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• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas for the study and all the datasets.

  This dataset contains CEL files and rma normalized expression value for microarray of stage I lung adenocarcinomas from Asian patients. In total, there are 69 patients and 138 samples, including 69 tumor samples and 69 adjacent normal samples.

  Dataset EGAD00010001901

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

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

  Study phs000387

• UW TAN Study of Metastatic Urothelial Carcinoma

  Patients with metastatic urothelial carcinoma treated at our institution, who elected to undergo rapid autopsy at the time of death, are included in this study. These patients agreed to submit their tissue (normal samples for germline analysis [kidney or liver] as well as primary and metastatic tumor sites [urothelial carcinoma]) and the time of autopsy. Each patient signed consent to allow study of these tissues including histologic, sequencing (DNA/RNA), and implantation in to animals as able for future study.

  Study phs001797

• Sequencing of 3D Organoids Derived From Colorectal Cancer Patients

  This study focuses on the whole-exome sequencing (WES) of patient-derived organoids (PDOs) established from colorectal cancer (CRC) tumors collected at Columbia University. CRC remains a major cause of cancer-related mortality due to its metastatic progression and resistance to therapy. To model CRC at the patient level, we generated 3D organoid cultures from primary and metastatic tumors, preserving their genetic and phenotypic characteristics. The study cohort consists of 9 CRC patients with microsatellite-stable adenocarcinomas from the ascending, transverse, and descending colon, as well as the rectum, with differentiation statuses ranging from well to moderate and moderate-poor. Notably, for one patient, we generated organoids from both the primary tumor and matched liver metastases, allowing for a comparative analysis of tumor evolution. PDOs were derived from these tumors and subjected to WES at early passage to profile somatic mutations, copy number variations, and other genomic alterations to identify mutational signatures. Mutations identified in the PDOs were cross-referenced and confirmed with mutational data from the Columbia Solid Tumor Panel, which was conducted on all tumor tissues prior to organoid establishment. Molecular technologies employed include next-generation sequencing (NGS) for WES, enabling high-resolution characterization of the genomic landscape of CRC PDOs. WES of PDOs allowed us to classify tumor samples based on oncogenic mutations and mutation types, with a specific focus on PIK3CA. Notably, the efficacy of PI3Kα-specific pharmacologic inhibitors in suppressing organoid growth was dependent on the mutational status of KRAS and PIK3CA, underscoring the importance of genomic context in therapeutic response. The dataset available through dbGaP includes raw WES data from CRC PDOs.

  Study phs003965

• Genomics Analysis Reveals Molecular Patterns of Tumorigenesis in HPV-Associated and HPV-Independent Sinonasal Squamous Cell Carcinoma

  The goal of this study was to identify molecular mechanisms of tumorigenesis in HPV-associated and HPV-independent sinonasal carcinoma using high-throughput sequencing approaches. Whole genome sequencing was performed for HPV-associated samples and whole exome sequencing for HPV-independent samples. Ultimately, we identified distinct molecular patterns of tumorigenesis between HPV-associated and HPV-independent disease. Data from patients for which informed consent allowed public sharing are included here.

  Study phs003591

• Targeted sequencing of genomic regions of interest in depression and obesity

  This study aimed to further explore the genetic relationship between MD and obesity taking advantage of targeted sequencing strategy. Specifically, we searched for genetic risk variants across the entire frequency spectrum in flanking genomic regions and genes previously associated with MD and obesity, assessed the contribution of those variants to the pathophysiology of comorbid MD and obesity, and provided a general overview of the cellular and molecular pathways mapped by those variants when these complex diseases co-occur.

  Study EGAS50000000330

• An Ultrasensitive Method for Detection of Cell-Free RNA

  Our study describes the development of a novel method for cell free RNA (cfRNA) analysis called RARE-Seq (Random priming & Affinity capture of cell-free RNA fragments for Enrichment analysis by Sequencing). We find RARE-Seq improves the limit of detection for tumor-naïve cancer detection while maintaining high specificity. We explore the potential utility of RARE-Seq in diverse clinical applications, including non-invasive ctRNA genotyping, treatment resistance monitoring, and molecular characterization of non-malignant conditions.

  Study phs004091

• Proteogenomic discovery of a novel class of cancer antigens by HLA ligandome analysis of colon cancer tissues

  CD8+ T cells recognize peptides displayed by HLA class I molecules on cell surfaces, monitoring pathological conditions such as cancer. Recent advances in proteogenomic analysis of HLA ligandomes have demonstrated that cells present a subset of cryptic peptides derived from non-coding regions of the genome; however, the roles of cryptic HLA ligands in tumor immunity remain unknown. In the present study, we comprehensively and quantitatively investigated the HLA class I ligandome of a set of human colorectal cancer (CRC) and matched normal tissues, showing that cryptic translation products account for a small fraction of the HLA class I ligandome and serve as antigens for patient T cell surveillance against colon cancer.

  Study JGAS000280

• scRNA-seq of HSPC treated with gemcitabine and carboplatin

  4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. The raw FASTQ-files are available as read 1 and read 2 files from 4 lanes for each sample giving a total of 16 FASTQ-files. The FASTQ-files were also processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression (dge) for each cell of each sample. This has resulted in one dge text file and one dge summary text file per sample. These 8 text-files with dge data are found in the zip-compressed analysis data-file.

  Dataset EGAD00001006080

• EORTC RP1335 SPECTA Lung cancer data

  SPECTAlung has recruited patients with thoracic malignancies, collecting FFPE material for molecular analysis. Illumina TST170 NGS panel was used for sequencing. The goal was to identify patients for whom a personalized treatment was possible and build a clinically-annotated molecular database for thoracic patients.

  Study EGAS00001004485

• CpG methylation changes associated with hyperglycemia in type 1 diabetes occur at angiogenic glomerular and retinal gene loci.

  Retinal and glomerular microangiopathy, and cardiovascular disease, contribute to the morbidity and mortality observed in adults with type 1 diabetes (T1D). While the level and duration of hyperglycemia are primary factors influencing these complications, the underlying molecular mechanisms behind glucose-induced organ damage remain poorly understood. In this study, blood samples from young T1D patients at diagnosis and three years later in average were analyzed for DNA methylation using whole-genome bisulfite sequencing. Significant DNA methylation changes in critical angiogenic gene loci were associated with HbA1c, a direct hallmark of chronic hyperglycemia. This finding may offer novel epigenetic insights for a better understanding of T1D complications.

  Study EGAS50000000370

• Whole Exome Sequences from Eivissan and Menorcan Individuals

  30 and 21 whole exome sequences for Eivissan and Menorcan healthy unrelated volunteers, respectively. The exomes were captured with the Agilent SureSelect Human All Exon V6 capture kit and pair-end sequenced in Illumina platforms. For each individual, a pair of ".fastq" files can be found containing the raw reads.

  Dataset EGAD50000000620

• Integrative Single-Cell Analysis of Transcriptome, Epigenome, and Lineage in HIV Latency and Activation

  With the development of triple combination antiretroviral therapy, routine HIV treatment eliminates nearly all actively infected cells. Nevertheless, the small reservoir of latently infected cells, which can remain dormant for long periods of time before becoming active and producing new virus particles, represents a crucial barrier to completely curing the disease. Identifying markers that identify latently infected cells or the biochemical factors that control latency activation could enable the effective use of a “shock and kill” strategy, where specific targeting or activation of latently infected cells eliminates the viral reservoir. Our recent work suggests that the global transcriptomic and epigenomic changes during hematopoietic differentiation affect viral latency and activation. Additionally, we recently found that global inhibition of histone deacetylase activity increases viral activation in these cells, further implicating epigenomic changes during activation. These results raise fundamental questions: What are the markers of latently infected cells? How do the transcriptomic and epigenomic states of a cell affect latency and activation? How does the differentiation state relate to viral latency? Here, we leverage our experimental platform for identifying latently and actively infected cells, single-cell transcriptome and epigenome sequencing, and our recently developed computational integration methods to investigate these questions. Our interdisciplinary team combines expertise in HIV basic science, HIV clinical treatment, and bioinformatics to develop an experimental and computational framework for integrated gene expression, chromatin accessibility, and lineage into a single picture of viral latency and activation. Specifically, this project will (1) use single-cell RNA-seq and single-cell ATAC-seq to map the diversity of infected cells, (2) investigate the relationship between hematopoietic differentiation state and viral activation, (3) determine viral integration sites through single-cell RNA-seq, (4) computationally integrate single-cell transcriptome and epigenome profiles, and (5) computationally infer cell lineage relationships among viral genomes and infected cells. To accomplish these goals, we will carry out the following aims: (1) Characterize lineage, transcriptomic and epigenomic diversity of single latently and actively infected primary cells. (2) Investigate latency and activation during in vitro differentiation. (3) Survey single cell diversity of re-activated and in vitro infected cells from cART-suppressed patients. Together, these aims will produce a comprehensive, integrated transcriptomic and epigenomic atlas of the HIV reservoir, identify DNA and RNA biomarkers of latency, and characterize clonal expansion patterns. Our work also develops a broadly applicable experimental and computational framework, laying a foundation for the discovery of novel insights into HIV latency and activation.

  Study phs002915

• Integrated genomic analyses identify ARID1A and ARID1B alterations in the childhood cancer neuroblastoma

  Neuroblastomas are tumors of peripheral sympathetic neurons and are the most common solid tumor in children. To determine the genetic basis for neuroblastoma we performed whole-genome sequencing (6 cases), exome sequencing (16 cases), genome-wide rearrangement analyses (32 cases), and targeted analyses of specific genomic loci (40 cases) using massively parallel sequencing. On average each tumor had 19 somatic alterations in coding genes (range, 3-70). Among genes not previously known to be involved in neuroblastoma, chromosomal deletions and sequence alterations of chromatin remodeling genes, ARID1A and ARID1B, were identified in 8 of 71 tumors (11%) and were associated with early treatment failure and decreased survival. Using tumor-specific structural alterations, we developed an approach to identify rearranged DNA fragments in sera, providing personalized biomarkers for minimal residual disease detection and monitoring. These results highlight dysregulation of chromatin remodeling in pediatric tumorigenesis and provide new approaches for the management of neuroblastoma patients.Data Provider: Johns Hopkins Sidney Kimmel Comprehensive Cancer Center (SKCCC)

  Study EGAS00001000369

• Comparison of single/pooled CTCs and bulk exome sequencing

  Single cell technologies allow the interrogation of tumor heterogeneity, providing insights into tumor evolution and treatment resistance. To better understand whether circulating tumor cells (CTCs) could complement metastatic biopsies for tumor genomic profiling, we characterized 11 single CTCs and 10 pooled CTC samples at the mutational and copy number aberration (CNA) levels, and compared these results with matched synchronous tumor biopsies from 3 metastatic breast cancer patients with triple-negative (TNBC), HER2-positive and estrogen receptor-positive (ER+) tumors. Similar CNA profiles and the same patient-specific driver mutations were found in bulk tissue and CTCs for the HER2-positive and TNBC tumors, whereas different CNA profiles and driver mutations were identified for the ER+ tumor, which presented two distinct clones in CTCs defined by mutations in ESR1 Y537N and TP53, respectively. Furthermore, de novo mutational signatures derived from CTCs described patient-specific biological processes. These data suggest that tumor tissue and CTCs provide complementary clinically relevant information to map tumor heterogeneity and tumor evolution.

  Dataset EGAD00001009052

• Khoe-San genome Project (KSGP)

  The Khoe-San Genome Project (KSGP) includes whole genome data generated for 190 study participants from Southern Africa (Namibia and South Africa) representing people speaking a Namibian Khoe-San language (n=150, 12 groups) or regional non-Khoe-San groups (n=40), specifically defined here as Namibian Himba (n=10), South African Southern Bantu (n=12 and representing the Ubuntu Genome Project led by the University of Limpopo) or South African Coloured/European (n=18). Deep whole genome data has been generated for the purposes of cataloguing the extent of regional genetic diversity, creating population specific references and evolutionary trajectories, while creating a population-matched panel of normal (PoN) genetic diversity required for disease associated studies across the region.

  Dac EGAC50000000798

• Genomic and Transcriptomic sequencing of neuroblastoma cell lines

  Genomic and Transcriptomic sequencing of neuroblastoma HSR and ecDNA cell lines. Data represents five 96-well plates that were processed with G&T sequencing, resulting in genomic and transcriptomic data from the same single cells. Dataset contains 95 bam files containing the DNA sequencing data and 95 bam files containing the RNA sequencing data of CHP212 cells, 380 bam files (190 DNA and 190 RNA) for TR14 cells, 188 bam files (94 DNA and 94 RNA) for Kelly cells and 192 bam files (96 DNA and 96 RNA) for IMR5/75 cells.

  Dataset EGAD50000000729

• cfMeDIP-seq for 18 patients with pleural mesothelioma

  The dataset contains cfMeDIP-sequencing data (bam files) for 18 plasma samples from pleural mesothelioma patients. The libraries were prepared according to the published protocol (Shen, S. Y., Burgener, J. M., Bratman, S. V. & De Carvalho, D. D. Preparation of cfMeDIP- seq libraries for methylome profiling of plasma cell-free DNA. Nat. Protoc. 14, 2749–2780 (2019)). Whole genome sequencing (WGS) was performed for pre-made libraries on NovaSeq X Plus with a 150 paired-end strategy. Low-quality reads and adapters were removed with Trim Galore version 0.6.6 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore). The trimmed reads were aligned to hg38 with Bowtie2 version 2.3.4.3. SAMTools version 1.9 was used to convert the SAM alignment files to BAM files, sort and index reads, and remove duplicates.

  Dataset EGAD50000002126

• Cell types of the human retina and its organoids at single-cell resolution. Cowan et al

  Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers, and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas.

  Study EGAS00001004561

• Progressive multifocal leukoencephalopathy (PML)

  We generated RNAseq, ATACseq, Multiomics and CITEseq for patients with Progressive multifocal leukoencephalopathy (PML) to profile the chromatin accessibility, transcriptional profiles and surface proteins at single-cell level.

  Study EGAS50000000139

• Adipocytes Regulate Fibroblast Function and Their Loss Contributes to Fibroblast Dysfunction in Inflammatory Diseases

  We profiled live synovial cells from 16 individuals with no diagnosed arthritis using single-cell RNA sequencing. Our study was designed to provide a reference single cell RNA sequencing dataset for researchers interested in studying arthritic synovium, providing sequencing data on healthy synovial cells for comparison to cells from diseased synovial tissues. Synovial tissue was collected post-mortem from three different sources between 2019-2021: the National Disease Research Interchange, a collaboration with Rush University and the Gift of Hope, and the Brigham and Women's Hospital Autopsy Department. To be included in the study, patients had to be between the ages of 18 to 72 and have no diagnosed arthritis or autoimmune diseases. Additionally, this study includes bulk RNA sequencing data of cultured primary synovial fibroblasts isolated from three rheumatoid arthritis patents. Cells were stimulated with either cortisol, fat conditioned media, TGFβ, TNFα, fat conditioned media with mifepristone, TGFβ with fat conditioned media, or TNFα with fat conditioned media. Cells were harvested 4 or 22 hours later and lysates collected for sequencing. Data from this study submitted to the Gene Expression Omnibus (GEO) may be accessed via accession number GSE233504.

  Study phs003304

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Study EGAS00001004564

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Study EGAS00001004567

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM67 WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Study EGAS00001004555

• Expression data

  This dataset contains the RPKM and raw read counts of expression for all the individuals. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005039