11769 results for "cancer rna-seq"

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• 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