5707 results for "canc*"

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• 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

• ParityImmune

  Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC)

  Dataset EGAD00010001412

• 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

• RNA-SEQ data from 47 CAF (Cancer Associated Fibroblast) samples sorted from fresh breast cancer

  Dataset EGAD00001003808

• Exome reads

  This dataset contains WES data (.bam files) and associated phenotype information from 10 patients included in our microbiome study who went on to anti PD-1 immunotherapy for the treatment of metastatic melanoma at the University of Texas MD Anderson Cancer Center. Both tumor and matching germ line normal were sequenced on each patient using Illumina HiSeq 2500. The average coverage was 283X in tumors and 135X in germline (tumor+germline overall:209, Range: 0-1552).

  Dataset EGAD00001003797

• 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

• SOFT study - sequencing premenopausal breast cancer (2017-11-22)

  Our project will examine the role of PIK3CA mutations and their sensitivity to endocrine therapies and its role, with the addition of complete ovarian suppression. We plan to test our hypotheses using tumour samples collected from patients enrolled in the SOFT/IBCSG24-02 clinical study (Suppression of Ovarian Function Trial - (NCT00066690). SOFT is a phase III trial that randomised 3066 premenopausal women to evaluate if adding ovarian suppression to adjuvant endocrine therapy will improve clinical outcomes. This dataset contains all the data available for this study on 2017-11-22.

  Dataset EGAD00001003811

• BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle

  BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle (2 paired tumor-normal samples and 11 tumor-only samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from 13 patients with chordoid glioma of the third ventricle using the QIAamp DNA FFPE Tissue Kit (Qiagen). Genomic DNA was also extracted from leukocytes in a peripheral blood sample from one of the patients and a non-neoplastic gastric biopsy specimen from one of the patients. Capture-based next-generation DNA sequencing was performed at the University of California, San Francisco Clinical Cancer Genomics Laboratory, using an assay that targets all coding exons of approximately 500 cancer-related genes, select introns of 47 genes, and TERT promoter with a total sequencing footprint of 2.8 Mb (UCSF500 Cancer Panel). Sequencing libraries were prepared from genomic DNA, and target enrichment was performed by hybrid capture using a custom oligonucleotide library (Nimblegen SeqCap EZ Choice). Captured libraries were sequenced as paired-end 100 bp reads on an Illumina HiSeq 2500 instrument. Duplicate sequencing reads were removed computationally to allow for accurate allele frequency determination and copy number calling.

  Dataset EGAD00001003818

• RNA sequencing of multiple tumor biopsies and patient-derived spheroids from five colorectal cancer patients (BAM files)

  Whole transcriptome, strand-specific RNA-seq libraries were prepared from total RNA purified using RNeasy mini kit (Qiagen) using Ribo-Zero technology (Epicentre, an Illumina company) for depletion of rRNA followed by library preparation using ScriptSeq ScriptSeq RNA-Seq Library preparation Kit from Illumina. The paired raw sequence reads were processed using TopHat2 and mapped to the humane reference genome HG19.

  Dataset EGAD00001003820

• Whole exome Sequencing (WES) of multiple tumor biopsies, patient-derived spheroids and leukocyte DNA from colorectal cancer patients (BAM files)

  WES was performed using the KAPA-Hyper prep kit from Illumina (Roche, Basel, Switzerland) for library construction, followed by exome capture using Niblegen SeqCap EZ Human Exome Library v3.0 (Roche). Reads were mapped using BWA MEM against the humane reference genome HG19.

  Dataset EGAD00001003821

• RRBS sequencing data of ovarian cancer, breast cancer, control tissues, and white blood cell DNA.

  The dataset comprises 8 breast cancer, 11 ovarian cancer, 1 benign tumour, 18 normal tissue, 2 endometrium, and 23 white blood cell samples. Genome wide methylation analysis was performed by Reduced Representation Bisulfite Sequencing (RRBS) on Illumina HiSeq 2500. Data is provided as FASTQ files

  Dataset EGAD00001003822

• Somatic mutation analysis based on Whole exome Sequencing (WES) of multiple tumor biopsies, patient-derived spheroids and leukocyte DNA from colorectal cancer patients (vcf files)

  Somatic mutations were called using whole exome Sequencing (WES) data from colorectal cancer samples (dataset EGAD00001003821) using MuTect2, with matched constitutional WES-data obtained from leukocytes samples as reference.

  Dataset EGAD00001003823

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  Whole genome sequencing data on 10 human cancer cell lines

  Dataset EGAD00001003824

• Exome sequencing data from tumor progression cohort

  This dataset, named Stockholm tumor progression cohort, contains exome-sequencing samples of matched primary and metastasis samples from 20 metastatic breast cancer patients. All patients have one or more sequenced normal samples as well. The total number of samples is 125. The dataset has been used, apart from other studies, to explore tumor evolution patterns in metastatic breast cancer at Karolinska Institute Stockholm.

  Dataset EGAD00001003837

• 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