12004 results for "cancer rna-seq"

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• Genome and transcriptome sequence data from a metastatic adult granulosa cell tumour patient

  Genome and transcriptome sequence data from a metastatic adult granulosa cell tumour patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003002

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003005

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectum patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectum patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003012

• Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient

  Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003018

• Genome and transcriptome sequence data from a metastatic renal cell carcinoma patient

  Genome and transcriptome sequence data from a metastatic renal cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003023

• Genome and transcriptome sequence data from an adenocarcinoma of the distal esophagus patient

  Genome and transcriptome sequence data from an adenocarcinoma of the distal esophagus patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003061

• Genome and transcriptome sequence data from a non-small cell lung carcinoma patient

  Genome and transcriptome sequence data from a non-small cell lung carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003653

• Genome and transcriptome sequence data from a metastatic endometrioid/mucinous ovarian carcinoma patient

  Genome and transcriptome sequence data from a metastatic endometrioid/mucinous ovarian carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004636

• Genome and transcriptome sequence data from a locally advanced oropharyngeal carcinoma patient

  Genome and transcriptome sequence data from a locally advanced oropharyngeal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004655

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004673

• Genome and transcriptome sequence data from a adenocarcinoma of the liver patient

  Genome and transcriptome sequence data from a adenocarcinoma of the liver patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004706

• Genome and transcriptome sequence data from a metastatic carcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002983

• Bam files from whole exome sequencing (WES)from multiple laser microdissected regions from tumor and paired biopsies from metastatic lesions.

  In this study we characterized genomic alterations in three bladder cancer patients with metastatic disease courses. Multiple regions were procured by laser microdissection or punctures from primary tumor, lymph node metastases and from distant metastases. Data provided here consist of 35 Bam files for WES (32 Tumors and 2 blood, 1 adjacent normal)

  Dataset EGAD00001002772

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of colon patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of colon patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011015

• Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

  We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Whole genome sequencing was performed as 150bp paired end reads on the Illumina NovaSeq 6000 platform.

  Dataset EGAD00001011174

• Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine patient

  Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005763

• The evolution of hematopoietic cells under cancer therapy

  WGS TAML samples with their remission controls obtained from bone marrow.

  Dataset EGAD00001007706

• Genome and transcriptome sequence data from a non-small cell lung carcinoma patient

  Genome and transcriptome sequence data from a non-small cell lung carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010942

• Genome and transcriptome sequence data from a metastatic breast ductal carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011021

• Organoid Derivation Project - GRCh38 - RNAseq (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011092

• Genome and transcriptome sequence data from a malignant peripheral nerve sheath tumor patient

  Genome and transcriptome sequence data from a malignant peripheral nerve sheath tumor patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015583

• Distinct immune cell infiltration patterns in pancreatic ductal adenocarcinoma (PDAC) exhibit divergent immune cell selection and immunosuppressive mechanisms

  Pancreatic ductal adenocarcinoma has a dismal prognosis. A comprehensive analysis of single-cell multi-omic data from matched tumour-infiltrated CD45+ cells and peripheral blood in 12 patients, and two published datasets, reveals a complex immune infiltrate. Patients have either a myeloid-enriched or adaptive-enriched tumour microenvironment. Lymphocyte enrichment is intrinsically linked with highly distinct B and T cell clonal selection, diversification, and differentiation. Using TCR data, we see the largest clonal expansions in CD8 effector memory, senescent cells, and highly activated regulatory T cells which are induced within the tumour from naïve cells. We identify pathways that potentially lead to a suppressive microenvironement, including targets of immunotherapy and checkpoints including TIGIT/PVR and SIRPA/CD47. PDAC patient tumors from the APACT clinical trial revealed that patients with myeloid enrichment had the shorter overall survival compared to those adaptive cell enrichment. We identify multiple therapeutic targets that should form the basis for rational design including boosting of B cell responses, targeting immunosuppressive macrophages, and specific Treg depletion approaches. The dataset is scRNA-seq data from PDAC patients.

  Dac EGAC50000000319

• PD-associated regulatory variants in human dopaminergic neurons reveals modulators of SCARB2 and BAG3 expression

  SNPs have been associated with the risk of Parkinson’s disease but not in regulatory regions. While those potentially disrupt TFBS altering gene expression and contributing to cis-regulatory variation. To study changes in A and B compartment interactions and in topologically associated domains (TADs), we sequenced: - 3D chromatin contact using LowC, 6 samples. 3 replicates for each condition: smNPC (controls) cells and differentiated neurons after 30 days. Resulting paired-end are provided as BAM files. In order to confirm the predicted impact of the PD-associated allele of rs144814361 on BAG3 promoter, we proceeded with genome editing of the TH-REP1 cell line by using prime editing to insert the “T” allele at the position chr10:119651405 in the BAG3 promoter. - Chromatin accessibility using ATAC-seq, 9 samples of derived cell line TH-REP1. 3 replicates for each condition: 1) iPSC Wild Type 2) SNP-BAG3 variant in iPSC 3) SNP-BAG3 variant in smNPC. BAG3 variant: heterozygous for the SNP variant: rs144814361 (chr10 119651405) Resulting sequencing are provided as paired-end FASTQ files.

  Dataset EGAD50000002258

• DNA methylation changes upon growth hormone treatment in children with idiopathic short stature

  This dataset includes DNA methylation profiles before and after GH treatment (with a duration of ~18 months in average) on 47 healthy children using customized methylC-seq capture sequencing. It includes 360 fastq files (i.e. 180 paired-end fastq files) where 40 fastq files were generated with HiSeq and 320 fastq files were generated with NovaSeq.

  Dataset EGAD00001008641

• Regulatory and Effector T cells in Oral Immunotherapy for Food Allergy

  This study consisted of a clinical trial for peanut oral immunotherapy (OIT) and a follow-up project (see below). Patients were included from 2013-2015, and samples from the last timepoints were collected in 2017. The study focused on peanut-specific CD4+ T cell responses before, during, and after OIT with peanut protein. We analyzed T cell gene expression, cytokine production, and T cell receptor β (TCRβ) and TCRα clonotypes, both in bulk T cell populations and single cells, and sought to correlate these data with differences in clinical sensitivity between peanut-allergic patients before OIT, and with differences in clinical outcome after OIT. The goal was to better understand the role of peanut-specific effector and regulatory T cells in peanut allergy and tolerance, which may inform more effective therapies (e.g., OIT combined with biologicals, probiotics, or adjuvants) in the future. Tolerance Following Peanut Oral Immunotherapy (PNOIT2, NCT01750879): The unifying objective of this project is to determine whether peanut oral immunotherapy (PNOIT)-induced clinical tolerance in the context of food allergy is significantly associated with the expansion of a specific regulatory T cell subset (CD45RA-, CD25++, FoxP3+ +) that is thought to be inducible in the gut-associated lymphoid compartment and associated with immunological tolerance. The hypothesis of the study is that the induction of Treg cells will be associated with clinical tolerance. The investigators will measure the change from baseline of induced Treg cells as a frequency of total CD4+ T cells during active treatment and compare that between participants who achieve significant clinical tolerance and those who do not. High Threshold Peanut Challenge Study (PAID-UP, NCT02698033): This protocol was designed to better characterize a sub-population of peanut-sensitized individuals who may be non-allergic, despite significant sensitization, or who may be allergic, but at high threshold doses. By specifically targeting participants who met the initial screening criteria of an earlier study, NCT01750879, but failed to react during the pre-treatment 443 mg challenge to peanut, the investigators anticipate that they will identify individuals who have become spontaneously tolerant, despite persistent sensitization. The investigators might also find that clinical sensitivity persists but only with higher thresholds, or that sensitivity has increased (or is variable) since the previous allergen exposure. By repeating food challenges through to a full serving dose (7.4 gram), the investigators will distinguish participants who react only at higher doses from those who were not truly peanut-allergic, address whether their sensitivity has changed, and have the opportunity to further investigate their immune response to peanut allergen. Methods: Peripheral blood mononuclear cells were isolated from patient blood samples, and stimulated with peanut protein. Peanut-activated CD4+ T cells were sorted based on the activation marker CD154. For a more recent study, the activation marker CD137 was used as well. Total RNA from peanut-activated CD154+ and resting CD154- CD69- T cells was used for cDNA synthesis and amplification (SMARTer ultra low input RNA kit for sequencing - v3; Clontech Laboratories). Libraries were prepared and sequenced on the Illumina HiSeq platform, at a read depth of approximately 30 million reads per sample. Genomic DNA from CD154+ and CD154- CD69- T cells was used to amplify and sequence the TCRβ CDR3 regions (immunoSEQ assay; Adaptive Biotechnologies). The immunoSEQ approach generates an 87 base-pair fragment capable of identifying the VDJ region spanning each unique CDR3. Amplicons were sequenced using the Illumina NextSeq platform. Using a baseline developed from a suite of synthetic templates, primer concentrations and computational corrections were used to correct for the primer bias common to multiplex PCR reactions. Raw sequence data were filtered on the basis of TCRβ V, D, and J gene definitions provided by the IMGT database (www.imgt.org) and binned using a modified nearest-neighbor algorithm to merge closely related sequences and remove both PCR and sequencing errors. For single-cell analysis, we aimed to recover TCR variable sequences from high-throughput single-cell libraries generated by popular platforms such as SeqWell and DropSeq. We paired TCR information with T cell single-cell RNA sequencing results from patients undergoing peanut OIT to show clonal expansion-related T cell phenotypes.

  Study phs001897