10161 results for "cancer rna-seq"

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• Cancer Proteomics Mass Spectrometry group

  Dac EGAC00001002236

• OV cancer cell lines DAC

  Dac EGAC00001002307

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002387

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002388

• Cancer Team Data Access Committee

  Dac EGAC00001002449

• GIS - NCCS Pancreatic Cancer DAC

  Dac EGAC00001002565

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002608

• Cancer Team Data Access Committee

  Dac EGAC00001002891

• Pancreatic cancer PDOs/CAFs DAC

  Dac EGAC00001002897

• Pan Cancer Plasma cfRNA DAC

  Dac EGAC00001002956

• DAC for noninvasive lung cancer subtyping

  Dac EGAC00001003474

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002994

• Ovarian cancer cfDNA dataset DAC

  Dac EGAC00001003234

• WGS of PMBCL

  Study EGAS00001006452

• Chromothripsis followed by circular recombination drives oncogene amplification in human cancer

  The mechanisms behind the evolution of complex genomic amplifications in cancer have remained largely unclear. We here identified a type of amplification, termed as “seismic amplification”, that is characterized by multiple rearrangements and discontinuous copy number levels. Seismic amplifications occurred in 9.9% (274/2,756) of cases across 38 cancer types and were associated with massively increased copy numbers and elevated oncogene expression. Reconstruction of the development of seismic amplification revealed a stepwise evolution, starting with a chromothripsis event, followed by formation of circular extrachromosomal DNA that subsequently underwent repetitive rounds of circular recombination. The resulting amplicons persisted as extrachromosomal DNA circles or had reintegrated into the genome in overt tumors. Together, our data indicate that the sequential occurrence of chromothripsis and circular recombination drives oncogene amplification and over-expression in a substantial fraction of human malignancies.

  Study EGAS00001005424

• Application of high-throughput, high-depth, targeted single-nucleus DNA sequencing in pancreatic cancer

  Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimized a highly automated nuclei extraction workflow that achieved fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals novel genomic evolution patterns of PDAC as well.

  Study EGAS00001006024

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination.

  Dataset EGAD00001008696

• National Cancer Institute Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) genome-wide association study (GWAS) of renal cell carcinoma (RCC) was conducted to investigate common genetic variants associated with RCC risk. The GWAS includes 1,453 RCC cases and 3,531 controls of European background from 4 studies (3 cohort, 1 case-control), scanned using the Illumina InfiniumHumanHap 550, 610 and 660W chips. This project was supported by the Intramural Research Program of the National Institutes of Health and NCI. Data from this GWAS were pooled with those from another GWAS of RCC (2,639 cases and 5,392 controls) conducted in Europe by the International Agency for Research on Cancer and the Centre National de Gènotypage. Findings from this collaboration are described in an upcoming report (Purdue et al. Nature Genetics 2011;43(1):60-65; PMID: 21131975). Only data from the NCI scan are included in this dbGaP submission.

  Study phs000351

• A Pilot Study of Neoadjuvant Nivolumab, Ipilimumab and Intralesional Oncolytic Virotherapy for HER2-Negative Breast Cancer

  This study was a single arm phase 1 trial that assessed the regimen safety and feasibility as well as tumor response in patients with localized HER2-negative breast cancer treated with talimogene laherparepvec (T-VEC) in combination with nivolumab and ipilimumab. The primary objective was to evaluate the safety and adverse event profile of this treatment combination. Six patients were enrolled, four having relapses after prior neoadjuvant chemotherapy, and two who were previously untreated. One patient had a pathological complete response, three patients had pathological partial responses, one showed no significant response, and one had disease progression. Biopsies demonstrated increased immune cell infiltration in samples from patients who responded to therapy. In this study, the checkpoint blockade immunotherapy combined with T-VEC provided responses in patients with advanced or relapsed HER2-negative breast cancer at the expense of long-term toxicities.

  Study phs003316

• Integrative genomic analyses reveal androgen-driven somatic alteration landscape in early-onset prostate cancer

  Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in eleven tumors diagnosed at young age, and pursued comparative assessments with seven elderly-onset PCA genomes. Remarkable age-related differences in structural rearrangement (SR) formation became evident, suggesting distinct disease pathomechanisms. Whereas EO-PCAs harbored a prevalence of balanced SRs, with a specific abundance of androgen-regulated ETS gene fusions including TMPRSS2:ERG, elderly-onset PCAs displayed primarily non-androgen-associated SRs. Data from a validation cohort of >10,000 patients showed age-dependent androgen receptor levels and a prevalence of SRs affecting androgen-regulated genes, further substantiating the activity of a characteristic "androgen-type" pathomechanism in EO-PCA.

  Study EGAS00001000400

• Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer

  A subset of Cancer-Associated Fibroblasts (CAF-S1) mediates immunosuppression in breast cancers (BC), but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 18000 single CAF-S1 fibroblasts from BC. We validate the 5 most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extra-cellular matrix proteins and TGF signaling respectively, are indicative of primary resistance to immunotherapies. Cluster 0 up-regulates PD-1 and CTLA-4 protein levels in regulatory T lymphocytes (Tregs), which in turn increases CAF-S1 cluster 3 cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance.

  Study EGAS00001004030

• Whole-genome sequencing of BRCA-mutant breast cancer patient samples from tumour, germline tissue and plasma

  The use of circulating tumor DNA (ctDNA) to profile mutational signatures presents a non-invasive opportunity for understanding cancer mutational processes. In this study we developed MisMatchFinder, a liquid biopsy approach for mutational signature detection using low- coverage whole-genome sequencing of ctDNA. Through analysis of plasma samples across multiple different cancers, we demonstrated that MisMatchFinder accurately infers single-base and doublet-base substitutions as well as indels to enhance detection of ctDNA and clinically relevant mutational signatures. This study contains fastq files from whole-genome sequencing of temporally matched tumour (fresh frozen biopsies), blood germline and plasma samples collected from a BRCA1-mutant breast cancer patient to directly compare mutation signature analysis using gold-standard tumour-germline paired variant calling with our novel ctDNA-based method (MisMatchFinder).

  Study EGAS50000000569

• Hereditary Cancer Diagnostics with I2HCP gene panel

  This dataset contains targetted DNA sequencing data generated in the context of genetic diagnostics of hereditary cancer. Target enrichment was performed with the I2HCP, a custom hereditary cancer gene panel based in Agilent SureSelect and developed by the Germans Trias i Pujol Research Institute (IGTP, Badalona, Catalonia, Spain) and the Catalan Institute of Oncology (ICO, L'Hospitalet de Llobregat, Catalonia, Spain). After the enrichment, 108 samples were sequenced in Illumina HiSeq machines and 130 in MiSeq machines. Some of the samples were sequenced on both platforms. The dataset also includes MLPA validation data for all identified copy-number alterations, annotated with exon resolution and information about negative MLPA results. All this data was generated in the context of routine diagnostics and compiled together with MPLA validation data for a genetic diagnostics oriented benchmark of germline CNV calling tools.

  Study EGAS00001004316

• Methylation-Based Immune Deconvolution in Prostate Cancer Patients Before and After Radical Prostatectomy

  To explore whether surgical treatment for prostate cancer leads to long-term immune changes, we conducted a pilot study of n=11 prostate cancer patients treated with radical prostatectomy. We also included n=8 patients managed with active surveillance as a comparison group. We examined intra-individual changes in circulating immune cell subsets using serial blood samples collected pre- and approximately 6-months post-prostatectomy, and from matched time points for the patients managed on active surveillance. Immune cell subsets were deconvoluted using genome-wide methylation data. We observed no meaningful changes in circulating immune cell subsets in either patient group, suggesting that any surgery-induced immune changes to the circulating immune profile may not be long-lasting. The genome-wide methylation data from the two time points will be made available through dbGaP.

  Study phs003660

• HGSOC organoid sequencing study

  Study EGAS00001007189

• Soft tissue sarcoma sequencing data

  Study EGAS00001006356

• Genomic characterization of retinoblastoma

  Study EGAS00001005248

• early-Duodenal Cancer sequencing study

  ...

  Study EGAS00001006357

• Small cell cancer NDS Oxford DAC

  Dac EGAC00001003350

• Cancer Team Data Access Committee

  Dac EGAC00001002762

• Small cell cancer NDS Oxford DAC

  Dac EGAC00001003343

• Asian lung cancer genome data

  Dac EGAC00001000248

• MCCB Breast Cancer Data Access Committee

  Dac EGAC00001000854

• Rectal Cancer Samples Data Access Committee

  Dac EGAC00001001034

• University of Florida Brain Cancer DAC

  Dac EGAC00001001035

• DAC for Familial Breast Cancer study EGAS00001003305

  Dac EGAC00001001087

• OSBREAC (Oslo Breast Cancer Research Consortium)

  Dac EGAC00001001186

• Ewha-Samsumg Lung cancer collaboration DAC

  Dac EGAC00001001237

• Ewha-Samsung Lung cancer collaboration DAC

  Dac EGAC00001001283

• UCL Cancer Institute Data Access Committee

  Dac EGAC00001001360

• Yale Cancer Center Data Access Commitee

  Dac EGAC00001001437

• Lung cancer TRM Data Access Commitee

  Dac EGAC00001001759

• Gene expression and Cancer

  Dac EGAC00001001772

• 4C Endometrial Cancer Data Access Committee

  Dac EGAC00001001956

• University of Calgary Charbonneau Cancer Institute

  Dac EGAC00001002170

• The MITIMM Cancer Data Access Committee

  Dac EGAC00001002268

• EPICC: Evolutionary Predictions in Colorectal Cancer

  Dac EGAC00001002299

• Cancer Sequencing Data Access Committee

  Dac EGAC00001002457

• Cancer Core Europe Data Access Commitee

  Dac EGAC00001002460

• Laboratory of Applied Cancer Genomics team

  Dac EGAC00001002508