52b505d2-4bab-47e3-a743-59b3cc7dd1b9 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001006233 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Exome sequencing for individualized cancer interpretation
| EGAD00001006236 | EGA
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
| 2533916 | ecrin-mdr-crc
Project description:Total RNA transcriptome profiling by high-throughput for individualized cancer interpretation
| EGAD00001006235 | EGA
Project description:PolyA selection transcriptome profiling by high-throughput for individualized cancer interpretation
| EGAD00001006234 | EGA
Project description:Cancer cell lines can provide robust and facile biological models for the generation and testing of hypothesis in the early stages of drug development and caner biology. Although clinical trials remain the ultimate scientific testing ground for anticancer therapies, the use of appropriate model systems to explore the molecular basis of drug activity and to identify predictive biomarkers during their development can have a profound effect on the design, cost and ultimate success of new cancer drug development. In order to capture the high degree of genomic diversity in cancer and to identify rare molecular subtypes, we have assembled a collection of >1000 cancer cell lines. These lines have been characterised using whole exome sequencing, genome wide analysis of copy number, mRNA gene expression profiling and DNA methylation analysis (http://cancer.sanger.ac.uk/cell_lines). To further characterise this panel of cell lines we have now compiled data for RNA sequencing. The current study represent data for ~450 of the cell lines in the panel, data for the remaining lines can be accessed via the CGHUB data browser hosted at UCSC. <br>This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of the EGA data set is EGAD00001001357 under EGA study accession EGAS00001000828.
2017-09-25 | E-MTAB-3983 | biostudies-arrayexpress
Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 677 genes in 52 breast cancer samples.
2023-08-08 | GSE37963 | GEO
Project description:The study is intended to collect specimens to support the application of genome analysis technologies, including large-scale genome sequencing. This study will ultimately provide cancer researchers with specimens that they can use to develop comprehensive catalogs of genomic information on at least 50 types of human cancer. The study will create a resource available to the worldwide research community that could be used to identify and accelerate the development of new diagnostic and prognostic markers, new targets for pharmaceutical interventions, and new cancer prevention and treatment strategies. This study will be a competitive enrollment study conducted at multiple institutions.
| 2140168 | ecrin-mdr-crc
Project description:We profile single cells from patients with colorectum cancer using Chromium 3’ and 5’ single-cell RNA-sequencing. Patients EXT001, EXT009, and EXT012 from the KUL dataset were first analyzed by Lee et al., 2020, and the raw data are available in ArrayExpress under the accession codes E-MTAB-8410 and E-MTAB-8107. Patients EXT018, EXT048, EXT113, and EXT121 from KUL dataset were previously analyzed by Joanito et al., 2022. The raw data of those patients are available in EGA under the accession codes EGAD00001008584 and EGAD00001008585.
2022-09-16 | E-MTAB-9934 | biostudies-arrayexpress
Project description:DNA methylation is a complex epigenetic marker that can be analysed using a wide variety of methods. Interpretation and visualisation of DNA methylation data can mask complexity in terms of methylation status at each CpG site, cellular heterogeneity of samples and allelic DNA methylation patterns within a given DNA strand. Bisulfite sequencing is considered the gold standard, however visualisation of massively parallel sequencing results remains a significant challenge. We created a program called Methpat that facilitates visualisation and interpretation of bisulfite sequencing data generated by massively parallel sequencing. To demonstrate this, we performed multiplex PCR that targeted 48 regions of interest across 95 human samples. The regions selected included known gene promoters associated with cancer, repetitive elements, known imprinted regions and mitochondrial genomic sequences. We interrogated a range of samples including human cell lines, primary tumours and primary tissue samples. Methpat generates two forms of output: a tab delimited text file for each sample that summarises DNA methylation patterns and their read counts for each amplicon and a HTML file that summarises this data visually. Methpat can be used with publicly available whole genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) datasets with sufficient read depths. Using Methpat, complex DNA methylation data derived from massively parallel sequencing can be summarised and visualised for biological interpretation. By accounting for allelic DNA methylation states and their abundance in a sample, Methpat can unmask the complexity of DNA methylation and reveal further biological insight in existing datasets. Multiplex bisulfite PCR and Next Generation sequencing of primary human samples and breast cancer cell lines.
2015-11-23 | E-GEOD-71804 | biostudies-arrayexpress
Project description:At the moment of union in fertilization, sperm and oocyte are transcriptionally silent. The ensuing onset of embryonic transcription (embryonic genome activation, EGA) is critical for development, yet its timing and profile are unknown in any vertebrate species. We here dissect hitherto inaccessible transcription during EGA by high resolution single-cell RNA-sequencing of precisely synchronized mouse one-cell embryos. This reveals a program of embryonic gene expression (immediate EGA, iEGA) initiating within four hours of fertilization. Expression during iEGA produces canonically-spliced transcripts, occurs substantially from the maternal genome, and is mostly down-regulated at the two-cell stage. Transcribed genes predict regulation by transcription factors (TFs) associated with cancer, including c-Myc. Blocking c- Myc or other predicted regulatory TF activities disrupts iEGA and induces acute developmental arrest. These findings illuminate intracellular mechanisms that regulate the onset of mammalian development and promise a new paradigm for the study of cancer
2023-01-09 | GSE222130 | GEO