14970 results for "cancer studies using rna-seq"

in 18.27 milliseconds.

• Single Cell Genome Sequence for DLP+ library A98181A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA919 passage 7, patient-derived xenograft SA1050A passage 1 on DLP+ library A98181A

  Dataset EGAD00001009479

• Single Cell Genome Sequence for DLP+ library A96109A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A96109A

  Dataset EGAD00001009452

• sWGS data of Pap test smears and tumor tissues

  Shallow whole-genome sequencing data divided into three groups: - sWGS data from Pap smears of patients with confirmed high grade serous ovarian cancer - sWGS data from matched tumor tissue (at diagnosis) from the same patients - sWGS data from Pap tests smears of healthy women

  Dataset EGAD00001010141

• Organoid Derivation Project: TGS (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 EGAD00001011089

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• Pathways Study

  The Pathways Study (NCI R01 CA105274, PI: Kushi), is a prospective cohort study of a diverse population of recently diagnosed breast cancer survivors in KPNC. The aims are to examine the effect on recurrence and survival of 1) lifestyle factors such as diet, physical activity, and use of complementary and alternative therapies and 2) molecular factors such as biomarkers of inflammation and tumor DNA methylation profiles. Recruitment into the cohort was from January 2006 to May 2013. Baseline data collection was by in-person interview (on average two months post-diagnosis), with follow-up via mailed or phone questionnaires at 6, 24, and 72 months and outcomes and comorbidities at 12, 24, 48, 72, and 96 months post-enrollment. The Pathways Study is now funded through May 2021 as a cancer cohort infrastructure grant (U01 CA195565, MPI: Kushi/Ambrosone). The Pathways baseline interview consists of interviewer- and self-administered questionnaires. Interviewer-administered questionnaires collected information including demographics, family health history, pregnancy health history, menstrual history, history of breast care screening procedures, smoking history, hormone use, medication history, and vitamin and mineral use. Self-administered questionnaires collected information on diet, physical activity, CAM use, lymphedema, and psychosocial and quality of life measures.

  Study phs001534

• Transcriptome sequencing of human colon organoid after co-cultivation with Bifidobacterium longum

  The large intestine has a dense milieu of indigenous bacteria, generating a complex ecosystem with crosstalk between individual bacteria and host cells. In vitro host cell modeling and bacterial interactions at the anaerobic interphase have elucidated the crosstalk molecular basis. Although classical cell lines derived from patients with colorectal cancer including Caco-2 cells are used, whether they adequately mimic normal colonic epithelial physiology is unclear. To address this, we performed transcriptome profiling of Caco-2 and Monolayer cells derived from healthy Human Colonic Organoid (MHCO) cultured hemi-anaerobically. Coculture with the anaerobic gut bacteria, Bifidobacterium longum subsp. longum differentiated the probiotic effects of test cells from those of physiologically normal intestinal and colorectal cancer cells. We cataloged non- or overlapping gene signatures where gene profiles of Caco-2 cells represented absorptive cells in the small intestinal epithelium, and MHCO cells showed complete colonic epithelium signature, including stem/progenitor, goblet, and enteroendocrine cells colonocytes. Characteristic gene expression changes related to lipid metabolism, inflammation, and cell-cell adhesion were observed in cocultured live Bifidobacterium longum and Caco-2 or MHCO cells. B. longum-stimulated MHCO cells exhibited barrier-enhancing characteristics, as demonstrated in clinical trials. Our data represent a valuable resource for understanding gut microbe and host cell communication.

  Study JGAS000740

• High Grade Serous Ovarian Carcinomas Originate in the Fallopian Tube

  High-grade serous ovarian carcinoma (HGSOC) is the most frequent type of ovarian cancer and has a poor outcome. It has been proposed that fallopian tube cancers may be precursors of HGSOC but evolutionary evidence for this hypothesis has been limited. To provide insights into the origins of HGSOC, we We performed whole-exome sequence and copy number analyses of laser-capture microdissected fallopian tube lesions (p53 signatures, serous tubal intraepithelial carcinomas (STICs), and fallopian tube carcinomas), ovarian cancers, and metastases from nine patients with HGSOC. The majority of tumor-specific sequence and structural alterations in ovarian cancers were present in STICs, including those affecting TP53, BRCA1, BRCA2 or PTEN genes. An eEvolutionary analyseis revealed that p53 signatures and STICs were are the precursors of ovarian carcinoma which in turn gave rise to metastatic lesionsand identify a. In one patient we identified a second STIC as a metastasis in the fallopian tube opposite from the affected ovary. These analyses revealed a window of seven years between the development of a STIC and the initiation of ovarian carcinomas, with development of metastases following rapidly thereafter. Our results provide insights into the etiology of ovarian cancer and have implications for the prevention, early detection and therapeutic intervention of this disease.

  Study EGAS00001002589

• METABRIC: Data from Batra et al (2021); DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation

  DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, RRBS-based profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, the study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.

  Study EGAS00001004327

• Dataset of methylation data from whole blood DNA

  This dataset includes raw data (.idat) for the Illumina Human450k beadchip and methylation levels (.txt files). Methylation level were treated for normalization and background substraction. We removed probes with at least one of the following characteristics: (1) weak signal (p > 0.01) (2128 CpG sites), (2) SNP-enriched sites (4100 sites), (3) out of a CpG context (not on a CG) (3149 sites), or (4) located on sex chromosomes (11,129 sites). A total of 465,071 CpG sites were analyzed initially. Signal was then normalized, first by scaling to the internal controls using the methylumi R package, then by applying the method of subset-quantile within array normalization (SWAN) implemented in the minfi R package.

  Dataset EGAD00010001593

• Summary Statistics GWAS SSNS

  Column 1 rsid: SNP identifier;Column 2 chromosome: name of chromosome on which the SNP is located;Column 3: position: base pair position on the chromosome;Column 4 minor_test_allele: the base that constitutes the minor allele;Column 5 major_allele: the base that constitutes the major allele;Column 6 maf: the frequency of the minor allele, indicated as a fraction of 1;Column 7 allele_freq_cases: the minor allele frequency in cases;Column 8 allele_freq_controls: the minor allele frequency in controls;Column 9 regression_pvalue: the p-value for the difference in allele frequency between cases and controls;Column 10 odds_ratio: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00010002316

• Evidence for Enhancer Activity in Intron 1 of TNFRSF1A Using CRISPR/Cas9 in Human Induced Pluripotent Stem Cell-derived Macrophages

  Use of CRISPR/Cas9 technology to study the TNFRSF1A gene, which plays a key role in autoimmune diseases such as ankylosing spondylitis, multiple sclerosis, and inflammatory bowel disease. By editing a specific regulatory element within the TNFRSF1A locus, we have identified the role of an enhancer element that is not well understood.

  Study EGAS50000000703

• Mutation screening in a large series of Japanese hearing loss patients using massively parallel DNA sequencing analysis.

  In the present study, mutation screening in a large series of Japanese hearing loss (HL) patients to clarify the prevalence and clinical characteristics of each deafness causative genes. Massively parallel DNA sequencing of 63 or 68 target genes were performed in 2969 unrelated Japanese HL patients to identify genomic variations responsible for HL.

  Study JGAS000490

• TS and WGS data

  The dataset contains the targeted sequencing (TS) and the whole genome low pass (WGS) BAM files of the study. For the TS: Samples: TS_XXX There are normal and tumor DNA samples. Each DNA strand has been sequenced independently (PoolA and PoolB). A TruSeq Custom Amplicon panel of 20 genes frequently mutated in ILC and/or ER-positive BC in general was designed using DesignStudio from Illumina: AKT1, ARID1A, CDH1, ERBB2, ERBB3, ESR1, FOXA1, GATA3, IGF1R, JAK2, MAP2K4, MAP3K1, NF1, PIK3CA, PTEN, RB1, RUNX1, STAT3, TBX3, and, TP53. For the WGS: Samples: WGS_XXX There are normal and tumor DNA samples. Samples were sequenced to an average target coverage of 0.5X.

  Dataset EGAD00001006393

• Chracterising cellur pathways underlying CD3/CD28 activation of human CD4+ cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001006612

• Chracterising cellur pathways underlying CD3/CD28 activation of human CD4+ cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/.

  Dataset EGAD00001006610