15075 results for "cancer studies using rna-seq"

in 35.67 milliseconds.

• Hereditary Cancer Diagnostics with I2HCP gene panel

  Germline blood DNA sequencing data generated in routine diagnostics of hereditary cancer using the I2HCP gene panel (~135 genes). There are 130 samples sequenced in a MiSeq machine and 108 sequenced in a HiSeq machine. There is a partial overlap between those two sets, meaning that some samples were sequenced in both machines. There is a strong enrichment in samples with copy-number variants (CNV), both single- and multi-exon, since this dataset was compiled for a benchmarking effort of CNV calling tools for genetic diagnostics.

  Dataset EGAD00001006171

• Mannheim Liquid Biopsy Unit, Heidelberg University & DKFZ

  The dataset consists of sequenced cell free DNA (cfDNA) samples from colorectal cancer patients. The samples were sequenced on an Illumina MiSeq machine using a custom amplicon sequencing approach. These amplicons were designed to cover the most common mutation hotspots in colorectal cancer. The data include 138 cfDNA samples from 34 different patients. For each patient several samples are available derived from blood drawn at different time points during treatment. In addition the data include samples from 22 histology slides and 30 samples derived from HT29/HCT116 cell lines that were used as controls.

  Dataset EGAD00001004574

• Transcriptome of memory B cells with autoproliferation in MS

  Transcriptional profile of resting/hi and autoproliferating/Dim memory B cells in Multiple sclerosis patients. In brief, non-proliferating (CFSEhi) and AP+ (CFSEdim) CD19+ CD27+ B cells from PBMCs of 5 natalizumab-treated female RRMS (NAT) patients were sorted following 7 days of autoproliferation. Transcriptome libraries were constructed from the same samples, except for one sample pair, which was excluded due to limited input material (5 donors as for Methylome, D1; D2, D3, D5, D6; samples from donor D4 unfortunately technically failed). SMARTer Total Stranded RNA-seq library construction with ribosomal depletion was performed and then sequenced on NovaSeq S4 lane.

  Dataset EGAD50000001270

• Capture-based Methods for Transcriptomic Profiling of FFPE material

  This dataset includes all FASTQ files for 11 samples where different capture-based methods for transcriptome profiling have been tested. Specifically, we have the 'traditional' RNA-seq experiment with fresh frozen (FF) material, and 3 different capture methods for the matching formalin-fixed paraffin-embedded samples: Agilent (AGI), IDT, and Twist Biosciences (TBS). In total, there are 43 samples with paired-end FASTQ files (1 sample did not have sufficient material to test all methods). Samples are identified by the R01-R11 IDs with a suffix that indicates the capture method used (or FF for fresh frozen).

  Dataset EGAD00001007655

• Sequencing data associated with Smith et al, Acta Neuropathologica, 2020 (PMID: 32519082)

  The dataset includes 144 BAM files of WGS, WES, and RNA-seq data from primary and PDOX samples analyzed in Smith et al, Acta Neuropathologica, 2020 (PMID: 32519082).

  Dataset EGAD00001007980

• Single-nucleus ATAC-seq of human fetal liver hematopoiesis

  The fetal liver is the primary haematopoietic organ during early human development, yet the timing and regulatory mechanisms governing blood formation remain incompletely understood. To define the cellular, transcriptional, and epigenetic changes underlying human fetal liver hematopoiesis over development, we generated a high-resolution, time-resolved single-nucleus multiome atlas of human fetal liver spanning 5–18 post-conception weeks (PCW) for CD45+CD235- cells. In total, 308,021 high-quality nuclei from 53 donors were profiled using paired chromatin accessibility and transcriptomic modalities. This study is for the chromatin accessibility.

  Study EGAS50000001632

• The Spatio-Temporal Evolution of Multiple Myeloma from Baseline to Relapse-Refractory States

  In multiple myeloma, the spatio-temporal evolution patterns of cancer cells in the bone marrow remain largely unknown. Here, we applied spatial-longitudinal sequencing, including a total of 179 samples collected from 25 patients during a follow-up of up to 14 years. Our study highlights focal bone lesions (FL) as hotspots of tumor evolution and provides possible explanations for their negative prognostic impact. We show a close phylogenetic relationship between baseline FL and relapse clones. In patients with ≥3 FDG-PET-positive FL at diagnosis, relapse was driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion was typically seen (p<0.01). Applying imaging-guided sampling, we identified a novel evolutionary pattern with unique treatment-resistant sub-clones at distinct locations. We observed multiple selective clonal sweeps, resistant clones that can be hidden over years, and epigenetic modifier mutations as a new class of relapse aberrations. Here we show that imaging can enhance tumor evolution studies and response assessment. The sophisticated evolution mechanisms in myeloma and presence of single cells that can drive relapse even after 10 years of remission suggest that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy.

  Study phs002625

• Tandem DNA Repeats Activate hTERT Gene Transcription

  Multiple independent sequence variants of the hTERT locus have been associated with telomere length and cancer risks in genome-wide association studies. Here, we identified an intronic variable number tandem repeat, VNTR2-1, as an enhancer-like element, which activated hTERT transcription in a cell and chromatin-dependent manner. VNTR2-1, consisting of 42-bp repeats with an array of E-boxes, cooperated with the proximal promoter in hTERT regulation by bHLH transcription factors and maintained hTERT expression during embryonic stem cell differentiation. Genomic deletion of VNTR2-1 in MelJuSo melanoma cells markedly reduced hTERT transcription, leading to telomere shortening, cellular senescence, and impairment of xenograft tumor growth. Interestingly, VNTR2-1 lengths varied widely in human populations.  To assess the genetic polymorphism of VNTR2-1 in human populations, we analyzed genomic DNA samples of Caucasian Americans and African Americans enrolled in the Georgia Centenarian Study.  VNTR2-1 in these genomic DNA samples were PCR amplified and subjected to sequencing analysis usinb the PacBio® SMRT method. The result showed that all VNTR2-1 alleles in Caucasian Americans contained 76 or more 42-bp repeats, whereas 32% of VNTR2-1 alleles in African Americans had fewer than 76 repeats.  

  Study phs002428

• Allele Balance Bias Identifies Systematic Genotyping Errors and False Disease Associations

  In recent years, Next Generation Sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the allele balance distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies (RVAS).

  Study EGAS00001003027

• Local In Time Statistics for processual research

  Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

  Study EGAS00001002520

• Illumina Human Exome (ExomeChip) genotype data from the Pomak villages in Greece (HELIC Pomak Isolate). 1040 samples all >=16 years old.

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina HumanExome Beadchip. The HELIC (Hellenic Isolated Cohorts) Pomak collection focuses on the Pomak villages in Greece. Recruitment of this population-based sample was primarily carried out at the village medical centres. www.helic.org

  Study EGAS00001000658

• Genome-wide association study in multiple human prion diseases suggests genetic risk factors additional to PRNP

  We conducted GWAS of sporadic CJD, variant CJD, iatrogenic CJD, inherited prion disease, kuru and resistance to kuru despite attendance at mortuary feasts. After quality control we analysed 2000 samples and 6015 control individuals (provided by the Wellcome Trust Case Control Consortium and KORA-gen), for 491032-511862 SNPs in the European study. Association studies were done in each geographical and aetiological group followed by several combined analyses.

  Study EGAS00000000097

• Post-liver transplant recurrent human hepatocellular carcinoma study (RHCCS)

  The whole exome sequencing showed that HERC5 deletion and under-expression associates with shorter: time to tumor recurrence, progression-free, and overall survival in hepatocellular carcinoma (HCC) in two independent studies (p1=0.004, HR1=1.80; p2=0.018, HR2=3.31) totaling 286 HCC patients. Matched primary and recurrent tumors indicated a clonal selection advantage in somatic single nucleotide and copy number variants (CNVs) in recurrent compared to primary tumors of Chinese HCC patients with Wnt signaling most activated.

  Study phs000782

• The Immunogenetics of Measles Immunity - Measles (MMR) vaccination (NIAID/NIH)

  To examine the role of gene polymorphisms (including functional studies of SNPs) on variations in vaccine-induced immune responses, in approximately 3,000 healthy school-age children, adolescents and young adults/adults, who were vaccinated with measles-containing vaccine (MMR). To achieve greatest power to detect SNPs associated with measles-specific immune response phenotypes, we pooled our data across three genotyping platforms and three cohorts (US cohort, San Diego cohort and Rochester cohort).

  Study phs001630

• Genetics and Pathophysiology of Autoinflammatory Disorders

  In this study, patients with suspected disorders of inflammation and innate immune system dysregulation will undergo whole exome sequencing. This will involve both family studies (often trios or multiplex families including affected and unaffected individuals) and sporadic cases. The overall objective is to discover rare/novel high-penetrance mutations in genes that have not yet been implicated as the cause of monogenic autoinflammatory diseases. The aim also includes discovery of variants associated with inflammatory disease susceptibility.

  Study phs001860

• Susceptibility loci for tanning ability in Japanese population identified by genome-wide association study

  We performed genome-wide association studies of Japanese Skin Type for Japanese individuals from a cohort study by the Tohoku Medical Megabank Project in order to identify variants related to tanning ability and skin pigmentation. We used imputed genotype data of 9,187 Japanese individuals, of which 4,475 individuals are from Miyagi prefecture and 4,712 individuals are from Iwate prefecture. Skin Type information was obtained from the questionnaire for cohort participants.

  Study JGAS000160

• APCDR AGV Project: Whole genome sequencing of 3 African populations (curated data)

  The African Genome Variation Project (AGVP) provides a resource to help design, implement and interpret genomic studies in sub-Saharan Africa (SSA) and worldwide. The AGVP represents dense genotypes from 1,481 and whole genome sequences (WGS) from 320 individuals across SSA. As part of the AGVP we sequenced 3 African populations; Baganda from Uganda (4x), Zulu from South Africa (4x), Gumuz, Wolayta, Oromo, Somali and Amhara from Ethiopia (8x).

  Study EGAS00001000960

• APCDR AGV Project: The African Genome Variation Project(dense array genotyping data)

  The African Genome Variation Project (AGVP) aims to provide a global resource to understand population diversity and help design, implement and interpret genomic studies in sub-Saharan Africa (SSA), and worldwide. The AGVP represents dense genotyping data on 1,481 individuals from 18 ethno-linguistic groups and low coverage whole genome sequencing data on 320 individuals from 7 ethno-linguistic groups in SSA.

  Study EGAS00001000959

• Distinct genomic profile and specific targeted drug responses in adult cerebellar glioblastoma

  Only a few studies have reported the molecular characteristics of adult cerebellar glioblastoma (C-GBM), a subtype comprising 1% of glioblastoma cases located within the infratentorial brain region due to the rarity. By identifying genomic profiles from 19 adult C-GBM samples, we revealed the genetic intertumoral heterogeneity in C-GBM as well as distinct genomic characteristics from those of supratentorial glioblastomas (S-GBMs), emphasizing the need of individualized therapies for C-GBM patients.

  Study EGAS00001002517

• International consensus definition of DNA methylation subgroups in juvenile myelomonocytic leukemia

  Known clinical and genetic markers have limitations in predicting disease course and outcome in juvenile myelomonocytic leukemia (JMML). DNA methylation (DNAme) patterns in JMML have correlated with outcome across multiple studies, suggesting it as a biomarker to improve patient stratification. However, standardized approaches to classify JMML based on DNAme patterns are lacking. We therefore sought to define an international consensus for DNAme subgroups in JMML and develop classification methods for clinical implementation.

  Study EGAS00001004682

• Multiomic Sequencing of Paired Primary and Metastatic Small Bowel Carcinoids

  Small bowel carcinoids are insidious tumors that often have metastatic spread at the time of diagnosis. Limited studies on the mutational landscape of carcinoids indicate that the tumors have a relatively low mutational burden. Loss of chromosome 18q and loss of CDKN1B have been reported in a minority of tumors. The development of targeted therapies will depend upon the identification of mutations that drive the pathogenesis and metastasis of carcinoid tumors.

  Study EGAS00001006988

• Panbody_nanoseq

  Different cell types within the human body are subject to different endogenous and exogenous exposures which may result in distinct patterns of mutagenesis. In non-clonal tissues, it is difficult to assess these mutational patterns, including the rate at which they occur. This study will examine the mutational rates and signatures operating across a wide range of normal tissues using the nanoseq technology to reliably call variants, irrespective of their clonal composition. Each cell type will be enriched for using laser capture microdissection. This will serve as a reference against which future work on benign and malignant disease entities can be compared.

  Study EGAS00001005521

• University of Miami Study on Genetics of Autism and Related Disorders (AutismDisorders)

  Autism spectrum disorders (ASD) are neurodevelopmental in origin and characterized by impairments in reciprocal social interaction and communication accompanied by restricted and repetitive patterns of interest or behavior. With improved surveillance and a broadening of the diagnostic criteria, the most recent prevalence studies suggest that ASD may affect as many as 1/166 children in the US. Treatments are limited resulting in little impact on the profound morbidity. Little is known about the etiology of ASD, but there is a strong genetic component. Genetic studies over the past decade have failed to identify definitive ASD genes, but have clearly shown that the underlying genetics are more complex than anticipated with the likelihood that multiple genes are acting independently and/or interactively. With this realization the field of ASD genetics is at a critical juncture. To move forward we must embrace new and creative paradigms to successfully dissect the genetic etiology of this disease. Specifically the current study will: Extend our ascertainment to the full range of ASD. We will increase our ASD dataset by collecting 600 families who meet clinical diagnostic criteria for the three most common ASDs: autism (AUT), Asperger disorder (ASP) and Pervasive Developmental Disorder-NOS (PDD-NOS). Phenotype assessment will be expanded to include the Social Responsiveness Scale (SRS) and detailed seizure data. Ascertainment will focus on parent-child trios. Further characterize the ASD-associated variations in the Gamma-Aminobutyric Acid (GABA) receptor (GABR) subunits. We will complete our GABR subunit variant analysis, including coding, UTR, regulatory, and conserved intronic sequence, concentrating on GABRA4 and GABRB1. We will also investigate the role of variation in other GABR subunits. All AUT specific findings will be examined in the entire ASD dataset. Identify the chromosome 19p ASD gene. Multiple genome-wide screens have provided significant evidence for linkage to Chromosome 19p and we have found evidence for significant association in the linked families within an ~3 Mb region. We will genotype 768 SNPs spaced at ~4 kb to refine the candidate region and delineate specific candidate genes for further testing. We will screen the strongest associated candidate genes for additional variants and evaluate evidence for association in the entire ASD dataset (SA5). Develop and apply the Phenotypic Homogeneity Distinction (PHD) algorithm for identification of the phenotypic signature of linkage and/or association signals. The PHD algorithm identifies phenotypic covariates that discriminate a target sample subset (e.g. the positively linked families or families carrying the associated risk allele) from its complement. The resulting PHD discriminators will define a homogeneous subset from our newly-ascertained ASD dataset to use, as a confirmatory dataset and for localization within genes under study in our other aims. Test for gene-gene interactions. To fully explain the spectrum of autism risk, we will test for interactions between genetic variations associated with ASD (such as those in GABR subunit genes). We will build upon our experience using the MDR method and extend our analyses across biological pathways using the entire ASD data set.

  Study phs000436

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

  Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but efficacy varies between patients and is believed to depend in part on the amount and properties of tumor infiltrating lymphocytes (TILs). To comprehensively depict and dissect the baseline landscape of the composition, lineage and functional states of TILs in lung cancer, here we generated deep single-cell RNA sequencing data for 12,346 T cells from the primary tumour, adjacent normal tissues and peripheral blood of 14 treatment-naive NSCLC patients. Combined expression and TCR-based lineage tracking revealed a significant proportion of effector T cells with common origins and similar functional states across peripheral blood and tumours pointing towards a highly migratory nature of these T cells. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of pre-exhausted to exhausted T cells is associated with better prognosis of lung adenocarcinoma (LUAD). In addition, we observed further heterogeneity within the tumour regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of this group of activated tumour Tregs, which included IL1R2, correlated with poor prognosis in LUAD. The T cell clusters revealed by our single cell analyses provide a new approach for patient stratification, and the accompanying compendium of data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer.

  Study EGAS00001002430

• The ALT pathway generates telomere fusions that can be detected in the blood of cancer patients

  Telomere fusions (TFs) can trigger the accumulation of oncogenic alterations leading to malignant transformation and drug resistance. Despite their relevance in tumour evolution, our understanding of the patterns and consequences of TFs in human cancers remains limited. Here, we characterize the rates and spectrum of somatic TFs across >30 cancer types using whole-genome sequencing data. TFs are pervasive in human tumours with rates varying markedly across and within cancer types. In addition to end-to-end fusions, we find novel patterns of TFs that we mechanistically link to the activity of the alternative lengthening of telomeres (ALT) pathway. We show that TFs can be detected in the blood of cancer patients, which enables cancer detection with high specificity and sensitivity even for early-stage tumours and cancers of high unmet clinical need. Overall, we report a novel genomic footprint that enables characterization of the telomere maintenance mechanism of tumours and liquid biopsy analysis.

  Dataset EGAD00001012101

• WES of precancerous lesions from 10 lynch patients and 3 sporadics

  Raw sequencing data of WES that were obtained from precancerous samples as adenoma and MMR-deficient crypts and paired healthy tissue from MSI CRC patients of which 10 are diagnosed with lynch syndrome and 3 had sporadic cancer. These data were analyzed in order to evaluate microsatellite instability though tumorigenesis and associated to splicing deregulation in MSI tumors RNA.

  Dataset EGAD50000000644

• Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer

  RNA sequencing data from breast cancers (n=18) and their matched HN tissues (n=36), healthy breast from cosmetic reduction mammoplasty (RM; n=5), and risk reducing mastectomies (RR, n=5), with peritumoral samples excised proximal to (TP, less than 2 cm) and distal from (TD, 5-10 cm) the primary tumor.

  Dataset EGAD00001006291

• lymphoma plasma cfRNA

  Dataset contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma (DLBCL) and 13 primary mediastinal large B-cell lymphoma (PMBCL) patients, and 22 cancer-free controls. Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001010259

• RNAseq of ribosomal footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Dataset EGAD00001001930

• Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

  Molecular cancer paper (https://doi.org/10.1186/s12943-021-01327-5): This dataset contain shallow whole-genome sequencing (sWGS) of plasma cell-free DNA from cancer patients and healthy subjects, obtained with both Nanopore and Illumina technology. A total of 6 cancer patients and 5 healthy subjects have been sequenced with Nanopore; 4 of the cancer patients have been also sequenced with Illumina. In addition, genomic DNA from white blood cells of one healthy subjects, genomic and 160bp DNA from HEK cells have been sequenced with Nanopore. Genome Biology paper: 3 additional healthy samples have been sequenced (HU), two different bioinformatic pipeline were applied. 2019: Fastqs from the molecular cancer paper were re-demultiplexed and adapter-trimmed (using guppy for multiplex samples, and porechop for singleplex) preserving 5' ends to allow fragmentomics analysis. HAC: All the samples were basecalled with the same updated High Accuracy model (the latest at the time of the analysis) and post-processed as the 2019 dataset. Raw FAST5 are currently available upon request, but will be uploaded soon.

  Dataset EGAD00001006888

• Exploring the Microbiome-Gut-Brain Axis with Respect to Psychoneurological Symptoms for Children with Solid Tumors

  The human body hosts tens of trillions of microbes, a number 10 times greater than the number of human body cells. The collection of these human-associated microbes and their genomes is called the “human microbiome”. More than 90% of these microbes live in the gastrointestinal (GI) tract, representing 500 species on average. With the development of high-throughput sequencing technology and bioinformatics tools (e.g., 16S ribosomal RNA or 16S rRNA sequencing and shotgun metagenomics analysis), recent progress has been made to elaborate the critical role that the gut microbiome plays in human health and disease. A significant disruption (dysbiosis) of the composition and function of the gut microbiome is associated with carcinogenesis, chemotherapeutic metabolism, and treatment-related symptom toxicities. The current state of science on the gut microbiome in cancer has only recently started in animal models and adults, and has not been well investigated in children diagnosed and treated for cancer, nor with respect to associations with cancer treatment-related toxicities. This proposed study will explore the hypothesis that dysbiosis of the gut microbiome is associated with cancer treatment-related GI and psychoneurological symptoms. We will collect both stool samples (for the gut microbiome) and patient-reported outcomes across chemotherapy.

  Study phs002960

• Samples obtained within X-pand project

  This dataset contains five bone marrow samples and three mobilised peripheral blood ones from different healthy individuals. The three bone marrow samples have been sequence with the 10x multiome kit using Illumina sequencers. The three mobilised peripheral blood ones have been split in two aliquots, one for 10x multiome and the other for 10x CITE-seq. Both libraries types have been sequenced with an Illumina sequencer. Raw data has been processed with cell-ranger and map to the human genome (GRCh38) to obtain the bam files.

  Dataset EGAD50000001108

• Whole-exome sequencing of 20 samples of actinic keratosis (10s) and cutaneous squamous cell carcinoma (10s)

  Whole-exome sequencing of 20 samples of actinic keratosis (10) and cutaneous squamous cell carcinoma (10) was performed to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns. 7 samples were shown to belong to the stem cell-like subclass (4 AK and 2 SCC), 12 - to the keratinocyte-like subtype (6 AK and 6 SCC) and one SCC sample is unclassified (was not included in the methylation analysis). Exome regions were captured using Agilent Low Input Exome-Seq Human v5 kit and sequenced on Illumina Hiseq4000 with paired-end 100-nucleotide reads.

  Dataset EGAD00001003765

• PCNSL single-cell dataset

  This dataset includes 4 samples with scRNA-seq and 3 sample with CITE-seq, scTCR-seq and scBCR-seq.

  Study EGAS50000000474

• arcOGEN_HumanCoreExome-24v1-0_subset_2

  Subset 2 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-24v1-0 with consent for osteoarthritis studies only.

  Dataset EGAD00010000927

• arcOGEN_HumanCoreExome-12v1-1_subset_2

  Subset 2 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-12v1-1 with consent for osteoarthritis studies only.

  Dataset EGAD00010000924

• arcOGEN_HumanCoreExome-12v1-0_subset_2

  Subset 2 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-12v1-0 with consent for osteoarthritis studies only.

  Dataset EGAD00010000923

• Dataset for 9 samples from the study EGAS00001007891

  This dataset links 9 samples from the study "Phosphoproteomics adds value to treatment recommendations in molecular tumor boards" (EGAS00001007891) to the study EGAS00001007934. Further information about the samples can be found in the respective studies.

  Dataset EGAD50000002316

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• Brazilian Thyroid WES

  Medullary thyroid cancer (MTC) is a rare malignant tumor that arises from parafollicular cells. Approximately 8% of thyroid cancer cases are MTC, and about 25% of these have a hereditary component. Incorporating molecular parameters into tumor classification is important. Besides, the presence of pathogenic germline variants can impact directly on cancer prevention. Thus, the aim of this study was to perform whole exome sequencing (WES) on a consecutive series of hereditary RET wild-type MTC patients to identify genetic variants that may be involved in the carcinogenesis of this tumor. WES was performed on 28 patients negative for germline RET pathogenic variants using the NovaSeq 6000 platform. Variant classification followed American College of Medical Genetics and Genomics guidelines.Our study represents a significant advancement in gene discovery for MTC genetics.

  Dataset EGAD50000000086

• SCANDARE ovarian WES data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 91 frozen samples (n = 53 at baseline, n = 31 Post-NAC, n= 7 Recurrence, and n = 62 germline DNA) from 64 ovarian cancer patients using WES technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001658

• Prediction of HLA genotypes using NGS data

  High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate. We compared the availability and accuracy of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, HLAscan, HLA*LA, and Kourami) using 1,275 cases from the 1000 Genomes Project data and created a new HLA-genotyping algorithm combining tools. Then, we assessed the new algorithm’s performance in 39 in-house samples with normal whole-exome sequencing (WES) data and polymerase chain reaction–sequencing-based typing (PCR-SBT) results.

  Dataset EGAD00001007733

• Whole exome and targeted DNA sequencing data for formalin-fixed paraffin embedded tissue from de novo small cell prostatic carcinoma cases

  This dataset consists of 44 compressed paired fastq files, 15 of which are generated from whole exome sequencing, and 29 of which are generated from DNA sequencing using a targeted gene panel capturing the exonic regions of 73 prostate cancer driver genes. Targeted DNA sequencing was performed on an Illumina MiSeq (v3 600 cycle kit), and exome sequencing was done using an Illumina HiSeq 2500 (v4 250 cycle kit) machine. The fastq files are named in accordance with the sample aliases provided, which reflect the pathology of interest to this study (small cell prostatic carcinoma--SCPC), whether it was sequenced using an exome or targeted gene panel, whether the FFPE sample was sourced from tumor or benign tissue (labeled T or B, respectively), and whether there exists multiple samples belonging to a single patient.

  Dataset EGAD00001004139

• CD4+ cell transcriptional profiling by RNA sequencing

  We use next generation sequencing to investigate the different transcriptomes of closely related CD4+ T-cells from healthy human donors to elucidate the genetic programs that underlie their specialized immune functions. Six cell types were included: Regulatory T-cells (CD25hiCD127low/neg with >95% FOXP3+ purity), regulatory T-cells activated using PMA/ionomycin, CD25-CD45RA+ ('naive' helper T-cells), CD25-CD45RO+ ('memory' helper T-cells), activated Th17 cells (>98% IL17A+ purity) and activated IL17-CD4+ T-cells (called 'ThPI'). Poly-T capture beads were used to isolate mRNA from total RNA, and fragment sizes of ~200 were sequenced from both ends on Illumina's genome analyzer. We confirm many of the canonical signature genes of T-cell populations, but also discover new genes whose expression is limited to specific CD4 T-cell lineages, including long non-coding RNAs. Additionally, we find that genes encoded at loci linked to multiple human autoimmune diseases are enriched for preferential expression upon T-cell activation, suggesting that an aberrant response to T-cell activation is fundamental to pathogenesis.

  Study phs000626

• Expression quantitative trait loci influence DNA damage-induced apoptosis in cancer

  Dataset with eQTL and e2QTL metadata. The analyses were performed using CD8+ T cells from 461 healthy European participants stimulated with high doses of 5 different carcinogens to induce early apoptosis. These include Methyl-methanesulfonate (MMS), tert-butyl-hydroperoxide (TBOOH), benzo(a)pyrene-7,8-diol-9,10-epoxide (BPDE), 4-hydroxycyclophosphamide (HC) and UVC radiation.

  Dataset EGAD50000000941

• Timing the Philadelphia chromosome and trajectory to chronic myeloid leukaemia

  We sequence >1000 whole genomes from 9 patients with CML, providing the largest sequencing dataset for this cancer. We reconstruct phylogenetic trees using somatic mutations and infer BCR::ABL1 timing and tumour growth rates. We correlate mutation landscapes and clonal trajectories with clinical features.

  Dataset EGAD00001015353

• NGS sequencing data of archival FFPE tumor tissue

  The aim of the study was to identify mutations in key ovarian cancer genes (BRCA1, BRCA2,TP53, PTEN, ATM, ATR, NF1) in archival fresh-frozen paraffin embedded (FFPE) tumor tissue from platinum-resistant ovarian cancer patients enrolled in the phase I/II GANNET53 clinical trial. From the enrolled 133 patients, archival FFPE tissue was available and DNA was extracted thereof. The DNA samples passing quality control (n=118) were NGS sequenced using the SureSeq™ Ovarian Cancer Panel and the NGS Library Preparation kit (Oxford Gene Technology), which covers all exons of 7 key ovarian cancer genes for single nucleotide variants (SNV) and indels, and the Illumina MiSeq platform. For the paired-end runs, one Read 1 (R1) and one Read 2 (R2) FASTQ file were created for each sample. FASTQ files were compressed and created with the extension \.fastq.gz.

  Dataset EGAD50000001371

• OV04 chemo prediction

  Predicting resistance to chemotherapy using chromosomal instability signatures Joe Sneath Thompson1,2,*, Laura Madrid2,*, Barbara Hernando1,*, Carolin M. Sauer3, Maria Vias3, Maria Escobar-Rey1,2, Wing-Kit Leung2,3, Diego Garcia-Lopez2, Jamie Huckstep3, Magdalena Sekowska3, Karen Hosking4,5, Mercedes Jimenez-Linan5,6, Marika A. V. Reinius3,5,6, Abhipsa Roy2, Omar Abdulle2, Justina Pangonyte3, Harry Dobson2, Amy Cullen2,3, Dilrini De Silva2, David Gómez-Sánchez1,7, Marina Torres1, Ángel Fernández-Sanromán1, Deborah Sanders3, Filipe Correia Martins3,5,6, Ionut-Gabriel Funingana3,4,5, Giovanni Codacci-Pisanelli3,4,8, Miguel Quintela-Fandino1, Florian Markowetz2,3,4, Jason Yip2, James D. Brenton2,3,4,5,6, Anna M. Piskorz#,2,3, Geoff Macintyre#,1,2 1 Spanish National Cancer Research Centre (CNIO), Madrid, Spain 2 Tailor Bio Ltd, Cambridge, UK 3 Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK 4 Department of Oncology, University of Cambridge, Cambridge, UK 5 Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK 6 Cancer Research UK Major Centre - Cambridge, University of Cambridge, Cambridge, UK 7 H12O-CNIO Lung Cancer Clinical Research Unit, Health Research Institute Hospital 12 de Octubre (imas12), Madrid, Spain 8 University of Rome "la Sapienza", Rome, Italy

  Dac EGAC50000000612

• Whole Genome and Exon Capture Sequencing of Bladder Cancers

  One primary bladder cancer and paired peripheral blood sample were subjected to whole genome sequencing on an Illumina HiSeq 2000 platform. This technology was utilized to investigate the genetic basis of a durable remission of metastatic bladder cancer in a patient treated with everolimus, a drug that inhibits the mTOR (mammalian target of rapamycin) signaling pathway. Among the somatic mutations found was a loss-of-function mutation in TSC1 (Tuberous Sclerosis Complex 1), a regulator of mTOR pathway activation. Targeted sequencing using an exon capture and sequencing assay was performed on 13 tumors derived from patients on the same everolimus trial as the index patient and the sequencing data from these tumors is included. TSC1 mutation status was correlated with response to everolimus. The index patient responder tumor and peripheral blood DNA were also subjected to exon capture and sequencing.

  Study phs000535

• Genomic Alterations and Transcriptional Phenotypes in Circulating Tumor DNA and Matched Metastatic Tumor

  We analyzed a prospective cohort of 49 plasma samples obtained before, during, and after treatment from 20 patients with recurrent small cell lung cancer. We conducted cfDNA low-pass whole genome sequencing (0.1X coverage) and exome sequencing (130X coverage) in comparison with time-point matched tumor characterized using whole-exome (130X) and transcriptome sequencing. A direct comparison of cfDNA and tumor biopsy revealed that cfDNA not only mirrors the mutation and copy number landscape of the corresponding tumor, but also identifies clinically relevant resistance mechanisms and cancer driver alterations not detected in matched tumor biopsies. Longitudinal cfDNA analysis reliably tracks tumor response, progression, and clonal evolution. Sequencing coverage of plasma DNA fragments around transcription start sites showed distinct treatment-related changes and captured the expression of key transcription factors n the corresponding SCLC tumors.

  Study phs003689