15020 results for "cancer studies using rna-seq"

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• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408

• The study provides comprehensive access to the set of EGA studies which may be useful as controls.

  The subjects studies in these datasets were selected due to being healthy control individuals or otherwise provide well characterised phenotype or exclude certain disease phenotype categories such that they may be useful as control population, such as to derive allele frequencies from a known reference population.

  Study EGAS00001000646

• MIBC NAC2020 cohort RNA sequencing

  The dataset contains RNA sequencing data from N=48 transurethral resections of bladder tumours (TURBTs) from N=48 patients with muscle-invasive bladder cancer who were treated with neoadjuvant chemotherapy followed by radical cystectomy. All TURBTs originate from formalin-fixed paraffin embedded tissue. We used the Illumina TruSeq RNA exome kit, previously known as the TruSeq RNA Access Library Prep Kit. This kit converts total RNA into template molecules of known strand origin, followed by sequence-specific capture of coding RNA. All samples were run in an Illumina NovaSeq6000 instrument. Paired FASTQ files from all 48 patients are provided.

  Dataset EGAD50000001025

• Integration of T Cell Repertoire, CyTOF, genotyping and symptomatology data reveals subphenotypic variability in COVID-19 Patients

  A total of 61 patients (33 mild and 28 severe) with a median age of 51 years who recovered from COVID-19 were included in this study (Table 1). All collected samples were confirmed in diagnosis of COVID-19 by RT-PCR and positive IgG serolog. For the 61 patients, TCR-seq, CyTOF, and genotyping data were generated and analyzed in separate studies, as part of larger cohorts. In total, there are 143 variables, with 129 being quantitative (TCRseq and CyTOF metrics) and 13 being qualitative (symptomatology and genotyping). For more information about cohort characteristics, data adquisition an pre-processing, please visit PMID: 39227859, 36969980 and 37287057.

  Dataset EGAD50000000840

• Single cell transcriptomes from vascularized human retinal organoids

  Both control and vascularized organoids were processed using the 10x Chromium 3' RNA method. Sequencing reads were aligned with STARsolo.

  Dataset EGAD50000001216

• TK-EPN862 - Patient-dervied xenograft model of Posterior Fossa A Ependymoma - RNAseq

  Ependymomas (EPN) are the third most common malignant brain cancer in children. Treatment strategies for pediatric EPN have remained unchanged over recent decades, with 10-year survival rates stagnating at just 67% for children aged 0-14 years. Moreover, patients who survive treatment for the most common subtype of pediatric EPN (posterior fossa A (PFA)), often suffer long-term neurological side effects as a result of therapy. It is evident that there is a need for safer, more effective treatments for pediatric EPN patients. There are ten distinct subgroups of EPN, each with their own molecular and prognostic features. To identify and facilitate the testing of new treatments for EPN, in vivo laboratory models representative of the diverse molecular subtypes are required. Here, we describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of PFA EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using immunohistochemistry, DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. Both patient and PDOX tumors classified as PFA EPN by methylation profiling, and shared similar histological features consistent with this molecular subgroup. RNA sequencing revealed that gene expression patterns were maintained across the primary and metastatic tumors, as well as the PDOX. Copy number profiling revealed gains of chromosomes 7, 8 and 19, and loss of chromosomes 2q and 6q in the PDOX and matched patient tumor. No clinically significant single nucleotide variants were identified, consistent with the low mutation rates observed in PFA EPN. Overexpression of EZHIP RNA and protein, a common feature of PFA EPN, was also observed. Despite the aggressive nature of the tumor in the patient, this PDOX was unable to be maintained past two passages in vivo. Others who have successfully developed PDOX models report some of the lowest success rates for EPN compared to other pediatric brain cancer types attempted, with loss of tumorigenicity not uncommon, highlighting the challenge in propagating these tumors in the laboratory. Here, we discuss our collective experiences with PFA EPN PDOX model generation and propose potential approaches to improve future success in establishing preclinical EPN models

  Study EGAS00001006844

• Gene Expression Study of Individuals with Sex Chromosome Aneuploidies

  Males and females show dramatic differences in their vulnerability to the same diseases. For example, compared to men, lupus is six times more prevalent, thyroid cancer is three times more prevalent, and unipolar depression is twice as prevalent in women. Diseases with a strong male bias include autism (5:1), dilated cardiomyopathy (3:1), and ankylosing spondylitis (5:1). Historically, such differences have been attributed solely to extrinsic factors such as circulating sex hormones or environmental influences. We hypothesized that intrinsic factors - genetic differences between XX and XY cells - have unappreciated biological consequences throughout the body and contribute to sex differences in disease incidence and severity. This hypothesis stems from our long-term effort to sequence the sex chromosomes of diverse mammalian species, which has identified a set of homologous genes on the X and Y chromosomes that are dosage-sensitive, expressed throughout the body, and encode regulators of chromatin modification, transcription, translation, and protein stability. These X- and Y-encoded genes differ in sequence and expression pattern, which likely manifests in genome-wide differences in gene regulation between XX and XY cells and influences all aspects of human biology, including sex differences in disease susceptibility. These hard-wired molecular sex differences have been largely overlooked and understudied, representing a significant gap in our knowledge of human biology.The gene expression study of individuals with sex chromosome aneuploidies takes advantage of natural human variation in sex chromosome number, i.e. sex chromosome aneuploidy, to investigate alterations in genome-wide gene expression that correlate with changes in X- and Y-chromosome dosage. We analyzed samples from 114 individuals with a variety of sex chromosome aneuploidies, including 45,X; 47,XXY; 47,XYY; 47,XXX; 48,XXYY; and 49,XXXXY. We generated lymphoblastoid cell lines (LCLs) from blood samples and, in some cases, fibroblast cultures from skin biopsies. We supplemented our collection with previously-derived cell lines. To evaluate gene expression, we performed deep profiling of the transcriptome (RNA-seq) from these LCLs and fibroblasts. We performed parallel analyses on samples collected from 62 control 46,XX and 46,XY individuals, 6 individuals with trisomy 21, and 14 individuals with structural variations of the X and Y chromosomes. In addition, we performed CRISPRi knockdowns on 3 of the 46,XX and 3 of the 46,XY fibroblast samples for the homologous transcription factors ZFX and ZFY, encoded on the X and Y chromosomes, respectively.In the April 2024 update, we added RNA-seq datasets derived from isolated CD4+ T cells and monocytes from 76 and 72 adults, respectively, with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXX; 47,XXY; 47,XYY. These individuals are largely a subset of the same cohort described above. In addition, we performed RNA-seq on in-vitro stimulated CD4+ T cells with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXY.In the August 2024 update, we added RNA-seq datasets generated from the following: 1) LCLs derived from individuals with AZFa deletions of the Y chromosome, 2) DDX3X and DDX3Y knockdown (via CRISPRi) in XY fibroblasts, and 3) 5-ethyl uridine (5-EU) treatment in XY and XYYYY LCLs.

  Study phs002481

• Profiling of 27 type 2 diabetes GWAS loci using next-generation (NG) capture C in a human beta-cell model

  Most type 2 diabetes association signals are due to variants that impact gene regulation but identifying the genes they impact is challenging. We generated interaction profiles at 27 T2D GWAS loci using next-generation (NG) capture C (6 replicates) in the human beta-cell model, EndoC-betaH1, along with chromatin accessibility profiling using ATAC-Seq (9 replicates).

  Dataset EGAD00001008655

• Intraductal transplantation models of human pancreatic ductal adenocarcinoma reveal progressive transition of molecular subtypes

  Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past few decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated. However, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present an orthotopic xenotransplantation model of human patient-derived PDAC organoids in which organoids are grafted via direct injection into the pancreatic duct of immunocompromised (NSG) mice. Tumors that arise from these intraductally grafted organoids (IGOs) enable the distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively, depending on which organoid they originate from. RNA-sequencing was used to characterize the tumors that resulted from IGO xenografts, and to compare the fast- and slow-progressing IGO tumors. Tumors generated using a traditional orthotopic xenograft model, in which organoids are injected into the parenchyma of the pancreas (i.e. orthotopically grafted organoids, or OGOs), were also sequenced for comparison with the IGO tumors. To further characterize the model, laser-capture microdissection followed by RNA-sequencing was used to compare intraductal to invasive lesions resulting from IGOs. To better understand the connection between KRAS signaling and the fast-progressing phenotype, RNA-sequencing was used to compare cultured organoids in which oncogenic KRAS (GeneID: 3845) was hyperactivated to control organoids, and to compare laser-capture microdissected lesions derived from IGOs of KRAS-hyperactivated organoids to lesions derived from control organoids. To ascertain copy number, low-coverage, whole genome DNA-sequencing was performed on organoids cultured in vitro, and on laser-capture microdissected lesions derived from IGO tumors.

  Study phs002045

• Whole exome sequencing and RNA sequencing of patient-derived pancreas neoplasm organoids

  Pancreatic cancers arise from two different precursors; intraductal papillary mucinous neoplasms (IPMN) and pancreatic intraepithelial neoplasm (PanIN), while biological differences in cancers originated from them remain obscure. Here, we analyzed their genomic and transcriptomic landscapes using patient-derived organoids.

  Study JGAS000263