15075 results for "cancer studies using rna-seq"

in 44.85 milliseconds.

• RNA-seq data from diagnosis and relapse samples of Down Syndrome acute lymphoblastic leukemia.

  Dataset EGAD00001003280

• sc-RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001009002

• UROMOL 2020 - RNA-seq data for validation

  Total RNAseq data from 47 patients with NMIBC.

  Study EGAS00001005050

• IMpower133 subtype assignments

  This dataset contains subtype assignments for 271 tumor samples profiled by RNA-seq.

  Dataset EGAD00001006926

• Evaluation of triple negative breast cancer with heterogeneous immune infiltration

  Identification of potential RNA markers fir TILs infiltration in patients with triple negative breast cancer with heterogeneous immune infiltration.

  Study EGAS00001007159

• ChIP-seq in colorectal cancer and paired adjacent normal mucosa

  This dataset includes ChIP-seq data for H3K27ac and H3K4me1 on 20 paired samples of colorectal cancer and adjacent normal mucosa. One tumor sample that failed QC is not available.

  Dataset EGAD00001007707

• Rapid Idiosyncratic Mechanisms of Clinical Resistance to KRAS G12C Inhibition

  Using deep RNA and whole exome sequencing of pre- and post-treatment autopsy samples, we reveal diverse clonal populations that occurred through altered cell intrinsic, tumor microenvironment and immunologic remodeling mechanisms of resistance.

  Study phs002734

• Dataset for urologic_cancer-RNA

  Rare cancer sequencing data of 75 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008851

• Single-nucleus RNA-sequencing of normal adrenal cortex and adrenocortical tumors

  BAM generated using Cell Ranger v3.1.0 and Space Ranger v1.3.1 and anonymized using BAMBoozle

  Dataset EGAD50000000835

• Sequence Data for DEEP Release August 2016

  DEEP (German Epigenome Project) sequence data of following samples (Sequencing Types: Chip-Seq, WGBS-Seq, RNA-Seq, sncRNA-Seq, NOMe-Se, DNase-Seq): 41_Hf01_LiHe_Ct, 41_Hf02_LiHe_Ct, 41_Hf03_LiHe_Ct, 01_HepG2_LiHG_Ct1, 01_HepG2_LiHG_Ct2, 01_HepaRG_LiHR_D31, 01_HepaRG_LiHR_D32, 01_HepaRG_LiHR_D33, 43_Hm01_BlMo_Ct, 43_Hm03_BlMo_Ct, 43_Hm05_BlMo_Ct, 43_Hm03_BlMa_Ct, 43_Hm05_BlMa_Ct, 43_Hm03_BlMa_TO, 43_Hm05_BlMa_TO, 43_Hm03_BlMa_TE, 43_Hm05_BlMa_TE, 51_Hf01_BlCM_Ct, 51_Hf03_BlCM_Ct, 51_Hf04_BlCM_Ct, 51_Hf02_BlCM_Ct, 51_Hf05_BlCM_Ct, 51_Hf06_BlCM_Ct, 51_Hf06_BlCM_T1, 51_Hf06_BlCM_T2, 51_Hf03_BlEM_Ct, 51_Hf04_BlEM_Ct, 51_Hf02_BlEM_Ct, 51_Hf05_BlEM_Ct, 51_Hf06_BlEM_Ct, 51_Hf06_BlEM_T1, 51_Hf06_BlEM_T2, 51_Hf03_BlTN_Ct, 51_Hf04_BlTN_Ct, 51_Hf02_BlTN_Ct, 51_Hf05_BlTN_Ct, 51_Hf06_BlTN_Ct, 51_Hf06_BlTN_T1, 51_Hf06_BlTN_T2, 51_Hf07_BmTM4_Ct, 51_Hf08_BlTM4_Ct, 51_Hf08_BmTM4_SP1, 51_Hf08_BmTM4_SP2, 51_Hf05_BlTA_Ct, 44_Mm01_WEAd_C2, 44_Mm03_WEAd_C2, 44_Mm02_WEAd_C2, 44_Mm07_WEAd_C2, 44_Mm04_WEAd_C1, 44_Mm05_WEAd_C1

  Dataset EGAD00001002527

• Epigenomics of Human CD8 T cell Differentiation and Aging

  The efficacy of the adaptive immune response declines dramatically with age, but the cell-intrinsic mechanisms driving the changes characteristic of immune aging in humans remain poorly understood. One hallmark of immune aging is the loss of self-renewing naive cells and the accumulation of differentiated but dysfunctional cells within the CD8 T cell compartment. Using ATAC-seq, we first inferred the transcription factor binding activities that maintain the naive and central and effector memory CD8 T cell states in young adults. Integrating our results with RNA-seq, we determined that BATF, ETS1, Eomes, and Sp1 govern transcription networks associated with specific CD8 T cell subset properties, including activation and proliferative potential. Extending our analysis to aged humans, we found that the differences between memory and naive CD8 T cells were largely preserved across age, but that naive and central memory cells from older individuals exhibited a shift toward a more differentiated pattern of chromatin openness. Additionally, aged naive cells displayed a loss in chromatin openness at gene promoters, a phenomenon that appears to be due largely to a loss in binding by NRF1, leading to a marked drop-off in the ability of the naive cell to initiate transcription of mitochondrial genes. Our findings identify BATF- and NRF1-driven gene regulation as targets for delaying CD8 T cell aging and restoring T cell function.

  Study phs001187

• CITE-seq for peripheral blood samples of 5 breast cancer patients

  Study EGAS00001006241

• scRNA-seq of relapsed/refractory multipe myeloma with 10x Chromium (3´ v2)

  This dataset includes 87 scRNA-seq samples of bone marrow aspirates of 20 relapsed/refractory patients generated with the 3´(v2) kit of the 10x Chromium platform. Bone marrow cells have been sorted using CD138 +/- fractions using magnetic beads for plasma cell enrichment and processed independently. For 14/20 patients multiple treatment timepoints are available that includes samples before treatment and at relapse during treatment.

  Dataset EGAD00001006903

• Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss

  The Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss, which constitute the Epidemiology of the Weiss Cohort Projects, consist of a series of inter-connected projects, building upon a set of cohort projects of various groups, mainly drug users from medication-assisted treatment programs, that Dr. Stanley H. Weiss first developed in the 1980’s plus several newer initiatives, each with an array of collaborators. Beginning in the 1980’s, Dr. Stanley H. Weiss started several long-term studies of persons who inject drugs (PWID) across the United States, ultimately enrolling over 10,000 participants through the early 1990’s with an average age then in their 30’s. About a quarter were enrolled from sites in New Jersey (NJ). These studies included the first testing of PWID for the human immunodeficiency virus (HIV) and the human T-cell lymphotropic viruses (HTLV I and HTLV II). Cumulative past support (initiation thru ~ 1999) for these cohort studies included ~ $20 million from intramural resources from the National Cancer Institute (NCI) and the National Institute on Drug Abuse (NIDA), plus multiple grants and in-kind support from the New Jersey Department of Health (NJDOH) totaling ~ $1 million. The Weiss Cohort Projects include the first large AIDS-era cohorts to include women at high risk for HIV. A high percentage of subjects in these studies are black or Latino. Thus, this is an ethnically diverse US cohort, with a high proportion of women included. These subjects are at high risk of parenteral and sexual infection from both drug use and sexual practices. Samples from other studies conducted by Dr. Weiss, in which detailed interviews were conducted, are included as controls (persons documented by us not to have a history of opioid drug use). As one of our groups of subjects have many persons of Haitian ancestry, we specifically included some Haitians who had never used opioids as controls. Our documentation includes such ancestry. These cohorts demonstrated high rates of HIV and HTLV-II infection in PWIDs, including one study initiated in 1981 with confirmation in the later cohorts. In the first two decades of these studies, among numerous publications was the first study showing a very high rate of hepatitis C infection among PWIDs. An example of how the studies’ long-time horizon proved essential was that it first became possible to test whether a person had ever been infected with hepatitis C virus (HCV), as well as how much HCV was in each person’s blood, many years after the specimens were collected. This allowed HCV amounts in blood to be compared for subjects who had died of liver disease early in the study versus those who survived. Then a sequence of published papers culminated in demonstrating, using a nested case-control design, that a high baseline HCV titer was predictive of early progression to death from end-stage liver failure. Outcomes related to HCV (end stage liver disease and hepatocellular carcinoma) remain under study. In the original cohort studies, the mean age at enrollment was ~ 33 years old, so that those still alive in 2022 are mainly now ~ 60 - 75 years old. Many participants have already died. The tincture of time has led to subjects reaching ages when many more are dying from a wide array of outcomes, including from many chronic diseases (including cancer) as well as from infectious agents (especially HIV, HCV) or drug overdose. Renewed collaboration with local drug treatment programs has led to new field-based studies, including examination of some currently evolving problems among drug users. Dr. Weiss joined the National Institute on Drug Abuse (NIDA) Genetics Consortium (NGC) in 2017, and through the NIDA project officer has had access to NGC contract resources (see below). NIH Certificate of Confidentiality, CC-DA-16-214 (attached) protects these studies. Past arrangements related to data on our subjects leads to restrictions on the use of data emanating from our study, such as potential commercialization and restrictions on whom may access and use these data. NIDA Genetics Consortium (NGC) resources further support these endeavors and will be used as part of the NGC analyses studying the genetics of substance use. Study participants signed informed consent for the information collected from them to be used with no time limit and for biologic specimens collected from them to be used without restriction in future research. Serum samples were collected from participants, and from many also plasma, white blood cells and/or urine samples. About 100,000 vials were stored. All specimens have been continuously preserved at sufficiently cold temperatures to prevent deterioration, and many subjects separated white blood cells were processed and frozen in such a way as to maintain viability. Detailed data from the participants has been accumulated over time, and in general, linkage has been retained in each sub-study in accordance with the consent forms and protocols. For some participants, specimens were collected at multiple times (that is, sequential specimens). Multiple specimens from a single person exist in this database, and efforts at de-duplication remain ongoing. Dr. Weiss should be contacted if an investigator requires unique individuals since: • Multiple phases of enrollment occurred, and as our prospective follow-up continues; Dr. Weiss may identify new instances of multiple enrollment. • Some persons are related to each other. • In general, in this dataset for dbGaP, only a single specimen/record form a given person is included. Advances in laboratory testing techniques now permit innovative new uses for our linked research biospecimen repository. The ongoing focus of an interdisciplinary research program based on these cohorts relates subjects’ diseases, behaviors, medical history, and outcomes with biological and exposure markers. Participants’ use of various substances was ascertained on study enrollments, many serially over time. Quantitative frequency of use data, also sometimes sequential over time, were ascertained. Active ascertainment of outcomes is being conducted, including matching to mortality and cancer databases. Investigators interested in collaborations on specific outcomes (which is not part of this dbGaP dataset) or in the use of our stored specimens are encouraged to contact the principal investigator, Dr. Weiss. The processing of the genomic data was done in conjunction with NIDA, and in accordance with some longstanding data cleaning steps used by NIDA in the NIDA Genetics Consortium (NGC), a group to which we shall be contributing these data for collaborative analyses. Since there is the potential for these steps to introduce certain types of potential biases, we summarize these here. Under contract from NIDA, cryopreserved sera or plasma (-80 C) or cells (in liquid nitrogen) were used, with most stored having been stored for 30 to 40 years in our biorepository. In the case of serum or plasma, in which only (largely) cell-free DNA fragments were available, DNA was extracted and restored prior to amplification. Industry standard DNA amplification techniques were done on all samples prior to genotyping in accord with established protocols of the NIDA Genetics Consortium. Our genotype data were run and processed on the Illumina Infinium OmniExpress_v_1.3 array. This array has 714,238 SNPs, and was designed many years ago. There were 628 SNPs on the array that do not correspond to any chromosome position, and these were removed. Genotype data were submitted by NIDA’s contracted genotyping laboratory in six batches over time to NIDA’s contracted dbGaP data management group, which conducted quality control (QC) analyses. QC analysis included an assessment of batch effects on for five of the six batches. (One of the batches, with only 12 samples, was too small for QC analysis of batch effects.) Standard NIDA Genetic Consortium cleaning was performed. Samples with a call rate <.85 were removed. Only one sample per person was retained. When more than one specimen was genotyped from one subject, only the sample with the higher call rate was retained (provided, of course, that that call rate was ≥ 0.85). We have retained some people we know are related, including some found to have been related through genotyping; the pedigree file describes those relationships. In summary, key cleaning steps include: 1. Using PLINK to check gender discrepancy. 2. Using PREST-PLUS and KING (Kinship-based Inference for GWAS) to check relatedness. 3. Using PEDCHECK and PLINK to check/zero-out Mendelian error. 4. Using PLINK to perform sample QC, SNP QC, along with KING to perform chromosome X and chromosome Y QC. 5. SNP-QC: Batch-effect: 5 Batches were compared (one batch, with few samples, was not). These five batches were compared to each other in all ten possible pairs, one batch vs. another batch, examining SNP allele frequency discrepancies by population (from GRAF), Fisher Exact Allelic test, with the criterion of p<5e-8 for removal. 6. SNP-QC: discordant SNPs in QC duplicates. Compared 25 QC duplicated samples with call rate > 0.95, removed SNPs with 3+ discordance. 7. There were 1,056 SNPs that were monomorphic; these have been retained so they can be included in analyses in which our dbGaP data are combined with those from other cohorts (in the latter of which those SNPs may not be monomorphic). The final cleaned dataset submitted has 8,898 samples and 606,793 SNPs.

  Study phs002140

• Cell and Circuit-Specific Exploration of HIV Neurogenomics in Context of Opiate and Cocaine Misuse

  Utilizing frozen postmortem brain tissue from the Manhattan HIV Brain Bank, we performed cell-type-specific, genome-wide sequencing of three different types: 1) single-nucleus RNA-sequencing (snRNA-seq), 2) in situ Hi-C, and 3) HIV integration site sequencing (IS-seq). We assayed tissue from three different donor types: 1) HIV-uninfected control (HIV-), HIV-infected (HIV+), and HIV-infected with HIV encephalitis (HIVE), who served as a positive control for active CNS viral infection. The diagnosis of HIVE was made by a board-certified neuropathologist on routine histopathology, based on the presence of a microglial nodule encephalitis with characteristic multinucleated syncytial cells and staining for HIV p24 antigen. Other HIV-infected individuals (the HIV+ group) did not have this histologic evidence of active HIV brain replication, and were variable with regard to cART status and virologic control prior to death. Donor characteristics, including ante-mortem plasma HIV loads, CD4 counts, and cART status, were documented. Quality controls were used for each assay: For snRNA-seq we applied filters to remove low quality nuclei from analysis and performed experiments in which mouse tissue was mixed with human tissue to determine a reliable HIV read count threshold. For Hi-C, we used paired HIV- and HIVE samples and processed all samples in parallel, at the same time. Correlation analysis was used to ensure biological replicates were aligned. For IS-seq, each time the assay was run, a positive and negative control were included. This allowed us to ensure a lack of contamination in IS-seq libraries and that, when a particular sample failed to yield library, this was due to low levels of HIV rather than a failure of the assay. Altogether, we built an integrative dataset from 79 sequencing files, including snRNA-seq, and cell type specific Hi-C, IS-seq, and ChIP-seq datasets. Human autopsy brain samples were collected by the Manhattan HIV Brain Bank (MHBB, U24MH100931), using protocols under the supervision of the Icahn School of Medicine at Mount Sinai (ISMMS) Institutional Review Board. Written informed consent was obtained either from decedents or their primary next of kin. Major Findings: Reorganization of open/repressive (A/B) compartment structures in HIVE microglia encompassing 6.4% of the genome was linked to transcriptional activation of interferon (IFN) signaling and cell migratory pathways and was partially recapitulated by IFN-gamma stimulation of cultured microglia. In contrast, decreased expression and repressive compartmentalization of genes regulating neuronal health and signaling was seen in both HIVE and HIV+ microglia. IS-seq recovered 1,221 integration sites in the brain that displayed distinct genomic patterns as compared to peripheral lymphocyte integration and were enriched for chromosomal domains newly mobilized into a permissive chromatin environment in HIVE microglia. Viral transcription occurred in a subset of highly activated microglia comprising 0.003% of all nuclei in HIVE brain. Our findings point to a disruption of microglia-neuronal interactions in the HIV infected brain and an interrelation of retroviral integration and expression with interferon-associated remodeling of the microglial 3D genome during progression to HIVE. Search terms: HIV, postmortem brain, microglia, substance abuse, viral integration, chromosomal conformation capture, Hi-C, chromatin, single nuclei RNA-seq, Irf8, NeuN, HIV encephalitis, neuron-microglia interaction, cytokine

  Study phs003080

• Baulac Lab - Paris Brain Institute

  Raw 10X single-nucleus RNA-seq data from human postoperative brain samples of patients with epilepsy and cortical malformations.

  Dac EGAC50000000546

• Transcriptomic profiling of lymphedema

  RNA-seq of skin from human subjects with and without lymphedema

  Dataset EGAD00001006246

• Spatial omics analysis of non-small cell lung cancers for revealing molecular statuses of intratumor heterogeneity and tumor microenvironment

  In this study, we perform spatial transcriptome analysis Visium/Xenium and other omics analysis using surgical specimens of Japanese non-small cell lung cancer cases to understand omics statuses of cancer cells and their surrounding stromal and immune cells in local tumor regions. We aim to stratify lung cancer patients with considering intratumor heterogeneity and complicated microenvironent of lung cancer tissues by using spatial omics data and histopathological information.

  Study JGAS000613

• Plasma whole genome sequencing from patients with stage IV colorectal cancer and microsatellite instability

  This study aims to explore genomic features of cancer in plasma WGS data from patients with advanced colorectal cancer. Cell-free DNA (cfDNA) was extracted from plasma using the QIAamp Circulating Nucleic Acid Kit. Libraries were prepared with 5 to 250 ng of cfDNA using the NEBNext DNA Library Prep Kit.

  Study EGAS00001006377

• Newcastle COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Newcastle University hospitals. These data also include healthy control volunteers treated with IV-LPS as inflammatory controls. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors.

  Dataset EGAD00001007866

• Aurora US Metastatic Breast Cancer Retrospective Project

  The AURORA US Metastatic Breast Cancer project is funded by the Breast Cancer Research Foundation (BCRF) Evelyn H. Lauder Founder's Fund for Metastatic Breast Cancer Research. This multi-center effort conducted within the Translational Breast Cancer Research Consortium (TBCRC) and cancer researchers to better understand the metastatic process through the study of both the primary and metastatic tissue. In the retrospective phase, TBCRC sites submitted matched primary and metastatic tissues and blood from previous collections for piloting the process. Samples were profiled using whole genome DNA sequencing, whole exome DNA sequencing, DNA methylation arrays, and RNA sequencing. The final freeze set for samples with successful nucleic acid extraction and molecular assays included 55 patients with 31 primary tissues and 102 metastases. Twenty patients had tissue collected at autopsy and included 19 with more than one metastasis. Metastases were from 20 different tissue locations with the most common sites being liver, lung, lymph node, and brain. The median age at primary diagnosis was 49 years. The clinical subtypes of the primary tumors were 34% Triple Negative, 30% ER+HER2-, 11% ER+HER2+, and 7% ER-HER2+. Patients received an average of 3 lines of therapy in the metastatic setting. The median overall survival from primary diagnosis was 4.5 years and overall survival from metastatic diagnosis was 2 years.

  Study phs002622

• Human tumor scATAC-seq

  We profiled 4 high-grade gliomas patient brain tumor samples by single-cell ATAC-seq using the 10X Chromium 3' technology. The raw fastq and index files are provided.

  Dataset EGAD00001008347

• ImmuNEO CD8 cell lines

  Paired RNA-Seq data from 16 samples of different tumors CD8+ T cells added to the study "Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification (H021)". Sequencing was performed on Illumina NextSeq 500. The sequencing was always paired

  Dataset EGAD50000000193

• RNA-Seq dataset for malignant pleural and peritoneal mesothelioma

  This dataset contains RNA sequencing data of pleural and peritoneal mesothelioma. The number of samples is 18. Sequencing was performed on Illumina NovaSeq 6000 and Illumina NovaSeqXPlus. The sequencing was always paired.

  Dataset EGAD50000001342

• Dual RNA-seq data of chlamydia infected M2 macrophages

  This dataset contains 8 unpaired fastq files sequenced with Ilumina NextSeq 2000. The files contain transcriptome data of host and pathogen from infected and uninfected samples from extracted total RNA at 30 hours post infection.

  Dataset EGAD50000001398