Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
Project description:High-grade serous ovarian cancer (HGSOC) is thought to originate from the fallopian tube (FT), highlighting the importance of studying molecular features across tumor samples. This dataset contains bulk RNA sequencing data from tumor samples of HGSOC patients. The data can be used for driver mutations and copy number alterations (CNAs) profiling and analysis of gene expression patterns, including regions relevant to HLA typing. This submission contains bulk RNA sequencing data associated with this study.
Project description:This study investigated mechanisms of acquired resistance to FGFR inhibitor therapy in RAS/RAF–wild-type colorectal cancer (CRC). RNA sequencing (RNA-seq) data from 47 RAS/RAF-wild-type colorectal cancer stem-cell (CRC-SC) spheroid lines previously deposited under GSE205787 were integrated with newly generated RNA-seq data from 31 additional RAS/RAF-wild-type CRC-SC spheroid lines and seven FGFR inhibitor-resistant CRC-SC derivatives. The resistant derivatives were established from parental CRC-SC spheroid lines by continuous exposure to erdafitinib or futibatinib. Comparative transcriptomic analysis between matched parental and resistant lines revealed consistent upregulation of EGFR and downregulation of PTPROt, a truncated isoform of PTPRO, in resistant derivatives. Gene set enrichment analysis further indicated activation of EGFR-related signaling pathways in FGFR inhibitor-resistant spheroids. In addition, the integrated RNA-seq dataset comprising 78 RAS/RAF-wild-type CRC-SC lines was used to validate the inverse correlation between EGFR and PTPRO mRNA expression, supporting the involvement of PTPROt downregulation and EGFR pathway activation in acquired resistance to FGFR inhibition.
Project description:Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here, we present an ultra-fast scanning data-independent acquisition (DIA) strategy consisting on 2-Th precursor isolation windows, dissolving the differences between data-dependent and independent methods. This is achieved by pairing a Quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer that provides >200 Hz MS/MS scanning speed, high resolving power and sensitivity, as well as low ppm-mass accuracy. Narrowwindow DIA enables profiling of up to 100 full yeast proteomes per day, or ~10,000 human proteins in half-an-hour. Moreover, multi-shot acquisition of fractionated samples allows comprehensive coverage of human proteomes in ~3h, showing comparable depth to next-generation RNA sequencing and with 10x higher throughput compared to current state-of-the-art MS. High quantitative precision and accuracy is demonstrated with high peptide coverage in a 3-species proteome mixture, quantifying 14,000+ proteins in a single run in half-an-hour.
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 74 samples of primary cells or cultured primary cells of different haemopoeitc lineages from cord blood, venous blood, bone marrow and thymus are included in this experiment. 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. There are 32 EGA data set accessions, which can be found under the Comment[EGA_DATA_SET] column in the 'Sample Data Relationship Format' (SDRF) file of this ArrayExpress record (http://www.ebi.ac.uk/arrayexpress/files/E-MTAB-3827/E-MTAB-3827.sdrf.txt). Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. Likewise, mapping of samples to these EGA accessions can be found in the SDRF file. Please note that the raw data files for 11 sequencing runs have yet been deposited at EGA, so they are marked with \\ot available\\ under the Comment[SUBMITTED_FILE_NAME] field in the SDRF file, and were included for the sake of completeness. Further iInformation on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu\
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 4 samples of primary cells from tonsil with cell surface markes CD20med/CD38high in young individuals (3 to 10 years old) are included in this experiment. 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 EGA data sets is EGAD00001001523. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu