12074 results for "cancer rna-seq"

in 28.88 milliseconds.

• Identification of genetic mutations characteristic for recurrence of serous ovarian cancer.

  Establishment of novel therapeutic strategy to overcome intractable cancer by molecular profiling of serous ovarian cancer

  Study JGAS000104

• RNA Editing Exome

  Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project.

  Dataset EGAD00001000626

• RNA Editing AZIN1 amplicon sequencing

  AZIN1 amplicon sequencing data of the EGAS00001000495 project.

  Dataset EGAD00001000708

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• UTUC RNAseq data

  RNA sequencing of upper urinary tract urothelial carcinoma

  Dataset EGAD00001007667

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• H3K27ac HiChIP Dataset for 19 T-ALL patients and one normal control sample

  19 H3K27ac HICHIP from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference.

  Dataset EGAD50000000023

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• Bulk exome sequencing of primary GBM - SF 10360

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10360

  Dataset EGAD00001002274

• NiCOL Study Target-seq dataset

  10 samples sequenced in Target-sequencing of a panel of 571 genes (Illumina NovaSeq 6000) - Raw FASTQ data - Annotated VCF

  Dataset EGAD00001010911

• Paired-end Whole Exome-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 50 paired-end Whole Exome sequencing samples from 3 patients. 3 normal blood samples are also included.

  Dataset EGAD00001010289

• ChIPseq of neuroblastoma

  This dataset contains 4 samples (2x input and 2x H3K27ac ChIPseq) in the IC-pPDXC-63 cell line.

  Dataset EGAD00001006557

• ChIP sequencing from a collection of PFA tumors

  ChIP data from PFA (n = 10). Raw data provided as FASTQ. Data generated on Illumina NovaSeq 6000 PE50.

  Dataset EGAD00001009045

• H3K27ac ChIPseq of cohesin-mutated and wildtype adult AMLs

  ChIP-seq targeting the H3K27ac histone modification in cohesin-mutated (STAG2 or RAD21 mutation) and cohesin wildtype (CTRL-AMLs) AMLs.

  Dataset EGAD00001011204

• Prostate Cancer Genome Sequencing Project

  Prostate cancer is a prevalent cause of cancer morbidity and mortality in men. In order to characterize the full range of somatic mutations in protein-coding genes that may drive the growth of prostate cancer, we sequenced the exonic regions of genomic and tumor DNA from over 100 patients with high-risk primary prostate cancer. Using hybrid capture and paired end DNA sequencing, we identified mutations in several novel putative prostate cancer genes. We interrogated copy number changes across tumor genomes using high-density SNP arrays, and identified a molecular subtype of cancer characterized by mutation of the ubiquitin ligase subunit SPOP and copy number loss at specific genomic loci.

  Study phs000447

• Colorectal_organoids_and_tumoroids___pulldown

  Targeted capture of cancer gene panel bait set in single cell derived organoids from colon tissue and colorectal cancer from 1 patient.

  Study EGAS00001000869

• RNA isoform repertoire of neuropsychiatric risk genes in human brain

  Neuropsychiatric disorders are highly complex conditions and the risk of developing a disorder has been tied to hundreds of genomic variants that alter the expression and/or products (isoforms) made by risk genes. However, how these genes contribute to disease risk and onset through altered expression and RNA splicing is not well understood. Here we show our current understanding of gene isoforms is far from complete and reveal the precise splicing profiles of neuropsychiatric disorder risk genes. Combining our new bioinformatic pipeline IsoLamp with nanopore long-read amplicon sequencing, we deeply profiled the RNA isoform repertoire of 31 high-confidence neuropsychiatric disorder risk genes in human brain. We show most risk genes are more complex than previously reported, identifying 443 novel isoforms and 28 novel exons, including isoforms which alter protein domains, and genes such as ATG13 and GATAD2A where most expression was from previously undiscovered isoforms. The greatest isoform diversity was present in the schizophrenia risk gene ITIH4. Mass spectrometry of brain protein isolates confirmed translation of a novel exon skipping event in ITIH4, suggesting a new regulatory mechanism for this gene in brain. Our results emphasize the widespread presence of previously undetected RNA and protein isoforms in brain and provide an effective approach to address this knowledge gap. Uncovering the isoform repertoire of neuropsychiatric risk genes will underpin future analyses of the functional impact these isoforms have on neuropsychiatric disorders, enabling the translation of genomic findings into a pathophysiological understanding of disease.

  Study EGAS00001007744

• Single cell transcriptional characterization of human megakaryocyte lineage commitment and maturation

  Single cell RNA-sequencing of sternal bone marrow reciding Hematopoietic Stem Cells (HSCs) and Megakaryocytes (MKs) from individuals undergoing elective open heart valve replacement. HSCs were defined as Lineage-, CD34+, CD38-, CD45RA-, CD90+, CD49f+ cells. MKs where CD41a+, CD42b+ and ploidy was determined with Hoechst. A sternal bone marrow scraping was taken directly following median sternotomy using a Volkmann’s spoon. The sample was collected into an EDTA Vacutainer tube containing 1.8mg/ml EDTA. 4mL of Dulbecco’s phosphate buffered saline (PBS, Sigma) containing 10% human serum albumin (HSA, Gemini Bio Products) was added and the whole volume was resuspended by pipetting 2-3 times. The sample was then put on metallic thermal beads (ThermoFisher Scientific) at a temperature between 0-4°C and transported to the University of Cambridge for further processing. For HSC isolation the cells were stained with the following antibody cocktail: PECy5 conjugated anti-lineage specific antibodies: CD2 (BD), CD3 (BD), CD10 (BD), CD11b (BD), CD11c (BD), CD19 (BD), CD20 (BD), CD56 (BD), biotinylated CD42b (Pab5, NHS Blood and Transplant, International Blood Group Reference Laboratory [IBGRL]), biotinylated GP6 (Pab5, NHS Blood and Transplant, International Blood Group Reference Laboratory [IBGRL]) used in combination with PECy5 conjugated streptavidin (Biolegend). Alexa Fluor 700 conjugated anti-CD34 (BD), PerCP-Cy5.5 conjugated anti-CD38 (BD), Pacific Blue conjugated anti-CD45RA (Invitrogen), PECy7 conjugated anti-CD90 (BD),PE conjugated anti-CD49f (BD). After staining cells were kept at 4°C before sorting using a FACS Aria Fusion flow sorter (BD). Single HSCs defined as Lineage-, CD34+, CD38-, CD45RA-, CD90+, CD49f+ cells were sorted by FACS directly into individual wells of a 96-well plate. Index sort data was collected for each single cell. For MK isolation the cells were stained for surface MK markers with mouse anti-human CD41a APC conjugated antibody (BD) and mouse anti-human CD42b PE conjugated antibody (BD) and for ploidy analysis with 1ug/ml Hoechst 33342 (Invitrogen). After incubation at 37°C for 30 minutes, the cells were kept at 4°C before sorting using a FACS Aria Fusion flow sorter (BD). Single cells and MK pools of 20 cells were sorted by FACS according to ploidy level using a 100uM nozzle directly into individual wells of a 96-well plate. cDNA synthesis and poly(A) enrichment was performed following the G&T-seq protocol (Macaulay et al. 2015), a variation of the Smart-seq2 protocol1. ERCC spike-in RNA (Ambion) was added to the lysis buffer in a dilution of 1:4,000,000.

  Dataset EGAD00001006677

• Frequent mutation of the FOXA1 untranslated region in prostate cancer

  We sequenced the coding and untranslated regions of 72 prostate cancer driver genes in 712 plasma cell free DNA samples from 428 men with metastatic prostate cancer, in an effort to understand the role of untranslated region mutations in late stage prostate cancer.

  Study EGAS00001003113

• Shanghai Breast Cancer Genetics Study (SBCGS)

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

  Study phs001088

• Shanghai Breast Cancer Genetics Study (SBCGS)

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

  Study phs000799

• RNA Editing Transcriptome

  Transcriptome sequencing data of tumor and 10 matched normal samples of the EGAS00001000495 project

  Dataset EGAD00001000627

• Prevalence of rare pathogenic variants in cancer-predisposing genes among Japanese advanced prostate cancer patients.

  The prevalence of rare pathogenic variants in cancer-predisposing genes including those associated with DNA repair remains unknown among Japanese patients with advanced prostate cancer. This study was designed to elucidate the prevalence of pathogenic variants in 27 known cancer-predisposing genes and to explore the prognostic significance of the variants identified.

  Study JGAS000509

• Lung Cancer Genetic Study Among Asian Never Smokers

  The Lung Cancer Genetic Study Among Asian Never Smokers includes data from four population-based studies conducted among Asian women: the Shanghai Women's Health Study (SWHS), the Hwasun Cancer Epidemiology Study (HCES1 and HCES2), the Female Lung Cancer Consortium in Asia (FLCCA, including sFLCA), and the Guangzhou Lung Cancer Study (GLCS). Shanghai Women's Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Lung cancer patients identified in the SWHS and non-cases were included in the current study.Hwasun Cancer Epidemiology Study-Lung Cancer (HCES1 and HCES2): The HCES is a hospital-based case-control study whose goal is to identify factors of the cancer development and clinical progression in a Korean population. Included in this project were 299 female lung cancer cases from HCES2, who were diagnosed between April 2004 and February 2013 at Chonnam National University Hwasun Hospital, a cancer specified hospital in Jeollanam-do province, South Korea. Controls were randomly selected from women with no previous cancer diagnosis at enrollment in the Namwon Study and the Dong-gu study, ongoing community-based cohort studies in South Korea. A total of 1,103 controls (273 from HCES1 and 830 from HCES2) were genotyped by MEGA. Guangzhou Lung Cancer Study (GLCS): The GLCS is a case-control study including never-smoking women lung cancer cases and controls from Guangzhou, China.In this study, the DNA samples of 1,195 subjects from SWHS and GLCS were genotyped using whole exome sequencing (WES), and the DNA samples of 7,174 subjects from SWHS, HCES1, HCES2, FLCCA, and sFLCA were genotyped using the Multi-Ethnic Global Array (MEGA).

  Study phs002366

• Germline Genomic Analyses of Breast Cancer in Latinas

  In this case-control study of breast cancer among Hispanic/Latina (H/L) women, the goals were to identify breast cancer susceptibility genes and genetic variants for risk of developing breast cancer in H/L women. There were two phases with whole exome sequencing (WES) done in a discovery phase and targeted sequencing of candidate genes in the replication phase. The candidate genes selected for replication came from the first phase and from genes known to affect breast cancer risk in prior studies. Cases and controls were drawn from several studies. Breast cancer cases for discovery phase included women from the City of Hope (COH) Clinical Cancer Genomics Community Research Network (CCGCRN), UCSF Cancer Genetics Clinic and USC Cancer Genetics clinic. Controls for discovery phase included women who did not have breast and were recruited through City of Hope community fairs. A separate group of controls included women from the California Teachers Study. Additional controls for discovery were obtained from WES already generated by the Multi-ethnic cohort (MEC) study. The discovery/WES results of known breast cancer genes were published (PMID 31206626). In the replication phase, we included cases and controls from the Cancer de Mama (CAMA) study which is a case-control study of breast cancer in Mexico, MEC for those not included in the discovery dataset, the San Francisco Bay Area Cancer study (phs000912), the Northern California Breast Cancer Registry, and the California Pacific Medical Center Research Institute Women's Cohort (phs000395). Cases from the PATHWAYS study who were recruited from Northern California Kaiser Permanente were also included. Results from the combined discovery and replication analyses are reported in PMID 36747679.

  Study phs003144