15080 results for "cancer studies using rna-seq"

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• single nuclei RNASeq of 5 regions of the human prenatal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Study EGAS00001006537

• SMARCB1 loss activates patient-specific distal oncogenic enhancers in malignant rhabdoid tumors

  Malignant rhabdoid tumor (MRT) is a highly malignant and often lethal childhood cancer. MRTs are genetically defined by bi-allelic inactivating mutations in SMARCB1, a member of the BRG1/BRM-associated factors (BAF) chromatin remodeling complex. Mutations in BAF complex members are common in human cancer, yet their contribution to tumorigenesis remains in many cases poorly understood. Here, we studied derailed regulatory landscapes as a consequence of SMARCB1 loss in the context of MRT. Our multi-omics approach on patient-derived MRT organoids revealed a dramatic reshaping of the regulatory landscape upon SMARCB1 reconstitution. Chromosome conformation capture experiments subsequently revealed patient-specific looping of distal enhancer regions with the promoter of the MYC oncogene. This intertumoral heterogeneity in MYC enhancer utilization is also present in patient MRT tissues as shown by combined single-cell RNA-seq and ATAC-seq. We show that loss of SMARCB1 drives patient-specific epigenetic reprogramming underlying MRT tumorigenesis.

  Study EGAS00001007590

• bulk Exome-seq of the 5 HCC patients which also have the single cell T cell RNA-seq data

  bulk Exome-seq data of the 5 HCC patinets. Single cell RNA seq data of these patients was under the accession number EGAD00001003337

  Dataset EGAD00001004149

• scRNA dataset for 15 samples

  This dataset includes single cell (sc)RNA-seq of N=3 patient-derived xenograft (PDX) samples profiled at baseline (no drug treatment) and N=12 samples from one PDX profiled during the course of treatment (N=1 sample each for 4 treatment arms x 3 timepoints). The dataset includes bam files that have been purged of reads mapping to cells where a majority of the reads from that cell mapped to the mouse genome. All scRNA-seq data were generated using the Chromium Next GEM Single Cell 5' Reagent Kits v2 (Dual Index) from 10X Genomics.

  Dataset EGAD50000001424

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• RNA-seq of human astroblastomas

  RNA-seq for fusion gene discovery of human astroblastomas

  Dataset EGAD00001009664

• The landscape of chromothripsis across adult cancer types

  Chromothripsis is a recently identified mutational phenomenon, by which a presumably single catastrophic event generates extensive genomic rearrangements of one or a few chromosome(s). Considered as an early event in tumour development, this form of genome instability plays a prominent role in tumour onset. Chromothripsis prevalence might have been underestimated when using low-resolution methods, and pan-cancer studies based on sequencing are rare. We analysed chromothripsis in 28 tumour types covering all major adult cancers (634 tumours, 316 whole-genome and 318 whole-exome sequences). We show that chromothripsis affects a substantial proportion of human cancers, with a prevalence of 49% across all cases. Chromothripsis generates entity-specific genomic alterations driving tumour development, including clinically relevant druggable fusions. Chromothripsis is linked with specific telomere patterns and univocal mutational signatures in distinct tumour entities. Longitudinal analysis of chromothriptic patterns in 24 matched tumour pairs reveals novel insights in the clonal evolution of tumours with chromothripsis. (H021)

  Study EGAS00001004250

• Paired Biopsy Project: West Coast Dream Team

  This project aims to analyze the paired metastatic biopsy samples from patients with metastatic castration-resistant prostate cancer (mCRPC), collected before the initiation of the first-line androgen receptor signaling inhibitor (ARSI) for mCRPC and after radiographic disease progression on that ARSI, to understand the resistance mechanisms. We generated both whole genome sequencing (WGS) and RNA-seq data on these samples. A majority of these samples have been deposited in the public domain along with prior publications, and this project contains the 16 WGS samples that have not yet been deposited.

  Study EGAS50000000327

• Transcriptome Sequencing PPGL

  RNA library preparation of samples with RNA Integrity Number (RIN) > 5.5 (median 7.1; range 5.6-8.9) was performed as described in the TruSeq Stranded mRNA Library Prep Kit (Illumina, RS-122-2101). Briefly, 0.7-1 µg total RNA PolyA+ fraction was purified and randomly fragmented, converted to double stranded cDNA and processed through subsequent enzymatic treatments of end-repair, dA-tailing, and ligation to adapters. Adapter-ligated library was completed by PCR with Illumina PE primers. The resulting purified cDNA library was applied to an Illumina flow cell for cluster generation and sequenced on an Illumina HiSeq2500 on a 51bp single-read format following manufacturer's protocols. cDNA libraries from FFPE tumors and low integrity RNA’s (RIN<5.5) from FF tumors (median 2.4; range 1-5.5) but % of fragments > 200 nucleotides higher than 20% (median 57.5; range 20-96) were prepared using QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015) with a UMI Second Strand Synthesis Module for QuantSeq FWD (Lexogen, 081), vendor’s protocol for low input/ low quality/ FFPE RNA using 200-500 ng of total RNA, according to availability, was used as starting material. PCR Add-on Kit for Illumina (Lexogen, 020) was used to adjust the library amplification number of cycles. Libraries were applied to an Illumina flow cell for cluster generation and sequenced on NovaSeq6000. Image analysis, per-cycle basecalling and quality score assignment was performed with Illumina Real Time Analysis software. Demultiplexing of BCL files to FASTQ format was performed with the bcl2fastq Software (Illumina).

  Study EGAS00001006044

• University of Hull

  Tumour Regulatory Molecules in Early Pancreatic Cancer Detection (TEM-PAC) and EARLY DIAgnosis of PAncreatic Cancer by combined proteomics and genomics testing of pancreatic cyst fluid (DIA-PAC) studies.

  Dac EGAC50000000402