Project description:H3K27ac ChIP-seq of 79 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). In addition, 4 samples derived from CD34+ cord blood cells of healthy donors were included. Due to patient confidentiality considerations, the raw data files for this dataset have been deposited to the EGA controlled-access archive under the accession numbers EGAS00001007094 (study); EGAD00001011060 (dataset).
Project description:Clinical and molecular risk factors were analyzed in a large cohort of patients with Atypical Teratoid Rhabdoid Tumors (ATRT) recruited to the European Rhabdoid Regsitry (EU-RHAB) and data were validated in a second independent cohort of ATRT patients.
Project description:The samples deposited here are part of the ATRT consensus cohort as published in Ho et al. ("Molecular subgrouping of Atypical Teratoid/Rhabdoid Tumors (ATRT) - a reinvestigation and current consensus") and have so far not been included in any publication.
Project description:Atypical teratoid/rhabdoid tumor (ATRT) is one of the most common brain tumors in infants. Although the prognosis of ATRT patients is poor, some patients respond favorably to current treatments, suggesting molecular inter-tumor heterogeneity. To investigate this further, we genetically and epigenetically analyzed a large series of human ATRTs. Three distinct molecular subgroups of ATRTs, associated with differences in demographics, tumor location, and type of SMARCB1 alterations, were identified. Whole-genome DNA and RNA sequencing found no recurrent mutations in addition to SMARCB1 that would explain the differences between subgroups. Whole-genome bisulfite sequencing and H3K27Ac chromatin-immunoprecipitation sequencing of primary tumors, however, revealed clear differences, leading to the identification of subgroup-specific regulatory networks and potential therapeutic targets. 49 ATRT samples were selected for RNA extraction and hybridization on Affymetrix Affymetrix Human Genome U133 Plus 2.0 Arrays. ---------------------------------------- This submission consists of the expression data for 49 of 170 samples only
Project description:This single cell RNA-seq experiment was performed to quantify DLL3 expression in circulating tumor cells in small cell lung cancer patients to predict response to tarlatamab treatment. CTCs enriched from the blood of three SCLC patients prior or post tarlatamab treatment using the CTC-iChip followed by magnetic depletion of RBCs were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system. Corresponding EGA study number: EGAS50000001401, EGA dataset number: EGAD50000002035
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:Single-cell RNA sequencing was performed on bone marrow mononuclear of a patient with acute myeloid leukemia with erythroid differentiation of the blasts and on peripheral blood mononuclear cells of a patient with acute myeloid leukemia with megakaryocytic differentiation of the blasts. Raw data for this dataset can be found at the EGA under accession EGAS00001006819.