5731 results for "canc*"

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• DESIGN-NKI RNA-seq

  RNA-Seq data of 36 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute, Amsterdam. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005715

• DESIGN-NKI low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005718

• NKI-MET HNSCC RNA-Seq

  RNA-Seq data of 8 HNSCC specimens from patients diagnosed with metastatic disease at The Netherlands Cancer Institute, Amsterdam. Primary HNSCC biopsy samples obtained prior to treatment were used for polyA mRNA sequencing.

  Dataset EGAD00001005720

• ART-NKI II HNSCC RNA-Seq

  RNA-Seq data of 25 HNSCC specimens from patients treated at The Netherlands Cancer Institute, Amsterdam and enrolled in the ARTFORCE trial. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005721

• DESIGN II HNSCC RNA-Seq

  RNA-Seq data of 28 HPV-negative HNSCC specimens from patients treated at the Netherlands Cancer Institute (Amsterdam), VU Medical Centre (Amsterdam) or MAASTRO Clinic (Maastricht) in The Netherlands. HNSCC biopsy samples were obtained prior to treatment (chemo-radiotherapy) for the prospective study within the DESIGN project and used for polyA mRNA sequencing.

  Dataset EGAD00001005722

• Illumina short-reads and 10X Genomics linked-reads sequencing data for MCF7 and a primary breast tumor sample

  This dataset contains whole genome sequencing data from Illumina short-reads sequencing (2X150bp) and 10X Genomics linked-reads sequencing. Both the sequencing technologies were used to sequence MCF7 cell line and a primary breast triple-negative cancer sample. The fastq of paired-end reads for both the samples sequenced with both the technologies is available.

  Dataset EGAD00001005724

• WES of blood and patient-matched cecum tumor tissue samples, Panel NGS of patient-matched cfDNA

  WES using IDT xGen Research Exome on Illumina NovaSeq 2x150bp: Normal sample (buffy coat), cecum tumor biopsy at diagnosis, ileocecal valve region tumor sample at week 19, pericolonic metastasis at week 19, lymph node metastasis at week 19, peritoneal metastasis at week 19. Week 19 samples from hemicolectomy. Deep coverage cfDNA NGS using PanCeq pan-cancer panel on NextSeq 2x150bp: week 2 and week 10.

  Dataset EGAD00001005737

• Whole exome sequencing of advanced gastric cancer

  To define the cellular characteristics of malignant ascites of advanced gastric cancer patients and search for therapeutic strategies, we obtained 5 malignant ascites and 1 cerebrospinal fluid from five patients with gastric cancer. We analyzed single-cell RNA-seq data of 180 cells from 4 malignant ascites and 1 cerebrospinal fluid metastasis using Fluidigm® C1™ System. Whole exome sequencing data was also generated from blood or tumor tissue.

  Dataset EGAD00001005740

• Whole-genome sequencing data for inflammatory breast cancer patients

  This study reports the whole-genome sequencing data for 20 inflammatory breast cancer patients, each of whom has one normal blood sample and one breast tumor sample. Overall, there are 40 files included in this study, in the format of BAM.

  Dataset EGAD00001005749

• Dataset for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancew

  The dataset for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer includes 169 bam files from targeted deep sequencing on the Illumina HiSeq2500. The samples analyzed include genomic DNA from white blood cells and cell-free DNA from longitudinal blood collections of patients with gastric cancer.

  Dataset EGAD00001005750

• Colon Cancer Organoid Cultures and Tumors RNASeq Data

  Four micrograms of total RNA was used for cDNA library construction using the KAPA Stranded mRNA-Seq Kit (KR0960-v3.15), following manufacturer's protocol. The adaptor-ligated libraries were enriched by 6 cycles of polymerase chain reaction (PCR). Libraries were sequenced using the Novaseq 6000 with paired end 151bp reads.

  Dataset EGAD00001005753

• Colon Cancer Organoid Cultures and Tumors Whole Exome Sequencing Data

  Five hundred fifty nanograms of genomic DNA were input for library preparation after fragmentation by Covaris S2, following the KAPA Hyper Prep Kit (KR0961-V1.14) protocols, with selection for a library size range of 250-450 bp. Three hundred nanograms per library DNA each from 12 samples were normalized and combined into a single pool for exome capture using the xGen Lockdown Probes and Reagents based on their standard protocols

  Dataset EGAD00001005754

• Genome and transcriptome sequence data from a pancreatic cancer patient

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

  Dataset EGAD00001005841

• Colon Cancer Organoid Cultures and Tumors Whole Genome Sequencing Data

  Five hundred nanograms of genomic DNA was fragmented by Covaris S2, the fragmented DNAs were performed end-repair, A-tailing at the 3 prime end, adaptors ligation with an IDT dual-indexed UMI adaptor system at the terminal ends. The adapter ligated library with size range 300-750bp were selected by dual-SPRI method. Twenty percent of the size selected PCR-free libraries were enriched by 5 PCR cycles prior to library size assessment by Bioanalyzer Fragment Analyzer. The PCR-free libraries were quantified by qPCR.The PCR-free libraries were denatured and diluted to optimal concentration. Illumina NovaSeq 6000 was used for Pair-End 151bp sequencing.

  Dataset EGAD00001005759

• Hyperpolarized 13C MRI in breast cancer

  Transcriptomics for samples obtained from six patients (MBR01, MBR03, MBR05, MBR07, MBR10, MBR11)

  Dataset EGAD00001005760

• cfDNA analysis reveals relation of POLR1D amplification to bevacizumab resistance in colorectal cancer patients

  Bevacizumab is an approved anti-angiogenic drug for patients with metastasized colorectal cancer (mCRC) targeting VEGF. The survival benefit of anti-VEGF therapy in mCRC patients is limited to a few months and acquired resistance mechanisms are greatly unknown. Using plasma DNA, we studied the evolution of tumor genomes in a cohort of patients with mCRC (n=150) and observed a recurrent focal amplification (8.7% of cases) on chromosome 13q12.2. Analysis of TCGA data (n=619) suggested an association with later stages, which we confirmed by longitudinal plasma analyses. We defined the minimally amplified region and studied the mechanistic consequences of copy number gain of the involved genes. The amplification of one gene, POLR1D, impacted cell proliferation, resulting in upregulation of VEGFA, an important regulator of angiogenesis which has been implicated in the resistance to bevacizumab. In several patients, we observed the emergence of this 13q12.2 amplicon under bevacizumab treatment, which was invariably associated with evolution of therapy resistance. Hence, we describe a novel resistance mechanism against a widely applied treatment in mCRC patients which will impact clinical management .

  Dataset EGAD00001005761

• Single cell PDAC samples

  h5 files from 15 single cell PDAC samples described in "Transcription phenotypes of pancreatic cancer are driven by genomic events events during tumour evolution"

  Dataset EGAD00010001811

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

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

  Dataset EGAD00001005763

• Exome and Transcriptome for gastric cancer gene-drug analysis

  Newly generated 52 gastric tumor specimens were subjected for targeted-exome and/or whole-transcriptome sequencing

  Dataset EGAD00001005766

• Multi-region sequencing of a RET fusion positive cancer patient

  Deep WGS sequencing (160x) of 2 different sites of disease of a patient with a RET fusion positive cancer. Amplicon sequencing of 19 other sites of the same patients for the RET fusion.

  Dataset EGAD00001005776

• Sequencing files for "The Evolutionary Origins of Recurrent Pancreatic Cancer."

  Files from DNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues. Sequencing files include those derived from whole exome sequencing as well as MSK-IMPACT sequencing.

  Dataset EGAD00001005779

• sWGS of non-cancer controls

  Paired end shallow whole genome sequencing (sWGS) data of cell-free DNA from plasma from self-reporting healthy individuals (MonRec Cohort)

  Dataset EGAD00001005805

• Exploiting evolutionary steering in cancer therapy

  This dataset contains 9 bam files of exome sequencing for an experiment of evolved resistance. Here a barcoded cell line (HCC827 - POT) has been treated under high concentrations of gefitinib (GEF) and trametinib (TRM) until resistance has evolved, as well as under control conditions (DMSO). The dataset contains exome sequencing of confluent cells for three replicates for each anti-cancer drug as well as two replicates of growth under DMSO conditions. The original barcoded cell line (POT) was also exome sequenced and is included in the cohort. Sequencing was performed on the Illumina NovaSeq platform.

  Dataset EGAD00001005782

• The identification of genetic vulnerabilities in head and neck cancers for the development of novel therapies (2020-01-15)

  CRISPR/Cas9 lethality screens in a set of Asian head and neck cancer cell lines to identify novel targets. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005784

• Somatic mutation and clonal evolution in premalignant lung disease - WGS (2020-01-15)

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005786