrePax3P3Fm/P3FmTrp53F2-10/F2-10; referred to hereafter as GEMM-ARMS) has been described previously23,24. These mice also carry Cre-activated reporters, eYFP to label Pax3::Foxo1-expressing cells and dsRED2 to labels Myh2-expressing cells. Some tumors are derived from GEMM-ARMS mice, and some are allografts of GEMM-ARMS tumors into immunodeficient mice

Dataset EGAD50000002241

HipSci_Illumina 450K Methylation analysis_Healthy volunteers

The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Methylation analysis using the Infinium HumanMethylation450 BeadChip on iPS cells generated from skin biopsies from healthy volunteers.

Study EGAS00001000865

Whole exome sequencing from early stage non-small cell lung cancer patients at MDACC

The purpose of the study is to evaluate the mutational landscape and tumor mutational burden in tumor from patients with early stage non-small cell lung cancer. Mutational landscape was compared to the T cell repertoire to determine the relationship between somatic mutations and T cell response in early-stage NSCLC.

Study EGAS00001004026

Panel-based next-generation sequencing study of human liver samples.

Panel-based next-generation sequencing study of 150 human surgical liver samples from Caucasian donors with detailed medical documentation. The overall purpose of the study was to identify expression quantitative trait loci (eQTL) in human liver for genes involved in absorption, distribution, metabolism and excretion of drugs, other xenobiotics, and endogenous substances.

Study EGAS00001003426

Oesophageal_Adenocarcinoma_Organoid_Hi_C

Hi-C Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This Hi-C data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

Study EGAS00001003122

Abnormal_foetal_development_exome_trios

This project is to explore the contribution of de novo mutations to severe structural malformations diagnosed prenatally using ultrasound. These malformations include heart, CNS, renal and GI abnormalities. In this pilot project we aim to exome sequence 30 parent-foetus trios to ~50X mean coverage and identify de novo functional variants using an algorithm developed in the Hurles group

Study EGAS00001000167

Somatic_mutation_and_clonal_evolution_in_premalignant_lung_disease

In this study we aim to characterise the landscape of mutation and clonal selection in normal lung and premalignant lung disease. The study combines targeted sequencing and whole-genome sequencing of microbiopsies of lung and bronchial epithelium. The range of patients studied will include healthy individuals, both smokers and non-smokers, and patients with premalignant lung disease.

Study EGAS00001002340

Chromatin_accessability_in_cytokine_induced_immune_cell_states

We isolated T cells and monocotyes from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed K27Ac ChM sequencing to assess the chromatin activity in different cytokines treated cells. These cellular profiles were used to map risk variants to the cytokine-induced cell states relevant for autoimmune diseases.

Study EGAS00001002749

Triple_Negative_Breast_Cancer_Whole_Genome_Validations

We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. This study will use a bespoke bait set to pulldown regions of interest found in whole genome sequencing to validate mutations found.

Study EGAS00001000426

Exome sequencing of stroke cases with good or bad recovery three months after stroke

With the aim to identify rare genetic variation involved in stroke recovery, this is a pilot study on extreme phenotypes of good and bad recovery. Exome sequencing was performed on 41 and 49 samples in the bad and good recovery subset, respectively. Rare Variant association Analysis was performed on the exome sequencing results.

Study EGAS00001003463

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