7296 results for "canc*"

in 51.61 milliseconds.

• Various_Cancer_Fusion_Gene_Sequencing

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from 50 commomon epithelial cancer samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000012

• The patterns and dynamics of genomic instability in metastatic pancreatic cancer

  Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97–98%, usually due to widespread metastatic disease. Previous studies indicate that this disease has a complex genomic landscape, with frequent copy number changes and point mutations, but genomic rearrangements have not been characterized in detail. Despite the clinical importance of metastasis, there remain fundamental questions about the clonal structures of metastatic tumours, including phylogenetic relationships among metastases, the scale of ongoing parallel evolution in metastatic and primary sites, and how the tumour disseminates. Here we harness advances in DNA sequencing to annotate genomic rearrangements in 13 patients with pancreatic cancer and explore clonal relationships among metastases. We find that pancreatic cancer acquires rearrangements indicative of telomere dysfunction and abnormal cell-cycle control, namely dysregulated G1-to-S-phase transition with intact G2–M checkpoint. These initiate amplification of cancer genes and occur predominantly in early cancer development rather than the later stages of the disease. Genomic instability frequently persists after cancer dissemination, resulting in ongoing, parallel and even convergent evolution among different metastases. We find evidence that there is genetic heterogeneity among metastasis-initiating cells, that seeding metastasis may require driver mutations beyond those required for primary tumours, and that phylogenetic trees across metastases show organ-specific branches. These data attest to the richness of genetic variation in cancer, brought about by the tandem forces of genomic instability and evolutionary selection.

  Study EGAS00000000064

• CLL Genome

  The Chronic Lymphocytic Leukemia (CLL) Genome Project aims to identify genetic alterations involved in the development and progression of the CLL, which are still unknown, with the objective of generating a comprehensive catalogue of genetic alterations in 500 independent tumours. The CLL Genome Project, as a contributing member of the International Cancer Genome Consortium (ICGC), has the purposes of creating diagnostic tools, discovering therapeutic targets and developing new strategies that will allow a customized therapy for CLL in order to make it more precise and effective. This study consists of two datasets. EGAD00001000023 described in the Nature paper (2011), Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia, and the dataset EGA00001000044 & & EGAD00001000083 described in the Nature (2011) paper, Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia.Additional data generated within the ICGC-CLL genome project can be found in studies EGAS00001000374 and EGAS00001001306

  Study EGAS00000000092

• CLL_Cancer_Whole_Genome_Sequencing

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from a range of cancer samples and subjected paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000014

• TMD_AMLK_Exome_Study

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 20 Primary Acute Megakaryocytic Leukemia samples and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 100 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes

  Study EGAS00001000027

• Local In Time Statistics for processual research

  Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

  Study EGAS00001002520

• Screening_for_abnormal_CGI_methylation_in_primary_colorectal_tumours

  A common hallmark of neoplastic cells is abnormal acquisition of CpG island (CGI) methylation and the silencing of associated gene promoters. To determine the extent and distribution of CGI methylation in colorectal cancer, we solexa sequenced MBD affinity purified DNA prepared from five colorectal tumours and matched colon mucosa from the same individuals.

  Study EGAS00001000076

• Whole exome sequencing from early stage non-small cell lung cancer patients at MDACC

  The purpose of the study is to evaluate the mutational landscape and tumor mutational burden in tumor from patients with early stage non-small cell lung cancer. Mutational landscape was compared to the T cell repertoire to determine the relationship between somatic mutations and T cell response in early-stage NSCLC.

  Study EGAS00001004026

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Background: Germline truncating mutations in DICER1, an RNase III-type endoribonuclease essential for processing of microRNAs, are seen in families with the pleuropulmonary blastoma-family tumor and dysplasia syndrome; these individuals have a propensity to develop non-epithelial ovarian tumors (i.e. sex-cord stromal and germ cell tumors). Methods: We sequenced the whole transcriptomes or exomes of 14 non-epithelial ovarian tumors and noted closely clustered mutations in the RNase IIIb domain of DICER1 in four cases. Using Sanger sequencing, we then analyzed additional ovarian tumors for mutations in this region. The impact of the mutations on the enzymatic activity of Dicer1 was determined using in vitro RNA cleavage assays. Results: RNase IIIb domain DICER1 mutations were found in 30/102 non-epithelial ovarian tumors (29%), predominantly Sertoli-Leydig cell tumors (26/43, 60%), including 4/4 from individuals with germline DICER1 mutations. The mutations were restricted to metal binding sites within the RNase IIIb catalytic centres critical for miRNA interaction and cleavage, and were somatic in all 14 cases where germline DNA was available for testing. Of 266 epithelial ovarian and endometrial cancers tested, one case, an ovarian carcinosarcoma, had a hotspot mutation. In vitro, the mutant DICER proteins showed reduced RNase IIIb activity but retained RNase IIIa activity. Conclusions: Somatic missense mutations of the RNase IIIb domain of DICER1 are common in non-epithelial ovarian tumors. Genetic, pathologic, and functional evidence suggest that these mutations do not obliterate DICER1 function, rather, they alter it in specific cell types, a novel mechanism through which perturbed microRNA expression is oncogenic.

  Study EGAS00001000135

• Familial_Thrombocytosis_germline_exome_sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 3 relatives from a family with multiple affected familial thrombocytosis (FT) patients. Germline DNA from 2-4 patients affected with FT will be used to prepare libraries and sequenced in one lane of HiSeq sequencing, mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000088

• Chordoma_Extension_Study

  Extension analysis to pursue candidate genes of interest in chordoma

  Study EGAS00001000892

• The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

  Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of DNA methylation in matched primary and recurring glioblastoma tumors, using data from a highly annotated clinical cohort that was selected through a national patient registry. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected FFPE samples, and we validate bisulfite sequencing as a multipurpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional characteristics of the profiled tumor samples. On the basis of these data, we identified subtle differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study establishes an open resource for dissecting DNA methylation heterogeneity in a genetically diverse and heterogeneous cancer, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology for a national cohort, thereby leveraging existing samples and data collected as part of routine clinical practice.

  Study EGAS00001002538

• UCSF Pediatric Bithalamic Glioma Genome Project

  Brain tumors are the most common solid tumors of childhood, and the genetic drivers and optimal therapeutic strategies for many of the different subtypes remain unknown. We performed targeted next-generation sequencing of approximately 500 cancer-associated genes on a cohort of 13 pediatric bithalamic diffuse gliomas, a lethal brain tumor of childhood for which the genetic basis is largely unknown. We identified that bithalamic diffuse gliomas harbor frequent mutations in the EGFR oncogene in the absence of accompanying gene amplification and only rare histone H3 mutation. These EGFR mutations were either small in-frame insertions within exon 20 (intracellular tyrosine kinase domain) or missense mutations within exon 7 (extracellular ligand-binding domain). Accompanying alterations included frequent TP53 mutation, CDK6 amplification or CDKN2C mutation, and BCOR and BCORL1 mutation or deletion.

  Study EGAS00001004033

• Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive NSCLC patients

  Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but efficacy varies between patients and is believed to depend in part on the amount and properties of tumor infiltrating lymphocytes (TILs). To comprehensively depict and dissect the baseline landscape of the composition, lineage and functional states of TILs in lung cancer, here we generated deep single-cell RNA sequencing data for 12,346 T cells from the primary tumour, adjacent normal tissues and peripheral blood of 14 treatment-naive NSCLC patients. Combined expression and TCR-based lineage tracking revealed a significant proportion of effector T cells with common origins and similar functional states across peripheral blood and tumours pointing towards a highly migratory nature of these T cells. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of pre-exhausted to exhausted T cells is associated with better prognosis of lung adenocarcinoma (LUAD). In addition, we observed further heterogeneity within the tumour regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of this group of activated tumour Tregs, which included IL1R2, correlated with poor prognosis in LUAD. The T cell clusters revealed by our single cell analyses provide a new approach for patient stratification, and the accompanying compendium of data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer.

  Study EGAS00001002430

• Mixed_Leukemia_Rearrangement_Screen

  Genomic libraries will be generated from total genomic DNA derived from Mixed Leukemia and MPD samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the illumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000180

• RNAseq_Pulldown_

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. In this experiment cDNA derived form Breast Cancer Cell lines was used in an Agilent whole exome pulldown experiment.

  Study EGAS00001000230

• Anaplastic_Meningioma_V3__cancer_gene_panel

  Investigation into causal genes underlying anaplastic meningioma

  Study EGAS00001001155

• GIST_SSGXVIII_trial_targeted_gene_sequencing

  Targeted cancer gene sequencing of samples enrolled in the SSGXVIII trial from Finland.

  Study EGAS00001001054

• TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

  We examined tumours from a large cohort of patients with metastatic urothelial bladder cancer (mUC) treated with an anti–PD-L1 agent (atezolizumab) and identified major determinants of clinical response and immune escape. Whole transcriptome profiles were generated for 368 patients using TruSeq RNA Access technology (Illumina). Somatic mutations were determined via whole exome sequencing for a subset of these patients. - Response was associated with CD8+ T effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden (TMB). On the other hand, lack of response was associated with a transforming growth factor β (TGF-β) signature, particularly in patients with CD8+ T cells preferentially residing in collagen-rich matrix surrounding tumours. Integration of these three independent biological features provided the best basis for understanding outcome in this setting. -

  Study EGAS00001002556

• Pulldown_cytosine_deaminases

  We are looking at the causal factors behind hyper-mutator phenotypes found in previous Breast Cancer sequencing studies.

  Study EGAS00001000233

• μSeq: Universal mutation rate quantification via deep sequencing of a single clonal expansion

  We use patient-derived colorectal cancer organoids to introduce µSeq, a universal framework for inferring mutation rates in diverse biological systems. Our approach extracts mutation rates from deep sequencing of single clonal expansions, with a time gain of tenfold or more compared to a mutation-accumulation line, at the cost of three billion read whole-genome sequencing.

  Study EGAS50000001761

• RNA_sequencing

  All cancers arise due to somatically acquired mutations in their genomes which alter the function of key cancer genes. Understanding the critical mutational events underlying the development of cancer is paramount for advancing prevention, early detection and effective treatment of the disease. Breast cancer is the most common cause of cancer death among women. Extraordinary recent advances in sequencing now make it a realistic aim to sequence large numbers of breast cancer genomes to find somatic mutations on a massive scale. NB bam files for manuscript A_Proteomic_Chronology_of_Gene_Expression_through_the_Cell_Cycle_in_Human_Myeloid_Leukemia_Cells are now available at the following link:http://www.ebi.ac.uk/ena/data/view/ERP008483

  Study EGAS00001000310

• Chondrosarcoma_Targeted_Sequencing_Study

  This Study uses a focused bait pull down library method to target findings of Chondrosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these finding in a larger set of patients.

  Study EGAS00001000277

• genome-wide cfDNA methylation analysis

  To characterise cfDNA methylome in metastatic prostate cancer

  Study EGAS00001003958

• Whole-exome Sequencing Combined with Functional Genomics Reveals Novel Candidate Driver Cancer Genes in Endometrial Cancer

  Endometrial cancer is the most common gynecological malignancy, with more than 280,000 cases occurring annually worldwide. Although previous studies have identified important common somatic mutations in endometrial cancer, they have primarily focused on a small set of known cancer genes and have thus provided a limited view of the molecular basis underlying this disease. Here we developed an integrated systems biology approach to identifying novel cancer genes contributing to endometrial tumorigenesis. We first performed whole-exome sequencing on 13 endometrial cancers and matched normal samples, systematically identifying somatic alterations with high precision and sensitivity. We then combined bioinformatics prioritization with high-throughput screening (including both shRNA-mediated knockdown and expression of wild type and mutant constructs) in a highly sensitive cell viability assay. Our results revealed 12 potential driver cancer genes including 10 tumor suppressor candidates (ARID1A, INHBA, KMO, TTLL5, GRM8, IGFBP3, AKTIP, PHKA2, TRPS1 and WNT11) and two oncogene candidates (ERBB3 and RPS6KC1). The results in the “sensor” cell line were recapitulated by siRNA-mediated knockdown in endometrial cancer cell lines. Focusing on ARID1A, we integrated mutation profiles with functional proteomics in 222 endometrial cancer samples, demonstrating that ARID1A mutations frequently co-occur with mutations in the phosphatidylinositol 3-kinase (PI3K) pathway and are associated with PI3K pathway activation. siRNA knockdown in endometrial cancer cell lines increased AKT phosphorylation supporting ARID1A as a novel regulator of PI3K pathway activity. Our study presents the first unbiased view of somatic coding mutations in endometrial cancer and provides functional evidence for diverse driver genes and mutations in this disease.

  Study EGAS00001000318