5731 results for "canc*"

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• Whole Exome sequencing of Gingivo-buccal Cancer - ICGC India Project Batch04

  This dataset pertains to whole exome sequencing of paired DNA samples of Gingivo-buccal oral cancer patient.DNA was isolated from the tumor and blood tissues of 47 patients (94 samples).We have performed Nextera exome capture and sequenced exome libraries in Illumina HiSeq platform.We have uploaded BWA-ALN aligned BAM files.

  Dataset EGAD00001003987

• 20180221_EGA_OESO

  Illumina platform sequencing of whole genome libraries prepared from normal, Barrett's oesophagus and oesophageal cancer samples from 44 donors

  Dataset EGAD00001003996

• Single-cell RNA sequencing on 12346 single T cells from 14 non-small cell lung cancer (NSCLC) patients

  Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naïve NSCLC patients

  Dataset EGAD00001003999

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• Lung cancer organoids

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004013

• Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Dataset EGAD00001004018

• 2014 sequenced Korean WES-Lung Cancer sample 36 pair

  This data is belong to WES-Lung Cancer patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 36 paired tumor/normal samples from Samsung Hospital. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001004027

• HBV-associated hepatocellular carcinoma

  Fastq files of whole-genome bisulfite sequence of non-cancerous tissue of HBV-associated hepatocellular carcinoma

  Dataset EGAD00001004032

• Molecular diagnosis of albinism (2018-03-14)

  Albinism is genetically heterogeneous rare genetic condition affecting 1:17000 in the Western world (but more frequent in Africa) whose main feature is a profound visual impairment, characterised by foveal hypoplasia, abnormal chiasmatic connections, nystagmus and photofobia. All these features result in severly altered visual acuity (<0,1), absent depth perception and poor night vision. People with albinism are primarily visually handicapped. In addition, for some types of albinism, the visual phenotype can be presented with partial or total hypopigmentation, hence resulting in a secondary phenotype which can lead to skin cancer if skin is not adequately protected. Recently a new syndrome has been described, FHONDA, with the same visual abnormalities of albinism but without pigment alteration. The traditional classification differentiates Oculoculatenous albinism (OCA), where hypopigmentation involves hair, skin and eyes versus Ocular Albinism (OA), where hypopigmentation only affects the eyes. These are non-sydrimic types of albinism. Some syndromic forms (Hermansky-Pudlak=HPS, Chediak-Higashi=CHS) affect cells beyond pigment cells, present in the lungs, immune system, platelets and intestines, resulting in more severe phenotypes that can be fatal. Mutations in at least 19 genes are assocaited with the corresponding types of albinism. Most hospitals will only diagnose the most frequent cases using traditional Sanger, MLPA approaches. Some will use CGH arrays. We aim to diagnose all cases of albinism through the Albinochip proposal, which combines a Sequenom first step of known mutations combined with subsequent NGS approaches. In some cases we fail to find a second mutation, these are good candidates for further full exome analyses. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004039

• CLL targeted exome sequencing (2018-03-14)

  Aim to characterise cancer gene landscape in CLL, particularly in cases with mutated POT1 gene. Treatment-naive CLL cases will be interrogated by targeted exome sequencing using a cancer gene panel. . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004037

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• Exome sequencing files for "A single mutant clone populates the pancreatic ductal system to generate coexisting neoplastic lesions"

  Files from whole exome sequencing of eight tumors from eight pancreatic cancer patients along with matched PanIN precursor lesion(s) and a matched normal tissue.

  Dataset EGAD00001004044

• Reference Epigenomes and Regulatory Landscape of CLL

  Analysis of the reference epigenomes and regulatory landscape of CLL as a whole and its major clinico-biological subtypes (with mutated and unmutated IGHV) in the light of the normal B-cell differentiation. We have extensively characterized the reference epigenomes of seven primary chronic lymphocytic leukemia samples (CLLs) with mutated (n=5) and unmutated IGHV (n=2) as well as several mature B-cell subpopulations (naive B cells from blood and tonsil, germinal center B cells, memory B cells and plasma cells from tonsil) using genome-wide maps of six histone marks (H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K9me3 and H3K27me3), DNA accessibility (ATAC-seq), DNA methylation (whole-genome bisulfite sequencing) and gene expression (RNA-seq). Furthermore, we have mapped the regulatory chromatin landscape of 100 additional CLL cases using chIP-seq of H3K27ac and ATAC-seq and linked these data to additional layers of information (whole-genome and/or whole-exome sequencing (WGS/WES), RNA-seq and DNA methylation microarrays) studied in the context of the International Cancer Genome Consortium (ICGC).

  Dataset EGAD00001004046

• Genomic analysis of Japanese gastric cancer

  fastq of 345 Japanese gastric cancer

  Dataset EGAD00001004051

• nanostring analysis

  mRNA expression profile of kidney cancer

  Dataset EGAD00010001535

• CNVs analysis

  kidney cancer tissue sample

  Dataset EGAD00010001536

• Single-cell transcriptome sequencing of regulatory and conventional T cells in breast cancer patients and healthy individuals.

  Identification of tumor-specific effects on gene expression profile of regulatory T cells and conventional T cells in humans, investigation of the clonal origin of regulatory T cells and impact analysis of tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral regulatory T cell repertoire in humans.

  Dataset EGAD00001004069

• Low-coverage Whole Genome Sequencing, Colorectal advanced adenomas, NKI-AvL TGO COCOS series

  For this tissue dataset, we applied low-pass whole genome sequencing to 96 advanced adenomas. Advanced adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Dataset EGAD00001004078

• Mutational consequences of precancerous liver disease

  Clonally expanded liver adult stem cell clones of healthy liver and cirrhotic liver (due to alcohol abuse, NASH and PSC), as well as biopsies of liver cancers were subjected to whole genome sequencing to determine the mutational impact of precancerous liver disease

  Dataset EGAD00001004105

• Cancer gene panel (T200.1) sequencing analysis of adult type ovarian granulosa cell tumors (Validation cohort from Hillman, et al)

  Cancer gene panel (T200.1) sequencing data from tumor/normal pairs for adult type ovarian granulosa cell tumor sequencing project. This data set contains 55 tumor panel sequencing data and 44 matched normal panel sequencing data generated using the MD Anderson Cancer Center T200.1 cancer gene hybrid capture platform, with sequencing performed on an Illumina HiSeq 2000. This dataset contains BAM files generated by aligning paired-end reads to the hg19 reference genome.

  Dataset EGAD00001004091

• Chip-exo and Chip-nexus for five TFs in three colorectal cancer cell lines

  Chip-exo and Chip-nexus for FOXA1, HNF4A, KLF5, MYC, and TCF7L2 in colorectal cancer cell lines LoVo, GP5D, COLO320DM

  Dataset EGAD00001004099

• Spatial Maps of Prostate Cancer Transcriptomes

  A total of 14 samples that has been analyzed with the Spatial Transcriptomics method. H&E stain can be sent if requested.

  Dataset EGAD00001004121

• The spatio-temporal evolution of lymph node spread in early breast cancer

  Set of multi-region sequenced breast cancer primary samples, lymph nodes and ctDNA. We collected samples from 11 breast cancer patients with lymph node involvement but no sign of distant metastasis. We performed a mix of whole-exome sequencing, targeted capture sequencing, and whole-genome sequencing of primary tumour samples and lymph nodes, as well as targeted capture sequencing of circulating tumour DNA.

  Dataset EGAD00001004122

• Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.

  CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene independent manner. In contrast, amplifications caused by whole chromosomal duplications have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects. Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

  Dataset EGAD00001004124