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• Raw molecular data for "Subclonal immune evasion in non-small cell lung cancer"

  Whole exome, RNA sequencing and TCR sequencing of organoid samples derived from TRACERx patients. The dataset also includes whole exome sequencing from the tumour samples from which the organoids were generated, as well as whole exome sequencing from PDX derived from said tumours.

  Dataset EGAD00001015537

• Lung Cell Atlas: Paediatric Spatial (2025-10-02)

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015723

• Single-cell expression of Hodgkin and Reed-Sternberg (HRS) cell

  Hybrid capture sequencing was performed to 3 purified Hodgkin and Reed-Sternberg (HRS) cell samples. In brief, Probes for 177 genes were designed and synthesized by Twist Bioscience. Hybridization capture of DNA libraries was performed using Twist Hybridization and Wash Kit (Twist Bioscience). The captured library was measured using Agilent Bioanalyzer High Sensitivity chip and Qubit dsDNA HS Assay Kit and run on Illumina Nextseq550. The BAM files were generated from the raw sequencing data using Cell Ranger (v6.0.2) mkfastq and count commands

  Dataset EGAD00001010892

• Bulk RNA sequencing of SARC PDOs and UroCa PDOs.

  This dataset contains raw FASTQ files from bulk RNA sequencing of SarBC-01 organoids at different passages (Passage 6, Pssage 19, Passage 59), UroBC-01 organoids (Passage 70), UroBC-16 organoids (Passage 19) and UroBC-22 organoids (Passage 8). RNA was isolated using the Quick-DNA/RNA Miniprep kit (Zymo Research, Irvine, CA, USA, D7001) and subjected to bulk RNA sequencing. TruSeq Stranded mRNA kit (Illumina, 20020594) was used for the library preparation according to manufacturer’s guidelines. Sequencing was performed on Illumina NovaSeq 6000 using paired-end 100-bp reads.

  Dataset EGAD00001011156

• Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

  Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, and integrative models using DNA and RNA have improved predictions of clinical benefit. However, identification of immune and tumor-intrinsic features in models using DNA or RNA alone have not been comprehensively explored in melanoma. In this study, we sequenced DNA and RNA of tumors from 67 melanoma patients receiving CPB, and aggregated this cohort with previously published data, yielding whole exome sequencing (WES) data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences, and found that melanoma patients with high TMB and either high TCB or high BCB survived longer and had higher response rates, as compared to patients with low TMB and either low TCB or low BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes which are associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs which are associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Gene ID: 11184) and the transcription factor TBX3 (Gene ID: 6926) which is overexpressed in poorly differentiated melanomas. We concluded that RNA-based (MAP4K1 and TBX3) or DNA-based (TCB and TMB) models combining with immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

  Study phs002683

• Genetic Analysis of the Chiari I Malformation

  This study used whole exome sequencing (WES) on families affected with Chiari I Malformation (CM1). Individuals were recruited from the Republic of Tartarstan in the Russian Federation, where CM1 has a high prevalence (approximately 413 out of 100,000). At least one-third of these affected individuals have an affected relative. In collaboration with Dr. Enver Bogdanov of Kazan State Medical University, seven extended families affected with CM1 were identified. Eligible participants for this study were required to 1) have CM1 and a family member with syringomyelia or CM1, or 2) be a family member of a patient with CM1 and have at least two immediate family members diagnosed with CM1. Adults and minors were eligible for this study and recruitment was through self and physician referral. Patients were excluded if they had a contraindication to MRI scanning, were unable to understand the risks of testing, were under one year of age, or could not undergo MRI scanning without sedation. Study participants underwent SPGR (Spoiled Gradient Recalled) and T1-weighted MR-imaging of the brain and cervical spinal cord to assess the volume of the posterior fossa, as well as the presence of CM1. Individuals were defined as having CM1 if the inferior aspect of the cerebellar tonsils were lying ≥=2 mm caudal to the foramen magnum. Individuals were defined as having a small posterior fossa volume if the ratio of the posterior fossa volume to the supratentorial volume was < 0.15. Sixty-two patients (both cases and controls) from the seven extended families had DNA extracted from blood lymphocytes contained in 10 milliliters of stored blood. Whole exome sequencing (WES) was performed by the National Intramural Sequencing Center (NISC). These genotype data, as well as the case-control phenotype data on CM1 diagnosis and small posterior fossa diagnosis, were made available to dbGaP.

  Study phs001795

• Effect of the Placental Transcriptome on Stunting in a Longitudinal African Cohort

  Mammals with placentas and flowering plants evolved genomic imprinting in nutritive tissues, the placenta and endosperm, respectively. In these tissues, the genomes inherited from the mother and father are in conflict over resource allocation to offspring. In imprinted genes, transcription is repressed on the paternal or the maternal allele, resulting in allele specific expression (ASE). We investigated the variation in ASE of imprinted genes in term human placentas in order to detect loss of imprinting (LOI), which leads to partial expression of the repressed allele. We collected the placental tissue from birth to women in our multigenerational, prospective cohort study in Mali, West Africa. We followed the women from their own infancies, early childhood to adulthood (age 18+ years). Contingent on prior informed consent, we collected placental tissue and umbilical cord tissue. We conducted RNA-Seq of the fetal compartment of the placentas and targeted DNA-Seq of the umbilical cord tissue, which is fetal, and of saliva samples from parents. Our sequencing effort produced two datasets. The first dataset is the whole transcriptome RNA-Seq dataset of 111 biopsies (59 placentas) and genotyping of 96 genes. Birth length, weight, and placental weight for the children associated with this dataset are listed in the phenotype file (DOI: 10.1093/molbev/msz226). The second dataset includes targeted RNA-Seq of 262 samples (251 placentas) and targeted DNA-Seq for 766 genes. The genes were selected because they met any one of the following criteria: (1) imprinted and reported in some studies, (2) highly expressed in placenta, or (3) relevant to diseases of interest in this cohort (https://doi.org/10.1093/g3journal/jkab176). This study provides the first systematic analysis of variation in LOI across genes and individuals in a human population, and should shed light on the hypothesis that the modulation of imprinting is an epigenetic mechanism and plays a role in the regulation of offspring growth.

  Study phs001782

• Global Microbiome Conservancy Sequence Data

  The human body is a complex ecosystem, hosting tens of billions of bacteria, primarily in the gut. This community, known as the 'gut microbiome', is vital to human health, affecting functions ranging from metabolism, immunity, and development, to behavior. Conversely, reduced microbiome diversity and other imbalances of the gut community (dysbiosis) are associated with many diseases of the industrialized world, such as metabolic syndrome, asthma, and inflammatory bowel diseases among others. Microbiome-based interventions thus hold the potential to revolutionize our understanding of, and therapeutic approaches to, many aspects of human health and disease. Despite many advances, current understanding of the human microbiome is largely limited to majority ethnic groups in industrialized nations, and does not reflect the full diversity of human commensal microbiota. In addition to the scientific ramifications of minority underrepresentation, there are significant translational and ethical implications as well: first, failing to capture the full diversity of healthy human microbiota may limit our ability to understand and generate effective therapeutics for many microbiome-associated diseases. Second, underrepresented groups are less likely to benefit from microbiome-based medical advances tailored to well-studied populations, propagating healthcare inequities.  Human gut microbial diversity is diminishing around the globe, due to the spread of industrialized diets and lifestyles, which are associated with reduced microbiome biodiversity. The Global Microbiome Conservancy (GMbC) is a non-profit collaboration between scientists and communities around the world that aims to 1) preserve the full biodiversity of the human gut microbiome, 2) characterize its evolution across populations and host lifestyles and 3) investigate its interactions with the human host. We are collecting gut microbiome and human DNA samples from diverse populations around the world, from isolated groups to urbanized populations, to culture and study this essential biodiversity and to preserve it in a living "seed bank" of bacterial isolates as a long-term safeguard against future extinctions. Human genetic data for the samples sequenced in this study can be found in phs002205.

  Study phs002235

• Shanghai Breast Cancer Genetics Study (SBCGS)

  The Shanghai Breast Cancer Genetics Study (SBCGS) includes data from four population-based studies conducted among Chinese women in urban Shanghai: the Shanghai Breast Cancer Study (SBCS), the Shanghai Breast Cancer Survival Study (SBCSS), the Shanghai Women's Health Study (SWHS), and the Shanghai Endometrial Cancer Study (SECS, contributing controls only). Shanghai Breast Cancer Study (SBCS): The SBCS is a population-based, case-control study conducted in urban Shanghai. Subject recruitment in the initial phase of the SBCS (SBCS-I) was conducted between August 1996 and March 1998. The second phase (SBCS-II) of recruitment occurred between April 2002 and February 2005. Breast cancer cases were identified through the population-based Shanghai Cancer Registry and supplemented by a rapid case-ascertainment system. Controls were randomly selected using the Shanghai Resident Registry. Approximately 3500 cases and 3500 controls were recruited in the study. Shanghai Breast Cancer Survival Study (SBCSS) and Shanghai Endometrial Cancer Study (SECS): The SBCSS also used the population-based Shanghai Cancer Registry to identify newly diagnosed breast cancer cases. A total of 5,046 breast cancer patients were recruited. In-person interviews were conducted to collect information on known breast cancer risk factors and anthropometrics by using protocols and questionnaires similar to those used in the SBCS. For genetic studies, controls for the SBCSS cases came from the SECS, which recruited healthy women between January 1997 and December 2003. With the exception of a few questions related specifically to breast or endometrial cancer risk, the questionnaires used in the SECS and the SBCS were very similar. Shanghai Women's Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Breast cancer patients identified in the SWHS and non-cases were included in the current study.

  Study phs001088

• Elucidating Transcription Regulation by Epigenetics in Neuroblastoma

  PURPOSE Whole-genome profiles of the epigenetic modification 5-hydroxymethylcytosine (5-hmC) are robust diagnostic biomarkers in adult patients with cancer. We investigated if 5-hmC profiles would serve as novel prognostic markers in neuroblastoma, a clinically heterogeneous pediatric cancer. Because this DNA modification facilitates active gene expression, we hypothesized that 5-hmC profiles would identify transcriptomic networks driving the clinical behavior of neuroblastoma. PATIENTS AND METHODS Nano-hmC-Seal sequencing was performed on DNA from Discovery (n = 51), Validation (n = 38), and Children's Oncology Group (n = 20) cohorts of neuroblastoma tumors. RNA was isolated from 48 tumors for RNA sequencing. Genes with differential 5-hmC or expression between clusters were identified using DESeq2. A 5-hmC model predicting outcome in high-risk patients was established using linear discriminant analysis. RESULTS Comparison of low- versus high-risk tumors in the Discovery cohort revealed 577 genes with differential 5-hmC. Hierarchical clustering of tumors from the Discovery and Validation cohorts using these genes identified two main clusters highly associated with established prognostic markers, clinical risk group, and outcome. Genes with increased 5-hmC and expression in the favorable cluster were enriched for pathways of neuronal differentiation and KRAS activation, whereas genes involved in inflammation and the PRC2 complex were identified in the unfavorable cluster. The linear discriminant analysis model trained on high-risk Discovery cohort tumors was prognostic of outcome when applied to high-risk tumors from the Validation and Children's Oncology Group cohorts (hazard ratio, 3.8). CONCLUSION 5-hmC profiles may be optimal DNA-based biomarkers in neuroblastoma. Analysis of transcriptional networks regulated by these epigenomic modifications may lead to a deeper understanding of drivers of neuroblastoma phenotype. "Reprinted from Applebaum et. JCO Precision Oncology, 2019, with permission from creative commons license."

  Study phs001831