11936 results for "cancer rna-seq"

in 16.15 milliseconds.

• Single-cell RNA sequencing of breast cancer lung metastasis and adjacent normal tissue

  This dataset contains single-cell RNA sequencing data from two samples: L1 (breast cancer metastasis to lung) and N3 (adjacent normal lung tissue) from a female patient. The samples were processed using 10X Chromium 3' technology and sequenced on Illumina NextSeq 500. This data supports the study "Endocrine therapy reprogramming of breast cancer facilitates metastatic escape via upregulation of P-Rex1/Rac1 signalling" which investigates how endocrine therapy reprograms breast cancer cells, leading to upregulation of P-Rex1/Rac1 signalling pathways that facilitate metastatic escape. The single-cell analysis reveals cellular reprogramming mechanisms in endocrine therapy-resistant breast cancer cells that form metastases in the lung.

  Dataset EGAD00001015769

• Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

  We discovered a conserved neural tri- lineage cancer hierarchy centered around glial progenitor-like cells. We also found that this progenitor population contains the majority of the cancer’s cycling cells, and, using RNA velocity, is often the originator of the other cell types. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, suggests a possible origin for glioblastoma hierarchy, and helps to identify cancer stem cell-specific targets.

  Study EGAS00001004422

• Dataset of 5 RNAseq from 3 non-muscle-invasive bladder cancer patients

  RNAseq (FASTQ files) of 5 tumor from 3 non-muscle-invasive bladder cancer patients. For patient UC2, RNA from 3 different synchronous tumors was extracted. Relating to the other datasets from the project : no RNA was available from patient UC4. NB : patients aliases are the following : ROXY : UC1, OMAD : UC2, MAKI : UC3, HAPE : UC4

  Dataset EGAD50000002009

• Human lymphoma plasma cfRNA - raw data

  This study contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma patients, 13 primary mediastinal large B-cell lymphoma patients and 22 cancer-free controls.

  Study EGAS00001007127

• Illumina TSO500 RNA Dataset for Manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  Illumina TSO500 RNA Dataset for Manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  Dataset EGAD00001015397

• Tumor Profiler Melanoma Study

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA, scDNA, and bkRNA data of the melanoma cohort.

  Study EGAS50000000599

• Bladder cancer subtyping study across 4 atezo clinical trials

  Checkpoint inhibitors targeting the PD-1/PD-L1 interaction have revolutionized cancer therapy across many indications. In urothelial carcinoma (UC), several PD-1/PD-L1 inhibitors have been approved for treatment in localized and metastatic disease. While these agents provide durable clinical benefit in a number of patients, the majority do not respond. A better understanding of the molecular mechanisms underlying response and resistance is needed to tailor existing treatments and develop new therapeutics in UC. We profiled tumors from 2803 patients from four late-stage randomized clinical trials evaluating the PD-L1 inhibitor atezolizumab in metastatic UC and muscle-invasive bladder cancer by RNA-seq, a targeted DNA panel, immunohistochemistry, and digital pathology. A machine learning algorithm identified four UC transcriptional subtypes, representing luminal desert, stromal, immune, and basal tumors. Overall survival benefit from atezolizumab over standard-of-care was observed in immune and basal tumors (45% of patients). Digital pathology showed enrichment of human interpretable features in specific molecular subtypes, and a self-supervised approach could classify molecular subtypes from H&E slides with high accuracy, suggesting that machine-based image interpretation could accelerate tumor molecular profiling. Somatic alterations showed limited capacity to identify responders. Finally, mechanisms of benefit with PD-L1 blockade appeared different in immune and basal tumors, with immune tumors benefiting from B/plasma cell enrichment, while basal tumors benefited from granulocyte enrichment. This study represents the largest integration of UC molecular and curated clinical data in randomized clinical trials to date, paving the way for prospective clinical studies tailoring treatment regimens to specific tumor molecular subtypes in UC and other indications.

  Study EGAS50000000497

• Somatic L1 retrotransposition dynamics in high-grade serous ovarian cancer

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from same patient were utilised to understand L1-mediated intrapatient heterogeneity.

  Study EGAS50000001198

• ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001231

• Fastq data for ChIP-Seq (H3K27ac) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (H3K27ac) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001403

• ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001233

• Fastq data for ChIP-Seq (Input) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (Input) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001409

• ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001229

• ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001232

• ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001234