14983 results for "cancer studies using rna-seq"

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• Single cell study of infant leukemias

  We have performed single cell RNA-sequencing for infant and childhood B-cell acute lymphoblastic leukemias as well as infant acute myeloid leukemias at diagnosis. The sequencing was performed with 10X Chromium single cell 3’ and 5’ chemistry.

  Dataset EGAD00001007853

• RNA-sequencing data from vitamin C experiment

  Fasq-files from 3 unaffected TET2 mutation carriers, 2 mutation carriers diagnosed with lymphoma and 3 family members without TET2 mutation. Time series data collected from 0, 6 and 12 months after daily dose of 1g vitamin C.

  Dataset EGAD00001010009

• DIPG MEK inhibition RNASeq

  RNA sequencing of Diffuse intrinsic pontine gliomas, primary patient derived DIPG cell cultures and isogenic trametinib resistant clones

  Dataset EGAD00001008212

• Single-cell short-read transcriptomes from CH, MDS and AML patients with splicing factor mutations

  Single-cell RNA sequencing from CH (n = 2), MDS (n = 6, MDS02 in 2 replicates) and AML (n = 1, in 2 replicates) samples with mutations in splicing factors (SF3B1 - n = 8, U2AF1 n = 1). cDNA from 10x Genomics 3' V3.

  Dataset EGAD00001011283

• Endometrial RNASeq of Patients with MRKH Syndrome and Healthy Controls

  Raw FastQ Files of 69 samples of endometrial tissue from uterus (rudiments) of patients diagnosed with MRKH Type 1/2 or healthy controls. Each sample consists of 2 lanes paired-end RNA sequencing data.

  Dataset EGAD00001006345

• HPS1 patient monocyte-derived macrophage and control macrophage RNAseq with and without infection

  4 HPS1 patient monocyte-derived macrophages and 4 controls were RNA sequenced at baseline and after Salmonella Typhimurium infection. We used paired end sequencing on an Illumina HiSeq 4000. Each sample was run on 3 lanes for sequencing depth, which we combined for our analysis.

  Dataset EGAD00001006978

• PARADIGM: Combined ctDNA and serum PSA for dynamic monitoring of metastatic prostate cancer starting first-line treatment

  The prognosis of newly-diagnosed metastatic prostate cancer is highly variable. The PARADIGM prospective cohort study evaluated predictors of survival in blood collected at the start of each of the first six treatment cycles from 114 high-volume metastatic patients starting androgen deprivation therapy combined with docetaxel or an androgen receptor pathway inhibitor.

  Study EGAS50000001357

• Cancer_Genome_Libraries_Tests

  Testing library production.Genomic libraries (500 bps) will be generated from total genomic DNA derived from commomon epithelial cancer samples and subjected to paired end sequencing on the llumina plateforms. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000208

• High intensity sequencing of plasma cfDNA and WBC gDNA

  We sought to define the technical feasibility of a high-intensity sequencing assay of cfDNA and matched white-blood cell (WBC) DNA covering a large genomic region (508 genes, 2Mb, 60,000x raw-depth) in a prospective study of 124 metastatic cancer patients, with contemporaneous matched metastatic tumor tissue biopsies, and age-matched 47 non-cancer controls.

  Study EGAS00001003755

• 20 Matched Pair Breast Cancer Genomes

  20 Matched Pair Breast Cancer Genomes

  Dataset EGAD00001000082

• bulkRNAseq of ovarian cancer cell lines

  bulkRNAseq of four ovarian cancer cell lines (PA-1, A2780, A2780/CP20, TOV-21G)

  Dataset EGAD50000002059

• Cancer-associated genome-wide hypomethylation and copy number aberrations

  Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

  Dataset EGAD00001001093

• Amplicon sequencing data from organoids of colorectal cancer patients.

  The dataset includes 13 bam files. Each bam file is a different colorectal cancer patient organoid.

  Dataset EGAD00001004313

• EORTC RP1335 SPECTA Lung cancer data - Oncomine

  EORTC RP1335 SPECTA Lung cancer data - Oncomine dataset

  Dataset EGAD00001006594

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• Base-excision repair pathway shapes 5-methylcytosine deamination signatures in pan-cancer genomes

  Transition of cytosine to thymine in CpG dinucleotides is the most frequent type of mutation in cancer. This increased mutability is commonly attributed to spontaneous deamination of 5-methylcytosine (5mC), which is normally repaired by the base-excision repair (BER) pathway. However, the contribution of 5mC deamination in the increasing diversity of cancer mutational signatures remains poorly explored. Here, we integrate mutational signatures analysis in a large series of tumor whole genomes with lineage-specific epigenomic data to draw a detailed view on 5mC deamination in cancer. We uncover tumor type-specific patterns of 5mC deamination signatures in CpG and non-CpG contexts. We demonstrate that the BER glycosylase MBD4 preferentially binds to open chromatin domains, which correlates with lower mutational burden in these domains. We validate our findings by modelling BER deficiencies in isogenic cell models. Overall, we establish MBD4 as the main actor responsible for 5mC deamination repair in humans.

  Study EGAS50000000536

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - RNAseq

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000977

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - WES

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000976

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty___WG__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003524