Project description:Arrested bone marrow (BM) lymphoid cell differentiation underlies the emergence of the most common childhood cancer, acute lymphoblastic leukemia (ALL). Recurrent genetic lesions often directly involve transcription factors (TFs), such as ETV6 and RUNX1 found in the most common ALL translocation. Here, we studied differential gene expression in ETV6-RUNX1 primary ALL samples and the REH cell line using single cell RNA-seq (scRNA-seq). Submitter declares that the raw data will be deposited in EGA due to patient privacy concerns. The raw data can be accessed at https://www.ebi.ac.uk/ega/studies/EGAS00001004374
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:This single cell RNA-seq experiment was performed to quantify DLL3 expression in tumor cells in small cell lung cancer patients.Tumors were rapidly dissociated after the surgical procedure using the Miltenyi Biotec Human Tumor Dissociation kit (cat# 130-095-929). Libraries were constructed using the VDJ NextGEM v1.1 10x Genomics Chromium kit according to the manufacturer's instructions. Samples were sequenced on a NextSeq 550 sequencer (Illumina). Corresponding EGA study number: EGAS50000001400, EGA dataset number: EGAD50000002034.
Project description:Single-cell RNA-seq libraries were generated from human PBMCs that were incubated with anti-HER2/CD3 TDB in the presence of KPL-4 cells. This dataset only contains the metadata and processed data. Raw data can be accessed via the EGA accession EGAS00001003734
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: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.
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.