9964 results for "cancer rna-seq"

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• Cancer Cell Line Exome Sequencing

  Genomic characterisation of a large series of cancer cell lines.

  Dataset EGAD00001001039

• WGS on patients 1-4, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of fifteen samples, tumour and whole blood, from the four initial patients.

  Dataset EGAD00001001343

• Reference DNA standards for GCLP pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Dataset EGAD00001002015

• Exome and Transcriptome for pan-cancer gene-drug analysis

  Total of 584 tumor specimens and/or patient-derived cells across 14 cancer types were subjected for whole-exome/targeted-exome and/or whole-transcriptome sequencing.

  Dataset EGAD00001003441

• Sci Trans Med - Mouliere et al, 2018. Non-ovarian cancer samples - STM4

  fastq files for shallow whole genome sequencing data as described in Mouliere et al, 2018. Files are those not included in STM2 i.e. these are largely non-ovarian cancer samples

  Dataset EGAD00001006132

• Whole-genome sequencing of gastric cancer with peritoneal metastasis

  Whole-genome sequencing of 135 tumor samples and 98 normal samples of gastric cancer with peritoneal metastasis

  Dataset EGAD00001006963

• Cell-free DNA TAPS provides multimodal information for early cancer detection

  TAPS data from 21 patients with HCC, 23 patients with PDAC, 30 non-cancer controls, 4 patients with cirrhosis, and 7 patients with pancreatitis.

  Dataset EGAD00001006871

• Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Dataset EGAD00001011123

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Dataset EGAD00001010043

• Sensitive circulating tumor DNA based residual disease detection in epithelial ovarian cancer

  We analyzed 264 plasma samples collected between June 2016 and September 2021 from 63 epithelial ovarian cancer patients using tumor-guided plasma cell-free DNA analysis to detect residual disease after treatment.

  Dataset EGAD50000000360

• Dataset for WGS head and neck cancer samples

  This dataset contain WGS sequencing data of head and neck cancer samples as well as blood plasma controls. Sequencing was performed on Illumina Novaseq 6000 using KAPA HyperPrep Kit. The sequencing was always paired.

  Dataset EGAD50000000233

• Detection of mutational patterns in cell free DNA (cfDNA) of colorectal cancer by custom amplicon sequencing

  Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell free (cf) DNA offers a non-invasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatics workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our method to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from 34 patients with advanced colorectal cancer. Our data demonstrates that recurrent and patient-specific mutational patterns can be reliably detected for the majority of patients. Furthermore, we show that the allele frequency of mutations in cfDNA correlates well with disease progression. Finally, we demonstrate that monitoring of cfDNA can outperform the predictive power of currently used tumor markers and reveal mechanisms of resistance to anti-EGFR antibody treatment.

  Study EGAS00001003382

• Drug-perturbation-based stratification of blood cancer

  As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

  Study EGAS00001001746

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178

• Gabriella Miller Kids First (GMKF) Pediatric Research Program in Susceptibility to Ewing Sarcoma Based on Germline Risk and Familial History of Cancer

  Ewing sarcoma (EWS) is a deadly bone cancer that occurs in children and adolescents. Mounting evidence suggests that a genetic predisposition exists for this pediatric cancer, although the specific genetic contribution has yet to be identified. EWS has never been linked to a specific cancer predisposition syndrome, although several case reports have been published that describe siblings and cousins with EWS. Furthermore, neuroectodermal tumors appear to occur more commonly in families with EWS. The two consistent epidemiology findings in EWS include a very strong Caucasian predilection and increased rates of hernia in EWS patients and their family members. Finally, the role of genetic microsatellite repeats in EWS tumorigenesis has been recently described, and these GGAA microsatellites are polymorphic in repeat size and location across the genome. The study goals of this Kids First project include (1) To identify cancer predisposition genes in EWS trios increasing disease risk, (2) To identify genome-wide GGAA microsatellite repeats in EWS trios increasing disease risk, and (3) To identity de novo mutation and structural variant rates in EWS trios reflecting underlying DNA repair defects that increase disease risk. As part of the Kids First Common Fund initiative, this study proposal will further elucidate the genetic contribution to pediatric cancer development. Around 375 of these trios were selected for whole genome sequencing as part of the Gabriella Miller Kids First fund. The EWS trios have been collected as part of the Children's Oncology Group's AEPI10N5 Study ("Genetic Epidemiology of Ewing Sarcoma"), and each trio has associated phenotypic data including a detailed family history. We will interrogate the sequence data using our genomic analysis pipeline at the University of Utah and the Utah Science Technology and Research initiative's (USTAR) Center for Genetic Discovery. We will look for the genetic contribution to EWS and the sequence data with be shared in a repository designated by the Kids First Common Fund. The WGS of these ~375 EWS trios will help us to understand the genetic origins of a deadly childhood cancer and may lead to novel strategies for prevention and treatment.

  Study phs001228

• Versatile workflow for cell-type resolved transcriptional and epigenetic profiles from cryopreserved human lung

  The complexity of the lung microenvironment and changes in cellular composition during disease progression make it exceptionally hard to understand molecular mechanisms leading to the development of chronic lung diseases. Although recent advances in cell-type resolved and single-cell sequencing approaches hold great promise for studying complex diseases, their implementation relies on local access to fresh tissue, as traditional tissue storage methods do not allow viable cell isolation. To overcome these hurdles, we developed a novel, versatile workflow that allows long-term storage of human lung tissue with high cell viability, permits thorough sample quality check before cell isolation, and is compatible with sequencing-based profiling, including single-cell approaches. We demonstrate that cryopreservation is suitable for the isolation of multiple cell types from human lung and is applicable to both healthy and diseased tissue, including COPD and tumour samples. Basal cells isolated from cryopreserved airways retain the ability to differentiate, indicating that cellular identity is not altered by cryopreservation. Importantly, using RNA sequencing and EPIC Array, we show that genome-wide gene expression and DNA methylation signatures are preserved upon cryopreservation, emphasizing the suitability of our workflow for -omics profiling of human lung cells. In addition, we obtained high-quality single-cell RNA sequencing data of cells isolated from the cryopreserved human lung, demonstrating that cryopreservation empowers single-cell approaches. Overall, thanks to its simplicity, our cryopreservation workflow is well-suited for prospective tissue collection by academic collaborators and biobanks, opening worldwide access to human tissue.

  Study EGAS00001004477

• Innate Immune Anti-Viral Deaminase Deregulation Fuels Pre-Leukemia Stem Cell Evolution

  This study evaluates the effect of Rebecsinib treatment on gene expression, isoform splicing, and ADAR1 mediated RNA editing in cells from an in vivo humanized mouse model which have been engrafted with human secondary AML cells. For analysis of cells from Rebesinib-treated animals, CD34+ cells were obtained from bone marrow and spleens of sAML-engrafted mice following once weekly treatment with 0 (Vehicle) or 5 or 10 mg/kg Rebecsinib. For analysis of cells from serial transplant recipients of cells harvested from Rebecsinib-treated mice, CD34+ cells were obtained from bone marrow and spleens of sAML-engrafted mice that were transplanted with cells from animals that received twice weekly treatment with 0 (Vehicle) or 10 mg/kg Rebecsinib. No further treatment was given to serial transplant recipients, thus allowing the analysis of molecular changes that are sustained following serial transplantation. Whole transcriptome sequencing was performed at The Scripps Research Institute Next Generation Sequencing Core on Illumina NextSeq 500 sequencers with 150bp paired-end reads.These data revealed a uniquely expressed ADAR1 splice isoform (with a retrained intronic region), global downregulation of normalized RNA editing events, and isoform switching from MCL1-L to MCL1-S in Rebecsinib-treated sAML-engrafted mice. These results demonstrate the anti-survival and anti-self-renewal effects of Rebecsinib treatment on the leukemia stem cell (LSC) population in sAML-engrafted mice as well as the reduction in the inflammation-induced, hyper-editing p150 isoform of ADAR1. Thus, Rebecsinib treatment has promise for reducing the LSC population in myeloproliferative disorders and associated cancers.

  Study phs002228

• single-cell transcriptomics data from immune cells

  Smart-seq2 protocol was used to perform single cell RNA-sequencing on 465 immune cells. The immune cells analysed include 215 HLA-DQ2: gluten-(DQ2.5-glia-α1, -α2, -ω1, and -ω2) tetramer-sorted T cells, 247 transglutaminase 2 (TG2)-positive plasma cells from intestinal biopsy or peripheral blood from celiac disease patients, and 3 unassigned cells in 3 batches.

  Dataset EGAD00001004081

• Single-cell RNA sequencing of cytokine-induced T cell responses

  Cytokines affect T cell responses by polarising them to different phenotypes. We isolated T cells from healthy platelet donors and cultured them in resting and stimulated condition, as well as in the presence of Th2, iTreg and Th17 polarizing cocktail. To characterize the efficacy of cytokine induced porization and subpopulation specific response, we profiled single cell transcriptome five days following polarization using 10x platform (3' v2).

  Dataset EGAD00001005290

• Genomic analysis of pancreatic neuroendocrine tumour with MEN1, ATRX, or DAXX mutations

  This dataset includes 52 samples from 19 individuals with pancreatic neuroendocrine tumours. These samples were analyzed using RNA-sequencing, whole-exome sequencing, shallow (~0.3x) whole-genome sequencing, and a 21-gene panel targeted capture sequencing. Everything was sequenced using the Illumina HiSeq and is provided in BAM or FASTQ format.

  Dataset EGAD00001006001

• Sequencing data for Hepatoblastoma samples

  This dataset contains DNA sequencing data for twelve hepatoblastoma tumor samples, four of which have matched normals. Nine of the samples also have RNA sequencing data from the tumor sample. The dataset comprises six samples from patient tissues and six from cell lines; see metadata for details.

  Dataset EGAD00001006621

• Sequence-based gene expression in uterine and ovarian carcinosarcomas

  Gynecologic carcinosarcomas (CS), including more generally uterine (endometrial) and less frequently ovarian localization, are histologically defined as biphasic neoplasms composed of carcinomatous (C) epithelial and sarcomatous (S) malignant components. We report a comprehensive analysis of 20 patients of macro-dissected samples of C and S components through RNA sequencing.

  Dataset EGAD00001009099

• DNA sequening

  The dataset consist of DNA and RNA sequencing results and metadata of the samples. All sample numbers starting with 6716 are tumor samples which has been sequenced using WES (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata) and in some cases blood for germline mutation analysis. Sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000382

• RNAseq from a study of MYC, BCL2 and BCL6 rearrangements in non-Hodgkin lymphoma.

  Paired-end ribodepletion RNAseq performed on 257 samples of Burkitt lymphoma, diffuse large B cell lymphoma, follicular lymphoma, and high-grade B cell lymphoma with MYC and BCL2 or BCL6 rearrangements. RNA was derived from either fresh frozen or formalin fixed/paraffin embedded (FFPE) tissues. Sequencing was performed on Illumina HiSeqX or NovaSeqX instruments.

  Dataset EGAD50000000496