7344 results for "canc*"

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• Ovarian Cancer Organoid Biobank

  WGS of ovarian cancer organoids, tumor samples and blood references. Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004387

• A Study to Evaluate Denosumab in Young Patients With Primary Breast Cancer (D-Beyond)

  This is a prospective, single arm phase IIa trial in which patients with early breast cancer will receive pre-operatively two doses of denosumab 120mg subcutaneously one week apart (maximum 12 days) followed by surgery. Tumor, normal breast tissue and blood samples will be collected at baseline and at surgery. Post-operative treatment will be at the discretion of the investigator.Primary objective: to determine if a short course of RANKL inhibition with denosumab can induce a decrease in tumor proliferation rates as determined by Ki67 immunohistochemistry (IHC) in newly diagnosed, early stage breast cancer in pre-menopausal women.

  Dataset EGAD00001004391

• PDAC

  ctDNA and protein markers for earlier detection of pancreatic cancers

  Dataset EGAD00001004399

• PLCRC study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from Colorectal cancer patients and subjected to short paired end sequencing on the llumina platform. 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.

  Dataset EGAD00001000947

• Transcriptome profiling for Korean Early Onset Gastric Cancer

  To identify transcriptome profile in this unique subset of gastric cancers, RNA-seq analyses were performed using frozen cancer tissue. Adjacent normal tissue of the same patients were used in differently expressed gene selection and fusion gene prediction.

  Dataset EGAD00001002187

• Barcelona kids with melanoma

  This set of samples is composed of eight young people (7-16 years old) that have developed melanoma with first-degree relatives that have also developed cancer, which suggests a genetic component to their disease. Here we want to sequence these samples in order to find the causative mutations. As these samples do not carry any of the high-penetrance mutations known to date, finding the genes(s) responsible will offer new insights into the genetic mechanisms underlying predisposition to melanoma.

  Dataset EGAD00001002198

• 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

• Low coverage WGS from plasma DNA

  Low coverage whole genome sequencing plasma DNA from 50 male, 54 female non-cancer donors. For the analysis of nucleosomal positioning all data from the non-cancer controls were merged. Furthermore, two patients with metastasized breast cancer were sequenced on a NextSeq with higher depth.

  Dataset EGAD00001002215

• RNA-Seq of tumors

  RNA-Seq on an Ion Torrent Proton of corresponding tumor material of two metastasized breast cancer patients (Breast7, Breast13).

  Dataset EGAD00001002216

• Paired-end sequenced plasma DNA samples

  Merged file of low-coverage WGS from 179 plasma DNA samples from non-cancer controls and cancer patients for assessment of size distribution of plasma nuclear DNA fragments.

  Dataset EGAD00001002217

• Identification of drug resistance genes in cancer cell lines by insertional mutagenesis

  Our aim is to identify genes involved in resistance to anti-cancer therapies. In order to do this we have taken advantage of a lentiviral vector (LV)-based insertional mutagen to mutagenize cancer cell lines. LV-transduced cell lines were then treated with anti-cancer therapies and the emergence of resistant clones scored. DNA from pools of resistant clones was collected, subjected to custom capture by baits designed against the LV sequence, and then sequenced to identify the LV-genomic junction. We hope that the identification of recurrently targeted genes in resistant cell population will allow us to identify genes that mediate drug resistance.

  Dataset EGAD00001002207

• PSCP_mutation analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shred by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002231

• The genetic evolution of precursor lesions in pancreatic cancer

  Mapping genetic evolution of pancreatic cancer precursor lesions such as IPMNs and PanINs.

  Dataset EGAD00001002232

• Direct transcriptional consequences of somatic mutation in breast cancer

  The disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription; co-ordinated secondary alterations in transcriptional pathways; and increased transcriptional noise. To catalogue the rules governing how somatic mutation Overall, 59% of 6980 exonic substitutions were expressed. Compared to other classes, nonsense mutations showed lower expression levels than expected with patterns characteristic of nonsense-mediated decay. 14% of 4234 genomic rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusion transcripts and premature poly-adenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes may drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data therefore reveals the rules by which transcriptional machinery interprets somatic mutation.

  Dataset EGAD00001002236

• Direct transcriptional consequences of somatic mutation in breast cancer

  The disordered transcriptomes of cancer encompass direct effects of somatic mutation on transcription; co-ordinated secondary alterations in transcriptional pathways; and increased transcriptional noise. To catalogue the rules governing how somatic mutation Overall, 59% of 6980 exonic substitutions were expressed. Compared to other classes, nonsense mutations showed lower expression levels than expected with patterns characteristic of nonsense-mediated decay. 14% of 4234 genomic rearrangements caused transcriptional abnormalities, including exon skips, exon reusage, fusion transcripts and premature poly-adenylation. We found productive, stable transcription from sense-to-antisense gene fusions and gene-to-intergenic rearrangements, suggesting that these mutation classes may drive more transcriptional disruption than previously suspected. Systematic integration of transcriptome with genome data therefore reveals the rules by which transcriptional machinery interprets somatic mutation.

  Dataset EGAD00001002237

• PSCP_bisulphite analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. 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/

  Dataset EGAD00001002235

• ChIP-Seq (H3K4me3, H3K4me1, H3K9me3, H3K27ac, H3K27me3, H3K36me3, Input) data for HL60 cell line generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency.

  ChIP-Seq (H3K4me3, H3K4me1, H3K9me3, H3K27ac, H3K27me3, H3K36me3, Input) data for HL60 cell line generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency.

  Dataset EGAD00001002238

• June 2016 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2016 data update (bam/fastq for CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087 ChIP-Seq and RNA-Seq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002239

• A case of colorectal cancer with ERBB2 c.2264T>C (p.Leu755Ser) mutation

  This data set contains next generation sequencing (NGS) data of two serial tumor samples (primary and a metastasis) from a patient with colorectal cancer showing an ERBB2 c.2264T>C (p.Leu755Ser). NGS was performed using the Illumina TruSeq Amplicon Cancer Panel (TSACP, Illumina) covering 212 amplicons in 48 cancer associated genes on the Illumina MiSeq sequencing platform. The dataset contains two BAM files.

  Dataset EGAD00001002252

• Trimmed bam-files from whole genome sequencing data from plasma DNA

  Single-end sequencing data (trimmed to 60bp) of 104 plasma samples from donors without tumors (male=50; female=54) were merged and used to establish coverage profiles around the TSS and to establish a gene expression prediction algorithm. Dataset includes merged alignements of low coverage whole genome sequencing from plasma DNA from 50 male, 54 female non-cancer donors. Furthermore, 2 patients with metastasized breast cancer were sequenced on a NextSeq with higher depth.

  Dataset EGAD00001002254

• Breast Cancer -Very young women with ER+ tumor

  Corresponding data set is composed of whole exome sequencing of Korean ER positive breast cancer under 35. This set provides 100 alignment files from normal-tumor paired whole exome sequencing of 50 patients. This is a part of total project data set.

  Dataset EGAD00001002256

• Whole exome sequencing of Finnish hereditary breast cancer families

  Dataset contains Whole Exome Sequencing(WES) data from 37 individuals as aligned bam-files. The reads have been aligned using bowtie2 to human genome hg19 build.

  Dataset EGAD00001002133

• A somatic reference standard for cancer genome sequencing.

  Paired PCR-free whole genome sequencing data of a matched metastatic melanoma cell line (COLO829) and normal across three lineages and across separate institutions, with independent library preparations, sequencing, and analysis. The data was generated with mean mapped coverages of 99X for COLO829 and 103X for the paired normal across three institutions. Overall, common events include >35,000 point mutations, 446 small insertion/deletions, and >6,000 genes affected by copy number changes. We present this reference to the community as an initial standard for enabling quantitative evaluation of somatic mutation pipelines across institutions.

  Dataset EGAD00001002142

• SCNA-Seq of plasma DNA samples

  Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping in plasma DNA of prostate cancer patients

  Dataset EGAD00001002149

• Genome-Wide Variations of End Motif in Cell-Free DNA Fragments Distinguish Immunotherapy Responders from Non-Responders in Head and Neck Cancer: A Multi-Institute Prospective Study

  Genome-Wide Variations of End Motif in Cell-Free DNA Fragments Distinguish Immunotherapy Responders from Non-Responders in Head and Neck Cancer: A Multi-Institute Prospective Study

  Dac EGAC50000000753

• Cell-Free DNA Fragmentation Distinguish Immunotherapy Responders from Non- Responders in Head and Neck Cancer: A Multi-Institute Prospective Study

  We performed whole-genome sequencing of 185 plasma cfDNA samples from 68 patients with head and neck squamous cell carcinoma (HNSCC) enrolled in a phase II clinical trial of neoadjuvant and adjuvant pembrolizumab. Using these data, we developed the regional motif diversity score (rMDS), a novel fragmentomic biomarker that predicts immunotherapy response and outperforms established cfDNA metrics.

  Study EGAS50000001286

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002645

• Genome and transcriptome sequence data from a multifocal hepatocellular carcinoma patient

  Genome and transcriptome sequence data from a multifocal hepatocellular carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002644

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002643

• Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient

  Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002642

• Genome and transcriptome sequence data from a metastatic small cell carcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from a metastatic small cell carcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002641

• Genome and transcriptome sequence data from a clival chordoma patient

  Genome and transcriptome sequence data from a clival chordoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002640

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002639

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002648

• Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002647

• Genome and transcriptome sequence data from an epithelioid mesothelioma patient

  Genome and transcriptome sequence data from an epithelioid mesothelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002646

• Impact of mutational profiles on response of primary oestrogen receptor-positive breast cancers to oestrogen deprivation

  Presurgical studies allow study of the relationship between mutations and response of estrogen receptor positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in Phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 Controls). In poor responders (based on Ki67 change) we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores   occur in approximately 30% of tumours. In Phase II we combine targeted sequencing on another 28 treated patients with Phase I. We find six genes frequently mutated: PIK3CA, TP53, CDH1, MLL3, ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy.

  Dataset EGAD00001002651

• Whole genome sequencing of 98 tumour-normal pairs for the pancreatic neuroendocrine cancer project

  Whole genome sequencing of 98 tumour-normal pairs for the PAEN-AU pancreatic neuroendocrine cancer project.

  Dataset EGAD00001002684

• Breast cancer PDTX sequencing data from Bruna et al, Cell 2016

  Breast cancer PDTX sequencing data from Bruna et al, Cell 2016 - Exome Sequencing - Shallow Whole Genome Sequencing - RRBS Methylation Sequencing

  Dataset EGAD00001002685

• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues.

  Dataset EGAD00001002266

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002534

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002531

• Genome and transcriptome sequence data from an ovarian cancer patient

  Genome and transcriptome sequence data from an ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002533

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002532

• Genome and transcriptome sequence data from a uterine sarcoma patient

  Genome and transcriptome sequence data from a uterine sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002538

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002537

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002536

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002535

• Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma patient

  Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002589

• Genome and transcriptome sequence data from an adnexal tumor probable of Wolffian origin patient

  Genome and transcriptome sequence data from an adnexal tumor probable of Wolffian origin patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002600