5735 results for "canc*"

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• 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

• Somatic mutation and clonal evolution normal breast tissue TGS (2020-01-15)

  Cancer is a genetic disease caused by an accumulation 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 breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005787

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas_LCM (2020-01-15)

  Samples prepared by LCM - 5 cases for pilot study. Bulk DNA not available. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005789

• Targeted sequencing data of breast tumors with germline BRCA1/2 mutations

  This dataset contains targeted sequencing of breast tumors with germline BRCA1/2 mutations (n = 30) and those without. Breast cancer related genes (n = 115) have been captured and sequenced.

  Dataset EGAD00001005802

• Anaplastic Thyroid Cancer aligned whole exome sequence data

  Whole exome sequence data in fastq format was aligned to the GRCH38 reference genome. Aligned sequence was preprocessed with GATK for Indel Realignment and Base Quality Score Recalibration. Duplicates were marked with Picard Mark Duplicates. Aligned sequence is in bam format. Details of the alignment can be found in he bam header. Tumour samples were classified as Anaplastic Thyroid, Poorly-differentiated or well-differentiated cancers.

  Dataset EGAD00001005791

• NanoString gene expression of PBMC from bladder cancer and RCC patients

  This dataset contains NanoString gene expression of PBMC from patients from IMvigor210, IMvigor211 and IMmotion150 cohorts

  Dataset EGAD00001005976

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  The dataset for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer includes 106 bam files from whole exome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include matched tumor/normal samples from non-small cell lung cancer patients treated with immunotherapy.

  Dataset EGAD00001005796

• RNA-seq from PDAC samples

  Bam and fastq files from RNA-seq of PDAC samples described in Transcription phenotypes of pancreatic cancer are driven by genomic events events during tumour evolution

  Dataset EGAD00001005799

• RNA-seq of SMARCA2/4 knock-down prostate cancer cell lines

  RNA-seq of SMARCA2/4 knock-down prostate cancer cell lines (LNCaP and 22Rv1, 15 samples altogether). Dataset contains BAM files from RNA-seq performed using Illumina HiSeq 2500.

  Dataset EGAD00001005800

• Spatial whole exome sequencing of metastatic melanoma

  We performed whole exome sequencing of 8 samples derived from a patient with metastatic melanoma. These represent six different regions of a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor, one pre-treatment biopsy that was treatment naive and one post-PD-1 inhibitor treated lesion. Exome sequencing data was generated using methods as previously described, including library preparation using the Agilent SureSelect XT Target Enrichment protocol (#5190-8646) prior to sequencing on an Illumina HiSeq 2000/2500 v3 system using 76bp paired-end reads. Raw sequencing data was then processed using Saturn V, the next generation sequencing data processing and analysis pipeline developed by the Department of Genomic Medicine at the UT MD Anderson Cancer Center.

  Dataset EGAD00001005819

• Spatial targeted gene sequencing of metastatic melanoma

  We performed deep targeted DNA sequencing for a panel of 265 cancer-related genes. This included subsampling 35 different regions of a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. Samples with cancer cell purity greater than 80% based on pathologic assessment were used for cancer gene panel DNA sequencing. Mean sequencing coverage was 861x and paired-end reads in FASTQ format were generated by the Illumina pipeline and aligned to the reference human genome hg19 build using the Burrows-Wheeler Alignment Tool (BWA, v0.7.5) with default settings. Aligned reads were further processed using GATK with best practices for removing duplicates, indel removal and recalibration.

  Dataset EGAD00001005821

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

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

  Dataset EGAD00001005823

• Genome and transcriptome sequence data from an uveal melanoma patient

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

  Dataset EGAD00001005824

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

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

  Dataset EGAD00001005825

• Genome and transcriptome sequence data from a colon cancer patient

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

  Dataset EGAD00001005826

• Genome and transcriptome sequence data from a primary unknown- upper GI or pulmonary patient

  Genome and transcriptome sequence data from a primary unknown- upper GI or pulmonary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005827

• Genome and transcriptome sequence data from a metastatic choroidal melanoma patient

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

  Dataset EGAD00001005828

• 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 EGAD00001005829

• 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 EGAD00001005830

• Genome and transcriptome sequence data from a poorly differentiated adenocarcinoma more consistent with metastatic melanoma patient

  Genome and transcriptome sequence data from a poorly differentiated adenocarcinoma more consistent with metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005831

• 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 EGAD00001005832

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the esophagus patient

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

  Dataset EGAD00001005835