14989 results for "cancer studies using rna-seq"

in 20.62 milliseconds.

• DAC for Angiosarcoma Study. National Cancer Centre Singapore.

  Dac EGAC00001001311

• Hyperpolarized 13C MRI in breast cancer DAC

  Dac EGAC00001001438

• Metastases of a cancer of unknown primary (CUP)

  Dac EGAC00001001484

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001500

• Hereditary Cancer Diagnostics with I2HCP Data Access Comitee

  Dac EGAC00001001541

• Inherited Predisposition to Cancer Projects Data Access Committee

  Dac EGAC00001001565

• Immunogenomics of Colorectal Cancer Data Access Committee

  Dac EGAC00001001596

• UZ Ghent Prostate Cancer Team Data Access Committee

  Dac EGAC00001001608

• Primary tumor and metastatic breast cancer data access

  Dac EGAC00001001687

• Cancer Alliance Data Access Committee

  Dac EGAC00001001641

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001906

• Singapore Gastric Cancer Consortium Data Access Committee

  Dac EGAC00001001955

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001988

• MSKCC Colorectal Cancer Plasma WGS Data Access Comittee

  Dac EGAC00001002741

• RNAseq analysis on metastatic Colorectal Cancer xenografts samples

  Dac EGAC00001002809

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001002829

• RNAseq analysis on metastatic Colorectal Cancer xenografts samples

  Dac EGAC00001003125

• NOWAC blood-breast cancer Data Access Committee

  Dac EGAC01000000024

• Singapore Gastric Cancer Consortium Data Access Committee

  Dac EGAC00001002251

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  Dac EGAC00001003503

• Paired healthy & tumor organoid Biobank _B15PON

  Study EGAS00001005865

• Berlin Neuroblastoma Dataset

  Study EGAS00001004022

• Leeds_Melanoma_Cohort

  Leeds Melanoma Cohort

  Study EGAS00001001158

• Intercepting Progression from Pre-Invasive to Invasive Lung Adenocarcinoma

  An improved understanding of the biology of lung cancer is needed to intercept the disease at an early point in its progression. In this project we have used multidimensional methods to profile the tumor microenvironment (TME) and to determine the crosstalk between cancer cells and the TME in pre-invasive to invasive human lung non-solid adenocarcinomas. Comparative analysis of the cellular and molecular events associated with the distinct histological stages will lead to identification of the critical events triggering progression and thereby identify targets to intercept disease progression. The data being submitted represents the genomic profiles of patient samples with pre-invasive and invasive human lung adenocarcinomas.

  Study phs002818

• Somatic Copy Number Analysis of Endometrial Carcinomas

  Endometrial cancer (EC) is the most commonly diagnosed gynecologic malignancy in the United States and is the sixth leading cause of cancer death amongst American women. The purpose of this study was to identify somatic (tumor-specific) copy number alterations in 7 clear cell ECs, 31 serous ECs, 17 endometrioid ECs, and the clear cell components of 2 endometrioid/clear cell ECs. To this end, DNAs from de-identified primary endometrial tumors and matched non-tumor tissues or blood were hybridized to high-density Illumina Infinium HumanHap650Y Beadchips or to high-density Human660W-Quad Beadchips and the data analyzed to annotate somatic copy number alterations throughout the genome.

  Study phs001690

• Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy

  Recurrent locally advanced head and neck cancer (HNC) patients, receiving re-radiotherapy (re-RT), are presented with short progression-free (PFS) and overall survival. Hence, biomarkers predicting therapy failure are urgently needed. We analyzed copy number variations (CNVs) in blood plasma of HNC patients collected before, during and after re-RT. Detectable CNVs after five and ten fractions of re-irradiation as well as at the end of re-RT were associated with short PFS. Furthermore, we found that CNV kinetics in longitudinally collected plasma reflected therapy response and could detect disease progression in advance of radiographic tumor assessments.

  Study EGAS50000000163

• Targeted DNA sequencing and mRNA sequencing data from patients with peritoneal metastasis from colorectal cancer

  Patients with peritoneal metastasis from colorectal cancer (PM-CRC) have inferior prognosis and respond particularly poorly to chemotherapy. This study aims to identify the molecular explanation for the observed clinical behavior and suggest novel treatment strategies in PM-CRC. Tumor samples (230) from a Norwegian national cohort undergoing surgery and hyperthermic intraperitoneal chemotherapy (HIPEC) with mitomycin C (MMC) for PM-CRC were subjected to targeted DNA sequencing, and associations with clinical data were analyzed. mRNA sequencing was conducted on a subset of 30 samples to compare gene expression in tumors harboring BRAF or KRAS mutations and wild-type tumors.

  Study EGAS50000000404

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010117

• Reconstruction of complex rearrangement patterns causing the initiation of clear cell renal cell carcinoma.

  The genomic hallmark of clear cell renal cell carcinoma is the loss of the short arm of chromosome three. This appears to be the earliest genomic event in the formation of these cancers. Often chromosome 3 is lost at the same time as part of chromosome 5 is duplicated via an unbalanced translocation, often with features consistent with focal chromothripsis. In this study, we sought to reconstruct the chromothriptic event that underlies the initiation of kidney cancer. We used long read sequencing (promethION, Oxford Nanopore Technologies) of patient tumour-derived DNA to elucidate how a single cell division error can generate cancer genome complexity.

  Study EGAS00001004015

• Spatial and temporal genomic evolution in glioblastoma

  Tumor heterogeneity is a challenging barrier to successful targeted therapy in glioblastoma. Identifying the mechanisms that drive cancer cells as they genetically evolve and adapt in response to treatment is a vital goal of modern cancer research. Analysis of sequencing data provides a method for uncovering the mechanisms sustaining tumor heterogeneity and driving evolution. Here, we analyzed genomic profiles of GBM biopsies taken from pre- and post-treatment GBMs (with matched germline controls), to understand 1) the intratumoral clonal compositions of primary GBM and 2) how GBM responds to therapeutic intervention. Our results provide a molecular portrait of GBM recurrence.

  Study EGAS00001001033

• Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer

  This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002509

• Tissue-specific cell-free DNA degradation quantifies circulating tumor DNA burden

  Profiling of circulating tumor DNA (ctDNA) may offer a non-invasive approach to monitor disease progression. Here, we developed a quantitative method, exploiting local tissue-specific cell-free DNA (cfDNA) degradation patterns, that accurately estimates ctDNA burden independent of genomic aberrations. Nucleosome-dependent cfDNA degradation at promoters and first exon-intron junctions was strongly associated with differential transcriptional activity in tumors and blood. A quantitative model, based on just 6 regulatory regions, could accurately predict ctDNA levels in colorectal cancer patients. Strikingly, a model restricted to blood-specific regulatory regions could predict ctDNA levels across both colorectal and breast cancer patients.

  Study EGAS00001004657

• European Genome-phenome Archive 15th Anniversary Celebration

  2023 marks the 15th Anniversary of the EGA, jointly managed by the European Bioinformatics Institute (EMBL-EBI) and the Centre for Genomic Regulation (CRG). To mark the occasion, a simultaneous celebration was held in both institutions on the 13th of December 2023. The teams gathered online to play a quiz game and celebrate all the achievements and milestones with two wonderful anniversary cakes. In 2008, the European Genome-phenome Archive was created at the EBI-EMBL in Cambridge to guarantee that human genome and phenome data were available to the international scientific community while data privacy was preserved. The six-person staff at the beginning of the project is now far behind us, with a team that reaches the number of 35 members. Since 2013, the European Bioinformatics Institute and the Centre for Genomic Regulation share responsibility for The European Genome-phenome Archive (EGA). At that time, the EGA had data for about 0,5 petabytes. Currently, the Archive contains more than 12 petabytes. 2023 comes to an end with several good news. The EGA has been renewed as an ELIXIR Core Data Resource. This was announced during the GA4GH 11th Plenary held in San Francisco last September when ELIXIR-Beacon was also confirmed to be a GA4GH Driver Project. Thus, the Beacon API has maintained this title since 2018. What’s more, the first Federated EGA dataset is now live on our website. This year we also launched new services for EGA users in September. By the numbers, in 2023 the EGA counts 2.5 PB archived, 371 studies published, 208 new submitters and 19 active projects in which the team is participating, among others. We look forward to continuing to support your research in 2024!

  Blog 15-anniversary

• Expression profiling of a human endocrine pancreas iPSC model

  Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to the endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. “insulin secretion”; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

  Dataset EGAD00001002148

• DAC - The Netherlands Cancer Institute - Antoni van Leeuwenhoek

  Dac EGAC00001003316

• THE NOWAC BLOOD-BREAST CANCER COMMITEE DATA ACCESS AGREEMENT

  Dac EGAC00001000743

• "Data Access Center Cancer Genomics Group"

  Dac EGAC00001000030

• Cancer Genome Database Data Access Committee (CGDB_DAC)

  Dac EGAC00001000033

• DAC for Single Cell Transcriptomics of Colorectal Cancer

  Dac EGAC00001000550

• Breast cancer multi-region sequencing from Sottoriva Lab

  Dac EGAC00001000890

• Harbin Medical University Cancer Hospital Data Access Commitee

  Dac EGAC00001000948

• DAC for study Non-coding RNAs in Breast Cancer

  Dac EGAC00001001090

• UT MD Anderson Cancer Center Genomic Medicine and Leukemia

  Dac EGAC00001001252

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001285

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001391

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001404

• Cancer Sequencing Data Access Committee

  Dac EGAC00001001428

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001505

• The data usage policy for epigenomic profile of diverse cancer

  Dac EGAC00001001540

• INSERM U981 Team : Genomics of Non-Melanoma Skin Cancer

  Dac EGAC00001001644