11768 results for "cancer rna-seq"

in 19.55 milliseconds.

• sWGS of non-cancer controls

  Paired end shallow whole genome sequencing (sWGS) data of cell-free DNA from plasma from self-reporting healthy individuals (MonRec Cohort)

  Dataset EGAD00001005805

• RBWES

  Retinoblastoma is a rare childhood cancer of the retina. We studied retinoblastoma by Whole-Exome-Sequencing.

  Dataset EGAD00001007591

• Osteosarcoma RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Dataset EGAD00001000826

• NSCCG CRC WES

  1006 Familial early onset gemrline CRC patients sequenced by the Molecular and Population Genetics group of the Institute of Cancer Research

  Dataset EGAD00001002204

• Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

  No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

  Study EGAS50000000211

• Whole Exome Sequencing of Pancreatic Neuroendocrine Tumors at The Human Genome Sequencing Center, Baylor College of Medicine (HGSC-BCM)

  Pancreatic neuroendocrine tumors (PNETs), often referred to as "islet cell tumors", are neuroendocrine neoplasms that arise from cells of the endocrine and nervous system within the pancreas. These rare tumors which originate from the pancreatic islet are divided into many categories and are often classified by the hormone most strongly secreted. With the collaboration of the Elkins Pancreatic Center, the Human Genome Sequencing Center (HGSC) at Baylor College of Medicine had access to approximately 30 untreated tumor specimens and matched normal blood samples. Since the onset and progression of cancer is driven by extensive mutation of the genome, we are combining enrichment of exonic DNA with next generation sequencing to detect and characterize the somatic mutation profile of patients with pancreatic neuroendocrine cancer. This work was done at the Human Genome Sequencing Center (HGSC) in collaboration with the Elkins Pancreatic Center at Baylor College of Medicine in Houston, TX and was supported by grant number 5U54HG003273 from National Human Genome Research Institute (NHGRI).

  Study phs000871

• International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

  The incidence of invasive breast cancer is rapidly increasing in East Asia, enriching in younger patients and luminal disease. We presented a deep proteogenomic landscape of a prospectively enrolled early-stage cohort in Taiwan to uncover the etiology, age-related subtype and oncogenic vulnerabilities underlying the heterogeneous disease. Multilayer proteogenomic architecture revealed distinct endogenous and environmental carcinogen-associated mutagenesis, linking APOBEC (apolipoprotein-B mRNA editing enzyme, catalytic polypeptide-like) cytidine deaminase and DBAC (dibenz[a,j] acridine) signatures to significantly elevated hormone biosynthesis and chemical carcinogenesis in younger patients, and identifying a novel subset of high mutation burden and immune escape potentially beneficial from combined epigenetic therapy and immunotherapy. A proteomics-informed classification resolves luminal heterogeneity, defines high-risk recurrent luminal disease and nominates biomarkers and actionable druggable pathways. Furthermore, proteogenomics profile distinguished a young luminal population susceptible to exogenous carcinogen and having DNA repair deficiency. This study illuminates the age-related molecular subtypes and oncogenic vulnerabilities, providing a proteogenomics-transformative guide for patient stratification and precision therapeutics beyond clinical staging.

  Study phs003150

• A Multi-Gene Mutation Classification of 468 Colorectal Cancers Reveals a Prognostic Role for APC

  Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinic-pathologic staging for decades. There is a need to molecularly stratify subpopulations of CRC to better predict outcome and assign therapies. Here we report targeted exome sequencing of 1,321 cancer-related genes on 468 tumor specimens, which identified a subset of 17 genes that best classify CRC, with APC (Gene ID: 324) playing a central role in predicting overall survival. APC may assume 0, 1, or 2 truncating mutations, each with a striking differential impact on survival. Tumors lacking any APC mutation carry a worse prognosis than single APC mutation tumors, but tumors with two APC mutations and KRAS (Gene ID: 3845) and TP53 (Gene ID: 7157) mutations confer the poorest survival among all the subgroups examined. Our study demonstrates a substantial prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.

  Study phs001111

• Retinoblastoma Aqueous Humor Liquid Biopsy Repository

  This study involves the use of the aqueous humor (AH, the clear fluid in the front of the eye) as an organ specific liquid biopsy for retinoblastoma. This relatively new liquid biopsy platform was started at CHLA/USC and was developed to overcome the lack of tumor tissue -- due to contraindication to biopsy -- for this cancer. We have demonstrated that the aqueous humor is an enriched source of tumor DNA. Previously tumoral information was only available after the eye was removed for treatment failure. Due to the AH liquid biopsy, we are now able to assay tumor derived molecular information from these eyes at diagnosis and longitudinally during treatment -- as opposed to only eyes that have failed therapy. We have demonstrated that using the platform we can identify the specific mutations in the RB1 gene that initiate tumorigenesis in this cancer as well as the secondary chromosomal alterations the drive further tumor growth. This database will provide sequencing information as well as associated clinical information and globe salvage outcomes.

  Study phs003077

• Genome-wide mutational consequences of nucleotide excision repair-deficiency through XPC deletion in a human adult stem cell culture

  Nucleotide excision repair (NER) is one of the main DNA repair pathways that protect cells against genomic damage. Deficiency in this pathway can contribute to the development of cancer and accelerate aging. NER-deficiency is an important determinant for cancer treatment outcome, as NER-deficient tumors are selectively sensitive to cisplatin treatment. While NER-deficiency has been linked to mutational Signature 5, not all NER-deficient tumors are characterized by a high Signature 5 contribution, illustrating the importance to further characterize the mutational consequences of NER-deficiency. Here, we analyzed the mutational profile of a human adult stem cell (organoid) culture that is deficient in NER through XPC deletion by CRISPR-Cas9 gene-editing, and subsequent whole-genome sequencing analysis of a clonally derived organoid. We found that XPC deletion results in an increase in base substitution load and specifically induces Signature 8 mutations, a mutational signature with previously unknown etiology. Presence of Signature 8 may, therefore, serve as a novel biomarker for NER-deficient tumors and could improve personalized treatment strategies.

  Study EGAS00001002681

• Primary prostate Hi-C

  Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. Despite large-scale tumour sequencing efforts, the impact of mutations on the genetic architecture in cancer remains ill-defined due to limited integration of genomics data across dimensions. We addressed this limitation by assessing the impact of structural variants on the chromatin states and the three-dimensional organization across benign and malignant primary prostate genomes. We find high concordance in the three-dimensional genome organization between malignant and benign prostate tissues, arguing for constraints to the three-dimensional genome of prostate tumours. Moreover, we identify structural variants as effectors of changes to focal chromatin interactions, guiding cis-regulatory element hijacking that imposes opposing expression changes on genes found at antipodes of a rearrangement. This leads to the repression of tumour suppressor gene expression and up-regulation of oncogenes, such as at the TMPRSS2-ERG and PMEPA1-ZNF156 loci. Collectively, our results argue that cis-regulatory element hijacking by structural variants overshadows large-scale topological changes to alter gene regulation and promote oncogenesis.

  Study EGAS00001005014

• Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones

  The molecular mechanisms underlying lethal castration-resistant prostate cancer remain poorly understood, with intratumoral heterogeneity a likely contributing factor. To examine the temporal aspects of resistance, we analyzed tumor heterogeneity in needle biopsies collected before and after treatment with androgen deprivation therapy. By doing so, we were able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome-wide data. Our data-driven analysis of transcriptomes identified several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Strikingly, certain cell populations present before treatment exhibited gene expression profiles that matched those of resistant tumor cell clusters, present after treatment. We confirmed that these clusters were resistant by the localization of active androgen receptors to the nuclei in cancer cells post-treatment. Our data also demonstrated that most stromal cells adjacent to resistant clusters do not express the androgen receptor, and we identified differentially expressed genes for these cells. Altogether, this study shows the potential to increase the power in predicting resistant tumors.

  Study EGAS00001006113

• Automated image-based profiling of complex drug induced phenotypes in patient-derived organoids

  We established a platform for high-throughput confocal fluorescence microscopy and automated image analysis to perform large-scale drug response profiling with patient derived organoids (PDOs). Using PDO lines newly established from colorectal cancer patients with a standardized workflow, we performed chemical perturbations with more than 500 experimental and clinically used compounds. Subsequently, we captured approx. six million images by confocal microscopy. To analyze drug-induced PDO re-organization on a single organoid level we developed SCOPE, a software framework for automated PDO high-throughput image analysis. We observed a rich variety of divergent and reoccurring compound induced phenotypes in organoids. Perturbation of cellular processes, including signaling by MEK, GSK3β, cyclin dependent kinases (CDKs) and others, led to recurring and distinct architectural changes. Highlighting the clinical relevance, PDO viability was heterogeneous after perturbation with anticancer drugs and matched clinical response of corresponding colorectal cancer patients. Our work opens new avenues for image-based profiling for accelerated drug discovery and clinical decision-making.

  Study EGAS00001003140

• Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection

  Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. We Here we developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

  Study EGAS00001003206

• Functional screening on patient-derived organoids identifies a therapeutic bispecific antibody that triggers EGFR degradation in LGR5+ tumor cells

  Patient-derived organoids (PDOs) have demonstrated predictive value in prospective clinical trials supporting selection of personalized treatments. Because PDOs retain the organization and physiological functions of their source tissue, PDO biobanks could also be an ideal substrate to screen for novel therapeutic interventions. Here we describe a large-scale functional screen of dual targeting bispecific antibodies (bAbs) on a colorectal cancer (CRC) PDO biobank to target their dependency on cancer stem cells. A novel drug discovery pipeline was assembled where therapeutic bAb panels generated against WNT and receptor tyrosine kinases (RTK) targets were functionally evaluated by high content imaging to capture the complexity of PDO responses across a wide range of different CRCs and paired normal colonic mucosa samples. Our strategy resulted in a bAb that specifically triggers EGFR degradation in LGR5+ CSCs and that exhibits unique therapeutic properties such as potent growth inhibition of KRAS mutant CRCs, blockade of metastasis initiation in preclinical models and minimal toxicity towards normal LGR5+ colon stem cells.

  Study EGAS00001004584

• The miR-185/PAK6 Axis Predicts Therapy Response and Regulates Survival of Drug-Resistant Leukemic Stem Cells in Chronic Myeloid Leukemia

  Overcoming drug resistance and targeting cancer stem cells remain challenges for curative cancer treatment. To investigate the role of miRNAs in regulating drug resistance and leukemic stem cell (LSCs) fate, we performed global transcriptome profiling in treatment-naïve chronic myeloid leukemia (CML) stem/progenitor cells and identified that miR-185 levels anticipate their response to ABL tyrosine kinase inhibitors (TKIs). miR-185 functions as a tumor suppressor; its restored expression impaired survival of drug-resistant cells, sensitized them to TKIs in vitro, and markedly eliminated long-term repopulating LSCs and infiltrating blast cells, conferring a survival advantage in pre-clinical xenotransplantation models. Integrative analysis with mRNA profiles uncovered PAK6 as a crucial target of miR-185 and pharmacological inhibition of PAK6 perturbed the RAS/MAPK pathway and mitochondrial activity, sensitizing therapy-resistant cells to TKIs. Thus, miR-185 presents as a potential predictive biomarker, and dual targeting of miR-185-mediated PAK6 activity and BCR-ABL may provide a valuable strategy for overcoming drug resistance in patients.

  Study EGAS00001004153

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures (Hipo_021)

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which escape discovery using short-read sequencing. We employed Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed ‘templated insertion thread’ (TI thread), characterized by short (mostly <1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. TI threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in cancer-driver genes. Our study shows the advantage of long-read sequencing in the discovery and characterization of complex somatic rearrangements.

  Study EGAS00001006629

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010114

• Deep whole genome ctDNA chronology of treatment-resistant prostate cancer

  Circulating tumor DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring. We performed deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and demonstrate that ctDNA harbors multiple dominant populations whose evolutionary histories frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally-expanded cancer driver alterations, each individual metastasis contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent androgen receptor (AR) pathway inhibitors, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment-resistance. Finally we leverage nucleosome footprints in ctDNA to infer mRNA abundance in synchronously biopsied metastases, including treatment-induced changes in AR pathway transcriptional activity.

  Dataset EGAD00001008460

• Somatic mutation and selection at epidemiological scale - TwinsUK_RENanoSeq_Buccal

  Utilising restriction enzyme NanoSeq, we hope to explore the somatic mutation burden and mutational signatures in buccal cells from TwinsUK donors. Some donors have paired blood samples and data from this will help contextualise that work. All donors have paired Targeted NanoSeq data from buccal swabs. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015621

• Somatic mutation and selection at epidemiological scale - Sanger_NanoSeq_RandD

  Bottleneck sequencing of human tissue including neurons, cord blood, sperm This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015624

• Whole genome sequencing of breast cancer and related clones

  Paired WGA (whole-genome amplificated) samples from 65 single cell-derived organoids and six fresh single cell-derived organoid samples both of which were established from normal mammary epithelial cells, 84 FFPE LCM (laser-capture microdissection) samples of breast cancer and related clones, 79 fresh-frozen LCM samples of non-cancer lobules of breast cancer patients, and 36 matched germline controls were subjected to whole genome sequencing using NovaSeq 6000 system (Illumina) or DNBSEQ-G400RS (MGI Tech).

  Dataset EGAD00001010833

• Advancing fast in the analysis of circulating tumour DNA

  In cancer patients, solid tumours also release DNA fragments into the blood, and they are called Circulating Tumours DNA (ctDNA). Nowadays, the standard procedure for cancer monitoring is analysis of surgically obtained biopsies. They generate a big amount of material, but the operation is highly invasive and provide medical doctors with a single-time snapshot of the tumours, which are often highly changeable. Analysis of ctDNA, on the other hand, can provide continuous information regarding the tumour itself without the need of invasive procedures. This is why interest in this method is growing, and with it, the need for its technological optimization. Guanhua Zhu and colleagues, at the Genome Institute of Singapore, developed a methodology to quantify ctDNA burden, which means to estimate the amount of tumours derived circulating DNA among all cell-free DNA in the blood of individuals. Their work, published in Nature Communications in april 2021 and summarized in a sketch below, uses state-of-the art methods to analyse cfDNA degradation patterns at promoters and exon regions, to discern it from the DNA coming from the tumours. The bright point of their approach is that simultaneously enable for profiling of actionable cancer mutations and quantitative estimation of ctDNA burden. Their sequencing data of ctDNA has been deposited in the EGA under the accession number EGAS00001004657. This study sums up to a total of 37 of cfDNA and 36 about ctDNA present up to date in the EGA archive. The existence of cfDNA was firstly described back in 2002, while the use of ctDNA analysis in the oncological field exploded only after 2016. The approach is rapidly evolving, moving in parallel with the ever-improving sequencing technologies. Especially, the possibility to obtain high quality sequences from minimal amount of material is a crucial factor. Being able to alleviate cancer patients of disturbing and often slow-recovery procedures, while at the same time improving the quality of diagnosis and disease monitoring seems like a lot to ask. Thankfully, we are blessed with brilliant and dedicated scientists from all around the world who collaborate to make this a reality, sharing their results, knowledge and data.

  Blog advancing-fast-in-the-analysis-of-circulating-tumour-dna

• Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration.

  The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines revealed a unique form of structural variation, termed heterocateny here, characterized by heterogeneous, interrelated, and repetative patterns of concatemerized virus and host DNA segments. Evidence of heterocateny was detected in extrachromosomal and/or intrachromosomal DNA in all cases. Unique breakpoint sequences shared across structurally heterogeneous virus-host concatemers within each cancer facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that unstable virus and virus-host concatemers in ecDNA or integrated form mediate insertion into and excision from chromosomes, capture, rearrangement, and rolling-circle amplification of host DNA, and chromosomal rearrangements. The data indicate that heterocatena is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intra-tumoral heterogeneity and clonal evolution.

  Study EGAS00001006652

• EGAD00010000268

  Metabric breast cancer samples (Expression raw data)

  Dataset EGAD00010000268