15028 results for "cancer studies using rna-seq"

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• Comprehensive molecular profiling for breast cancer patients and high-risk individuals.

  Although germ-line mutations in BRCA1 and BRCA2 gene are responsible for familial breast and ovarian cancer, the detailed mechanism of tumorigenesis is yet unknown. Here, we performed next-generation sequencing to determine the genomic profiles of familial breast cancer tumorigenesis. Target-capture sequencing of fresh-frozen or formalin-fixed-paraffin-embedded (FFPE) samples of breast cancer or normal breast tissue were performed.

  Study JGAS000368

• The landscape of somatic mutations in epigenetic regulators across 1000 pediatric cancer genomes

  To define the frequency and pattern of somatic mutations in epigenetic regulators in pediatric cancer, we sequenced 633 genes, encoding the majority of proteins involved in patterning the epigenome, in 1000 pediatric tumors spanning 21 different cancer subtypes. This analysis establishes an epigenetic landscape of pediatric cancer, which expands the knowledge for potential therapeutic targets and for developing personalized therapy.

  Study EGAS00001000449

• TOTHER3 dataset

  This dataset contains the FASTQ and BAM files for TOTHER3 study. Targeted DNA-Seq experiment were realized with 49 samples. Since this data was obtained with a panel of genes protected by Intellectual Property (IP), these files only contain information to validate the results published and, in consequence, sensible data had to be specifically removed.

  Dataset EGAD50000000562

• Bulk 3' mRNA-Sequencing of human ASC-derived kidney tubuloids

  Bulk 3' mRNA-Seq raw files (FASTQ) from human kidney tubuloids derived from 4 separate donors in collagen-based dome culture and suspension culture. Samples were collected for sequencing on day 7 of passage 3, 4, and 5. Total = 24 samples.

  Dataset EGAD50000002335

• McGill EMC Community projects Release 7 for cell line "SaOS-2"

  Complete reference epigenome (as defined by IHEC) of a SaOS-2 cell line with osteosarcoma.

  Dataset EGAD00001007678

• Mixture of 2 (closer mtDNA)

  Mixture of 2 unrelated individuals (of close mtDNA haplogroup) sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008727

• CBD-RAW-SC-ADT: 10X Single-Cell Features Barcode (CITE-seq)

  Raw Illumina sequencing data and CellRanger BAM output files. For further information regarding this dataset, please contact Stephen Sansom at contact@combat.ox.ac.uk.

  Dataset EGAD00001007962

• Multiple Myeloma ChipSeq data on six histone modifications

  The data contained in this dataset is ChipSeq BAM files aligned to reference genome hg38. The ChipSeq was based on a combination of six histone modifications as follows: H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K27Ac and H3K36me3. The samples are patient-derived xenografts generated by passaging primary patient CD138+ selected cells through the SCID-rab myeloma mouse model.

  Dataset EGAD00001008353

• Tam-seq of tumor samples for HGSOC copy-number signatures study

  This dataset contains targeted amplicon sequencing of DNA extracted from 300 samples of 142 patients (158 methanol-fixed relapse biopsies and 142 FFPE archival diagnostic tissues). Samples were sequenced on Illumina HiSeq 2500 and were aligned to human genome assembly GRCh37 (hg19)to produce 600 bam files (2 technical replicates per sample).

  Dataset EGAD00001004173

• EGAD00010000387

  Cambridge control samples using a 1.2M genotyping chip from Illumina

  Dataset EGAD00010000387

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• Whole-genome cfDNA TAPS sequencing data from 91 people with various types of cancer and from non-cancer controls

  TAPS data in the form of BAM files from 214 samples: plasma (at 80x) and matched germline (at 30x) pairs from 61 cancer and 30 non-cancer subjects, fresh-frozen matched tumour biopsies (at 80x) from 16 subjects, as well as several follow-up plasma samples (at 80x) from 10 subjects with colorectal cancer.

  Dataset EGAD50000000996

• Metastatic_Breast_Cancer_Whole_Genome

  We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000902

• Breast_Cancer_FRT_RNA_seq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000420

• Triple_Negative_Breast_Cancer_RNA_Sequencing

  We propose to definitively characterise the somatic genetics of triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000377

• The Cancer Dependency Map (DepMap)

  The Cancer Dependency Map (DepMap) aims to accelerate precision cancer medicine by creating a comprehensive map of tumor vulnerabilities. The DepMap project genomically profiles a wide range of cancer models and characterizes them for their sensitivity to genetic and compound perturbations. The data is computationally analyzed to create a systematic overview of the genetic dependencies and compound sensitivities of cancer types and the predictive biomarkers that point to patient populations most likely to benefit from targeting of these vulnerabilities. The DepMap public portal has become a comprehensive resource to identify cancer vulnerabilities by providing datasets at scale, cutting-edge computational tools, and sophisticated visualization tools that together have accelerated the discovery of novel targets and biomarkers. Please visit Depmap.org to access the public portal.

  Study phs003444

• Genetic Alterations in Benign Breast Biopsies of Subsequent Breast Cancer Patients

  Fibrocystic changes are associated with an increased risk of breast cancer (approximately 1.5-2 times that of the general population). Although the relative risk seems low, because of the high frequency of such changes, the absolute risk is significant. Genetic alterations have been found in fibrocystic changes with or without epithelial changes, suggesting that critical oncogenic events are occurring at an early stage. We investigated a unique collective of 17 breast cancer patients who, prior to the diagnosis of invasive breast cancer, underwent open surgical biopsy showing fibrocystic changes of the breast. Massive parallel sequencing targeting genes frequently mutated in breast cancer was performed on the fibrocystic breast tissue as well as the ensuing cancer tissue.

  Study EGAS00001003563

• The mutational landscape of skin tumours in CYLD cutaneous syndrome determined

  Patients with germline mutations in CYLD can develop hundreds of benign skin tumours called cylindromas. The development of multiple tumours within a single patient at sun-protected and sun-exposed sites, varying tumour histological patterns and grades of malignancy allow for the testing of several genetic hypothesis in relation to cutaneous carcinogenesis. By adopting the unprecedented approach of whole genome sequencing of multiple benign skin tumours within individuals in multigenerational families, we set out to study the impact of mutational diversity on models such as multistep carcinogenesis as well as non-sequential carcinogenesis. Using non-negative matrix factorisation (NMF) to discover mutational signatures, we found distinct mutational signatures in identical benign tumours (N=2 patients; n=11 tumours) at sun exposed and sun protected skin tumours within a mother and her daughter. We found recurrent mutations in epigenetic modifying genes in CCS tumours which are known to have an oncogenic dependency on Wnt signalling. We also demonstrate that cutaneous tumours that metastasize to the lung carry a a UV signature, supporting the origin from the skin. Distinct malignant tumours, such as BCC and malignant spiradenocarcinoma carried unique driver mutations. These findings add new dimensions to the existing paradigms of UV-induced skin cancer and highlight the utility of studying rare disease to gain novel insights into genetic mechanisms of tumour formation.

  Dataset EGAD00001004573

• Germline genome sequencing samples from the Hereditary Cancer Syndromes (ICCon) Cancer Flagship

  A prospective study of individuals with suspicion of a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or was not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing and a comprehensive cancer virtual gene panel analysis were undertaken.

  Study EGAS00001007045

• A Genome-Wide Association Study of Peripheral Arterial Disease

  The Electronic Medical Record Phenotypes and Community-engaged Genomic Association Study aims to identify genetic variants mediating susceptibility to peripheral arterial disease (PAD). The study leverages a biorepository of blood samples of 1688 PAD cases and 1649 controls, and the electronic medical record (EMR) to annotate the biorepository. PAD cases were identified from the vascular laboratory database as having an ankle brachial index (ABI) <0.9 at rest or after exercise or having non-compressible vessels. Controls were without prior history of atherosclerotic vascular disease and when tested, no evidence of ischemia on a stress test. Phenotypes and environmental exposures including age, ethnicity, demographic and anthropometric data are derived from the Mayo Electronic Medical Record (EMR). Comorbidities were determined using algorithms for diabetes and hypertension based on ICD-9 codes and medication use. Relevant laboratory data, including lipid levels, fasting blood sugar and serum creatinine at index date or within a 1-year window of the index date were extracted. Medication classes at index date were identified using Mayo's Natural Language Processing-based system with RxNorm codification and NDF-RT terminologies mapping. Smoking status was confirmed by natural language processing of clinical notes. Genotyping of ~600,000 SNPs across the genome is being conducted at the Broad Institute using the Illumina 660W platform. Statistical analyses will be conducted to identify genetic variants associated with susceptibility to PAD.

  Study phs000203

• Genome-Wide Association Study of Heparin-Induced Thrombocytopenia

  Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. We performed a genome-wide association study (GWAS) with positive functional assay as the outcome. Genetic associations were investigated in a cohort of functional assay-confirmed HIT cases, antibody-positive (function assay-negative) controls, and antibody negative controls. Both PF4-specific enzyme-linked immunosorbent assay (ELISA) and serotonin release assay (SRA) were positive in every HIT case. GWAS genotyping was performed at the Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences (IMS). All samples in the discovery and replication cohorts were genotyped using the lllumina® Infinium HumanOmniExpressExome BeadChip, which contains 958,497 markers, including 273,000 functional exonic markers. Quality control was accomplished using sample and marker call rate ≥98%, sex mismatch, duplicate concordance, and removal of related samples through identity by descent. Genomic imputation was performed for samples using Minimac4 and the phase3 v5 reference panel data from the 1000 genomes project. The primary GWAS analysis used multivariable logistic regression assuming an additive genetic model with functional assay-confirmed case status as the outcome. Both PF4/heparin antibody negative and antibody positive controls were considered controls in the primary analysis. Logistic regressions were used to generate odds ratios and 95% confidence intervals (95%CIs) after adjustment for age, sex, and first three principal components.

  Study phs002863

• Hyperhaploid Multiple Myeloma

  Hyperhaploid multiple myeloma is a rare numerical aberration group defined by a range of 24-34 chromosomes which is associated with a poor prognosis. Hyperhaploid samples were sequenced by either exome or targeted panel sequencing. Samples had a median of 13 monosomies (range 12-14), which in general were those not associated with trisomies in hyperdiploid samples. The chromosomes traditionally trisomic in hyperdiploid myeloma were disomic in hyperhaploid myeloma with retention of heterodisomy. We examined the hyperhaploid samples for frequently mutated genes and found that 9/9 (100%) hyperhaploid samples had a mutation in TP53, exceeding the overall rate of mutation in newly diagnosed patients (5.5%), indicating an oncogenic dependency in this group. All samples with TP53 mutation also had monosomy of chromosome 17, indicating bi-allelic inactivation of TP53. As such, this high risk group is part of Double-Hit myeloma. DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either the entire exome (MedExome, Nimblegen) or a targeted panel of 140 genes using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads.

  Study EGAS00001003203

• Ontario Institute for Cancer Research; Biliary Tract Cancer

  Next Generation Sequencing data from Biliary Tract cancers

  Study EGAS50000000972

• SNP array datas of 'Matched' cancer/PNE

  SNP array data of 31 Matched cancer/PNE samples

  Study EGAS00001003331

• Small RNA sequencing of endometrial cancer patients with samples collected prior to diagnosis and controls

  This dataset contains unpaired FASTQ files of 316 endometrial cancer cases and 316 matched controls representing circulating RNAs. RNA count files are provided as the output of sncRNA pipeline and represent 12 RNA types (isomiR, lncRNA, precursor miRNA, miRNA, miscRNA, mRNA, piRNA, scaRNA, snoRNA, snRNA, tRF, and tRNA). We also provide metadata of the samples.

  Dataset EGAD50000000391