11768 results for "cancer rna-seq"

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• Single-cell multi-omics and mtDNA genotyping of human peripheral blood cells

  This dataset comprises two mtscATAC-seq libraries (customized 10X ATAC-seq) generated from donor M80 and donor H05, and one DOGMA-seq library (customized 10X multiome) generated from donor H05, all derived from primary human peripheral blood mononuclear cells. Patient M80 is an 80-year-old male with mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS), while donor H05 is a healthy 5-year-old pediatric donor. The raw FASTQ files have been provided.

  Dataset EGAD50000001489

• ATAC-seq in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  ATAC-seq performed in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives to profile alterations in chromatin accessibility associated with constitutional MLH1 epimutation.

  Dataset EGAD50000000714

• scDNA-seq

  Single cell DNA-seq data (CLL gene panel - Tapestri single-cell DNA CLL panel, Mission Bio)

  Dataset EGAD00001008960

• scRNA-seq of monocultures and co-cultures of PDAC-PDOs and CAFs

  scRNA-seq of monocultures and co-cultures of patient-derived PDAC organoids and matched CAFs. 3 sample sets per patient.

  Dataset EGAD00001009655

• Human tumor scATAC-seq

  We profiled 4 high-grade gliomas patient brain tumor samples by single-cell ATAC-seq using the 10X Chromium 3' technology. The raw fastq and index files are provided.

  Dataset EGAD00001008347

• McGill EMC Release 4 for assay "ATAC-seq"

  McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688)

  Dataset EGAD00001001300

• BLUEPRINT: WGBS-seq for monocytes and neutrophils

  WGBS-seq for monocytes and neutrophils

  Dataset EGAD00001000673

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• T-cell receptor sequencing of tumor-infiltrating lymphocytes (TIL) in breast cancer

  The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing patients’ tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating widely available archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of various tumor environments. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and revealed higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top ten dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is readily applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

  Study EGAS00001007125

• CRC cell line ATAC-seq

  ATAC-Seq data for C32, CACO2, CL11, HT29, SW403, SW480, SW948 MSS CRC cell lines, and HCEC-1CT normal colon cell line

  Dataset EGAD50000000296

• Two scRNA-seq datasets from control and irradiated organoids.

  Dataset includes two scRNA-seq samples from control and irradiated organoids. Files included in the dataset are Fastq files. Sample libraries produced with Chromium X were sequenced on an Illumina NovaSeq 6000 sequencer.

  Dataset EGAD50000001933

• BLUEPRINT: WGBS-seq of B cells

  Whole Genome Bisulfite-seq of four B cell samples

  Dataset EGAD00001000710

• CLL ATAC Seq of Untreated and IBET762 treated samples

  CLL PBMC cells were isolated using ficoll gradient. They have been treated with IBET762 or DMSO as solvent control and ATAC Seq has been performed on them.

  Dataset EGAD00001008723

• Results of scRNA-seq analysis of a PBMC collected from a male with a mosaic 45,X/48,XYYY karyotype

  Results of scRNA-seq analysis of a PBMC collected from a male with a mosaic 45,X/48,XYYY karyotype

  Dataset EGAD00001008645

• BLUEPRINT September 2016, ATAC-seq for bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002710

• Dataset to study clonal evolution in iAMP21 patient SJBALL021901 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJBALL021901 with 71 high quality cells sequenced (67 blast and 4 normal)

  Dataset EGAD00001009755

• CITE-seq

  This dataset contains the raw sequencing data (Runs) from all of the 10x Genomics single-cell CITE-seq Experiments, as well as the demultiplexed cell-donor identities matrices which were generated with Vireo (Analysis).

  Dataset EGAD00001009820

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Dataset EGAD00001009964

• ctDNA mutation analysis using the SiMSen-seq approach

  Mutation analysis in plasma samples with low ctDNA levels using a molecular barcoding technology, i.e. the single target approach SiMSen-seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing).

  Dataset EGAD00001006104

• release_2: ICGC PedBrain: whole exome sequencing and Target-Seq

  release_2: ICGC PedBrain: whole exome sequencing and Target-Seq

  Dataset EGAD00001001624

• Single-cell ATAC-Seq (Chromium Next GEM Single Cell ATAC kit v1.1 from 10X Genomics )

  Human data for chromatin accessibility (scATAC-Seq) in CD34+ B cell precursors.

  Dataset EGAD00001010910

• Epigenetic profiles of neuroblastoma PDXs

  This dataset contains bam files for ChIP-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft). It includes the bam files for the H3K27ac mark as well as the bam files of the corresponding input DNA for each sample.

  Dataset EGAD00001003394

• FASTQ Files from Breast Tumor Biopsies Collected Across Five Timepoints in the PROMETEO Phase II Trial

  The dataset contains RNA sequencing raw data from tumor biopsies collected at five time points during the SOLTI-1503 PROMETEO trial: baseline (pre-NAC), post-NAC screening, Cycle 2 Day 1, Cycle 3 Day 1, and surgery. The study intervention consisted of intratumoral injections of T-VEC followed by intravenous administrations of atezolizumab prior to surgery. The data is obtained from tumor samples of patients included in the study: female breast cancer patients with residual disease after neoadjuvant chemotherapy, including both triple-negative and Luminal B-like subtypes. Each sample includes raw paired-end RNAseq reads (~110 million reads per library) aligned to the GRCh38/hg38 reference genome

  Dataset EGAD50000002165

• Dataset for upper_gastrointestinal_tumor-RNA

  Rare cancer sequencing data of 44 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008853

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

  Dataset EGAD00001004938