15070 results for "cancer studies using rna-seq"

in 32.40 milliseconds.

• Avelumab or M7824 for People with Recurrent Respiratory Papillomatosis

  This submission includes genomic data derived from the study of clinical samples from two different phase II trials. These trials evaluated the clinical efficacy and safety of avelumab or M7824 in the treatment of adults with recurrent respiratory papillomatosis (RRP). Subjects with aggressive RRP were treated with three to six doses of avelumab or M7824. Pre-treatment or post-treatment snap frozen papilloma and normal mucosa samples were subjected to whole exome sequencing and bulk RNA-seq. A total of twenty subjects were enrolled and treated. 

  Study phs002373

• Novel Approach to High-Throughput Identification and Characterization of Neoantigens

  This study focuses on the development of novel approach for the screening, identification and characterization of neoantigen-specific T-cell receptors (TCRs). The developed method consists of collecting targeted RNA-Seq from a T-cell specific gene panel via 3' end Illumina sequencing combined to Oxford Nanopore based full-length TCR sequencing post T-cell activation. The data generated during this study demonstrates feasibility of the approach on a Jurkat control cell line as well as T-cells isolated from the blood of 3 independent healthy donors.

  Study phs002372

• Splicing signature analysis of RNU4-2, RNU5A-1 and RNU5B-1

  Pathogenic variants in the snRNA RNU4-2 were recently described as a frequent cause of neurodevelopmental disorders. In our study we further delineate the phenotype associated with RNU4-2 and we also identify pathogenic variants in RNU5A-A and RNU5B-1. Capture-based RNA-Seq were performed to compare splicing pattern between affected and control individuals. A strong signature based on alternative 5' splice site usage was found for RNU4-2 patients, and we suggest an either 5' or 3' signature depending on the variant's localiztion in U5 genes.

  Study EGAS50000000889

• Identification_of_immune_mechanisms_associated_with_the_high_rate_of_relapse_in_patient_with_visceral_leishmaniasis_and_HIV_co_infection

  RNA-seq transcriptomics of whole blood samples from longitudinal follow-up of a cohort of visceral leishmaniasis (VL) patients with and without HIV coinfection, from active disease through apparent cure and potential relapse. Analysis will identify potential correlates of relapse to identify immune mechanisms underlying the high rate of relapse in HIV/VL coinfection. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003465

• Y90 radioembolization followed by intravenous Nivolumab for advanced hepatocellular carcinoma

  To evaluate the efficacy of combination therapy with ICI and RT in patients, a Phase II trial (CA209-678) was conducted to investigate the efficacy and safety of Y90-RE followed by nivolumab in patients with advanced HCC (NCT03033446, n = 36). Interestingly, the ORR was found to be 30.6% in all patients and 43.5% when restricted to patients with only intrahepatic tumors, suggesting possible synergism between Y90-RE and ICI. Here we present whole exome sequencing (WES) and RNA-seq data for 33 patients treated with Y90 radioembolization followed with Nivolumab.

  Study EGAS00001006834

• scRNA-seq and scTCR-seq data IMCISION

  We performed single cell RNA and TCR sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and on-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset.

  Study EGAS00001007368

• Low T cell diversity is associated with poor outcome in bladder cancer - Single cell RNAseq and TCRseq data

  T cells are crucial effector cells in the endogenous defense against cancer, yet the clinical impact of their quantity, diversity, and dynamics remains underexplored. In this study we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients (n samples = 8). The goal was to investigate T cell subtypes of expanded and non-expanded T cell clones in blood and in tumors.

  Study EGAS50000000938

• Somatic_mutation_in_skin_epidermis__SMS_

  We aim to assess the range and depth of mutations in genes linked with cancer in skin epidermis surrounding lesions which are undergoing surgical removal. Patient history will be collected to provide a detailed outline of tumour type (including histology), skin type, and sunlight exposure. We will perform ultra-deep targeted sequencing using genes implicated in cancer to try and understand the background of mutations surrounding these lesions

  Study EGAS00001002165

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• SMRT-seq

  In this study, we enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model.

  Dataset EGAD00001006875

• ChIP-sequencing

  Raw reads from ChIP- [Anti-Histone H3 (acetyl K27) (Abcam, ab4729)] and input sequencing of EBV transformed lymphoblastoid cells from three carriers of TET2 mutation (Ly9, Ly11 and Ly14) and two wild-type (Ly8 and Ly10) family members using Illumina HiSeq Rapid paired-end 60 bp sequencing.

  Dataset EGAD00001004781

• scATAC-seq of first and second trimester human gonads - HUGODECA dataset

  Comprehensive map of first- and second-trimester gonadal development in humans using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays, and imaging. ArrayExpress Accession: E-MTAB-10570

  Dataset EGAD00001009387

• Population Architecture using Genomics and Epidemiology (PAGE): Multiethnic Cohort (MEC)

  The Multiethnic Cohort (MEC) has established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factors (e.g., diet, smoking, physical activity), biomarkers and clinical data for five racial/ethnic groups. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. Within the PAGE investigation, the MEC proposes to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). The specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 5) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356.

  Study phs000220

• Improved T Cell Immunity Following Neoadjuvant Chemotherapy in Ovarian Cancer

  This study characterized the evolution of the peripheral immune cell function and composition across the course of standard of care platinum and taxane chemotherapy in ovarian cancer using bulk and single cell transcriptomic approaches. Serial blood samples were collected from ten patients with advanced high-grade serous ovarian cancer treated with chemotherapy. Single cell sequencing was performed on five patients' samples collected before the initiation of chemotherapy and after the third cycle of chemotherapy.

  Study phs002862

• Whole-exome sequencing profiling of patients with metastatic prostate cancer at VHIO

  Metastatic prostate cancer (mPC) is enriched for homologous recombination repair (HRR) gene alterations, which have prognostic and predictive value. Routine clinical implementation of next-generation sequencing (NGS) is still limited. We investigated the association between genomic and functional loss of HRR, using NGS and a RAD51 immunofluorescence (RAD51-IF) iprimary or metastatic biopsies from patients with stage IV prostate cancer. Whole-exome sequencing was pursued for paired tumor-normal samples.

  Study EGAS50000000736

• Identification of mutations and structural rearrangements in plasma DNA form metastatic prostate cancer patients

  In this study we analysed patients with metastatic prostate cancer to scan their tumor genomes noninvasively in plasma DNA. We enriched 1.3 Mbp of seven plasma DNAs (4 CRPC cases: CRPC1-3 and CRPC5; 3 CSPC cases: CSPC1-2 and CSPC4) including exonic sequences of 55 cancer genes and 38 introns of 18 genes, where fusion breakpoints have been described using Sure Select Custom DNA Kit.

  Study EGAS00001000453

• Viral Respiratory Pathogens Genetics

  The overall purpose of this study is to investigate the host genetic factors in response to influenza virus infection, with the focus on influenza vaccination in the first substudy "Adult Influenza Vaccine Genetics" and with the focus on influenza natural infection and other acute respiratory infections (ARIs) in the second substudy "Acute Viral Respiratory Infection Genetics". In the first substudy, healthy adults were enrolled in 2008 (male cohort) and 2010 (female cohort) and immunized with seasonal influenza vaccine. In the second substudy, healthy adults were invited to enroll to be followed for acute respiratory illness through two consecutive influenza seasons 2009-2010 and 2010-2011. Peripheral blood genomic DNA samples were collected from all the subjects, and time-series RNA and serum samples were obtained pre- and post- immunization/infection. Genotyping was carried out on peripheral blood genomic DNA samples using Illumina HumanOmniExpress-12 v1 arrays. Peripheral blood RNA samples obtained at each visit were analyzed using Illumina Human HT-12 (for all the samples) and HiSeq 2000 (for 130 samples in the "Acute Viral Respiratory Infection Genetics" study). Serum specimens were tested using hemagglutination-inhibition (HAI) antibody assay for Influenza H1N1, H3N2, and Influenza B strains. A detailed description of each substudy is provided under their own pages below and via the grouping tool in the right-hand box: phs000635 Adult Influenza Vaccine Genetics phs001031 Acute Viral Respiratory Infection Genetics

  Study phs001030

• Genome_Diversity_in_Africa_Project__Uganda

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics

  Study EGAS00001002523

• Paired-end RNA-seq analysis of the 3D evolution of glioma cell populations. Part 1.

  Dataset includes 160 double-stranded RNAseq libraries collected from 16 patients with adult diffuse glioma. The majority of these samples were spatially-mapped during sample collection, enabling the genomic information derived from them to be mapped in 3D space.

  Dataset EGAD00001005222

• ABHD11 Autoimmunity Study DAC

  This DAC oversees controlled access to human RNA-seq data generated as part of the project “ABHD11 inhibition and T cell function in autoimmunity” at Swansea University. The DAC will evaluate and approve access requests based on scientific merit and alignment with participant consent. Data requests will be considered from academic researchers and healthcare professionals working on immunology or autoimmunity.

  Dac EGAC50000000750

• Islet RFX6 Study Manuscript Data

  This submission includes raw FASTQ files (for bulk RNA-seq and 10X joint snATAC+snRNA multiome profiling experiments), sample phenotype files, and genotypes for the data included in the manuscript.

  Dataset EGAD00001008777

• Gene expression in human monocyte differentiation

  This dataset consists of RNA-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. In total, it includes 63 samples.

  Dataset EGAD00001007956

• Single cell mRNA sequencing of primary GBM - SF 10281

  We collected fresh tissue from an untreated GBM (SF10281) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003114

• Single cell mRNA sequencing of primary GBM - SF 10679

  We collected fresh tissue from an untreated GBM (SF10679) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003113

• Single cell mRNA sequencing of primary GBM - SF 10592

  We collected fresh tissue from an untreated GBM (SF10592) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003112

• Microinjection of hIPSC-derived intestinal organoids with Salmonella Typhimurium

  To generate an RNA-Seq dataset for organoids apically stimulated with Salmonella Typhimurium.These data are part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001001363

• Single-Nuclei RNA-seq of healthy (post-mortem) and temporal lobe epilepsy (biopsy) subjects.

  To identify dysfunctional neuronal subtypes underlying seizure activity in the human brain, we have performed single-nucleus transcriptomics analysis of >110,000 neuronal transcriptomes derived from temporal cortex samples of multiple temporal lobe epilepsy and non-epileptic subjects.

  Dataset EGAD00001006575

• Genome Wide Association Study of Chronic TMD: Discovery Phase

  The OPPERA project is investigating effects of genetic, physiological, psychological and clinical factors on the risk of developing painful temporomandibular disorder (TMD). This case-control study is a discovery-phase genome wide association study that aims to identify commonly-occurring genetic variants associated with chronic TMD. It represents the first step in a series of studies that seek to identify the genetic background of TMD. For related phenotype and targeted genotype data, please see additional studies from the OPPERA project at dbGaP phs000761).

  Study phs000796

• Genome-Wide Association Analysis of Biomarkers in the InCHIANTI and BLSA

  Version 1 The aim of this study was to identify gene(s) associated with serum iron concentrations. This dataset contains the results from a meta-analysis of 1919 subjects from the InCHIANTI and Baltimore Longitudinal Study of Aging (BLSA). Both studies are population based prospective studies that evaluate the contributors of normal aging. Version 2 We performed genome wide analysis of 93 circulating biomarkers in the InCHIANTI study of 1210 individuals, after imputation from the 1000 genomes project.

  Study phs000215

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

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

  Dataset EGAD00001003821

• To profile the landscape of sebaceous tumours_RNAseq

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Dataset EGAD00001015368

• Evaluation_of_size_selection_on_cancer_specific_sequencing_libraries

  A couple of previously characterized and sequenced libraries will be repeated using a couple of differing size selection criteria and skim sequenced using an Illumina HiSeq. The resulting sequence will be analyzed to determine the optimal DNA library size for our specific downstream analysis.

  Study EGAS00001000293

• Korean Young Age Diffuse Gastric Cancers

  The incidence of diffuse gastric cancers (DGC) remains steadily high, but relatively small numbers of DGCs have been evaluated with whole exome sequencing (WES). Clinicopathological features of DGC vary according to age, but the molecular basis for these variations is unclear. To identify genomic alteration in this unique subset of gastric cancers, whole exome and SNP6 analyses were performed using frozen cancer tissue. The same analyses were also performed using blood of the same patients.

  Study EGAS00001001711

• The data access committee for Detection and characterization of lung cancer using cell-free DNA fragmentomes

  Dac EGAC00001002184

• Cancer-Unknown-Primary-Array-Methylation-H021

  CUP samples using 850k

  Dataset EGAD00010002036

• Estimating transcription factor variability in PC-9 cells using scRNA-seq

  PC-9 cells were barcoded following protocol from Chang et al. Nature Biotech. 2021, which does not affect downstream analysis. PC-9 cells were trypsinized into single-cell suspensions and processed using Chromium Single Cell Gene Expression 3’ Library and Gel Bead Kit V2.0 following the manufacturer’s instructions (10X Genomics). Cells were counted and checked for viability using Vi-CELL XR cell counter (Beckman Coulter), and then injected into microfluidic chips to form Gel Beads-in-Emulsion (GEMs) in the 10X Chromium instrument. Reverse transcription was performed on the GEMs, and RT products were purified and amplified. Expression libraries were made from the cDNA and profiled using the Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified with Kapa Library Quantification Kit (Kapa Biosystems). Illumina HiSeq2500 (Illumina) was used to sequence the libraries.

  Dataset EGAD00001011041

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 26 patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Study EGAS50000000146

• Targeted sequencing of genes recurrently mutated in AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Dataset EGAD00001000606

• Dataset for hepatopancreaticobiliary_malignancy-RNA

  Rare cancer sequencing data of 119 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008863

• Locally advanced prostate cancer cohort

  Fastq files from RNA sequencing and BAM files from tNGS of normal and tumor samples from 17 patients from the locally advanced prostate cancer cohort.

  Dataset EGAD50000002380

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

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

  Dataset EGAD00001003999

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of 10x Genomics 5'prime single-cell RNA sequencing of 40 tumor biopsy samples or triple negative breast cancer. Samples are taken before and after immuno checkpoint blockade treatment. Processed according the 10X genomics protocol, sequenced on Immumina NovaSeq6000. Raw sequencing reads are further processed with Cellranger 3.0 to get gene-expression matrices.

  Study EGAS50000000527

• Fred Hutchinson Cancer Research Center - Whole-Exome Sequencing of Hereditary Prostate Cancer Families

  The specific aim of this study is to identify hereditary prostate cancer (HPC) susceptibility genes using a novel study design, whereby whole-exome sequencing will be undertaken on multiple affected relatives from 19 HPC families, in which ≥ 3 affected relatives were diagnosed with clinically aggressive and/or early onset prostate cancer (PC). While whole-exome sequencing of unrelated affected individuals would result in hundreds of candidate disease variants, this family-based, aggressive/early onset phenotype approach will provide an enriched genetic background for discovery and significantly reduce the number of candidate mutations that will require follow-up. Findings from this pilot study will immediately be followed-up to confirm whether candidate mutations found in each family segregate with disease in the remaining unscreened relatives. As part of this pilot study, we aim to: Perform whole-exome sequencing on 80 affected and 11 unaffected relatives from 19 HPC families that have multiple men diagnosed with an aggressive and/or early onset disease phenotype using the Illumina HiSeq platform; and, Analyze sequencing data using BWA, SAMtools and SeattleSeq to prioritize candidate HPC mutations that segregate with aggressive and/or early onset disease in affected relatives.

  Study phs000350

• Non-small cell lung cancer targeted sequencing

  Targeted sequencing of non-small cell lung cancer samples. BAM files of paired end reads aligned to hg19 using BWA MEM v0.7.1573. This targeted panel covers 370 genes of clinical relevance in non-small cell lung cancer.

  Dataset EGAD00001007918

• Characterization of High-Grade Serous Ovarian Cancer Subtypes via Single-Cell and Spatial-Transcriptomics Profiling

  We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors. The initial dataset (added October, 2020) contains 3 samples (3 individuals). The next dataset (added November, 2022) contains 34 samples from 8 individuals. The samples in the second dataset were sequenced in five different ways: 1) rRNA depletion and bulk RNA sequencing of tumor chunks, 2) rRNA depletion and bulk RNA sequencing of dissociated cells, 3) poly-A capture and bulk RNA sequencing of dissociated cells, 4) poly-A capture and scRNA sequencing of dissociated cells, 5) barcoding and pooling cells and scRNA sequencing (2 pools of 4 samples each). The third dataset (added June, 2024) contains data from one spatially resolved transcriptomics experiment (4 samples, one per Visium capture area, describing one tumor from one individual) and scRNA sequencing on 5 samples (5 individuals).

  Study phs002262

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• Enhancing OSCC Prediction: The Prognostic Power of WPOI and Tumor Budding, and the Limited Impact of Molecular Resection Margins

  This dataset contains sequences with results of mutations observed in patients with oral squamous cell carcinoma. Mutations were detected by NGS in tumor tissue, tumor margins, and peripheral blood as a healthy control. Study was using a panel of 88 cancer-related genes, which were selected based on a literature search.

  Study EGAS50000000074

• Variant analysis on FFPE specimen from NSCLC patients (FoundationOne CDx)

  This study assessed the presence of somatic variants via the FoundationOne CDx panel of commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing panels. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001139

• Prospective Lynch Syndrome Database materials

  The Prospective Lynch Syndrome Database data. These data contain necessary clinical tables to reproduce the previous PLSD papers using the clinical tables for individual level cancer incidence by age, sex and MMR gene affected. The tables contain the demographics, individual cancers at given age, and therapeutic and prophylactic surgeries removing total or partial organs.

  Study EGAS50000001715