6137 results for "canc*"

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• Genomic gain of EBV's LMP-1 in NKTCL

  The study found a high recurrence of genomic gain of LMP1 locus within EBV-associated NKTCL. The pilot data set and extended dataset of 77 WGS NKTCLs found 18/77 tumoral genomes to harbour genomic gain of LMP-1 locus within the EBV viral genomes within NKTCL tumoral sequencing data. The study also found 1/10 NKTCL cell lines to be positive for LMP-1 locus gain within EBV genomes too. This dataset includes solely the confirmatory WGS data of LMP-1 gain from NKYS cell lines using Oxford Nanopore long-read sequencing technology.

  Study EGAS50000000260

• A Combined Omics and Tissue Biobank for Paediatric Cancers

  The Swedish Childhood Tumour Biobank (BTB) is a nonprofit national infrastructure for samples and genomic data collection from pediatric patients diagnosed with central nervous system and other solid tumours in Sweden. Fresh frozen tumour tissue and patient’s matched blood are collected from affected patients and genomic data is continuously generated and made available for approved medical research projects. We expect that the accessibility of biological samples and/or data to the research community will contribute to further advances in the understanding of tumour biology, which in turn will impact many aspects of clinical care of children with cancer, by refining diagnosis and/or identifying oncogenic drivers and therapeutic targets.

  Study EGAS50000000209

• Osteosarcoma_Whole_Genome

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

  Study EGAS00001000147

• Single-cell RNA sequencing of 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes

  Hodgkin lymphoma (HL) is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of non-cancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding crosstalk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 HL tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the HL-specific immune microenvironment at single-cell resolution. Library preparation was performed using the 10x Genomics Chromium system, and Illumina sequencing was used to generate 3' gene expression data for every cell. Downstream analysis was performed in R to identify HL-specific microenvironment patterns and identify novel cell populations.

  Study EGAS00001004085

• Radiotherapy_induced_sarcoma

  Whole genome library making will be performed on genomic DNA derived from radiotherapy induced sarcoma samples and matched normal DNA from the same patients. Next Generation sequencing will be performed on the resulting libraries and mapped to build 37 of the human reference genome to facilitate the identification of mutations

  Study EGAS00001000138

• Genetic landscape of pediatric Osteosarcoma

  We performed whole-genome sequencing of 37 paired tumor/normal OS genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes

  Study EGAS00001000263

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_squamous_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002725

• The genomic landscape of pediatric acute lymphoblastic leukemia

  Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer and arises from B- or T-lineage lymphocyte precursors. ALL comprises dozens of subtypes, and genomic analyses have largely been performed within these subtypes. Here we analyze pediatric ALL genomes across all subtypes, including 768 whole genomes, 1,729 exomes, and 1,889 transcriptomes in 2,754 patients. Most ALL subtypes harbor 4 or more driver alterations per sample, similar to adult cancers, despite low mutation burdens. Hyperdiploid B-ALL copy gains are likely acquired early and synchronously, with copy gains occurring before ultraviolet-induced mutations. By contrast, ultraviolet-induced mutations precede copy gains in iAMP21 B-ALL. Overall, we identified 378 putative ALL driver genes. Most driver alterations vary in prevalence across ALL subtypes, with B-ALL enriched for Ras and B-lineage-related alterations, and T-ALL enriched for PI3K, JAK, and cell cycle alterations. Most B-ALL (54.3%) and T-ALL (51.2%) samples bear at least one rare driver gene alteration (present in less than 2% of samples), including 30 putative novel cancer driver genes associated with ubiquitination, SUMOylation, non-coding, and other functions. Known or novel alterations associated with poor outcomes in specific subtypes include TBL1XR1 alterations in ETV6-RUNX1 patients, CREBBP in Ph-like-CRLF2, SETD2 in hyperdiploid, and PTEN in TAL1 patients. Intriguingly, DUX4 and KMT2A subtypes separate into CEBPA/FLT3- or NFATC4-expressing subgroups with potential clinical implications. Together, these results deepen understanding of ALL etiology and outcomes, and facilitate ALL model development.

  Study EGAS00001005250

• Orphan_Tumour_Study___RNAseq

  The aim of this study is to study the genomes of ultra rare childhood tumours

  Study EGAS00001002534

• Kidney_tumour_RNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002487

• X10_sequencing_of_Oesophageal_Adenocarcinoma_Organoids

  X10 Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical resection of the tumour. All model derivations took place with the CGaP facility in Sanger. This PacBio data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003264

• Oesophageal_Adenocarcinoma_Organoid_10x

  10x 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 10x data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003191

• Oesophageal_Adenocarcinoma_Organoid_ATAC

  ATAC Sequencing of 5 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 ATAC data will be combined with other sequencing data in order to generate

  Study EGAS00001003890

• Oesophageal_Adenocarcinoma_Organoids_Iso_Seq

  RNA Sequencing of 5 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 PacBio RNA data will be combined with other sequencing data in order to generate accurate reference cancer genomes and study how structural variants affect gene expression

  Study EGAS00001004051

• RNA-seq of Liver Cancer

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002879

• 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

• The genomic imprint of cancer therapies helps timing the formation of metastases

  Study EGAS00001003416

• Cell_lines_with_telomere_fusion_induced_rearrangements

  Whole-genome somatic rearrangement and point mutation analysis in cell lines with induced telomere fusions.

  Study EGAS00001001059

• ICGC PanCancer Analysis of Whole Genomes

  Study EGAS00001001692

• Multiple_Myeloma_Diagnosis_to_Relapse_study_samples

  The study will investigate serial samples from the same patient taken at the time of MGUS or SMM diagnosis, and later at the time of evolution towards MM. Samples will be sequenced by whole genome along with a matched normal to obtain the highest possible amount of information toinvestigate genomic changes at disease evolution.

  Study EGAS00001001299

• Fibroblast heterogeneity and immunosuppressive environment in Human breast cancer

  Carcinoma-associated fibroblasts (CAF) are key players in the tumor microenvironment. Here, by combining 6 well-known stromal markers, we identify four CAF subsets (CAF-S1 to CAF-S4) in human breast cancer (BC) that exhibit distinct activation patterns and accumulate differently in BC subtypes.

  Study EGAS00001002508

• Lung_Progression_versus_Regression_Whole_Genome_Sequencing

  Around 50 samples of pre-invasive lung cancer lesions showing subsequent clinical and pathological progression or regression

  Study EGAS00001000837

• WGS___Mutant_clone_mapping_in_normal_oesohagus_and_skin

  We will use whole genome sequencing to examine normal appearing oesophageal epithelium and skin to determine the mutational burden. DNA will be extracted from epithelia of a defined size and we will overlay positional information from the epithelial pieces to give clone maps over a wide area. This will be done in both oesophageal epithelium and skin

  Study EGAS00001002416

• Identifying_new_diagnostic_and_treatment_pathways_for_patients_with_unclassifiable_sarcomas

  Whole genome sequencing of tumour normal pairs of human undifferentiated sarcomas.

  Study EGAS00001001604

• Histone chaperone CHAF1A promotes proliferation and tumorigenicity in gastric cancer and impacts prognosis via context-depedent regulation of gene expression

  The histone chaperone CHAF1A is associated with some tumors, but its mechanisms in tumor biology remain elusive. Gastric cancer (GC) has significant heterogeneity among patients, and novel prognostic markers and therapeutic targets may improve its outcomes. The role of CHAF1A in GC is unknown. In this study, we demonstrated that CHAF1A was overexpressed in GC tissues accompanied by low expression of wild-type P53 and high expression of the proliferation marker MKI67. In vitro, CHAF1A knockdown inhibited cell proliferation, induced cell cycle arrest and promoted apoptosis, while CHAF1A overexpression had contrary effects. In vivo, CHAF1A knockdown inhibited tumorigenicity of GC cells. A microarray assay with CHAF1A inhibition and a PathScan signaling antibody array with CHAF1A overexpression showed that CHAF1A inhibited the P53 pathway, activated stress response and induced glycolytic metabolism. In 665 patients, the expression level of CHAF1A protein was an independent predictor for overall survival and disease-free survival in non-cardia GC and also had survival associations in patients with small or perineural invasion-negative tumors. Tumor mRNA analyses based on next-generation sequencing in patients indicated that CHAF1A promoted the Warburg effect by depressing oxidative phosphorylation and increasing glycolysis. Furthermore, the heterogeneous clinical significance of CHAF1A among patient subgroups was associated with its differential regulation of gene expression involved with glycolysis and cell proliferation and survival, indicating that the role of CHAF1A is depended on patient characteristics. These results reveal critical roles and clinical values for CHAF1A in GC. CHAF1A may have context-dependent effects in GC, which increases understandings for GC heterogeneity.

  Study EGAS00001003064