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• The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

  Purpose In high-grade osteosarcoma, prognostic factors at diagnosis are insufficient for stratifying patients into relevant subgroups. Recently, a transcriptomic study developed the G1/G2 gene expression signature, in which the G2 signature was associated with unfavorable survival. An orthogonal study identified MYC amplification as an unfavorable prognostic factor using targeted next-generation sequencing. The purpose of this study was to validate the independent prognostic value and to investigate the combined prognostic value of the G1/G2 signature with, MYC amplification and/or MYC expression for survival prediction. Material and methods This study included pediatric and adolescent patients with high-grade osteosarcoma. RNA sequencing was performed in 48 patients. Whole-exome sequencing was performed in 40 patients. Gene expression signature scores, MYC amplification (defined as > 7 copies) and MYC expression levels were calculated. Multivariable Cox proportional hazards analysis was performed for event-free survival (EFS) (primary endpoint) and overall survival (OS) (secondary endpoint). Results In the full cohort, the 3-year event-free survival rate was 37%. In multivariable Cox regression analysis with metastatic disease stage (n=21, 44%) as covariate, the G2 signature and MYC expression were independently associated with worse outcomes in terms of EFS (Hazard ratio (HR) 3.32, 95% confidence interval (CI) 1.34-8.21 and HR 3.38, 95%-CI 1.71-6.66, respectively) and OS (HR 4.07, 95%-CI 1.19-13.9 and HR 2.88, 95%-CI 1.22-6.76, respectively). MYC amplification was not associated with EFS or OS in univariable analysis (HR 1.88, 95% -CI 0.74-4.77 and HR 0.79, 95%-CI 0.21-3.05, respectively). Conclusion The G2 gene expression signature and MYC expression were independently associated with unfavorable outcomes in a pediatric cohort of patients with high-grade osteosarcoma. The combined prognostic value warrants further prospective validation and could potentially serve as a stratification marker for future osteosarcoma treatment protocols.

  Study EGAS00001008073

• Genetic data of a monozygotic twin pair discordant for ALS

  We performed whole exome sequencing of a monozygotic twin pair discordant for ALS. This dataset contains two VCF files: one of the healthy twin and one of the ALS twin. Library was prepared according to Agilent SureSelectQXT Kit protocol and processed using Illumina NextSeq 550 sequencer). Fastq files were aligned on the reference human genome hg19 (GRCh37) and, for each patient, a list of variations in a VCF format file (Variant Call Format) was produced by GATK software and annotated by wAnnovar.

  Dataset EGAD50000001329

• Sequencing data for the Genomic Autopsy Study

  The .cram files of the Trio or Quad sequencing data used for generation of the genomic autopsy study. This contains a mix of genome sequencing and exome sequencing data for probands and their parents. A subset of families (n=32) did not provide consent to publicly sharing their data.

  Dataset EGAD00001009737

• Next Generation Sequencing to Predict Risk of Events from Coronary Artery Disease

  Coronary artery disease (CAD) and myocardial infarction (MI) remain the leading cause of death worldwide and in the US. In recent years, clinical studies that considered intermediate phenotypes (phenotypic or genomic data isolated between DNA and the main disease phenotype) have greatly enhanced our understanding of complex traits like CAD by enabling inference of biological networks from the combination of genetic and genomic datasets isolated from disease-relevant tissue(s). The NGS-PREDICT study used whole transcriptome sequence data generated from primary macrophages derived in vitro from venous blood that was obtained from CAD cases and non-CAD controls. This study provided a valuable resource for the validation of biomarkers identified in STARNET NGS data from macrophages obtained from patients with and without CAD. It also can be used as a reference dataset for the study of metabolic syndrome as well as other systemic inflammatory diseases.

  Study phs003883

• Childhood Cancer Data Initiative (CCDI): NCI-COG Pediatric MATCH Precision Medicine Clinical Trial

  The National Cancer Institute-Children's Oncology Group (NCI-COG) Pediatric Molecular Analysis for Therapy Choice (MATCH) trial provides a framework for biomarker-driven early phase trials of targeted therapies in pediatric and young adult cancer patients across the United States. Pediatric MATCH enrolled more than 1,300 patients with treatment-refractory cancers, offering access to molecular screening and investigational targeted therapies. To further advance this, matched diagnostic, refractory tumor, and normal samples from Pediatric MATCH cases were molecularly characterized, creating one of the largest comprehensive data sets available for childhood cancers. This analysis has the potential to provide novel insights into the genetics of refractory pediatric, adolescent, and young adult cancers, as well as inform potential therapeutic strategies. The following molecular characterization assays were performed: Tumor whole exome sequencing (WES) Tumor whole genome sequencing (WGS) Tumor RNA sequencing (RNA-seq) Blood whole exome sequencing (WES) Blood whole genome sequencing (WGS)

  Study phs002883

• Single-cell RNA sequencing of human IL-18R supported CAR T cells targeting oncofetal Tenascin C

  C.TNC-CAR.Zip18R CAR-T cells are from 2 donors and multiplexed 10x Genomics scRNA-seq were performed with a hashtag to label each sample. For tumor and CAR-T cell cocluture samples, CAR-T cells were extracted from 3 time points. The raw data are fastq format for total 20 samples considering sequencing lanes. The multiplexing information, CAR and Zip18R sequences are deposited in analyses.

  Study EGAS50000000772

• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  This study included samples from metastatic breast cancer patients who underwent a biopsy in the context of SAFIR01 (NCT01414933), SAFIR02 (NCT02299999), SHIVA (NCT01771458) and MOSCATO (NCT01566019) prospective trials. These French multicentre trials used high throughput genome analysis on fresh frozen tumor biopsies as a therapeutic decision tool for metastatic cancer patients, with solid cancers (SHIVA, MOSCATO) or specifically with breast cancer (SAFIR01, SAFIR02). All patients gave their informed consent for translational research and genetic analyses of their somatic DNA. Overall, whole-exome sequencing for a total of 216 pairs of metastatic tumor and unmutated DNA derived from corresponding blood samples was performed using Illumina technology. The results of the analysis of the mutational profile of metastatic breast cancer was reported in Lefebvre et al. (PMID:28027327).

  Study EGAS00001001695

• Gut 16S rRNA/FINRISK 2002

  Gut microbiome 16S rRNA raw data for N=7174 FINRISK 2002 participants. FINRISK fecal samples were mailed to the Knight laboratory at the University of California (San Diego, CA), for microbiota sequencing using the standard Earth Microbiome Project protocols (https://earthmicrobiome.org/protocols-and-standards/). DNA was extracted using a magnetic bead-based DNA extraction protocol. Amplicon sequence data for the V4 region of the 16S rRNA gene was generated using 515F (Parada) and 806R (Apprill) primers. For a total of 25μl reaction volume, 13 µl PCR-grade water was combined with 10 µl PCR master mix (Platinum Hot Start PCR Master Mix, 2x, ThermoFisher), 0.5 µl forward primer (10 µM), 0.5 µl reverse primer (10 µM), and 1 µl template DNA. Amplification was performed in triplicate reactions, and triplicate PCR reactions were pooled afterwards. Expected products were visualized on agarose gels (300–350 bp) and quantified with Quant-iT PicoGreen dsDNA kit (Invitrogen). Equal amounts (240 ng) of amplicon were combined for each sample and cleaned (MoBio UltraClean PCR Clean-Up Kit). Cleaned amplicon pools were sequenced with 515F and 806R primers.

  Dataset EGAD50000000287

• WES analysis of paired tumor and non-tumoral DNA of 4 patients with non-muscle-invasive bladder cancer

  We performed WES of tumor DNA and non-tumoral DNA (extracted from PBMC) of 4 patients with non-muscle invasive bladder cancer, who after the tumor resection went on to receive BCG treatment as they had high-risk disease. In order to identify tumor-specific mutations that could give rise to patient-specific neo-epitopes, we performed paired WES of tumor and non-tumoral DNA for each patient. For patient UC2, 3 different tumors were resected at the same time and DNA from these 3 tumors were sent separately for WES.

  Study EGAS50000001382

• Long-read Nanopore and Ion Torrent sequencing data for BRCA1/2 variant detection

  This dataset contains long-read sequencing (LRS) data generated using Oxford Nanopore Technologies (ONT) for the analysis of BRCA1 and BRCA2 variants in individuals referred for hereditary breast genetic testing. The study includes samples previously analyzed using Ion Torrent sequencing, enabling comparison between short-read and long-read sequencing approaches.

  Dac EGAC50000000946

• Epigenomes and Transcriptomes of Brain Samples of Schizophrenics and Controls

  We examined the effects of antipsychotic medications on the cell-specific epigenomics and transcriptomics in the frontal cortex of schizophrenic subjects. We performed ChIP-seq (H3K4me3 and H3K27ac) and RNA-seq on neuronal and non-neuronal nuclei of postmortem frontal cortex samples from two cohorts of schizophrenics, either previously treated or not with antipsychotic medications, and control subjects individually matched by sex and age. In total, we tested 29 schizophrenics (15 untreated and 14 treated patients) and their matched control samples. Two replicates were produced on each brain sample for each assay. ChIP-seq data were generated using MOWChIP-seq (Zhu et al., PMID: 31666743) and RNA-seq data were produced using the combination of SMART-seq2 (Picelli et al., PMID: 24385147) and a Nextera XT DNA library preparation kit. The filename contains the information on the experimental group, the number of the sample within the group, the type of the brain nuclei, the epigenomic/transcriptomic data set (either H3K27ac or mRNA), and the number of replicate. For example, “SCZ-1-untreated-neuron-H3K4me3-R1” refers untreated schizophrenic sample #1, replicate 1 ChIP-seq data on H3K4me3.

  Study phs002487

• NextGen Consortium: Globin Gene Expression in Sickle Cell Genotype-Specific iPS Cells

  Implement an efficient, highly reproducible and 'scalable' system for the production of large numbers of sickle cell anemia-specific iPS cells (iPSC). Derive and characterize a novel, in vitro system for the production of an unlimited supply of erythroid lineage cells from the directed differentiation of 'clinical grade' transgene-free iPS cells; use this system to recapitulate erythroid-lineage ontogeny in vitro with the sequential development of primitive and definitive erythropoiesis, accompanied by the appropriate expression of stage-specific globin genes. Identify developmental gene expression profile differences between erythroid precursors that produce primarily HbF and those that produce primarily HbA or HbS. Determine the effects of the three known HbF major quantitative trait loci (QTL) on globin gene expression in disease-specific iPS cells during in vitro erythropoiesis. Search for novel HbF genetic modifiers associated with markedly elevated HbF levels found in sickle cell anemia patients naturally, or in response to hydroxyurea treatment, by examining gene expression profiles and mRNA sequence of their iPSC-derived erythroid cells. Develop and use a CRISPR-based gene editing platform to study the effect of novel HbF genetic modifiers, explore globin switching, and correct the HbS mutation in sickle iPSC lines.

  Study phs001212

• ChIP-seq profiling of H3K4me1 and H3K27ac in iPSCs and iPSC-derived endoderm cells in CPRF patients with LSD1 mutations and healthy controls

  LSD1 patient (children) and control (healthy fathers) derived iPSCs and endoderm differentiated cells were expanded and harvested for ChIP-seq experiment following the procedure described in Trovato et al, PMID: 39214979. Cells were cross-linked in PFA, sonicated and soluble fractions were collected for IP with H3K4me1 or H3K27ac antibodies. Sequencing libraries were prepared using the NEBNext Ultra II DNA Library Preparation Kit (New England Biolabs) and sequenced on Illumina NextSeq 500 (75 bp in single-end mode).

  Study EGAS00001008242

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• White blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

  Liquid biopsies are providing new opportunities for detection of residual disease in cell-free DNA (cfDNA) after surgery but may be confounded through identification of alterations arising from clonal hematopoiesis. Here, we identify circulating tumor-derived DNA alterations (ctDNA) through ultrasensitive targeted sequencing analyses of matched cfDNA and white blood cells from the same patient. We apply this approach to analyze samples from patients in the CRITICS trial, a phase III randomized controlled study of perioperative chemotherapy in patients with operable gastric cancer. After filtering alterations derived from matched white-blood cells, the presence of ctDNA predicts recurrence when analyzed within nine weeks after preoperative treatment and after surgery in patients eligible for multimodal treatment. These analyses provide a facile method for distinguishing ctDNA from other cfDNA alterations and highlight the utility of ctDNA as a predictive biomarker of patient outcome to perioperative cancer therapy and surgical resection in patients with gastric cancer.

  Study EGAS00001004114

• Dynamics of sequence and structural cell-free DNA landscapes in small-cell lung cancer

  Patients with small-cell lung cancer (SCLC) have an exceptionally poor prognosis, calling for improved real-time non-invasive biomarkers of therapeutic response. We performed targeted error-correction sequencing on 171 serial plasmas and matched white blood cell (WBC) DNA from 33 patients with metastatic SCLC who received systemic treatment with chemotherapy or immunotherapy-containing regimens. Tumor-derived sequence alterations and plasma aneuploidy were evaluated serially and combined to assess changes in total cell-free tumor load (cfTL). Longitudinal dynamic changes in cfTL were monitored to determine circulating cell-free tumor DNA (ctDNA) molecular response during therapy. Combined tiered analyses of tumor-derived sequence alterations and plasma aneuploidy allowed for assessment of ctDNA molecular response in all patients. Molecular responses captured the therapeutic effect and long-term clinical outcomes in a more accurate and rapid manner compared to radiographic imaging. Patients with sustained molecular responses had longer overall (log-rank p=0.0006) and progression-free (log-rank p<0.0001) survival, with molecular responses detected on average 4 weeks earlier than imaging. ctDNA analyses provide a rapid approach for the assessment of early on-therapy molecular responses and have important implications for the management of patients with SCLC, including the development of improved strategies for real-time tumor burden monitoring.

  Study EGAS00001006831

• Susceptibility loci for tanning ability in Japanese population identified by genome-wide association study

  We performed genome-wide association studies of Japanese Skin Type for Japanese individuals from a cohort study by the Tohoku Medical Megabank Project in order to identify variants related to tanning ability and skin pigmentation. We used imputed genotype data of 9,187 Japanese individuals, of which 4,475 individuals are from Miyagi prefecture and 4,712 individuals are from Iwate prefecture. Skin Type information was obtained from the questionnaire for cohort participants.

  Study JGAS000160

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  We performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants associated with the disorder.

  Study EGAS50000000411

• A conserved enhancer in ecDNA-containing Medulloblastoma

  Extrachromosomal DNA (ecDNA) fundamentally reshapes the regulatory landscape of cancer cells by providing a platform for massive oncogene amplification and heightened chromatin accessibility. This research investigates how ecDNA-resident enhancers operate within large-scale molecular hubs to drive potent, long-range transcriptional activation that transcends standard chromosomal boundaries. By analyzing the unique structural configurations of these elements, the work identifies key mechanisms that contribute to rapid tumor evolution and significant phenotypic plasticity. These findings highlight the critical role of non-chromosomal regulatory elements in maintaining oncogenic signaling and suggest new avenues for therapeutic intervention in aggressive, ecDNA-driven malignancies.

  Study EGAS50000001609

• A conserved enhancer in ecDNA-containing Medulloblastoma

  Extrachromosomal DNA (ecDNA) fundamentally reshapes the regulatory landscape of cancer cells by providing a platform for massive oncogene amplification and heightened chromatin accessibility. This research investigates how ecDNA-resident enhancers operate within large-scale molecular hubs to drive potent, long-range transcriptional activation that transcends standard chromosomal boundaries. By analyzing the unique structural configurations of these elements, the work identifies key mechanisms that contribute to rapid tumor evolution and significant phenotypic plasticity. These findings highlight the critical role of non-chromosomal regulatory elements in maintaining oncogenic signaling and suggest new avenues for therapeutic intervention in aggressive, ecDNA-driven malignancies.

  Study EGAS50000001610

• A conserved enhancer in ecDNA-containing Medulloblastoma

  Extrachromosomal DNA (ecDNA) fundamentally reshapes the regulatory landscape of cancer cells by providing a platform for massive oncogene amplification and heightened chromatin accessibility. This research investigates how ecDNA-resident enhancers operate within large-scale molecular hubs to drive potent, long-range transcriptional activation that transcends standard chromosomal boundaries. By analyzing the unique structural configurations of these elements, the work identifies key mechanisms that contribute to rapid tumor evolution and significant phenotypic plasticity. These findings highlight the critical role of non-chromosomal regulatory elements in maintaining oncogenic signaling and suggest new avenues for therapeutic intervention in aggressive, ecDNA-driven malignancies.

  Study EGAS50000001608

• A Genome-Wide Association Study in Patients Experiencing Drug-Induced Long-QT Syndrome and/or Torsades de Pointes; A Collaboration Between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Institute Center for Genomic Medicine

  The goal of this study was to identify genetic risk factors for drug-induced prolongation of the QT interval (diLQT) and the ventricular arrhythmia torsades de pointes (TdP). We conducted a genome-wide association study (GWAS) focusing on subjects with a history of long QT and/or TdP after taking medication. Controls for this study were individuals with a history of cardiac arrhythmias who had begun treatment with potentially QT-prolonging antiarrhythmics. An additional control group of normal volunteers were given ibutilide, a drug with documented proarrhythmic properties. All study participants were recruited and treated/evaluated at Vanderbilt University Medical Center. This study was conducted by the Pharmacogenomics of Arrhythmia Therapy subgroup of the Pharmacogenetics Research Network, a nationwide collaboration of scientists studying the genetic contributions to drug response variability. Genotyping was performed by the RIKEN research institute in Japan using the Illumina 610 Quad Beadchip platform.

  Study phs000331

• Timing chromosomal amplification events using patterns of somatic mutations in high hyperdiploid acute lymphoblastic leukemia

  This dataset included samples with high hyperdiploid acute lymphoblastic leukemia (ALL) collected from the Division of Clinical Genetics, Lund University, Sweden. All samples were subjected to whole genome sequencing using the Illumina HiSeqX platform. Paired-end sequencing (2x150bp) was done to ~60x coverage for diagnostic samples and ~30x coverage for remission samples. The paired-end reads were aligned to the human reference genome GRCh37 (https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.25/) by the Burrows-Wheeler Aligner tool (version 0.7.17). Duplicate reads marking and local realignment were performed by GATK (version 4.0.11.0).

  Study EGAS00001007052

• Germline hypomorphic CARD11 mutations in severe atopic disease

  We described five patients from four unrelated families who had severe atopic dermatitis and susceptibility to mild skin viral infections. Some patients also exhibited other allergic symptoms such as asthma and food allergy. We performed targeted sequencing for affected patients A-I of family A and B-I of family B, whole exome sequencing for D-I, D-II.1 and healthy mother D-II.3 of family D, and whole genome sequencing for C-I and healthy mother C-II.2 of family C. We identified three different novel damaging missense mutations of CARD11 (GeneID:84433) in patients A-I (L194P), B-I (R975W), and C-I (E57D). In patients D-I and D-II.1, a dup183_196 (p.K196_V197insMKEERDSYNDELVK) mutation was found in the coil-coil domain of the protein. These mutations act as dominant negatives impeding the scaffolding function of the wild type protein, which leads to downstream NF-kB and mTORC1 signaling defects after TCR stimulation. Sanger sequencing later identified the corresponding CARD11 mutations in the affected family members (C-II.1, D-II.2) that are not included in the dbGaP submission. Hypomorphic CARD11 dominant negative mutants are novel causes of severe atopic disease.

  Study phs001369

• Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

  This dataset accompanies the manuscript "Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance Through Serial Biopsies and Comprehensive Analytics". In this study we discuss the clinical implications and consequences of molecular heterogeneity in a metastatic breast cancer patient identified through serial biopsies, multi-omic analysis, and longitudinal patient monitoring, performed through the precision oncology program, Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART). This case study describes a metastatic breast cancer patient with a highly heterogenous tumor that began as ER positive/HER2 negative on diagnosis, then was found to be ER negative/HER2 positive in a metastatic liver lesion (Study biopsy #1), and finally triple negative (TNBC) in another metastatic liver biopsy (Study biopsy #2). Multi-omic assays included clinical genomic panel sequencing, clinical immunohistochemistry, a clinical protein profiling assay (Intracellular Signaling Protein Profiling), RNA sequencing, and RPPA. Here we provide the expression data from RNAseq and RPPA data on Study biopsy #2 for the patient discussed in this case report. Note: The first liver biopsy did not yield sufficient material for RNAseq or RPPA.Raw RNA FASTQ files from Study biopsy #2 of the liver Gene expression (RNAseq) files from Study biopsy #2Protein expression (RPPA) files (level 2, 3, 4) for Study biopsy #2

  Study phs002321