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• Whole Exome Sequencing of Bipolar cases, matched controls at Broad Inst on a cohort from Netherlands

  This research project was a collaboration between VU and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 943 Bipolar case/control samples from collaborators in the Netherlands. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and the samples were sequenced on Illumina HiSeqX machines producing cram files

  Dataset EGAD50000000619

• Uterine leiomyoma: DNA methylation, chromatin activity and gene expression

  In this study, we observed the effects of different uterine leiomyoma driver mutations to tumor DNA methylation, chromatin activity and gene expression, to form a comprehensive view on the epigenetic consequences of the mutations.

  Study EGAS00001004499

• Deep sequencing of the gut microbiome from 946 healthy donors of the Milieu Intérieur cohort

  In this study, we aim to determine, in a thousand healthy donors, how the profile and dynamics of the gut microbiome are affected by host factors such as sex, age and lifestyle parameters.

  Study EGAS00001004437

• Genetic_factors_underlying_premature_coronary_heart_disease_in_patients_with_normal_coronary_arteries

  The study will analyse by exome sequencing 42 Greek patients with premature MI and no vessel disease to identify genetic factors underlying this condition.

  Study EGAS00001000133

• Accurate mutation detection in leukemia by re-sequencing a cancer gene set

  With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of cancer genes across a patient cohort with limited processing time. Here, we re-sequenced a set of cancer genes in T-cell acute lymphoblastic leukemia (T-ALL) using the Roche/454 technology coupled with Nimblegen sequence capture. First, we investigated how a maximal sensitivity and specificity of mutation detection can be achieved through a benchmark study. We tested nine combinations of different mapping and variant-calling methods, varied the variant calling parameters, and compared the predicted mutations with a large independent validation set obtained by capillary re-sequencing. We found that the combination of two mapping algorithms, namely BWA-SW and SSAHA2, coupled with the variant calling algorithm Atlas-SNP2 yields the highest sensitivity (95%) and the highest specificity (93%). Next, we applied this analysis pipeline to identify mutations in a set of 58 cancer genes, in a panel of 18 T-ALL cell lines and 15 T-ALL patient samples. We confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN. Interestingly, we also found mutations in several cancer genes that had not been linked to T-ALL before, including JAK3. Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4. In conclusion, we established an optimized analysis pipeline for Roche/454 data that can be applied to accurately detect gene mutations in cancer, which led to the identification of several new candidate T-ALL driver mutations.

  Study EGAS00001000268

• Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors

  Cell-free tumour-derived DNA (ctDNA) allows non-invasive monitoring of various cancers but its utility in renal cell cancer (RCC) has not been well established. A combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n=90) with various renal tumour subtypes, were used to determine ctDNA content in plasma and urine. Our data revealed lower plasma ctDNA levels in RCC relative to other cancers, with untargeted detection of ~33% for both cohorts. A highly sensitive personalised approach, applied to plasma and urine from select patients (n=22), improved detection to ~50%, including in patients with early stage and even benign lesions. A machine-learning based model, applied to untargeted data, predicted this detection, potentially offering a means of triaging patient samples for personalised analysis. We observed that plasma, and for the first time, urine ctDNA may better represent tumour heterogeneity than a single tissue biopsy. Longitudinal sampling of >200 plasma samples revealed that ctDNA can track disease course. These data highlight low ctDNA levels in RCC but indicate potential clinical utility provided improvement in isolation and detection approaches.

  Study EGAS00001003530

• Copy number and mutation profiling of Stage 1 epithelial ovarian cancer biopsies

  This project aims at characterizing the genome-wide copy number profile and the variant profile of 139 genes om the five major histotytpes of early-stage (stage I) epithelial ovarian cancer (EOC), to provide insight in the the aethiology and development of the disease.

  Study EGAS00001004961

• A study of resistance to novel coronavirus infection in health care workers

  There have been cases of what appear to be nosocomial infections among healthcare workers at several hospitals. The infected healthcare workers were assumed to have contracted the disease through close contact with infected patients. However, we confirmed at each medical institution that there were many healthcare workers who had apparently had closer contact with infected patients than with infected patients, but had not contracted the disease. Thus, the purpose of this study was to clarify the internal factors that make individuals less susceptible to novel coronavirus infection and their stress tolerance, and to establish a system that contributes to the appropriate allocation of healthcare workers and the creation of a system that can more safely deal with this disease in the future.

  Study JGAS000562

• Genetic and Genomic Stability Across Lymphoblastoid Cell Line Expansions

  This study was focused on exploring genetic and genomic stability across cell line expansions. We used DNA and cell lines sampled from six apparently healthy research participants. We assayed genome-wide genetic variants and inferred structural variants for DNA extracted from blood, from transformed cell cultures, and from three generations of expansions.

  Study phs001650

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Study EGAS00001007182

• Resolution of tumour cell populations enhances specificity of treatment options for precision cancer medicine

  This dataset comprises FASTQ files for single-cell RNA-seq and single-cell ATAC-seq data. These data were generated using 10x Genomics' multiome kit. In this cohort, there are 25 samples from 17 human cancer patients.

  Dataset EGAD00001015782

• Biomarker Data Subset

  This dataset contains data for CBC counts and absolute protein abundance measurements from ELISA experiments.

  Dataset EGAD00001011163

• Swedish Bipolar Disorder exome sequencing (SWEBIC)

  This research project was a collaboration between the Karolinska Institute and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 5340 SWEBIC Bipolar case samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000001123

• Whole-genome sequencing of the parental tumor and established organoids from a patient with gastric-type cervical adenocarcinoma

  This study aims to evaluate the genetic characteristics of patient-derived organoids established from gastric-type cervical adenocarcinoma and to assess their similarity to the parental tumors using whole-genome sequencing.

  Study JGAS000796

• Cellular Dynamics Upon Immune Checkpoint Inhibition

  Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet most patients experience limited or no clinical benefit. To elucidate the mechanisms of response and resistance, we analyzed single-cell RNA-sequencing data from 141 patients across multiple cancer types and ICI treatment modalities, with longitudinally paired samples. Using a robust, integration-free deep phenotyping framework, we annotated 876,410 cells into 80 granular states. We identified consistent compositional changes in 17 cell subtypes following ICI treatment, including enhanced adaptive immune responses and reduced interferon-responsive cells. Co-regulated cell communities within the tumor microenvironment (TME) highlighted coordinated interplay between immune and non-immune components. Importantly, we discovered two distinct patient groups with divergent TME dynamics post-treatment: responders showed expansion of naive lymphocytes, while non-responders exhibited increased immune-experienced/suppressive cells. This dichotomy offers a potential predictive biomarker for patient stratification. Our comprehensive analysis of TME dynamics during ICI treatment advances understanding of response mechanisms and personalized cancer immunotherapy.

  Study EGAS50000000459

• Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer

  Mismatch repair deficient colorectal cancers have high mutation loads and many respond to immune checkpoint-inhibitors. We investigated how genetic and immune landscapes co-evolve in these tumors. All cases had high truncal mutation loads. Driver aberrations showed a clear hierarchy despite pervasive intratumor heterogeneity: Those in WNT/βCatenin, mitogen-activated protein kinase and TGFβ receptor family genes were almost always truncal. Immune evasion drivers were predominantly subclonal and showed parallel evolution. Pan-tumor evolution, subclonal evolution, and evolutionary stasis of genetic immune evasion drivers defined three MMRd CRC subtypes with distinct T-cell infiltrates. These immune evasion drivers have been implicated in checkpoint-inhibitor resistance. Clonality and subtype assessments are hence critical for predictive immunotherapy biomarker development. Cancer cell PD-L1 expression was conditional on loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and likely contributes to the high recurrence risk of MMRd CRCs with impaired CDX2 expression.

  Study EGAS00001005769

• Timing the Philadelphia chromosome and trajectory to chronic myeloid leukaemia

  We sequence >1000 whole genomes from 9 patients with CML, providing the largest sequencing dataset for this cancer. We reconstruct phylogenetic trees using somatic mutations and infer BCR::ABL1 timing and tumour growth rates. We correlate mutation landscapes and clonal trajectories with clinical features.

  Dataset EGAD00001015353

• Therapeutic Resistance to PI3K-alpha Inhibitors

  We have studied the tumor genomic evolution in a patient with metastatic breast cancer bearing an activating PIK3CA mutation. The patient was treated with the PI3Kα inhibitor BYL719 and achieved a lasting clinical response on BYL719, but eventually progressed to treatment and died shortly thereafter. A rapid autopsy was performed and a total of 14 metastatic lesions were collected for further analysis. In order to identify possible genetic determinants of acquired resistance to PI3Kα inhibition, we took a three-step approach. First, we examined both the primary tumor (before BYL719 treatment) and the new lung metastasis by whole genome sequencing (DNA from the spleen was used as a normal control). Then, we analyzed the primary tumor, lung metastasis, and the peri-aortic lesion that remained stable (responding) at the time of progression to BYL719 therapy by whole exome sequencing. Finally, to confirm and expand our findings, we sequenced the primary tumor and all the metastatic lesions to >500-fold coverage using a custom targeted deep-sequencing assay, MSK-IMPACT. Using this 3-step approach, we have demonstrated that patient’s lesion underwent parallel genetic evolution at multiple metastatic sites with different PTEN genomic alterations leading to a convergent PTEN- null phenotype resistant to PI3Kα inhibition. In order to expand our observations, we analyzed paired samples (pre-treatment and at progression) from six additional patients enrolled in the BYL719 trial. Acquired bi-allelic loss of PTEN was found in one additional patient treated with BYL719 whereas in two patients PIK3CA mutations present in the primary tumor were no longer detected at the time of progression. To functionally characterize our findings, inducible PTEN knockdown in sensitive cells resulted in resistance to BYL719, while simultaneous PI3K-p110β blockade reverted this resistance phenotype, both in cell lines and in PTEN-null xenografts derived from our patient. We conclude that parallel genetic evolution of separate sites with different PTEN genomic alterations leads to a convergent PTEN-null phenotype resistant to PI3Kα inhibition.

  Study EGAS00001000991

• Dataset-linking-WGS-and-WES-files-from-EGAS00001004276-via-README-for-new-study-EGAS00001005327

  This dataset contains 538 Tumor and Control WGS and WES files for samples already submitted and published in study EGAS00001004276

  Dataset EGAD00001007817

• Massively Multiplex Single-Cell Hi-C of HeLa Cells

  In this study, we developed a massively multiplexed, single-cell Hi-C protocol to study the chromosomal architecture of single HeLa cells.

  Study phs001269

• Clonal hematopoiesis in metastatic urothelial and renal cell carcinoma

  This study aimed to determine the prevalence and clinical relevance of clonal hematopoiesis in metastatic urothelial and renal cell carcinoma.

  Study EGAS50000000870

• This data consists of iPSC derived model systems stimulated with different media.

  This data consists of iPSC derived model systems stimulated with different media (where possible from the top/bottom separately) to provide insight into which more accurately reflects the human gut environment.

  Dataset EGAD50000001918

• Exome_sequencing_of_Bilateral_Anophthalmia_cases__Pilot_Study_

  This pilot study aims to generate pilot data to inform future study designs by resequencing the whole exomes of 10 unrelated individuals diagnosed with Bilateral Anophthalmia.

  Study EGAS00001000356

• NICHD Genomic and Proteomic Network for Preterm Birth Research (GPN)

  We performed genome-wide association studies (GWAS) to study the Spontaneous Preterm birth (SPTB). Maternal and neonatal DNA from 743 SPTB (20 to and less than 34 weeks), and 752 controls (39 to and less than 42 weeks) who fully consented for public research usage were collected from participants in several clinical centers in Alabama, Illinois, New York, North Carolina, Rhode Island, Texas, and Utah. Cases were 1:1-matched with controls according to race/ethnicity (White, Hispanics, African Americans, and Others), maternal age (<20, 20-29, 30-39, 40+), and parity (yes or no). To determine the case-control status for each participant, a Gestational Age (GA) was determined. DNA samples were taken from blood or saliva if blood was not available. Automated DNA extractions were performed on the Qiagen M48 robot, and samples were organized in 96-well plates with barcoding and sample tracking systems. Subsequent manipulations were performed on the Biomek FX liquid handling workstation with 96-channel pipetting. DNA quantitation was performed by dye-based assay on a Molecular Devices SpectraMax Plus plate reader. Samples were genotyped using Affymetrix Genome-Wide Human SNP Array 6.0. This work was conducted at the Microarray Facility at the University of Pennsylvania. Patient data were collected through chart reviews and patient interviews, which included Demographic information (parental age, race, ethnicity, etc.); Medical history (pre-pregnancy weight, height, medications, STD history, medical conditions, etc.); Social history (marital status, years of education, alcohol use and tobacco use); Obstetrical history including outcome of all prior pregnancies and dates of termination; History of preterm labor or premature rupture of membranes symptoms, evaluation or hospitalization for those symptoms in current pregnancy; Medications taken during current pregnancy; History of cervical evaluation (manually or ultrasonographically) or fetal fibronectin measurements; Pregnancy complications; Labor (type, indications, membrane status, and induction method); Delivery type and indications for cesarean section; Neonatal outcome (sex, weight, length, Apgar score, neonatal complications, admission to intensive care unit, etc.); and Maternal family history of SPTB.

  Study phs000714

• snRNA-seq data of 11 regionally sampled GBM tissue for 4 patients

  This dataset contains snRNA-seq data of 11 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed in an unbiased manner without any sorting procedure. Nuclei were dissociated from frozen tissue using Chromium Nuclei Isolation Kit. Nuclei barcoding, cDNA preparation, and library construction were performed following the Evercode WT or WT mini User Manual, by combinatorial barcoding to assign a unique barcode to each cell.

  Dataset EGAD50000000778