7201 results for "canc*"

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• Balanced_Ependymoma

  We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000174

• Oesophageal_Adenocarcinoma_Organoid_Hi_C

  Hi-C Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This Hi-C data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003122

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__pancreas_LCM_

  Samples prepared by LCM - 5 cases for pilot study. Bulk DNA not available.

  Study EGAS00001003197

• Enhanced detection of circulating tumor DNA by fragment size analysis

  Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on sensitivity for detecting genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for non-invasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 cancer patients using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90–150 bp, and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90–150 bp improved detection of tumor DNA, with more than 2-fold median enrichment in >95% of cases, and more than 4-fold enrichment in > 10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with AUC> 0.99 compared to AUC < 0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC > 0.91, compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection. This could reduce the required depth of cfDNA sequencing for clinical applications, earlier diagnosis and study of tumor biology.

  Study EGAS00001003258

• Molecular profiling of longitudinally observed small colorectal polyps: a cohort study

  Knowledge of the natural history of colorectal adenomas is limited because these lesions are removed upon detection. The few studies in which small adenomas have been left in situ for a limited period of time have shown that most lesions remain stable or even completely vanish. Lesions that have grown in size more often turn out to be advanced adenomas when resected. Specific DNA copy number changes (cancer associated events or CAEs) are associated with progression of adenomas to cancer. The aim of the study was to evaluate whether growth of small colorectal polyps left in situ is associated with specific molecular features.

  Study EGAS00001003284

• Chordoma_Extension__known_cancer_genes_

  Extension analysis to pursue candidate genes of interest in chordoma

  Study EGAS00001000895

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty__WG_

  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 EGAS00001003311

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Cancer_Mastectomy__Targeted_

  Sequencing of LCM-derived microbiopsies from 30 women who mastectomies due to Breast Cancer. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations.

  Study EGAS00001003318

• Whole genome and RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  Paediatric glioblastoma (pedGBM) is characterised by substantial intertumoural heterogeneity. In order to identify the genetic lesions underlying tumourigenesis, we analysed whole genomes and transcriptomes of pedGBMs and in vitro model systems by next generation sequencing. Novel fusions of the receptor tyrosine kinase MET lead us to investigate targeted therapy using MET inhibitors. This study is part of the International Cancer Genome Consortium PedBrain Tumor Project (ICGC PedBrain, http://www.pedbraintumor.org/).

  Study EGAS00001001139

• Whole genome sequencing of Ewings Sarcoma

  Sarcomas are cancers of the bone and soft tissue often defined by their gene fusions. However, the timing, context, and processes by which these pathogenic fusions arise are unknown. We explored this in Ewing sarcoma, a cancer driven by EWSR1-ETS fusions, with very few cooperating mutations. Combining whole-genome sequencing with enhanced informatics, we found that the EWSR1-ETS fusion arose from striking rearrangement clusters in 42% of cases (52/124). Notably, these were organized in loops that universally contained the fusion at their center, while also weaving up to 18 genes together with it. We found the same pattern of rearrangements in three additional types of sarcoma. From these data, we define a new signature for sarcoma fusions that precedes other somatic changes, in the earliest replicating DNA of the genome. This dramatic, sudden process impinges on many genes – generating multiple coding changes that profoundly affect the transcriptome, with the disease-defining gene fusion at its core. These rearrangement loops emerge in an early ES clone from which both the primary tumor and the lethal relapse emerged, and then evolved in parallel until clinically detected.

  Study EGAS00001003385

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  Next generation sequencing (NGS) of circulating tumour DNA (ctDNA) supports blood-based genomic profiling but is not routinely implemented in the clinic. TARGET is a molecular profiling programme with the primary aim to match patients to early phase clinical trials based on analysis of both somatic mutations and copy number alterations (CNA) across a 641 cancer-associated gene panel in a single ctDNA assay. For the first 100 TARGET patients, ctDNA data showed good concordance with matched tumour and results were turned round within a clinically acceptable timeframe for Molecular Tumour Board (MTB) review. When applying a 2.5% Variant Allele Frequency (VAF) threshold actionable mutations were identified in 41/100 patients, with 11 of these patients going onto a matched therapy. These data support the application of ctDNA in an early phase trial setting where broad genomic profiling of contemporaneous tumour material enhances patient stratification to novel therapies and provides a practical template for bringing blood-based analyses to the clinic.

  Study EGAS00001003407

• The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program 'CASCADE'

  Background: Understanding the cancer genome is seen as a key step in improving outcomes for cancer patients. Genomic assays are emerging as a possible avenue to personalised medicine in breast cancer. The majority of work in this area has targeted primary tumours however, and very few studies have performed comprehensive profiling of advanced disease. Evolution of the cancer genome during the natural history of breast cancer is largely unknown, as is the profile of disease at death. We sought to study in detail these aspects of advanced breast cancers that have resulted in lethal disease. Methods and Findings: Three patients with ER-positive, HER2-negative breast cancer and one patient with triple negative breast cancer underwent rapid autopsy as part of an institutional prospective community-based rapid autopsy program. Cases represented a range of management problems in breast cancer, including late relapse after early stage disease; de novo metastatic disease; discordant disease response and disease refractory to treatment. Between 5 and 12 metastatic sites were collected at autopsy together with available primary tumours and longitudinal metastatic biopsies taken during life. Samples underwent paired tumour-normal whole exome sequencing and single nucleotide polymorphism arrays. Subclonal architectures were inferred by jointly analysing all samples from each patient. Mutations were validated using high depth amplicon sequencing.Between cases, there were significant differences in mutational burden, driver mutations, mutational processes and copy number variation. Within each case, we found dramatic heterogeneity in subclonal structure from primary to metastatic disease and between metastatic sites, such that no single lesion captured the breadth of disease. Metastatic cross seeding was found in each case and treatment drove subclonal diversification. Subclones displayed parallel evolution of treatment resistance in some cases, and apparent augmentation of key oncogenic drivers as an alternative resistance mechanism. We also observed the key role of mutational processes in subclonal evolution.Limitations of this study include the potential for bias introduced by joint analysis of formalin fixed archival specimens with fresh specimens, and the difficulties in resolving subclones with whole exome sequencing. Other alterations that could define subclones such as structural variants or epigenetic modifications were not assessed. Conclusions: This study highlights the variety of mechanisms that shape the genome of metastatic breast cancer, and the value of studying advanced disease in detail. Treatment drives significant genomic heterogeneity in breast cancers which has implications for disease monitoring and treatment selection in the personalised medicine paradigm.

  Study EGAS00001002153

• Genetic Landscape of Esophageal Squamous Cell Carcinoma Defined by Exome Sequencing on Chinese Patient Cohort and Cell Lines

  Esophageal Squamous Cell Carcinoma (ESCC) is one of the deadliest cancers worldwide. To define the genetic landscape of ESCC, whole exome sequencing was performed on 113 pairs of tumor and normal DNA samples collected from Chinese individuals with treatment-naive primary ESCC, along with 8 cell lines, including 7 from KYSE series ESCC cell lines and one immortalized esophageal squamous epithelial cell line Het-1A.

  Study EGAS00001000932

• Sequencing of liver cancer cell lines

  Liver cancer is a dreadful disease with limited therapeutic options. How to translate genomic findings into biomarkers and precision treatment is challenging. A large cell line-based platform was established, termed as Liver Cancer Model Repository. Heterogeneities in patients were faithfully recapitulated by 81 liver cancer cell lines at genomic and transcriptomic levels. This platform provides a rich resource and models to study cancer drivers and drug responses in liver cancer.

  Study EGAS00001002237

• High-resolution structural genomics reveals new therapeutic vulnerabilities in glioblastoma

  We investigated the role of 3D genome architecture in instructing functional properties of glioblastoma stem cells (GSCs) by generating the highest-resolution 3D genome maps to-date for this cancer. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including individual physical interactions between regulatory regions and their target genes. Residing in structurally conserved regions in GSCs was CD276, a gene known to play a role in immuno-modulation. We show that, unexpectedly, CD276 is part of a stemness network in GSCs and can be targeted with an antibody-drug conjugate to curb self-renewal, a key stemness property. Our results demonstrate that integrated structural genomics datasets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.

  Study EGAS00001003493

• Ewings_Sarcoma_Rearrangement_Screen

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing’s sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewings’ sarcoma tumours.

  Study EGAS00001000362

• Myelodysplastic_Syndrome_Follow_Up_Series

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from MDS and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to discover the prevalence of our findings using bespoke pulldown methods and sequencing the products from a larger set of patient DNA.

  Study EGAS00001000224

• MutWP5__CRUK_Mutographs_of_Cancer__BRCA_Carriers___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 EGAS00001003523

• Tissue-specific mutation accumulation in human adult stem cells during life

  Gradual accumulation of mutations in human adult stem cells during life is associated with various age-related diseases, including cancer. The number of stem cell divisions throughout life is believed to be a major determinant for mutation accumulation and could explain the extreme variation of cancer incidence across different organs. Yet, mutation patterns and rates of healthy adult stem cells remain unknown. Here, we determined genome-wide mutation patterns in primary adult stem cells of the small intestine, colon and liver of human donors with ages ranging from 3 to 87 years. We find that the number of mutations increases linearly with age up to several thousand mutations per cell at 87 years of age, while mutation spectra remain constant throughout life. Small intestine and colon stem cells have a 2-fold higher mutation rate per year compared with liver stem cells. These differences could be exclusively attributed to the mutagenic action of spontaneous deamination of cytosine residues and may reflect the high stem cell division rate in these tissues. The genomic distribution of somatic mutations is non-random and predominantly associated with DNA replication dynamics in the small intestine and colon, and with transcription in the liver. These results indicate that a stable balance between various mutagenic and DNA repair processes is maintained throughout life and that the activity of these processes in adult stem cells varies between tissues.

  Study EGAS00001001682

• Mechanisms_of_patient_response_to_Dabrafenib_in_Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)•NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]•CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Study EGAS00001000946

• Onco-exaptation of an Endogenous Retroviral LTR Drives IRF5 Expression in Hodgkin Lymphoma

  The transcription factor interferon regulatory factor 5 (IRF5) is upregulated in Hodgkin lymphoma (HL) and a key regulator of the aberrant transcriptome characteristic of this disease. Here we show that IRF5 upregulation in HL is driven by transcriptional activation of a normally dormant endogenous retroviral LOR1a long terminal repeat (LTR) upstream of IRF5. Specifically, through screening of RNA-seq libraries, we detected LTR-IRF5 chimeric transcripts in multiple HL cell lines but not in normal B-cell controls. In HL, the LTR was in an open and hypomethylated epigenetic state and we further show the LTR is the site of transcriptional initiation. Among HL cell lines, usage of the LTR promoter strongly correlates with overall levels of IRF5 mRNA and protein, indicating that LTR transcriptional awakening is a major contributor to IRF5 upregulation in HL. Taken together, oncogenic IRF5 overexpression in HL is the result of a specific LTR transcriptional activation. We propose that such LTR derepression is a distinct mechanism of oncogene activation (“onco-exaptation”) and that such a mechanism warrants further investigation in molecular and cancer research.

  Study EGAS00001001205

• Evolution of GBM through therapy

  Primary glioblastoma (GBM) tumours recur following treatment. This is likely due to intratumour heterogeneity (ITH), which reduces the effectiveness of cancer therapies by enabling therapy-driven tumour evolution: Darwinian selection of genotypically and/or phenotypically distinct cells (subclones) that resist treatment to seed regrowth of an even less treatable recurrence. To investigate this we sequenced a pilot cohort of nine paired primary and locally recurrent GBM tumours, alongside matched blood samples, in order to begin characterising therapy resistant cells and thereby infer the mechanisms by which they evaded treatment. These data were included in the first data release from the Glioma Longitudinal AnalySiS (GLASS) consortium.

  Study EGAS00001003546

• Germline variants collaborate with somatic mutations and initiate and/or drive disease in primary myelodysplastic syndrome (MDS) and therapy-related myeloid neoplasms (t-MN)

  Therapy-related myeloid neoplasms (T-MN) are poorly characterized secondary hematological malignancies following chemotherapy/radiotherapy exposure. We compared the clinical and mutational characteristics of T-MN (n=129) and primary myelodysplastic syndrome (P-MDS, n=108) patients. Although the somatic mutation frequency was similar between T-MN and P-MDS patients (93% in both groups), the pattern was distinct. TP53 mutations were more frequent in T-MN (29.5% versus 7%), while spliceosomal complex mutations were more common in P-MDS (56.5% versus 25.6%).In contrast to P-MDS, the ring sideroblasts (RS) phenotype was not associated with better survival in T-MN, most probably due to genetic association with TP53 mutations. SF3B1 was mutated in 96% of P-MDS with ≥15% RS, but in only 32% T-MN. TP53 mutations were detected in 92% T-MN with ≥15% RS and SF3B1 wild-type cases. Interestingly, T-MN and P-MDS patients with “Very low” or “Low” Revised International Prognostic Scoring System (IPSS-R) showed similar biological and clinical characteristics. In a Cox-regression analysis, TP53 mutation was a poor prognostic factor in T-MN, independent of IPSS-R cytogenetic, disease-modifying therapy and NRAS mutation.Our data have direct implications for T-MN management and provide evidence that, in addition to conventional disease parameters, mutational analysis should be incorporated in T-MN risk stratification.

  Study EGAS00001003547

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• Pulldown_DNA_methylation_study_v2

  Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

  Study EGAS00001000979