7825 results for "canc*"

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• Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Dataset EGAD00001000293

• Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Dataset EGAD00001000290

• Cancer Genome Project Exome Sequencing

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from cancer 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 re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products.

  Dataset EGAD00001000289

• Molecular characterization of invasive lobular carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Dataset EGAD00001000288

• Renal Cancer Exome Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Dataset EGAD00001000287

• RNA sequencing

  We propose to definitively characterise the somatic genetics of 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.

  Dataset EGAD00001000285

• Whole genome analyses of the childhood cancer neuroblastoma

  Neuroblastomas are tumors of peripheral sympathetic neurons and are the most common solid tumor in children. To determine the genetic basis for neuroblastoma we performed whole-genome sequencing (6 cases), exome sequencing (16 cases), genome-wide rearrangement analyses (32 cases), and targeted analyses of specific genomic loci (40 cases) using massively parallel sequencing. On average each tumor had 19 somatic alterations in coding genes (range, 3-70). Among genes not previously known to be involved in neuroblastoma, chromosomal deletions and sequence alterations of chromatin remodeling genes, ARID1A and ARID1B, were identified in 8 of 71 tumors (11%) and were associated with early treatment failure and decreased survival. Using tumor-specific structural alterations, we developed an approach to identify rearranged DNA fragments in sera, providing personalized biomarkers for minimal residual disease detection and monitoring. These results highlight dysregulation of chromatin remodeling in pediatric tumorigenesis and provide new approaches for the management of neuroblastoma patients.

  Dataset EGAD00001000282

• SCAT_Osteosarcoma_Validation

  This experiment is to validate putative somatic substitutions and indels identified in an exome screen of ~50 osteosarcoma tumour/normal pairs. It is the first stage in our ICGC commitment to study osteosarcoma. The validation process is an important component of our analysis to clarify the data prior to looking for evidence of new cancer genes, or subverted pathways important in the development of cancer. 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 EGAD00001000280

• Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Dataset EGAD00001000284

• OICR PANCREATIC CANCER DATASET 2

  OICR PANCREATIC CANCER DATASET 2

  Dataset EGAD00001000276

• 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.

  Dataset EGAD00001000283

• Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

  Dataset EGAD00001000175

• Matched breast cancer fusion gene study

  Matched breast cancer fusion gene study

  Dataset EGAD00001000097

• Cancer Genome Libraries Tests

  Cancer Genome Libraries Tests

  Dataset EGAD00001000094

• Breast Cancer Exome Resequencing

  Breast Cancer Exome Resequencing

  Dataset EGAD00001000093

• Cancer Exome Resequencing

  Cancer Exome Resequencing

  Dataset EGAD00001000092

• ER-, HER2-, PR- breast Cancer genome sequencing

  ER-, HER2-, PR- breast Cancer genome sequencing

  Dataset EGAD00001000088

• Matched Ovarian Cancer Sequencing

  Matched Ovarian Cancer Sequencing

  Dataset EGAD00001000084

• 20 Matched Pair Breast Cancer Genomes

  20 Matched Pair Breast Cancer Genomes

  Dataset EGAD00001000082

• Genomics of Colorectal Cancer Metastases - Massively Parallel Sequencing of Matched Primary and Metastatic tumours to Identify a Metastatic Signature of Somatic Mutations (MOSAIC)

  Genomics of Colorectal Cancer Metastases - Massively Parallel Sequencing of Matched Primary and Metastatic tumours to Identify a Metastatic Signature of Somatic Mutations (MOSAIC)

  Dataset EGAD00001000080

• ALK inhibitors in the context of ALK-dependent cancer cell lines

  ALK inhibitors in the context of ALK-dependent cancer cell lines

  Dataset EGAD00001000078

• Cancer Single Cell Sequencing

  Cancer Single Cell Sequencing

  Dataset EGAD00001000067

• Breast Cancer Follow Up Series

  Breast Cancer Follow Up Series

  Dataset EGAD00001000066

• Triple Negative Breast Cancer sequencing

  Triple Negative Breast Cancer sequencing

  Dataset EGAD00001000063

• COLO-829/COLO-829BL

  COLO-829 is a publicly available immortal cancer cell line and COLO-829BL is a lymphoblastoid cell line derived from the same patient

  Dataset EGAD00000000055

• EGAD00000000054

  NCI-H209 is an immortal cell line derived from a bone marrow metastasis of a patient with small cell lung cancer, taken before chemotherapy. The specimen showed histologically typical small cells with classic neuroendocrine features. NCI-BL209 is an EBV-transformed B-cell line derived from the same patient as the small cell lung cancer cell line, NCI-H209

  Dataset EGAD00000000054

• EGAD00000000053

  Sequencing data from Breast Cancer samples

  Dataset EGAD00000000053

• EGAD00000000049

  RNA-SEQ data from oestrogen-receptor-alpha-positive metastatic lobular breast cancer sample

  Dataset EGAD00000000049

• EGAD00000000048

  Sequencing data from oestrogen-receptor-alpha-positive metastatic lobular breast cancer sample

  Dataset EGAD00000000048

• EGAD00000000013

  WTCCC1 project Breast cancer (BC) samples

  Dataset EGAD00000000013

• FFPE tumor RNA exome capture sequencing

  This dataset includes raw, untrimmed FASTQ files generated from bulk RNA exome capture sequencing of FFPE tumor samples from 268 stage III colorectal cancer patients, prior to receiving adjuvant chemotherapy treatment. RNA libraries were prepared with the Illumina TruSeq RNA Exome kit and sequenced (PE51bp) using an Illumina NovaSeq 6000 with an S4 flow cell. The metadata file "RNAseq_metadata.tsv" contains columns with relevant quality metrics "DV200" and "cDNA_ng_ul" per sample, and a column indicating whether the sample was part of one or more published analyses: Franken et al., Eur. J. Cancer, 2026. PMID: 41650786. DOI: https://doi.org/10.1016/j.ejca.2026.116262 Crnovrsanin et al., XXX, 2026. PMID: XXX. DOI: XXX

  Dataset EGAD50000002440

• Mitochondrial peroxiredoxin 3 is a tractable cancer therapeutic target modulated by SLC7A11

  This study is aimed at elucidating the anti-tumor mechanism and therapeutic potential of the PRX3 inhibitor thiostrepton in mesothelioma by investigating its effects on mitochondrial redox homeostasis, oxidative stress–induced apoptosis, and tumor suppression in preclinical and clinical settings. Mesothelioma explants are treated with thiostrepton and subjected to RNA sequencing under baseline, untreated control, and thiostrepton-treated conditions to characterize treatment-induced transcriptional alterations and identify molecular pathways associated with therapeutic response and resistance.

  Study EGAS50000001827

• Biomarker analysis and treatment dynamics following preoperative ipilimumab plus nivolumab in locally advanced urothelial cancer from the phase 1B NABUCCO study

  In the current analysis of the full NABUCCO trial population (cohorts 1 and 2), we aimed to explore both potential biomarkers for response to combination ICB, as well as treatment dynamics to gain a better understanding of the effects of ICB on the urothelial cancer tumor microenvironment (TME).

  Study EGAS50000001781

• Whole transcriptome sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the whole transriptome sequencing data

  Study EGAS50000001742

• TCR and BCR sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the TCR and BCR sequencing data

  Study EGAS50000001743

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509

• Parallel sequencing of extrachromosomal circular DNAs and transcriptomes in single cancer cells

  Study EGAS00001007026

• Multi-omics datasets (WES, RNA-seq) of mesothelioma MIST2 study, a phase II CDK4/6 (abemaciclib) clinical trial

  This study comprises 26 mesothelioma patients with whole exome and RNA sequencing, to to assess potential sensitivity to CDK4/6 inhibition in p16ink4A-negative mesothelioma.

  Study EGAS50000001823

• Multi-omics datasets (WES, RNA-seq) of mesothelioma NERO study, a phase II PARP inhibitor clinical trial

  Niraparib Efficacy in Patient With Unresectable Mesothelioma, NERO, this randomised phase II trial is designed to evaluating the efficacy of the PARP inhibitor Niraparib versus active symptom control.

  Study EGAS50000001825

• Liquid-based genomic profiling in high-risk localized prostate cancer.

  In this study, we evaluated the feasibility and performance of tissue and liquid-based genomic profiling in patients with high-risk localized prostate cancer. Genomic DNA from 12 FFPE tissue samples and cell-free DNA from 27 plasma samples were analyzed using Illumina TruSight Oncology (TSO) 500 panels.

  Study EGAS50000001712

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk

  Study EGAS00001006137

• Deep whole genome ctDNA chronology of treatment-resistant prostate cancer

  Study EGAS00001005783

• cell-free DNA Target sequencing from primary and recurrent/metastatic breast cancer patients

  Breast cancer is one of the most common cancers occurring worldwide in women. Even after curative treatment based on clinical subtypes according to molecular features, the risk of relapse still remains. Cell-free DNA (cfDNA) is an emerging tool for clinical cancer detection to monitor the risk of recurrence, therapeutic efficacy and tumor progression. In occurrence of relapse, genomic, transcriptomic and epigenetic profiles are altered, and reflected in cfDNA fragmentation patterns. In this study, we focus on the transcriptionally dynamic loci associated with therapy resistance in breast cancer, and develop the target sequencing approach using cfDNAs to detect individuals with recurrent/metastatic breast cancer.

  Study JGAS000812

• Development of actionable molecular targets and/or biomarkers for prognostication and patient stratification in gynecological cancer based on whole-exome sequencing and epigenomic analysis

  We collected 157 oral MPA-treatment samples from 66 cases (53 endometrial hyperplasia from 31 cases, 19 atypical polypoid adenomyoma from 14 cases, 1 normal endometrium from 1 case, and 84 endometrial carcinoma from 53 cases) and matched normal tissues/whole blood. The purpose of this study is to develop actionable molecular targets and/or biomarkers for prognostication and patient stratification.

  Study JGAS000813

• Whole exome sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the whole exome sequencing data

  Study EGAS50000001744

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.

  Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dac EGAC50000000169

• Cellular Dynamics Upon Immune Checkpoint Inhibition

  Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet most patients experience limited or no clinical benefit. To elucidate the mechanisms of response and resistance, we analyzed single-cell RNA-sequencing data from 141 patients across multiple cancer types and ICI treatment modalities, with longitudinally paired samples. Using a robust, integration-free deep phenotyping framework, we annotated 876,410 cells into 80 granular states. We identified consistent compositional changes in 17 cell subtypes following ICI treatment, including enhanced adaptive immune responses and reduced interferon-responsive cells. Co-regulated cell communities within the tumor microenvironment (TME) highlighted coordinated interplay between immune and non-immune components. Importantly, we discovered two distinct patient groups with divergent TME dynamics post-treatment: responders showed expansion of naive lymphocytes, while non-responders exhibited increased immune-experienced/suppressive cells. This dichotomy offers a potential predictive biomarker for patient stratification. Our comprehensive analysis of TME dynamics during ICI treatment advances understanding of response mechanisms and personalized cancer immunotherapy.

  Study EGAS50000000459

• WGS, DuplexSeq and NanoSeq genomic data from histologically normal tissue in cancer patients

  The extent to which mutagenic and non-mutagenic processes, including cancer treatment, contribute to somatic evolution in histologically normal tissue remains unclear. We subjected 168 cancer-free normal samples representing 16 different organs from 22 patients with metastatic cancer enrolled in the PEACE research autopsy study to high-depth duplex panel sequencing (coverage >20,000x). In every sample we identified somatic mutations (range 170 - 2,978) at exceedingly low variant allele frequencies (median VAF 0.0000323), consistent with a patchwork of mutated cells in normal tissue. By analysing the mutational spectra of each sample, we extracted 16 distinct single base substitution mutational signatures, reflecting somatic mutational processes that have moulded the genomes of normal cells. Signatures were found to be associated with diverse aetiologies, including alcohol-related mutation acquisition in liver tissue, smoking-induced mutagenesis in lung and cardiac tissue, and multiple distinct treatment-induced processes, which correlated with treatment and its duration. On average, in this cohort in which patients had each received several lines of anti-cancer therapy, exogenous sources, including treatment-related mutagenesis, underpinned >40% of mutations in liver samples, yet <10% in brain samples. Finally, we observed clear differences in the extent and effects of selection in different tissues, with positive selection in certain tissues, including lung (TP53, EGFR and PIK3CA), liver (NF2L2) and spleen (BRAF, NOTCH2), and limited selection in others, such as brain and cardiac. Over 25% of driver mutations in normal tissue exposed to systemic anti-cancer therapy, including mutations in TP53, could be attributed to treatment-induced mutagenesis. Immunotherapy, while not associated with mutagenesis, was linked to an excess of driver mutations in PPM1D and TP53, illustrating how non-mutagenic treatment can sculpt somatic evolution. Our study reveals the rich tapestry of mutational processes and driver mutations in cancer-free normal tissue, and the profound impact of cancer therapeutic and life-time environmental exposures on normal tissue somatic evolution.

  Study EGAS00001008326

• Comprehensive Genomic Profiling of a National Cohort of Pediatric Papillary Thyroid Carcinoma in Hungary

  Pediatric papillary thyroid carcinoma (PTC) is a rare childhood malignancy with increasing incidence and distinct clinicopathological features, including high rate of locoregional metastases and different molecular background compared to adult cases. Traditional treatments (surgery, radioactive iodine) are effective but pose long-term risks, prompting the exploration of targeted therapies. We performed comprehensive genomic profiling on 21 pediatric PTC patients utilising the Illumina TruSight Oncology 500 platform and detected mutations, gene fusions, copy number variations and revealed tumor mutational burden.

  Study EGAS50000001833

• WES and RNA sequencing of mesothelioma patients from CONFIRM clinical trial

  CONFIRM is a placebo controlled, double-blind randomised phase III clinical trial designed to investigate the efficacy of the anti-PD1 inhibitor nivolumab in patients with relapsed mesothelioma. This study applied the whole exome sequencing and transcriptomic sequencing to uncover determinants of efficacy in patients exhibiting the most extreme response outcomes.

  Study EGAS50000001814