12213 results for "cancer rna-seq"

in 108.54 milliseconds.

• Plasma DNA aberrations in systemic lupus erythematosus revealed by genomic and methylomic sequencing

  We performed a high-resolution analysis of the biological characteristics of plasma DNA in systemic lupus erythematosus (SLE) patients using massively parallel genomic and methylomic sequencing. A number of plasma DNA abnormalities were found. First, aberrations in measured genomic representations (MGRs) were identified in the plasma DNA of SLE patients. The extent of the aberrations in MGRs correlated with anti-double–stranded DNA (anti-dsDNA) antibody level. Second, the plasma DNA of active SLE patients exhibited skewed molecular size-distribution profiles with a significantly increased proportion of short DNA fragments. The extent of plasma DNA shortening in SLE patients correlated with the SLE disease activity index (SLEDAI) and anti-dsDNA antibody level. Third, the plasma DNA of active SLE patients showed decreased methylation densities. The extent of hypomethylation correlated with SLEDAI and anti-dsDNA antibody level. To explore the impact of anti-dsDNA antibody on plasma DNA in SLE, a column-based protein G capture approach was used to fractionate the IgG-bound and non–IgG-bound DNA in plasma. Compared with healthy individuals, SLE patients had higher concentrations of IgG-bound DNA in plasma. More IgG binding occurs at genomic locations showing increased MGRs. Furthermore, the IgG-bound plasma DNA was shorter in size and more hypomethylated than the non–IgG-bound plasma DNA. These observations have enhanced our understanding of the spectrum of plasma DNA aberrations in SLE and may provide new molecular markers for SLE. Our results also suggest that caution should be exercised when interpreting plasma DNA-based noninvasive prenatal testing and cancer testing conducted for SLE patients.

  Study EGAS00001000962

• Ischemic stroke in a Swedish case-control study.

  Background. Genetic risk scores (GRS), summing up the total effect of several single nucleotide polymorphisms (SNPs) in genes associated with either coronary risk or cardiovascular risk factors, have been tested for association with ischemic stroke with conflicting results. Recently an association was found between a GRS, based on 29 SNPs discovered by genome-wide association studies (GWAS) and hypertension. The aim of our study was to investigate the possible association of the same GRS with ischemic stroke on top of other “traditional risk factors”, also testing its potential improvement in indices of discrimination and reclassification, in a Swedish case-control study. Methods and results. Twenty-nine SNPs were genotyped in 3,677 stroke cases and 2,415 controls included in the Lund Stroke Register (LSR), the Malmö Diet and Cancer (MDC) study and the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). The analysis was conducted in the entire material, and separately for the three samples. After adjustment for hypertension, diabetes mellitus and smoking habits, the GRS was associated with ischemic stroke in the entire material [OR (95% CI) 1.086 (1.029-1.147) per SD increase in the GRS p=0.003] with similar trends in all three samples; LSR [1.050 (0.967-1.140)]; p=0.25], MDC [1.168 (1.060-1.288); p=0.002] and SAHLSIS [1.124 (0.997-1.267); P=0.055]. Measures of discrimination and reclassification improved marginally using the GRS. Conclusions. A blood pressure GRS is independently associated with ischemic stroke risk in three Swedish case-control studies, however, the effect size is low and adds marginally to prediction of stroke on top of traditional risk factors including hypertension.

  Study EGAS00001000936

• Accurate detection and classification of pediatric sarcomas based on cell-free DNA fragmentation patterns

  Sequencing of cell-free DNA in the blood of cancer patients (“liquid biopsy”) provides attractive opportunities not only for early diagnosis, but also for minimally invasive monitoring of treatment response and disease courses. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we developed an integrated genetic/epigenetic analysis method and applied it to 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. We achieved sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. We evaluated different metrics for cell-free DNA fragmentation analysis and developed LIQUORICE, a bioinformatic tool for detecting circulating tumor DNA based on tumor-specific chromatin structure. Using machine learning methods, we combined several fragmentation-based metrics into an integrated approach for liquid biopsy analysis tailored to cancers with low mutation rates but widespread epigenetic deregulation. Clinical associations highlighted the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. Additionally, we performed low coverage whole-genome-sequencing on 43 tumor biopsy samples from patients with Ewing sarcoma, in order to compare copy number aberrations detected in cell-free DNA and biopsy samples of the same patients. For validation of the epigenetic signatures inferred from cell-free DNA, we further performed reduced representation bisulfite sequencing (RRBS) on 38 matched biopsy samples from patients with Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent somatic mutations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.

  Study EGAS00001005127

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• Exome sequencing from cfDNA blood samples. 159 samples at 2x101bp Illumina reads in Fastq format.

  Differential presence of exons (DPE) by next generation sequencing (NGS) is a method of interpretation of whole exome sequencing. This method has been proposed to design a predictive and diagnostic algorithm with clinical value in plasma from patients bearing colorectal cancer (CRC). The aim of the present study was to determine a common exonic signature to discriminate between different clinical pictures, such as non-metastatic, metastatic and non-disease (healthy), using a sustainable and novel technology in liquid biopsy. Through DPE analysis, we determined the differences in DNA exon levels circulating in plasma between patients bearing CRC vs. healthy, patients bearing CRC metastasis vs. non-metastatic and patients bearing CRC metastasis vs. healthy comparisons. We identified a set of 510 exons (469 up and 41 down) whose differential presence in plasma allowed us to group and classify between the three cohorts. Random forest classification (machine learning) was performed and an estimated out-of-bag (OOB) error rate of 35.9% was obtained and the predictive model had an accuracy of 75% with a confidence interval (CI) of 56.6-88.5. In conclusion, the DPE analysis allowed us to discriminate between different patho-physiological status such as metastatic, non-metastatic and healthy donors. In addition, this analysis allowed us to obtain very significant values with respect to previous published results, since we increased the number of samples in our study. These results suggest that circulating DNA in patient’s plasma may be actively released by cells and may be involved in intercellular communication and, therefore, may play a pivotal role in malignant transformation (genometastasis).

  Study EGAS00001006656

• RNASeq Neoantigen Immunogenicity Landscape

  Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.

  Study EGAS00001007509

• Multi-Layered Molecular Profiling Informs the Diagnosis and Targeted Therapy of Desmoplastic Small Round Cell Tumor

  Desmoplastic small round cell tumor (DSRCT) is an ultra-rare soft tissue sarcoma with dismal prognosis and limited therapeutic options. Here, we identified individual therapeutic targets in a cohort of 30 DSRCT patients by use of multilayered molecular profiling (genomic, transcriptomic, and (phospho-)proteomic analyses) within the DKFZ NCT DKTK MASTER program. 28 of the 30 patients received at least one personalized treatment recommendation. In line with the observation that DSRCTs are an entity with a low mutational load, most of the treatment recommendations were based on target gene or -protein expression. 13 patients received a recommended therapy, resulting in four partial responses, four stable diseases, and five progressive diseases. Eight of 13 patients received the multi tyrosine kinase inhibitor pazopanib, with mixed response. Based on high ERBB2 expression levels, two patients received the antibody drug conjugate trastuzumab deruxtecan (T-DXd), showed exceptional, long-lasting responses and are currently (8/2024) still on treatment and progression-free. We detected high ERBB2 protein expression in all DSRCT samples with proteome data (n = 9), which suggests that ERBB2 may be a particularly useful therapeutic target for DSRCT patients. For one of the two exceptional responders we did not detect a substantial ERBB2/HER2 overexpression, which may indicate that T-DXd could also be efficacious in DSRCT patients with low levels of HER2, as also described for breast cancer patients. In conclusion, multi-omic molecular profiling revealed personalized therapeutic targets in patients with DSRCT with HER2 targeting, with T-DXd as a promising therapeutic option for this ultra-rare and difficult-to-treat tumor entity.

  Study EGAS00001007934

• The long term effects of chemotherapy on normal blood - WGS dataset

  In developed countries, ~10% of individuals are exposed to systemic chemotherapy for cancer and other diseases. Many chemotherapeutic agents act by increasing DNA damage in cancer cells, hence triggering cell death. However, there is limited understanding of the extent and consequences of collateral DNA damage to normal tissues. To investigate the impact of chemotherapy on mutation burdens and cell population structure of a normal tissue we sequenced blood cell genomes from 23 individuals, aged 3-80 years, treated with a range of chemotherapy regimens. Substantial additional mutation loads with characteristic mutational signatures were imposed by some chemotherapeutic agents, but there were differences in burden between different classes of agent, different agents of the same class and different blood cell types. Chemotherapy also induced premature changes in the cell population structure of normal blood, similar to those of normal ageing. The results constitute an initial survey of the long-term biological consequences of cytotoxic agents to which a substantial fraction of the population is exposed during the course of their disease management, raising mechanistic questions and highlighting opportunities for mitigation of adverse effects.

  Dataset EGAD00001015339

• DEMENTIA-SEQ: WGS in Lewy Body Dementia and Frontotemporal Dementia

  Lewy body dementia, amyotrophic lateral sclerosis/frontotemporal dementia, and multiple system atrophy are age-related, neurodegenerative syndromes that are poorly understood. Delineating the genetic risk that is driving the pathophysiology of these neurological diseases is fundamental for understanding disease mechanisms and for developing disease-modifying treatments. In version 1 of the study/dbGaP deposition, we performed a whole-genome sequencing study consisting of 7,403 total samples, including 2,633 genomes from patients with Lewy body dementia, 2,641 frontotemporal dementia patients, and 1,980 neurologically healthy controls. Of these, 6,907 were uploaded to dbGaP as the basis of the DementiaSeq, phs001963 dataset. The data relating to these samples are available on dbGaP. In version 2 of this study/dbGaP deposition, we made much of these data available on Anvil. More specifically, data for 6,254 of these samples were also uploaded to the ALS Compute platform on AnVIL. The data for the remaining 653 samples are only available on dbGaP. The dbGaP/AnVIL Table lists the availability of dbGaP and AnVIL for each individual sample: phd008475.In version 3 of the study/dbGaP deposition, we added whole-genome sequence data generated using DNA samples obtained from 683 patients diagnosed with multiple system atrophy.

  Study phs001963

• Transcriptome and Epigenome of TIL Infusion for Cancer Immunotherapy

  Adoptive T cell therapy (ACT) using ex vivo–expanded autologous tumor-infiltrating lymphocytes (TILs) can mediate complete regression of certain human cancers. The impact of TIL phenotypes on clinical success of TIL-ACT is currently unclear. Samples were analyzed from TIL infusion products from metastatic melanoma human patients who responded to TIL-ACT (responders) and patients who did not (non-responders). Single cell transcriptome of TIL infusion products were analyzed for CD8 TIL phenotype and function. In patients with available neoantigen reactive TIL, single cell TCR clonotyping was performed to study anti-tumor TIL states between responders and non-responders. Epigenetic studies on TIL infusion products were performed using ATAC sequencing between paired CD39- C69- and CD39+ CD69+ CD8+ TILs.

  Study phs002436

• DAC for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  While endometrioid and mucinous ovarian cancers represent nearly a quarter of ovarian cancers, their molecular characteristics and pathologic origins are poorly understood. To characterize the genomic and epigenomic alterations of these ovarian cancer subtypes and evaluate links to morphologically similar tumors from other sites, we performed sequence, copy number, mutation signature, rearrangement, and methylation analyses from tumor samples and matched normal tissues of 133 patients. These analyses included patients with ovarian endometrioid (n=44), ovarian mucinous (n=43), uterine endometrial (n=15), and gastrointestinal mucinous cancers (n=31). In addition to identifying genes previously known to be involved in these tumors, we identified alterations in RAD51C, NOTCH4, SMARCA1/4 and JAK1 in ovarian endometrioid, ESR1 in uterine endometrioid, and SMARCA4 in ovarian mucinous cancers. Whole genome sequencing revealed rearrangements involving PTEN, NF1, and NF2 in ovarian endometrioid tumors, and NF1 and MED1 in ovarian mucinous cancers. The number of alterations and affected genes in ovarian and uterine endometrioid cancers were similar as were genome-wide methylation profiles, suggesting that these tumors may have a similar tissue of origin. By contrast, methylation patterns in ovarian mucinous cancers were more similar to other gastrointestinal mucinous cancers, including mucinous cancers of the stomach, colon, and pancreas. These analyses provide insights into the genomic landscapes and origins of mucinous and endometrioid ovarian carcinomas, providing new avenues for early clinical intervention and management of patients with these cancers.

  Dac EGAC50000000341

• CRISPR-screening identifies mechanisms of resistance to KRASG12C and SHP2 inhibitor combinations in non-small cell lung cancer

  Although KRASG12C inhibitors show clinical activity in patients with KRAS G12C mutated NSCLC and other solid tumor malignancies, response is limited by multiple mechanisms of resistance. The KRASG12C inhibitor JDQ443 shows enhanced preclinical antitumor activity combined with the SHP2 inhibitor TNO155, and the combination is currently under clinical evaluation. To identify rational combination strategies that could help overcome or prevent some types of resistance, we evaluated the duration of tumor responses to JDQ443 �� TNO155, alone or combined with the PI3K�� inhibitor alpelisib and/or the CDK4/6 inhibitor ribociclib, in xenograft models derived from a KRASG12C-mutant NSCLC line and investigated the genetic mechanisms associated with loss of response to combined KRASG12C/SHP2 inhibition.

  Study JGAS000643

• Clinical Outcomes of 344 Diffuse Large B-Cell Lymphoma patients

  This study examines clinical outcomes of patients with diffuse large B-cell lymphoma (DLBCL). We analyzed a cohort of 344 patients from the German High-Grade Non-Hodgkin Lymphoma Study Group (DSHNHL). To protect patient confidentiality, all samples were pseudonymized. The dataset includes clinical key characteristics, such as patient age at diagnosis, sex, ECOG performance status, disease stage, serum lactate dehydrogenase levels, bulky disease, bone marrow involvement, extranodal involvement, and B-symptoms. We used these data alongside proteomic and transcriptomic profiles to explore relationships between clinical features and molecular signatures, reconstructing regulatory networks. Insights from this integrative analysis aim to identify key pathological drivers and biomarkers of DLBCL progression, ultimately informing improved risk stratification and targeted therapeutic approaches.

  Study EGAS50000001054

• DCIS Whole Exome & Whole Genome Sequencing Data

  Primary DCIS and recurrent DCIS/IBC (total n=82, ipsilateral n=78 and contralateral n=4) as well as non-recurrent DCIS (n=32) cases were identified through hospital databases from Royal Melbourne Hospital (RMH), Nottingham City Hospital (UK), the LifePool cohort and Peter MacCallum Cancer Centre (PMCC). All cases were micro-dissected from haematoxylin stained sections (range 4-20 sections) by manual micro-dissection to achieve >50% tumour tissue purity. DNA was extracted using the FFPE AllPrep kit (Qiagen, MD, USA). Depending on the success and timing of DNA extraction (Figure 1), cases were analysed by a targeted sequencing panel (n=46, samples pre-2020), whole exome sequencing (WES, n=67), or low-coverage whole genome sequencing (LCWGS). WES: DNA was processed by the Australian Genome Research Facility (AGRF) using the Twist Bioscience Human Comprehensive Exome v1 or v2 (Twist Bioscience HQ, South San Francisco, CA, USA) according to the Twist Target Enrichment Standard Hybridisation Protocol. Sequencing was performed on the Illumina NovaSeq 6000 with 150 bp paired-end reads for a median depth of 101.29x, range: 20.39-247x. Whole Genome Sequencing (WGS): Libraries for four paired samples with matched stromal DNA were made, processed and sequenced by AGRF using the IDT xGen Kit (USA) according to the manufacturer’s protocol, aiming to achieve 60x depth for tumour DNA and 30x for matched normal. File type: Paired-end FASTQ.

  Dataset EGAD50000001846

• EGAD00000000013

  WTCCC1 project Breast cancer (BC) samples

  Dataset EGAD00000000013

• Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine tumor patient

  Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine tumor patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003048

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003051

• Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor patient

  Genome and transcriptome sequence data from a metastatic malignant peripheral nerve sheath tumor patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003052

• Genome and transcriptome sequence data from an adrenocortical carcinoma patient

  Genome and transcriptome sequence data from an adrenocortical carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003053

• Genome and transcriptome sequence data from a small bowel carcinoma patient

  Genome and transcriptome sequence data from a small bowel carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003055

• Genome and transcriptome sequence data from a solitary fibrous tumors (sarcoma) patient

  Genome and transcriptome sequence data from a solitary fibrous tumors (sarcoma) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003056

• Genome and transcriptome sequence data from a metastatic mullerian tumor of endometrium patient

  Genome and transcriptome sequence data from a metastatic mullerian tumor of endometrium patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003059

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003060

• Genome and transcriptome sequence data from an adenocarcinoma of the distal esophagus patient

  Genome and transcriptome sequence data from an adenocarcinoma of the distal esophagus patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003061

• Genome and transcriptome sequence data from an extraosseous osteosarcoma patient

  Genome and transcriptome sequence data from an extraosseous osteosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003062

• Genome and transcriptome sequence data from an atypical bronchial carcinoid patient

  Genome and transcriptome sequence data from an atypical bronchial carcinoid patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003063

• Genome and transcriptome sequence data from an appendiceal adenocarcinoma patient

  Genome and transcriptome sequence data from an appendiceal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003066

• Genome and transcriptome sequence data from a metastatic gastroesophageal adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic gastroesophageal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003067

• Genome and transcriptome sequence data from a pancreatic neuroendocrine tumor patient

  Genome and transcriptome sequence data from a pancreatic neuroendocrine tumor patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003069

• Genome and transcriptome sequence data from a pleural mesothelioma patient

  Genome and transcriptome sequence data from a pleural mesothelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003071

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the pancreas patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the pancreas patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003073

• Genome and transcriptome sequence data from a metastatic colon caner patient

  Genome and transcriptome sequence data from a metastatic colon caner patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003075

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003076

• Genome and transcriptome sequence data from a metastatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003077

• Genome and transcriptome sequence data from a metastatic colorectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic colorectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003086

• Genome and transcriptome sequence data from a pancreatic neuroendocrine patient

  Genome and transcriptome sequence data from a pancreatic neuroendocrine patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003089

• Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient

  Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003090

• Genome and transcriptome sequence data from a clear cell carcinoma of ovary patient

  Genome and transcriptome sequence data from a clear cell carcinoma of ovary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003091

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003695

• Genome and transcriptome sequence data from a metastatic meningioma patient

  Genome and transcriptome sequence data from a metastatic meningioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003697

• Genome and transcriptome sequence data from a thymic carcinoma patient

  Genome and transcriptome sequence data from a thymic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003700

• Genome and transcriptome sequence data from a primary unknown patient

  Genome and transcriptome sequence data from a primary unknown patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003722

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003730

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003735

• Genome and transcriptome sequence data from a sinus adenocarcinoma patient

  Genome and transcriptome sequence data from a sinus adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003737

• Genome and transcriptome sequence data from a Ewing sarcoma patient

  Genome and transcriptome sequence data from a Ewing sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003738

• Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient

  Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003715

• Genome and transcriptome sequence data from a mullerian mixed tumor with carcinosarcoma of the ovaries patient

  Genome and transcriptome sequence data from a mullerian mixed tumor with carcinosarcoma of the ovaries patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003610

• Deep amplicon sequencing to infer malignant clonal populations for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  A total of 192 positions per patient were deeply sequenced in each corresponding tumor sample (including 4 experimental controls and SNVs predicted to originate at each node of the sample phylogeny, see Zhang et al. for details). Genomic DNA templates were used as starting material to generate PCR products. PCR was set up using Phusion DNA polymerase according to the manufacturer’s specifications. The standard PCR conditions used were an initial denaturation at 98C for 30 seconds, followed by 35 cycles of 98C for 10 seconds, 60C for 15 seconds and 72C for 8 seconds, and a final extension at 72C for 10 minutes. PCR products were cleaned up using PCRClean DX beads. Amplicons were pooled by template for sequencing sample preparation. Sample preparation involved a second round of amplification using Phusion DNA polymerase with 6 PCR cycles, with primers specified in Zhang et al. DNA quality was assessed using the Caliper LabChip GX HighSensitivity Assay and DNA quantity was measured using a Qubit dsDNA HS assay kit on a Qubit fluorometer. The indexed libraries were pooled together and sequenced on the Illumina NextSeq500 platform with paired-end 150bp reads using v2 chemistry reagents.

  Dataset EGAD00001003986

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the cheek patient

  Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the cheek patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004603

• Genome and transcriptome sequence data from a metastatic basal cell carcinoma of frontal scalp patient

  Genome and transcriptome sequence data from a metastatic basal cell carcinoma of frontal scalp patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004621

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the cervix patient

  Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the cervix patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004616

• Genome and transcriptome sequence data from a clear cell carcinoma of the left ovary patient

  Genome and transcriptome sequence data from a clear cell carcinoma of the left ovary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004608

• Integrative genome profiling in AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Dataset EGAD00001001873

• Development, maturation and maintenance of human prostate inferred from somatic mutations

  Stem cells within prostate epithelium frequently undergo malignant transformation, but there is limited information on their clonal dynamics and mutation burden in healthy human prostates. We sequenced whole genomes from 409 microdissections of prostate epithelium across 8 donors, using phylogenetic reconstruction with spatial mapping in a 59-year-old man’s prostate to provide high-resolution reconstruction of tissue dynamics across the lifespan. Somatic mutation burden increases linearly with age, at ~16 mutations/year/clone, and is higher in peripheral than peri-urethral regions. The 24-30 independent glandular subunits are established as rudimentary ductal structures during fetal development by 5-10 embryonic cells each. Puberty induces formation of further side branches and terminal acini by local stem cells disseminated through the rudimentary ducts during development. During adult tissue maintenance, clonal expansions are small, with limited geographic scope and minimal migration. Driver mutations are rare in normal ageing prostate epithelium, but the one canonical driver we did observe generated a sizable intraepithelial clonal expansion. By resolving unbiased, continuously occurring lineage-marking mutations, we define stem cell dynamics through embryogenesis, puberty and ageing, with relevance for prostate cancer.

  Dataset EGAD00001006591

• Spatially confined sub-tumor microenvironments in pancreatic cancer

  Intratumoral heterogeneity is a critical frontier in understanding how the tumor microenvironment (TME) propels malignant progression. Here, we deconvolute the human pancreatic TME through large-scale integration of histology-guided regional multiOMICs with clinical data and patient-derived preclinical models. We discover subTMEs, histologically definable tissue states anchored in fibroblast plasticity, with regional relationships to tumor immunity, subtypes, differentiation, and treatment response. Reactive subTMEs rich in complex but functionally coordinated fibroblast communities were immune-hot and inhabited by aggressive tumor cell phenotypes. The matrix-rich deserted subTMEs harbored less activated fibroblasts and tumor- suppressive features yet were markedly chemoprotective and enriched upon chemotherapy. SubTMEs originated in fibroblast differentiation trajectories and transitory states were notable both in single cell transcriptomics and in situ. The intratumoral co-occurrence of subTMEs produced patient-specific phenotypic and computationally predictable heterogeneity tightly linked to malignant biology. Therefore, heterogeneity within the plentiful, notorious pancreatic TME is not random but marks fundamental tissue organizational units.

  Dataset EGAD00001008155

• Somatic mutation rates scale with lifespan across mammals

  The rates and patterns of somatic mutation in normal tissues are largely unknown outside of humans. Comparative analyses can shed light on the diversity of mutagenesis across species and on long-standing hypotheses regarding the evolution of somatic mutation rates and their role in cancer and ageing. Here, we used whole-genome sequencing of 208 intestinal crypts from 56 individuals to study the landscape of somatic mutation across 16 mammalian species. We found somatic mutagenesis to be dominated by seemingly endogenous mutational processes in all species, including 5-methylcytosine deamination and oxidative damage. With some differences, mutational signatures in other species resembled those described in humans, although the relative contribution of each signature varied across species. Remarkably, the somatic mutation rate per year varied greatly across species and exhibited a strong inverse relationship with species lifespan, with no other life-history trait studied displaying a comparable association. Despite widely different life histories among the species surveyed, including ~30-fold variation in lifespan and ~40,000-fold variation in body mass, the somatic mutation burden at the end of lifespan varied only by a factor of ~3. These data unveil common mutational processes across mammals and suggest that somatic mutation rates are evolutionarily constrained and may be a determinant of lifespan.

  Dataset EGAD00001008032

• Dataset for neuroendocrine_adrenal_tumor-EXON

  Rare cancer sequencing data of 164 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008891

• Dataset for other_cancer-EXON

  Rare cancer sequencing data of 137 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008896

• Organoid Derivation Project: WGS (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011090

• Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) tumor patient

  Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015291

• Genome and transcriptome sequence data from a diffuse aarge B-cell lymphoma (relapse) tumor patient

  Genome and transcriptome sequence data from a diffuse large B-cell lymphoma (relapse) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015308

• Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm tumor patient

  Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015312

• The mutation burden of narrowband ultraviolet B phototherapy in human skin - Nanoseq

  Background: Ultraviolet radiation (UV) is used as a treatment for psoriasis, but UV can also induce mutations which may lead to development of skin cancer. Information on the mutagenicity of narrowband UVB (NBUVB) would help inform clinicians and patients who are concerned about the potential risks of this treatment.

  Dataset EGAD00001015249

• The mutation burden of narrowband ultraviolet B phototherapy in human skin - WGS

  Background: Ultraviolet radiation (UV) is used as a treatment for psoriasis, but UV can also induce mutations which may lead to development of skin cancer. Information on the mutagenicity of narrowband UVB (NBUVB) would help inform clinicians and patients who are concerned about the potential risks of this treatment.

  Dataset EGAD00001015250

• A Genome-Wide Association Study in Breast Cancer Patients from the Prospectively Randomized SUCCESS Trial

  The SUCCESS-A Study (http://www.success-studie.de) is a randomized Phase III study of response to treatment of early primary breast cancer with adjuvant therapy after surgical resection. The primary outcome is disease-free survival and secondary outcomes are overall survival and toxicity. The study design includes comparison of two pairs of treatment regimes performed in sequence. The first randomization contrasts treatment with and without Gemcitabine (3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC)-chemotherapy, followed by 3 cycles of Docetaxel(D)-chemotherapy versus 3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC), followed by 3 cycles of Gemcitabine-Docetaxel(DG)-chemotherapy). The second randomization contrasts treatment with Zoledronate for two versus five years. Patients were recruited from 2005 to 2007 and a total of 3754 patients were included from 250 study sites across Germany. Genome-wide SNP microarray data and phenotype outcomes for the first phase of the study (treatment with and without Gemcitabine) are included in the GARNET (Genomics and Randomized Trials Network) pharmacogenomic study in this dbGaP submission. (The Zoledronate treatments are still underway). SUCCESS-A is a an open-label, multicenter, 2x2 factorial design, randomized controlled, Phase III study comparing the disease free survival after randomization in patients treated with 3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC)-chemotherapy, followed by 3 cycles of Docetaxel(D)-chemotherapy versus 3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC), followed by 3 cycles of Gemcitabine-Docetaxel(DG)-chemotherapy, and to compare the disease free survival after randomization in patients treated with 2 years of Zoledronate versus 5 years of Zoledronate in patients with early primary breast cancer. Patients were required to have histopathological proof of axillary lymph node metastases (pN1-3) or high risk node negative, defined as: pT>2 or histopathological grade 3, or age , ≤ 35 or negative hormone receptor, but were not allowed to have evidence of distant disease. Patients were entered into the study no later than 6 weeks after complete resection of the primary tumor. No antineoplastic treatment other than surgical treatment, the defined cytotoxic and endocrine treatment, and radiotherapy was allowed prior to study entry and during the course of the study. After surgery, leading to complete resection of the invasive and intraductal components of the primary tumor, patients were randomized to one of the following two treatments for the first phase of the project (which is included in this GARNET pharmacogenomics study): AA: 3 cycles of 5-Fluorouracil 500 mg/m² i.v. body surface area and Epirubicin 100 mg/m² i.v. and Cyclophosphamide 500 mg/m² i.v., (FEC100), each administered on day 1, repeated on day 22, subsequently followed by 3 cycles of Docetaxel 75 mg/m² body surface area i.v. (D), and Gemcitabine 1000 mg/m² i.v. (30 min infusion) (G), administered on day 1, followed by Gemcitabine 1000 mg/m² i.v. (30 min infusion) on day 8, repeated on day22 AB: 3 cycles of 5-Fluorouracil 500 mg/m² i.v. body surface area and Epirubicin 100 mg/m² i.v. and Cyclophosphamide 500 mg/m² i.v., (FEC100), each administered on day 1, repeated on day 22, subsequently followed by 3 cycles of Docetaxel 100 mg/m² body surface area i.v. (D), administered on day 1, repeated on day 22 A second randomization was made for assigning patients to one of the following two subsequent treatments for the second phase of the project (NOT included in the pharmacogenetic study in this dbGaP submission): BA: Zoledronic acid 4 mg i.v., every 3 months for the duration of two years, subsequently followed by zoledronic acid 4 mg i.v., every 6 months for the duration of additional three years BB: Zoledronic acid 4 mg i.v., every 3 months for the duration of two years Patients with positive hormone receptor status (≥10% positively stained cells for estrogen and/or progesterone) of the primary tumor were recommended to receive Tamoxifen treatment 20 mg p.o. per day for 2 years, after the end of chemotherapy . Subsequent to chemotherapy, postmenopausal patients with positive hormone receptor status were recommended to be treated with Anastrozole (Arimidex®) 1 mg p.o. for additional 3 years, premenopausal patients will continue Tamoxifen treatment for those additional 3 years. In addition to tamoxifen, all patients with positive hormone receptor status of the primary tumor and under the age of 40 or restart of menstrual bleeding within 6 months after the completion of cytostatic treatment or with premenopausal hormone levels as defined below were recommended to receive Goserelin (Zoladex®) 3.6 mg subcutaneously every 4 weeks over a period of 2 years following chemotherapy. Premenopausal endocrine status will be assumed, if the following serum levels are met: LH < 20 mIE/ml, FSH < 20 mIE/ml and E2 > 20 pg/ml. Endocrine therapy will start after the end of chemotherapy. All patients with breast conserving therapy or more than 3 axillary lymph node metastases or in the following cases after mastectomy will receive adjuvant radiotherapy: T3/T4-carcinoma, T2-carcinoma > 3 cm, multicentric tumor growth, lymphangiosis carcinomatosa or vessel involvement, involvement of the pectoralis fascia or a safety margin < 5 mm. Radiotherapy was usually performed after the chemotherapy and parallel to the beginning of the zoledronic acid therapy. Initially, DNA was extracted for performing SNP microarray assays using blood collected at baseline prior to the first randomization. However, the first set of SNP microarray results indicated a quality problem with approximately 50% of the DNA samples. A majority of the problematic samples were replaced with DNA extracted from redrawn blood. The remaining problematic samples were 'restored' using an Illumina FFPE Restoration procedure. A total of 3322 subjects (1638 from arm AA and 1684 from arm AB) were successfully genotyped. Among those, 1771 were from original blood samples, 1092 from redrawn blood samples and 459 from restored blood samples. The SUCCESS-A study is part of the Genomics and Randomized Trials Network (GARNET, http://www.garnetstudy.org) funded by the National Human Genome Research Institute (NHGRI). The overarching goal is to identify novel genetic factors that contribute to disease-free survival for breast cancer patients using different forms of chemotherapy through large-scale genome-wide association studies of treatment response in randomized clinical trials. The study was conducted at the University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Germany. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were performed at the GARNET Coordinating Center at the University of Washington.

  Study phs000547

• Prader-Willi Syndrome and Early-onset Morbid Obesity Natural History Protocol

  This observational study will involve the comprehensive assessment of the medical, behavioral and nutritional history and the clinical features of individuals with Prader-Willi syndrome and individuals with features of PWS-like/EMO. A blood sample will be obtained from the participants in order to create a DNA and RNA repository. In those PWS participants with a known deletion a blood sample will be collected for DNA in order to perform array comparative genome hybridization (aCGH) microarray or Methylation-Specific Multiplex Ligation-dependent Probe Amplification (MS-MLPA) studies to characterize the extent of the deletion. DNA samples will be sent to the Consortium Center at Baylor College of Medicine for the performance of the aCGH studies and to either Dr. Driscoll or Dr. Butler lab for MS-MLPA analysis. No drugs or treatments will be administered through this protocol. Our goal is to enroll as many participants as possible over a 8 year period. Currently we have enrolled 297 total subjects of which 265 have PWS and 32 EMO. Our original goal was to have enrolled over the first 5 years a clinical database of 200 individuals with PWS and 100 with EMO. We have exceeded expectations in PWS enrollment, but have fallen short in the enrollment of individuals with EMO. Therefore, we would like to reset our goals. We now propose to have an enrollment goal of 400 total subjects of which 350 will have PWS and 50 will have EMO. Eligible participants will be initially enrolled in the natural history study from the 4 clinic sites currently involved with PWS (University of Florida, Kansas University Medical Center, Vanderbilt University and University of California at Irvine). Participants assessed will serve to provide a background of information and a willing cohort for future interventional studies. All participants will have had standard genetic testing at a commercial laboratory prior to entry into the study. The PWS participants will be classified into one of the 3 main molecular classes (deletion, UPD and ID). The EMO participants will have had laboratory testing ruling out PWS and chromosomal aneuploidy (e.g., trisomy 21, Klinefelter syndrome, etc.). Going forward we feel it is important that all newly recruited EMO subjects have an aCGH as part of their evaluation so we can identify those with discrete deletions, duplications or copy number variants (CNV) and compare them to those without aCGH abnormalities. The participants will be assessed annually (0-3 years of age) or biennially (> 3 years) in the Clinical Research Center (or equivalent facility) using standardized protocol including photographs for documentation purposes to compare the evolution of the clinical phenotype.

  Study phs000575

• Kids First: Genomic Etiologies of CHARGE Syndrome, Related Conditions and Structural Anomalies

  Developmental disorders with structural birth defects account for the majority of morbidity and mortality in children's hospitals, and the genetic bases of many clinical phenotypes remain unknown. Genetic testing for individuals with structural malformations has uncovered the basis of many such birth defects; however, many more cases remain unsolved, posing challenges for diagnosis, treatment, and prevention. Multiple anomaly conditions are particularly challenging to diagnose, since they often present with unique combinations of clinical features that vary widely between affected individuals, even in the same family. CHARGE Syndrome (Coloboma of the eye, Heart Defects, Atresia of the choanae, Retardation of growth and development, Genital abnormalities including pubertal delay and infertility, Ear abnormalities with deafness and vestibular disorders) is a multiple anomaly condition that affects a wide variety of organ systems. CHARGE Syndrome is caused in most cases by monoallelic pathogenic variants in CHD7, the gene encoding ATP-dependent helicase chromodomain DNA binding protein 7. Both de novo and inherited variants in CHD7 have been reported in CHARGE, and a growing number of families present with individuals who test positive for a pathogenic CHD7 variant yet exhibit only mild features. Similarly, individuals with CHARGE Syndrome often exhibit broad variability and reduced penetrance of clinical features, consistent with pleiotropic roles for CHD7 during development and/or additional genetic contributors or modifying alleles. Recent work has also implicated RERE, KMT2D, EP300, and PUF60 in having a role in CHARGE Syndrome.We hypothesize that (1) some cases of CHARGE are due to other genetic etiologies including oligogenicity, and (2) genetic modifiers contribute to the broad clinical variability and reduced penetrance of CHARGE features. To address these hypotheses, we have generated a cohort of 223 deeply clinically phenotyped individuals with CHARGE Syndrome and related disorders and structural anomalies who tested negative by chromosomal microarray, single gene sequencing, next generation panel sequencing, or exome sequencing. These individuals exhibit clinical CHARGE-like features including structural birth defects affecting craniofacial, ocular, neurosensory, brain, heart, mediastinal, renal, genitourinary, and skeletal organs. Our cohort includes these 223 individuals as well as affected and unaffected family members who consented to clinical and research genetic testing and donated blood samples for DNA and RNA isolation and sequencing. Building on this valuable cohort, we propose to use exome and genome sequencing to identify novel genetic etiologies of CHARGE and related developmental disorders for which alternative genetic tests have been inconclusive. Identification of novel pathogenic genetic variants and contributing modifier alleles within the coding and non-coding portion of the genome of these individuals will improve genetic diagnosis and provide important insights toward understanding the developmental mechanisms of structural birth defects.

  Study phs002592

• Single Cell and Tissue Level Functional Genomics Analysis of Astrocyte-Related Mechanisms in Taupathy

  This data is the first part of a larger single cell and tissue level functional genomics analysis of dementias with tau pathology.  Cellular resolution will clarify the role of glial genes and pathways in neurodegenerative disease. This includes understanding the role of microglia and astrocytes in neurodegenerative disorders characterized by Tau protein pathology. To achieve a refined view of microglial neuroinflammatory signaling in tau-associated neurodegeneration, we performed a functional genomic analysis that integrated time-course gene expression data from mouse models expressing human mutant MAPT (the tau gene) with single nuclear sequencing data obtained from patients with frontotemporal dementia with Tau protein pathology (Pick’s disease). This included microglia-specific gene expression data obtained from single nuclear sequencing of postmortem frozen precentral gyrus samples collected from 16 total individuals, including 8 subjects with clinical diagnosis of behavior variant frontotemporal dementia and neuropathological diagnosis of Pick’s disease (Tau protein pathology) and controls (n=8). Our findings present detailed molecular profiles of disease-associated microglial transitions over the course of tau-associated neurodegeneration. Furthermore, we demonstrate overlap between microglia profiles obtained from precentral gyrus of patients with Pick’s disease with those up-regulated during the neurodegenerative stage in mice expressing human MAPT mutations.

  Study phs002197

• Sex chromosome aneuploidies give rise to changes in the circular RNA profile

  Purpose The landscape of circular RNAs (circRNAs), an important class of non-coding RNAs that regulate gene expression, has never been described in human disorders of sex chromosome aneuploidies. We profiled circRNAs in Turner syndrome females (45,X;TS) and Klinefelter syndrome males (47,XXY; KS) to investigate how circRNAs respond to a missing or an extra X chromosome. Methods Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. CircRNAs were identified using a combination of circRNA identification pipelines (CIRI2, CIRCexplorer2 and circRNA_finder). Results Differential expression of circRNAs was observed throughout the genome in TS and KS, in all tissues. The host-genes from which several of these circRNAs were derived, were associated with known phenotypic traits. Furthermore, several differentially expressed circRNAs had the potential to capture micro RNAs that targeted protein-coding genes with altered expression in TS and KS. Conclusion Sex chromosome aneuploidies introduce pervasive changes in the circRNA transcriptome, demonstrating that the genomic changes in these syndromes are more complex than hitherto thought. CircRNAs may help explain some of the genomic and phenotypic traits observed in these syndromes.

  Study EGAS00001006404

• Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

  Molecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), were missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we used Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis revealed genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells (MDCs). Importantly, we detected heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observed remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

  Study EGAS00001004943

• Therapy-Induced APOBEC3A Drives Evolution of Resistance to Targeted Therapies in Non-Small Cell Lung Cancer

  The purpose of this study was to identify mechanisms of resistance and associated mutational signatures in non-small cell lung cancers (NSCLCs) treated with targeted therapies. Whole genome sequencing (WGS) and whole exome sequencing (WES) were performed on tumor tissue or cell lines derived from oncogene-driven NSCLCs before and after treatments with tyrosine kinase inhibitors. Somatic mutations were called and mutational signature analysis was performed, revealing enrichment of APOBEC mutational signatures mutational signatures in post-treatment tumors after the development to resistance to targeted therapies. The cohort includes WGS and WES data of tumor and normal tissues from patients with oncogene-driven NSCLCs harboring EGFR mutations, ALK fusions or NTRK1 fusions, who were treated with molecularly targeted therapies that target these oncogenes.

  Study phs003256

• Recording physiological history of cells with chemical labeling.

  Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins that become labeled in the presence of both a specific cellular activity and a fluorescent substrate. The recording period is set by the presence of the substrate, whereas the cellular activity controls the degree of the labeling. The use of distinguishable substrates enabled the recording of successive periods of activity. We recorded protein-protein interactions, G-protein-coupled receptor activation and elevations in intracellular calcium. Recordings of elevated calcium levels allowed selections of cells from heterogenous populations for transcriptomic analysis and tracking of neuronal activities in flies and zebrafish.

  Study EGAS50000000056

• Genomic and clinical characterization of a familial GIST kindred intolerant to imatinib

  Familial gastrointestinal stromal tumors (GIST) are rare. We present a kindred with multiple family members affected with multifocal GIST who underwent whole genome sequencing of the germline and tumor. Affected individuals with GIST harbored a germline variant found within exon 13 of the KIT gene, (c.1965T>G; p.Asn655Lys, p.N655K) and a variant in the MSR1 gene (c.877C>T; p.Arg293*, pR293X). Multifocal GISTs in the proband and her mother were treated with preoperative imatinib, and resulted in severe intolerance. The clinical features of multifocal GIST, cutaneous mastocytosis, allergies and gut motility disorders seen in the affected individuals may represent manifestations of the multifunctional roles of KIT in interstitial cells of Cajal or mast cells and/or may be suggestive of additional molecular pathways which can contribute to tumorigenesis.

  Study EGAS50000000372

• EGA synthetic data

  Synthetic Data One of the limitations in genomics research is that human genomics data is not openly available; access must be controlled according to participant consent agreements and data protection regulations such as GDPR. Obtaining authorization to access such data can sometimes take a long time, resulting in delays to important research work. In this context, synthetic genomic and phenotype data can be useful resources for researchers to avoid these delays. Synthetic data are artificially generated datasets, often created with algorithms, which can be used without the need for authorization to test new products and tools, build technical demonstrators, validate data models, and train AI models. The EGA provides access to synthetic cohort datasets augmented with rich synthetic metadata that overcomes these real data usage restrictions. Whilst synthetic datasets are not included in the general EGA mandate and services, we can consider such submissions and evaluate their acceptance on the basis of their unique use cases not already covered by existing synthetic datasets. Access to synthetic data studies is managed by the EGA Helpdesk Data Access Committee. Study ID Title Located in EGAS00001002472 CINECA synthetic cohort EUROPE UK1 referencing fake samples Central EGA EGAS00001005591 Synthetic data - Genome in a Bottle Central EGA EGAS00001005042 Test Study for EGA using data from 1000 Genomes Project - Phase 3 Central EGA EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Central EGA EGAS50000000190 EOSC4Cancer Synthetic Colorectal Cancer Genomic data Central EGA EGAS50000000086 Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023 Federated EGA Sweden EGAS50000000678 Synthetic - GDI synthetic data Federated EGA Spain

  Documentation synthetic-data

• Gliomas, glioneuronal and neuronal tumors

  The dataset represents a total of 85 DNA samples from 22 male and 20 female pediatric patients affected with gliomas, glioneuronal, and neuronal tumors. The samples were subject to whole genome sequencing, WGS, [71 samples, (representing 18 male and 17 female individuals)] and whole exome sequencing, WES, [14 samples, (representing 4 males and 3 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 84 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from one patient. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 85 files in the CRAM format (lossless compression) with a total file size of ~13,3 TB. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000300

• Genome and transcriptome sequence data from a glioblastoma multiforme patient

  Genome and transcriptome sequence data from a glioblastoma multiforme patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003004

• Genome and transcriptome sequence data from an ovarian adenocarcinoma patient

  Genome and transcriptome sequence data from an ovarian adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003036

• Genome and transcriptome sequence data from a chordoma patient

  Genome and transcriptome sequence data from a chordoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003040

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003024

• Genome and transcriptome sequence data from an endometrial adenocarcinoma patient

  Genome and transcriptome sequence data from an endometrial adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003025

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003029

• Genome and transcriptome sequence data from a breast carcinoma patient

  Genome and transcriptome sequence data from a breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003043

• Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the palate patient

  Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the palate patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003065

• Genome and transcriptome sequence data from a metastatic rectal adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003693

• Genome and transcriptome sequence data from a pleomorphic sarcomatoid epithelioid carcinoma patient

  Genome and transcriptome sequence data from a pleomorphic sarcomatoid epithelioid carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003694

• Genome and transcriptome sequence data from a metastatic myoepithelial carcinoma of parotid patient

  Genome and transcriptome sequence data from a metastatic myoepithelial carcinoma of parotid patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003701

• Genome and transcriptome sequence data from a high grade serous carcinoma of the fallopian tube/ovary/peritoneum patient

  Genome and transcriptome sequence data from a high grade serous carcinoma of the fallopian tube/ovary/peritoneum patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003702

• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003719

• Genome and transcriptome sequence data from a peripheral T-cell lymphoma patient

  Genome and transcriptome sequence data from a peripheral T-cell lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003729

• Genome and transcriptome sequence data from a melanoma of the right buccal mucosa patient

  Genome and transcriptome sequence data from a melanoma of the right buccal mucosa patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003716

• Genome and transcriptome sequence data from a squamous cell carcinoma of the anus patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of the anus patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003723

• Genome and transcriptome sequence data from a T-cell rich B cell lymphoma patient

  Genome and transcriptome sequence data from a T-cell rich B cell lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003724

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectosigmoid patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectosigmoid patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003725

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003727

• Genome and transcriptome sequence data from a metastatic gastrointestinal stromal tumor patient

  Genome and transcriptome sequence data from a metastatic gastrointestinal stromal tumor patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003728

• Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient

  Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003733

• Genome and transcriptome sequence data from a spindle cell carcinoma of the left parotid patient

  Genome and transcriptome sequence data from a spindle cell carcinoma of the left parotid patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003734

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003736

• Genome and transcriptome sequence data from an adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from an adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003742