7827 results for "canc*"

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• 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 EGAD00001003743

• Genome and transcriptome sequence data from a pleomorphic xanthoastrocytoma patient

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

  Dataset EGAD00001003744

• Highly differentiated, fusion-negative rhabdomyosarcoma.

  Sequencing was performed using OncoPanel v.2 (OPv2), an Agilent SureSelect custom designed bait set consisting of the coding regions of 504 genes, previously linked to human cancer. Sequencing wa sperformed on an Illumina HiSeq 2500. 14 highly differentiated, fusion-negative rhabdomyosarcoma tumor samples, and 8 non-matched normal skeletal muscle samples weer sequenced. BAM files are available for download.

  Dataset EGAD00001003746

• Raw DNA and RNA data from breast cancer organoids, control samples and biopsies

  Whole genome sequencing data for primary tumors, matching control material from blood and their corresponding organoid. Whole transcriptome data for organoids.

  Dataset EGAD00001003751

• Prostate Cancer - RNA-Seq unmapped reads

  Prostate Cancer - RNA-Seq unmapped reads

  Dataset EGAD00001003756

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers: multi-timepoint exome sequencing of a single patient's disease

  This dataset is a time-series of EGFR-mutant NSCLC clinical specimens from an individual patient profiled using tumor-based whole exome sequencing and the data is in BAM format. DNA was extracted from FFPE for primary tumor and frozen tumor tissue samples and matched non-tumor tissue using the Qiagen Allprep DNA/RNA Mini Kit.  The library preparation protocol was based on the Agilent SureSelect Library Prep and Capture System. DNA was resuspended in a low TE buffer and sheared (Duty Cycle 5%; Intensity 175; Cycles/Burst: 200; Time: 300s, Corvaris S2 Utrasonicator).  Bar-coded exome libraries were prepared using the Agilent Sure Select V5 library kit per manfucaturer’s specifications. The libraries were run on the HiSeq2500. Raw paired end reads (100bp) in FastQ format generated by the Illumina pipeline were aligned to the full hg19 genomic assembly obtained from USCS, gencode 14, using bwa version 0.7.12. Picard tools version 1.117 was used to sort, remove duplicate reads and generate QC statistics. Tumor DNA was sequenced to median depth of 303X (range 114.39-383.41) and the matched germline DNA to average depth of 231.65.

  Dataset EGAD00001003769

• Multi-omics Profiling of Asian Breast Cancers

  186 tumor/normal matched samples from whole exome sequecing and 178 samples (168 tumors, 10 normals) from whole transcriptome sequencing

  Dataset EGAD00001003776

• Exome sequencing and RNAseq data

  Whole Exome Sequencing of 9 Colorectal Cancer (CRC) samples performed on Illumina HiSeq4000 consisting of aligned paired reads. RNAseq data sequenced on Illumina NextSeq500 consisting of FASTQ single reads from 3 CRC colon samples. A total of 12 samples from five patients (we matched normal tissue or pbmc and tumors) were sequenced on Illumina NextSeq500.

  Dataset EGAD00001003788

• Computational approach to discriminate human and mouse sequences in patient-derived tumour xenografts

  Whole Exome Sequencing was performed in a dilution series containing known amounts of human and mouse DNA, 3x 100% human 0% mouse, 2x 90/10, 3x 50/50, 2x 25/75 and 3x 0/100. A set of breast cancer clinical samples, matched normal tissue and matched PDTXs (total number = 14) were also analysed. Paired-end 75bp sequences for the dilution series and paired-end 125bp for the clinical samples were obtained on Illumina HiSeq2500; fastq files are provided. A triplicate analysis of the transcriptome using RNA-seq was also performed for the Universal Human RNA Reference and the Universal Mouse RNA Reference samples. Paired-end 150bp fastq files obtained on Illumina HiSeq4000 are provided.

  Dataset EGAD00001003800

• Deciphering the genomic, epigenomic and transcriptomic landscapes of pre-invasive lung cancer lesions to determine prognosis

  Background: Lung carcinoma-in-situ (CIS) lesions are the pre-invasive precursor to lung squamous cell carcinoma. However, only half progress to invasive cancer in three years, while a third spontaneously regress. Whether modern molecular profiling techniques can identify those pre-invasive lesions that will subsequently progress and distinguish them from those that will regress is unknown. Methods: Progressive and regressive CIS lesions were laser-captured and their genome, epigenome and transcriptome interrogated. We analysed 83 progressive lesions, 41 regressive and 33 normal epithelial control samples. DNA methylation and gene expression profiles were further validated using publicly available lung cancer data. Results: Somatic mutation burden was higher in progressive lesions than regressive CIS lesions, across base substitutions, rearrangements, and copy number changes. Driver mutations were present in both progressive and regressive CIS lesions, but were more numerous in progressive cases. Progressive and regressive CIS lesions had distinct epigenomic and transcriptional profiles, with a strong chromosomal instability signature. Gene expression, methylation and copy number profiles can all predict accurately which CIS lesions will progress to lung cancer. Conclusion: Pre-invasive CIS lesions that will subsequently progress to invasive lung cancer can be distinguished from those that will regress using molecular profiling. Progression is associated with a strong chromosomal instability signature. These findings inform the development of novel therapeutic targets.

  Dataset EGAD00001003883

• Congenital mesoblastic nephroma and infantile fibrosarcoma

  The genetic basis of many rare childhood cancers remains unknown. These include a spectrum of infant soft tissue tumors without canonical gene fusions, encompassing congenital mesoblastic nephroma (CMN) of the kidney and infantile fibrosarcoma (IFS). Here, we integrated whole genome and transcriptome sequencing and identified diagnostic markers and novel therapeutic strategies.

  Dataset EGAD00001003884

• Congenital mesoblastic nephroma and infantile fibrosarcoma

  The genetic basis of many rare childhood cancers remains unknown. These include a spectrum of infant soft tissue tumors without canonical gene fusions, encompassing congenital mesoblastic nephroma (CMN) of the kidney and infantile fibrosarcoma (IFS). Here, we integrated whole genome and transcriptome sequencing and identified diagnostic markers and novel therapeutic strategies.

  Dataset EGAD00001003885

• Highly differentiated, fusion-negative rhabdomyosarcoma.

  Sequencing was performed using OncoPanel v.2 (OPv2), an Agilent SureSelect custom designed bait set consisting of the coding regions of 504 genes, previously linked to human cancer. Sequencing wa sperformed on an Illumina HiSeq 2500. 8 highly differentiated, fusion-negative rhabdomyosarcoma tumor samples were sequenced. BAM files are available for download.

  Dataset EGAD00001003887

• Udated data for October 2017 data release 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.

  October 2017 data update (bam/fastq) 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 EGAD00001003906

• Single-cell RNA sequencing on 11,138 single T cells from 12 colon and rectal cancer (CRC) patients

  Deep single-cell RNA sequencing data for 11,138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any academic research institutions complying with the laws and bioethic regulation policies of China will be approved.

  Dataset EGAD00001003910

• Patient-derived organoids from gastrointestinal cancers

  Patient-derived organoids model treatment response of metastatic gastrointestinal cancers (80 targeted exome capture samples and 2 whole-genome sequencing samples)

  Dataset EGAD00001003926

• Exome reads

  Cancer exomes consisting of FASTQ paired-end reads from ovary samples

  Dataset EGAD00001003916

• RNA-seq reads

  Cancer RNA-seq consisting of FASTQ paired-end reads from ovary samples

  Dataset EGAD00001003918

• Homologous recombination deficient breast cancers

  Exome sequencing data from homologous recombination deficient primary breast cancers as assessed by the functional RAD51 based HR test. There are 12 tumour samples, of which 10 also have matching normal.

  Dataset EGAD00001003929

• CancerSEEK ctDNA FASTQ files

  Sequencing data from 1,005 cancer patients and 812 healthy controls. All samples prepared using Safe-SeqS technology and sequenced on an Illumina MiSeq and/or HiSeq instrument. Paired FASTQ files for correspond to read 1 and the index read present (R and I respectively).

  Dataset EGAD00001003931

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq.

  Dataset EGAD00001004180

• Whole genome sequencing of primary and metastatic high risk prostate cancer.

  Pan Prostate Cancer Group Melbourne BAM files. The total of 381 samples consist of 158 primary tumour samples, 46 metastasis samples and 177 whole blood samples. All sequencing was carried out on illumina HiSeq X Ten or HiSeq 2000 systems and were mapped to hg19 using BWA. The resulting BAM files were sorted by Samtools.

  Dataset EGAD00001004182

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004192

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004193

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004201