15075 results for "cancer studies using rna-seq"

in 48.18 milliseconds.

• ATAC Dataset for 19 T-ALL patient samples and 1 normal control sample

  19 ATAC-seq from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference

  Dataset EGAD50000000024

• ChIPseq data for Glioblastoma (EGAS00001003953, H016)

  ChIPseq data for human glioblastoma patients, EGAS00001003953. Mix of input, H3K27ac, H3K27me1, H3K27me3, H3K36me3, H3K4me1, H3K4me3, H3K9me3 and BRD, 20 human samples, 2 cell lines (LN229, ZH487).

  Dataset EGAD00001006548

• ATAC Analysis of Treg and Tfh cells

  Treg and Tfh cells (8 Samples)from the same donors was subject to ATAC-seq processing. Paired end fastq-files are supplied.

  Dataset EGAD00001007660

• G&T-seq: Parallel sequencing of single-cell genomes and transcriptomes

  Development of a method for separation and parallel sequencing of the genomes and transcriptomes of single cells.

  Dataset EGAD00001001332

• Spatial transcroptomic analyses against non-metastatic and metastatic lymph node from breast cancer patients

  We performed spatial transcroptomic analyses against non-metastatic and metastatic lymph node from breast cancer patients to investigate how metastasized breast cancer cells affect gene expression in lymph nodes

  Study JGAS000616

• Patient-derived models of primary breast cancer for preclinical development of novel neoadjuvant therapies

  Generation of the first large-scale cohort of mouse intraductal patient-derived xenograft (MIND-PDX) models of primary invasive breast cancer (IBC) and a collection of matched PDX-derived organoids (PDXO) representing all molecular subtypes of IBC, including estrogen receptor (ER-) positive breast cancer. Furthermore, we show that our IBC-MIND cohort can serve as a platform to test experimental neoadjuvant treatment options in different molecular subtypes of breast cancer.

  Study EGAS50000000398

• ESGI_Exome_sequencing_in_Circulating_Tumor_Cells_to_determine_therapy_related_markers_____

  The objectives of this project are the identification of markers related to cancer therapy resistance in the blood of breast cancer patients and to study the genetic changes in cancer cells during this development of resistance. Whole genome amplified DNA from Circulating Tumor Cells (CTCs), selected during the course of systemic treatment from blood of metastatic breast cancer patients, will be exome sequenced . The patients selected for this study did not respond to therapy.

  Study EGAS00001000747

• LICA-CN project - 116 liver cancer cases

  LICA-CN project - 116 liver cancer cases

  Study EGAS00001002300

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• PanProstate Cancer Group DK data

  THE PAN PROSTATE CANCER PROJECT: Many groups around the world have generated Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The pan prostate group have gathered with the idea that the accumulated data, should be collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals. The combined collection would include the following categories: (i) cancers from different ethnic groups: eg Caucasian, Asian, Black Caribbean; (ii) cancer from different stages of progression from normal, to organ-confined disease, to metastases; (iii) early-onset prostate cancer; (iv) prostate cancer from aggressive and indolent disease; and (v) prostate cancer patients managed by different treatments with information linked to long-term clinical follow up data in many cases.This study contains the samples from the Danish prostate group.

  Study EGAS50000001616

• Phylogenetic reconstruction of breast cancer

  The aim of this study was to identify the evolutionary trajectories of metastatic breast cancer. We present whole genome sequencing data (primary tumours, axillary lymph nodes, distant metastasis and matched normal tissues) from 16 breast cancer patients. This work sheds light on the routes on which tumour cells metastasize and their role in disease progression in ER-positive breast cancer.

  Study EGAS00001004356

• whole-genome sequencing of gastric cancer

  Gastric cancer is one of the most common cancers. Genome-wide analysis of genomic signatures might reveal novel mechanisms for gastric cancer tumorigenesis. Here, we analyzed structural variations and mutational signatures via whole-genome sequencing of 168 gastric cancer samples. Our data demonstrates diverse models of complex structural variations operative in GC, which lead to high-level amplification of oncogenes.

  Study EGAS00001003512

• EGAD00010000748

  Genotyping using Illumina Human OmniExpress12v1.0

  Dataset EGAD00010000748

• EGAD00010000417

  Han Chinese samples using Illumina OMNIExpress (cases)

  Dataset EGAD00010000417

• EGAD00010000423

  Han Chinese samples using Illumina OMNIExpress (controls)

  Dataset EGAD00010000423

• Array_dataset_TS

  DNAm Case samples using Illumina Infinium 450K

  Dataset EGAD00010001261

• Infinium Omni2.5

  Case control samples using Infinium Omni2.5

  Dataset EGAD00010001198

• PDX-OmniExpress24

  Primary and PDX SqCC samples using Infinium OmniExpress-24

  Dataset EGAD00010001228

• Botswana Identifiler dataset

  Autosomal STR genotypes using 15 Identifiler loci

  Dataset EGAD00010001255

• Array_dataset_Male

  DNAm Case samples using Illumina Infinium 450K

  Dataset EGAD00010001260

• Array_dataset_Female

  DNAm Case samples using Illumina Infinium 450K

  Dataset EGAD00010001262

• Illumina_HumanCoreExome

  Genotyped samples using Illumina Infinium HumanCoreExome Beadchip

  Dataset EGAD00010001410

• PanNEN_Methylation

  Methylation data of tumors using illumina Infinium MethylationEPIC

  Dataset EGAD00010002253

• EpS_methylation_850K

  Methylation profile (array data using EPIC_850K) from tumour samples (epithelioid sarcoma)

  Dataset EGAD00010002571

• Genome-wide methylation detection and episignature analysis using PacBio long-read sequencing

  Study EGAS00001008250

• Metformin for Oral Cancer Prevention

  The M4OC-PREVENT clinical trial addressed whether metformin has utility in the prevention of oral cancer. It is a phase IIa clinical trial of metformin ER 2,000 mg per day given for 12-14 weeks to individuals with oral premalignant lesions, either oral leukoplakia or erythroplakia (which are precursors to oral cancer). The goal was to determine if metformin decreases the size of oral leukoplakia (clinical response). Additionally, effects on biomarkers of cancer risk and metformin effect were ascertained. The clinical trial was performed at the University of California San Diego Moores Cancer Center, the University of Minnesota, and the British Columbia Cancer Agency, with monitoring and oversight provided by the University of Arizona.

  Study phs002437

• Assessment of genomic copy number alterations in breast cancer

  The aim of this study was to assess genomic copy number alterations in a panel of breast cancer cell lines. These data were used to identify common aberrations associated with breast cancer, and also to identify aberrations associated with response to therapeutic compounds.

  Study EGAS00000000059

• A clinically and genomically annotated Early onset colorectal cancer and late onset colorectal cancer

  This study aimed to identify genomic characteristics of early-onset colorectal cancer (EOCRC) compared to late-onset cases. Whole-genome sequencing (WGS) was performed on EOCRC and late-onset colorectal cancer (LOCRC) tissues and blood samples to analyze their genomic profiles.

  Study EGAS50000000544

• WTCCC case-control study for Coronary Artery Disease - Combined Controls

  WTCCC genome-wide case-control association study for Coronary Artery Disease (CAD) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000004

• WTCCC case-control study for Type 1 Diabetes - Combined Controls

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000015

• WTCCC case-control study for Coronary Artery Disease, Hypertension, T2D - combined cases

  WTCCC genome-wide case-control association study using the cardiovascular disease CAD, HT and T2D as combined case collection and the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000005

• WTCCC case-control study for Type 2 Diabetes - Combined Controls

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000017

• ChIP-sequencing fragment coverage

  Raw sequencing reads from H3K27ac ChIP and input DNA from lymphoblastoid cells of three TET2 mutation carriers and two wild-type family members were quality and adapter trimmed with cutadapt version 1.16 in Trim Galore version 0.3.7 using default parameters. Trimmed reads were aligned to hs37d5 reference genome using Bowtie2 (version 2.1.0). Duplicate reads were removed with samtools rmdup (v1.7). Fragment coverage of paired-end reads was calculated from bam files with BEDtools genomecov (v2.26.0).

  Dataset EGAD00010001671

• Dataset for Fragle Software Development and Evaluation

  Fragle is a deep learning based two stage model that quantifies ctDNA from blood plasma derived cfDNA bam files. Fragle was developed using some previously published datasets and some newly generated data. Fragle was evaluated using some validation cohorts and some unseen cohorts. Some of these cohorts are newly created consisting of total 365 low pass (2-3X) whole genome sequencing bam files mapped to hg19/GRCh37. This dataset contains these newly generated bam files.

  Dataset EGAD50000000167

• nanoCUSA

  This study aims to provide raw nanopoore sequencing data from tumor samples obtained during neurosurgery using a Cavitating Ultrasonic Aspirator. Acquired data with a subsequent neural network classifier with nanopore-specific diagnostic score thresholds assures high specificity while achieving acceptable sensitivity.

  Study EGAS50000000187

• Genomic Variation in Diffuse Large B Cell Lymphomas

  Integrative analysis of genetic lesions in 574 diffuse large B cell lymphomas (DLBCL). The study investigates genomic structural variation, genetic alteration and its effect on the development and biology of lymphomas by using high throughput sequencing, gene expression, and methylation status.

  Study phs001444

• Non-invasive whole genome sequencing of a human fetus

  The overall purpose of this study was to demonstrate the feasibility of producing haplotype-phased whole genome sequence data from a fetus using free fetal DNA isolated from maternal plasma collected during the first half of gestation.

  Study phs000500

• Single-cell multiome ATAC and gene expression profiling of hepatoblastoma tumor organoids

  10X Genomics single-cell multiome profiling of hepatoblastoma tumor organoids using Chromium Next GEM Single-Cell Multiome ATAC + Gene Expression Kit. Single-cell transcriptomics data (bam file) of multiplexed sample of hepatoblastoma tumor organoids: 3E, 8F1, 10F2, 13F2, 13E, 17E and 96F1. Single-cell solutions were obtained from fresh organoid samples using enzymatic digestion.

  Dataset EGAD50000000795

• Single-cell transcriptomic profiling of hepatoblastoma tumor organoids

  10X Genomics single-cell transcriptomic profiling of hepatoblastoma tumor organoids using Chromium Next GEM Single-Cell 3’ Reagent Kits v3.1 or 3’ CellPlex Multiplexing Kit. Single-cell transcriptomics data (bam files) of hepatoblastoma tumor organoids: 3E, 8F1, 10F2, 13F2, 13F2 late, 13E, 17E, 17F1, 22E, 27F1, 28F1, 31E, 96F1, 121E and 135. Single-cell solutions were obtained from fresh organoid samples using enzymatic digestion.

  Dataset EGAD50000000796

• DNA Methylation Profiles of T2D and Control Subjects from the GCAT Cohort Using EPIC v2

  This dataset contains DNA methylation data from 400 individuals (200 Type 2 Diabetes cases and 200 controls) from the GCAT (Genomes for Life) cohort. The methylation profiling was performed using the Illumina Infinium MethylationEPIC v2.0 BeadChip, which offers comprehensive coverage of over 850,000 CpG sites. Data are provided in IDAT file format, enabling raw signal-level analysis and downstream processing.

  Dataset EGAD00010002740

• M116 Whole Genome Sequencing

  Whole Genome Sequencing (WGS) was performed using DNA extracted from M116’s blood, saliva, and urine samples. DNA was fragmented to 350 bp, followed by library preparation, paired-end 150 bp WGS, and variant calling, all conducted by Novogene®. Sequencing was carried out with a 10X coverage (approximately 60 Gb and 200 million reads per sample) using the NovaSeq X Plus platform (Illumina). Files types included in this dataset are raw Fastq files.

  Dataset EGAD50000001286

• WGS

  A genome-wide approach based on next generation sequencing (NGS) is performed on trios ( Patient+ Father + Mother) with SAID in order to identify known and new gene variants associated with certain forms of the disease. Whole-genome sequencing (WGS) was performed on frozen PBMCs. DNA was extracted using Chemagic Prime ( Perkin Elmer) and quantified with nanodrop. The raw sequencing data is generated on the Novaseq 6000 using an S4 flowcell, with a sequencing depth of ~30X

  Dataset EGAD50000002026

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese Collection of Research Bioresources (Japanese B cell DNA bank), National Institutes of Biomedical Innovation, Health and Nutrition in Japan. We sequenced those genomic DNAs using PacBio Sequel II and analyzed genomic structural variations.

  Study JGAS000596

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese Collection of Research Bioresources (Japanese B cell DNA bank), National Institutes of Biomedical Innovation, Health and Nutrition in Japan. We sequenced those genomic DNAs using PacBio Sequel II and analyzed genomic structural variations.

  Study JGAS000505

• The analysis of gene mutations in Hematology malignancy

  We analysed the mutations of target genes regarding malignant lymphoma and myeloma to investigate the relationships between clonal evoutions and disease status. The gene mutation analyses using NGS at the point of diagnosis and relapse or proceeding disease.

  Study JGAS000232

• Whole genome sequencing data of paediatric KMT2A-rearranged acute lymphoblastic leukemia

  Whole genome sequencing data from infant (<1 y) paediatric (< 18 y) KMT2A-rearranged acute lymphoblastic leukemias. Dataset includes fastq and BAM files from diagnostic and remission (control) samples of 3 patients. Dataset consists of two experiments depending on library preparation method; "Experiment 1" is made using normal WGS library preparation (pcr+), and "Experiment 2" is made using pcr-free library preparation method.

  Dataset EGAD50000001568

• BAM-format HiFi whole genome sequencing reads (PacBio Revio) from stabilized human saliva

  HiFi whole‑genome sequencing data from a single human saliva sample collected and stabilized using an Oragene device. Sequencing was performed on a SMRT® Cell using PacBio Revio™ SPRQ chemistry. Sequencing produced >100 Gb of HiFi reads yielding >30× genome coverage suitable for comprehensive variant and methylation analysis. Dataset includes long‑read HiFi sequences in BAM format, containing both aligned and unaligned reads.

  Dataset EGAD50000002398

• Whole Genome Methylation in CLL

  We have extensively characterized the DNA methylome of chronic lymphocytic leukemia (CLL) with mutated and unmutated IGHV as well as several mature B cell subpopulations using whole-genome bisulfite sequencing and high-density microarrays.

  Study EGAS00001000272

• Spectrum and significance of MYC and BCL2 mutations in DLBCL

  We analyzed the spectrum and clinical significance of MYC and BCL2 mutations in 347 DLBCL cases from population-based cohort of BC, Canada. Mutational status of MYC and BCL2 coding exons were sequenced using TSCA assay.

  Study EGAS00001002206

• Whole genome amplification and whole genome sequencing of human single cells

  Human single fibroblasts and T-lymphocytes were amplified using multiple annealing and looping-based amplification and multiple displacement amplification. Amplified products were next subjected to whole genome sequencing with the goal of performing a genetic variant analysis.

  Study EGAS00001003108

• Clonal evolution and clinical implications of genetic abnormalities in blastic transformation of chronic myeloid leukaemia

  Blast crisis (BC) predicts dismal outcomes in patients with chronic myeloid leukaemia (CML). We comprehensively investigated genetic abnormalities in 136 BC and 148 chronic phase (CP) samples obtained from 216 CML patients using exome and targeted sequencing.

  Study EGAS00001005075

• Molecular profiling of DLBCL patients treated in the PETAL trial

  Using whole-exome sequencing and shallow whole genome sequencing for simultaneous screening of mutations, copy number alterations, and translocations, 5 biology-based risk profiles could be reproduced in an independent cohort of DLBCL patients, from the PETAL trial.

  Study EGAS00001005828

• Clonal_dynamics_and_mutation_burden_in_male_germline_

  This work aim to study clonal dynamics of pathogenic mutations in male germline. Using Nanoseq method, sperm from normal panel will be compared with sperm from men who have either clinical phynotypes or they have child(ren) with germline predisposition syndromes.

  Study EGAS00001006346

• Targeted sequencing of brain AVM tissues

  We previously identified somatic activating KRAS mutations in a majority of human arteriovenous malformations (AVMs), using whole exome sequencing. We have now performed targeted sequencing on AVMS, investigating genes in the RAS-MAPK pathway, angiogenesis and brain vascular disorders among others.

  Study EGAS00001006729

• Summary statistics of meta-analysis using two genome-wide association study of inflammatory bowel disease in Koreans.

  We combined samples from 1,469 inflammatory bowel disease (IBD) patients consisted of 896 Crohn’s disease (CD) and 573 ulcerative colitis (UC) and 4,041 controls used in our previously published GWAS with 1,726 additional IBD patients (725 CD and 1,001 UC) and 378 additional controls genotyped using the Asian Screening Array (ASA). We uploaded summary statistics of three meta-analyses in text files.

  Dataset EGAD00001006983

• Paired WGS data of 45 samples and 2 paired WES sample of RRMM (multiple myeloma)

  Here is mostly paired WGS data of RRMM, 45 samples (tumors and controls) in 86 runs. This data was produced by using Illumina TruSeq Nano DNA and NovaSeq6000 or HiSeq X Ten for sequencing. One tumor/control pair is WES data using Agilent SureSelect V5+UTRs and NovaSeq6000 for sequencing.

  Dataset EGAD00001009682

• Megabase scale methylation phasing using Nanopore long reads and NanoMethPhase

  This paper describes the work by Akbari V,. et al. on detection of allele specific methylation using oxford nanopore sequencing data. They have developed set of tools, SNVoter and NanoMethPhase, and workflow which enable the detection of allele specific methylation even in samples with sparse coverage of nanopore sequencing data.

  Dataset EGAD00001007920

• Dataset of the sequenced and imputed genotypes

  Samples from 149 trios from the Saguenay-Lac-Saint-Jean asthma familial cohort were all sequenced using a custom capture panel developed by our group, followed by next-generation sequencing. This custom capture panel covers around 3% of the genome, including coding and non-coding immune regulatory regions. We inferred the sequence in the non-sequenced siblings who were part of the same families as the trios and we imputed the sequence using IMPUTE2 in the whole cohort.

  Dataset EGAD00001004268

• Naive B-cell receptor heavy chain repertoire of celiac patients and healthy controls

  High throughput sequencing dataset of antibody repertoires from naive B-cells, taken from blood samples of 100 individuals from Norway. 48 healthy controls and 52 patients with celiac disease. Sequencing was performed using a 300*2 paired-end kit by Illumina MiSeq. The sequences were processed using pRESTO. Each fastq file in the dataset is the repertoire of a single individual.

  Dataset EGAD00001004512

• Single-cell Multi-omics Sequencing of Human Early Embryos

  The whole blood of six female volunteers and sperm from one male volunteer were used to extract genomic DNA using a DNeasy Blood &amp; Tissue Kit (QIAGEN). 500 ng gDNA was fragmented into 300 bp by Covaris. Then, the libraries were constructed using a KAPA Hyper Prep Kit (Kapa Biosystems). In total we have 7 samples and the files we uploaded are pair-end fastq files.

  Dataset EGAD00001004108

• Whole exome sequencing and target gene sequencing of ESCC cases and healthy controls from Henan high-risk region

  In total, 186 FH+ ESCC cases were sequenced using whole-exome sequencing, then 1935 ESCC cases and 1186 geographically-matched healthy controls were sequenced using 7 Mb custom designed Roche SeqCap kit which targeted about 600 genes. The libraries were constructed and then sequenced in Illumina platform.

  Dataset EGAD00001004556

• Lymphocyte LCM WGS (2020-02-20)

  Using whole genome sequencing of lymphocytes excised from human tissue using laser capture microscopy (LCM), we identify the mutations arising in these microenvironments. This work will contribute towards developing a catalogue of mutations present in tissue resident lymphocytes across a range of tissues, and will characterize the mutational signatures that result from each microenvironment. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005992

• A proteogenomic atlas of the human neural retina

  The human neural retina is enriched for alternative splicing, and it is estimated that more than 10% of variants associated with inherited retinal diseases (IRDs) alter splicing. Previous research mainly used short-read RNA-sequencing techniques to investigate retina-specific splicing and splicing factors. However, this technique provides limited information about transcript isoforms. To gain a deeper understanding of the human neural retina and its isoforms, we generated a proteogenomic atlas that combines PacBio long-read RNA-sequencing data with mass-spectrometry and whole-genome sequencing data from three healthy human neural retina samples. About one third of the nearly 60,000 transcript isoforms were novel, and ten novel peptides that confirmed novel isoforms were detected. This study highlights the importance of studying tissue-specific transcriptomes in greater detail to better understand tissue-specific regulation and to identify disease-causing variants.

  Study EGAS50000000070

• Controlling cell differentiation with precision through understanding the structure and dynamics of gene regulatory networks

  We established a set of transgenic human ES cell lines that carry inducible expression gene cassette for singe transcriptional factor induction with Tet-ON system. Transcriptome data was obtained 48h after transgene induction by Microarray. We established inducible human ES lines about more than 700 genes, and achieved microarray analysis on 115 genes. Our data set has multiple characteristic properties; 1) the same platform across data set, 2) analyzed with dynamic cell status, 3) pre-determined initiation point on gene perturbation, 4)inducible in different cell status. In parallele, we also performed RNA sequenncig analysis on 435 transgene induced ES lines as well. 32 transgene induced transcriptome data were obtained from both Microarray and RNA sequencing, normalizing technical gaps between them. We hope those systematic data set to reveal transcriptional network structure and molecular mechanisms of cell differentiation.

  Study JGAS000121

• RA-Map, A multi-omic survey of whole blood and subsets in early rheumatoid arthritis and vaccine study controls

  Rheumatoid arthritis (RA) is a chronic inflammatory disorder of unknown aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the molecular heterogeneity and pathogenesis of RA, we performed a comprehensive clinical and molecular profile of 267 RA patients for up to 18 months to establish a high quality biobank of barcoded samples that included plasma, serum, peripheral blood cells, whole blood RNA, RNA from lymphocyte and monocyte subsets, genomic DNA and urine. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and auto-antibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource for the development and application of targeted therapies for RA and reveal further insights into disease pathogenesis and therapeutic response.

  Study EGAS00001004424

• Etiological Investigation of Cancer Susceptibility in Inherited Bone Marrow Failure Syndromes: A Natural History Study

  Background: A prospective cohort of Inherited Bone Marrow Failure Syndrome (IBMFS) will provide new information regarding cancer rates and types in these disorders. Mutations in IBMFS genes are relevant to carcinogenesis in sporadic cancers. Patients with IBMFS who develop cancer differ in their genetic and/or environmental features from patients with IBMFS who do not develop cancer. These cancer-prone families are well suited for cancer screening and prevention trials targeting those at increased genetic risk of cancer. Carriers of IBMFS gene mutations are at increased risk of cancer. The prototype disorder is Fanconi Anemia (FA); other IBMFS will also be studied. Objectives: To determine the types and incidence of specific cancers in patients with an IBMFS. To investigate the relevance of IBMFS gene mutations in the carcinogenesis pathway of the sporadic counterparts of IBMFS-associated cancers. To identify risk factors for IBMFS-related cancers in addition to the primary germline mutations. To determine the risk of cancer in IBMFS carriers. Design: Natural history study, with questionnaires, clinical evaluations, clinical and research laboratory tests, review of medical records, cancer surveillance. Primary endpoints are all cancers, solid tumors, and cancers specific to each type of IBMFS. Secondary endpoints are markers of pre-malignant conditions, such as leukoplakia, serum or tissue evidence of carcinogenic viruses, and bone marrow morphologic myelodyplastic syndrome or cytogenetic clones.

  Study phs001481

• Isolation of bacteria in infected brains in patients with Parkinsons disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis).

  Dac EGAC00001001197

• RNAseq of fibroblasts

  RNA sequencing data of fibroblasts from 3 controls and 3 patients with RBMX variants.

  Dataset EGAD50000002371

• Direct RNA sequencing of 10 postmortem human brain samples

  Contains fast5 data for each of the 10 samples sequenced.

  Dataset EGAD00001015347

• RNA sequencing BRAF fusion partners

  Contains RNAseq data for 14 transduced/non-transduced organoids

  Dataset EGAD00001005380

• Multidimensional Proteomics analysis of intractable cancers with prospective observational cohort for precision medicine

  Multi-omics project of Non small cell Lung Cancer. Exome and RNAseq datasets were generated from normal-tumor pairs of Non small cell Lung Cancer patients from the retrospective cohort.

  Study EGAS50000000592

• germline variants in children with hematological cancer

  Trio parent-child whole exome sequencing has been used to identify cancer predisposing syndrome (CPS) in our pediatric patients with hematological cancer, and it was identified in 3.8% of the total number of patients(131).

  Study EGAS00001006907

• Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

  Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

  Study phs001041

• Time Lapse to Cancer-Defining the Transition from Polyp to Cancer

  In the US, CRC incidence has declined with uptake in colonoscopy for early detection and removal of polyps, the precursor lesion, can stop a cancer from developing but in spite of this, CRC remains the second leading cause of cancer death in the United States. One third of people who undergo screening colonoscopy will have adenomatous polyps, but less than 5% of the time are these polyps presumed to go on to develop into cancer. Why does one polyp develop into cancer while another one that looks very similar does not. In this proposal we will identify what molecular genetic changes in the genome, in the mRNA expression and genetic methylation patterns will distinguish a polyp that has already transformed into cancer from one that has not.

  Study phs001384

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• Genome-wide mutation analysis of germinal-center B-cell derived lymphomas within the ICGC MMML-Seq Consortium

  Germinal-center B-cell derived lymphomas (GCB-lymphomas) are the most common B-cell lymphomas in children and adults, with Burkitt Lymphomas (BL) predominating in childhood and follicular lymphoma (FL) and diffuse large B-cell lymphomas (DLBCL) predominating in older age groups. The cell-of-origin in all these lymphomas is supposed to be a germinal center B-cell and transformation of FL in DLBCL or intermediate DLBCL/BL (intL) can occur. In the framework of the German ICGC MMML-Seq we are currently exploring sequencing data of GCB-lymphomas and paired normal controls as well as normal B-cell subsets separated by FACS. This includes whole genome, transcriptome, miRNAome and whole methylome datasets.

  Study EGAS00001000394

• DAC for "Detection of Gene Fusions using Targeted Next-Generation Sequencing – a Comparative Evaluation"

  Dac EGAC00001001905

• EGAD00010000815

  ATL tumor samples using Affymetrix 250K SNP array

  Dataset EGAD00010000815

• EGAD00010000811

  ATL tumor samples using Illumina 610K SNP array

  Dataset EGAD00010000811

• EGAD00010000813

  ATL tumor samples using Illumina 450K Methylation array

  Dataset EGAD00010000813

• EGAD00010000502

  Case samples using SNP Array 6.0

  Dataset EGAD00010000502

• Gencode_15K

  Lymphoma samples using CytoSNP

  Dataset EGAD00010000947

• Gencode_550K

  Lymphoma samples using HumanOmni

  Dataset EGAD00010000949

• Gencode_500K

  Lymphoma samples using 450k

  Dataset EGAD00010000948

• HC_genotyping

  HC genotyping data for lead SNPs using Illuminia Global Array V2.0

  Dataset EGAD00010002475

• SWEPIC_methylation_controls

  CONTROL SAMPLES methylation data using Illumina EPIC technology

  Dataset EGAD00010002638

• Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing - NGS targeted capture control cohort

  In routine diagnostic pathology, cancer biopsies are preserved by Formalin-Fixed, Paraffin-Embedding (FFPE) procedures for examination of (intra-) cellular morphology. Such procedures inadvertently induce DNA fragmentation, which compromises sequencing-based analyses of chromosomal rearrangements. Yet, rearrangements drive many types of hematolymphoid malignancies and solid tumors, and their manifestation is instructive for diagnosis, prognosis and treatment. Here, we present FFPE-Targeted Locus Capture (FFPE-TLC) for targeted sequencing of proximity-ligation products formed in FFPE tissue blocks, and PLIER, a computational framework that allows automated identification and characterization of rearrangements involving selected, clinically-relevant, loci. FFPE-TLC, blindly applied to 149 lymphoma and control FFPE samples, identifies the known and novel rearrangement partners. It outperforms fluorescence in situ hybridization (FISH) in sensitivity and specificity, and shows clear advantages over standard capture-NGS methods, finding rearrangements involving repetitive sequences which they typically miss. FFPE-TLC is therefore a powerful clinical diagnostics tool for accurate targeted rearrangement detection in FFPE specimens.

  Study EGAS00001005325

• 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

• 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

• Molecular pathways and cellular subsets associated with adverse clinical outcomes in overlapping immune-related myocarditis and myositis

  ScRNA-seq FASTQ files from myocarditis and control cardiac muscle samples; and myositis and control skeletal muscle samples.

  Dataset EGAD50000000488

• ATAC_TPO3_2023

  Human engineered CRC organoids (APC KO; KRAS G12D; TP53 KO) were grown in glucose, lactate or with DCA . Samples were collected and processed for bulk ATAC-seq.

  Dataset EGAD50000000088

• Enzymatic methylation sequencing of intestinal metaplasia

  We perform genome-wide EM-seq of 14 patients with concurrent matched normal, dysplasia and early gastric samples from South Korea. The dataset contains cram files from 38 samples.

  Dataset EGAD50000001538

• HiChIP for 2 samples

  This dataset contains H3K27ac HiChIP data from ta primary sample and a patient derived model (PDX) of the novel FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001787

• Paired-end Whole Exome-seq analysis of TERT promoter duplication in GBM

  Dataset contains paired-end Whole Exome sequencing data from 5 tumor samples and 1 single normal blood sample from a single primary GBM patient.

  Dataset EGAD00001008768

• AVENIO Expanded ctDNA panel sequence alignments (BAMs) from plasma DNA of lung cancer patients from the OSCILLATE trial

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 100 plasma samples from patients with lung cancer undergoing treatment in the OSCILLATE trial. After 150 bp paired-end sequencing, reads were aligned to the human genome reference with the AVENIO Oncology Analysis Software. These files are the sorted non-deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Study EGAS50000000103

• Multi-omics RNA profiling of glioblastoma patient tissues

  Multi-omics profiling of paired primary and recurrent glioblastoma patient tissues

  Dataset EGAD00010001895

• TXT_CD138N_15

  TPM matrices of counts from RNA sequencing (RNAseq) from longitudinal CD138(–) BM fractions.

  Dataset EGAD00001011145

• SNF_RNAseq_CD138n_20f

  TPM matrices of counts from RNA sequencing (RNAseq) from baseline CD138(–) BM fractions.

  Dataset EGAD00001011142