12216 results for "cancer rna-seq"

in 11.27 milliseconds.

• Single-Cell Sequencing of Genomic DNA, RNA, and ADT in CRISPR-Edited Cells

  CRAFTseq data containing multi-modal single-cell genomic DNA amplicon, cDNA and surface-protein from various primary cell types and cell lines, including human CD4 T cells, Jurkat cells, HH cells, Daudi cells and HEK293T cells. Cells were edited with CRISPR HDR or base editing. Also contains bulk RNA-seq data for edited human primary CD4 T cells and Daudi cells.

  Study phs004042

• Genetic and Epigenetic Screens in Primary Human T Cells Link Candidate Causal Autoimmune Variants to T Cell Networks

  We aimed to define the target genes and pathways in which autoimmune disease-associated genetic variants operate. We performed single cell-CRISPR-interference screens in primary human T cells and bulk RNA-seq on T cells containing CRISPRi and single gRNAs to assess how T cell regulatory regions containing autoimmune-associated genetic variants affect nearby gene expression and cellular programs.

  Study phs004072

• RNA-seq and Hi-C data of a chromothripsis patient's iPS cells

  This dataset contains RNA-seq and Hi-C data files of induced pluripotent stem (iPS) cells and iPS cell-derived neural progenitors (NPCs) derived from a germline chromothripsis patient and both parents. iPS cells of the patient (cell lines 14 and 15), the father (lines 23 (with two replicates) and 32) and mother (line 30) were differentiated to NPCs and RNA was collected on day 0, day 7 and day 10 of differentiation. In addition, Hi-C data for two iPS cell-derived NPC lines from the patient (14 and 15) and two lines from the father (23 and 32) was generated.

  Dataset EGAD00001002242

• RNA-seq analysis refines molecular subtypes of hepatocellular carcinoma

  This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the consistency between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. We further characterized HCC subtypes using transcriptomic and clinicopathological features. Our study provided a robust molecular classification based on a large HCC dataset from a Western country, improving our understanding of the mechanisms of carcinogenesis and facilitating the development of genome-based precision medicine in HCC.

  Dataset EGAD00001015427

• RNA-seq of CML074 Tumor tissue; Timpepoint 1

  Dataset EGAD00001001259

• RNA-seq of CML074 Tumor tissue; Timpepoint 2

  Dataset EGAD00001001260

• The paired FF/FFPE colon set, RNA-Seq

  Dataset EGAD00001000831

• Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

  Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we found a significant B cell association with extended OS with PD-L1 blockade, independent of CD8+ T cell signals. We then derived gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA-seq data. Importantly, we found increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B cells were also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to PD-L1 blockade efficacy in NSCLC.

  Study EGAS00001005013

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• RNA-Seq

  RNA Sequencing

  Dataset EGAD00001001121