11932 results for "cancer rna-seq"

in 57.00 milliseconds.

• Young Boost Trial for Breast Cancer patients

  The Young Boost Trial (YBT, YOUNG BOOST / BOOG 2004-01 (Borstkanker) | Kanker.nl investigated the optimal radiation dose for breast cancer patients aged 50 years or younger, treated with breast-conserving therapy (BCT). In this randomized study, participants were assigned to receive either a 26 Gy or a 16 Gy radiation boost, with the primary endpoint being local recurrence. To explore potential predictive biomarkers of treatment response in this patient group, whole exome sequencing (WES) was performed on tumor samples to identify genetic factors that could guide personalized treatment strategies and improve clinical outcomes for these young breast cancer patients.

  Study EGAS50000000797

• 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

• Genomics_of_acral_lentiginous_melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003740

• Exceptional Outcomes in a Phase Ib Study Combining PARP and MEK Inhibition, With or Without Anti-PD-L1, for BRCA-Wildtype Platinum-Sensitive Recurrent Ovarian Cancer

  To evaluate regimens combining PARP and MEK inhibition, with or without PD-L1 inhibition, for BRCA-wildtype platinum-sensitive recurrent ovarian cancer (PSROC).

  Study EGAS00001007496

• Primary ER-positive Breast Cancer Treated with Neoadjuvant Letrozole

  These are tumor biopsies and corresponding normal samples from patients with early stage ER+/HER2- breast cancer who had received the aromatase inhibitor letrozole for 10-21 days prior to surgery.

  Study phs000857

• The dataset for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  The dataset for “Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers” includes 409 cram files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000000695

• Transcriptome sequence data from a metastatic breast cancer patient

  Transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003690

• Molecular Classification of Hormone Sensitive and Castration Resistant prostate cancer, using non-negative matrix factorization molecular subtyping

  We aim to identify molecular subtypes of prostate cancer using consensus non-negative matrix factorization and correlate these with existing biomarkers to inform future immunotherapeutic strategies.

  Study EGAS00001006204

• Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA.

  3784 whole genome sequencing bam files were generated from plasma cell-free DNA of healthy individuals and patients with cancer. Paired reads were mapped to hg19 human reference genome.

  Study EGAS00001006553

• RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Dataset EGAD00001015534

• Low-coverage whole-genome sequencing of cancer and healthy plasma circulating DNA

  Plasma samples from patients with melanoma (stage II/III/IV) and breast cancer (stage IV) as well as healthy individuals were subjected to low-coverage whole-genome sequencing (less than 10x average depth). This dataset contains raw fastq files from 39 breast cancer, 127 melanoma and 42 healthy control plasma samples.

  Dataset EGAD00001011817

• The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer

  The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer includes 538 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001005339

• Identification_and_functional_validation_of_driver_mutations_in_colorectal_cancer

  Targeted exome sequencing of human colorectal cancers for the identification of novel cancer drivers.

  Study EGAS00001000044

• Breast Cancer Matched Pair Cell Line Whole Genomes

  Breast Cancer Matched Pair Cell Line Whole Genomes

  Dataset EGAD00001000130

• Yale Policy for head and neck cancer and HPV clinical trials

  Yale Policy for human controlled access data associated with head and neck cancer and HPV clinical trials

  Dac EGAC50000000403

• Single cells of colorectal cancer organoids

  Dataset contains 854 single cell sequenced colorectal cancer organoids.

  Dataset EGAD00001005422

• Whole_Genome_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008280

• Single_cell_ATAC_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008283

• Single_cell_ATAC_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008279

• Single_cell_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008281

• Bulk_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008282

• Bulk_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008278

• FFPE Normal Panel V3 Cancer Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Dataset EGAD00001001122

• 108 samples liver cancer and normal controls (54 pairs), whole exome sequencing

  liver cancer paired with normal controls, viral and non-viral origin

  Dataset EGAD00001006005

• Single Cell RNAseq of PBMC from renal cancer patients

  Single Cell RNAseq of PBMC from renal cancer patients

  Dataset EGAD00001006175

• Whole Genome Scan for Pancreatic Cancer Risk in the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium (PanScan)

  Within the framework of the NCI-sponsored Cohort Consortium, investigators from 12 prospective epidemiologic cohorts formed the Pancreatic Cancer Cohort Consortium in 2006. This study, also known as "PanScan", is funded by the National Cancer Institute (NCI) and involves conducting a genome-wide association study (GWAS) of common genetic variants to identify markers of susceptibility to pancreatic cancer. In 2007, the study was expanded to include 8 case-control studies. The study team includes scientists from the cohorts comprising the Consortium, the NCI and the Pancreatic Cancer Case Control Consortium (PanC4). PanScan I and II were conducted in 12 cohort studies and 8 case-control studies, leading to the discovery of four novel regions in the genome associated with risk for pancreatic adenocarcinoma. The third phase of PanScan (PanScan III) was conducted using recently identified incident pancreatic cancer cases drawn from fourteen cohorts from the cohort consortium, including nine prospective cohorts who participated in PanScan I, and five newly joined cohorts. The nine cohort studies that participated in PanScan I and had new genotyping of cases in PanScan III include ATBC, CPS-II, EPIC, HPFS, NHS, PHS, PLCO, SMWHS, and WHI; the five newly joined cohort studies include the Agricultural Health Study (AHS), the Multiethnic Cohort Study (MEC), the Melbourne Collaborative Cohort Study (MCCS), the Vitamins and Lifestyle Study (VITAL), and Selenium and Vitamin E Cancer Prevention Trial (SELECT). In addition to the cases from cohorts, we also included cases from the Gastrointestinal Cancer Clinic of Dana-Farber Cancer Institute Study (DFCI-GCC); from the University Hospital in Heidelberg, Germany, which is part of a larger European clinical case-control study (PANDoRA); and from clinic-based cases from eastern Spain (PANKRAS-II). The dbGaP datasets available include all subjects previously made available from PanScan I and II, plus 1,582 new incident pancreatic cancer cases of European descent from prospective cohorts, case-control studies or case series (genotyped as part of PanScan III). Also included are 61 pancreatic cancer cases and 67 control subjects from PanScan I as well as 173 pancreatic cancer cases from PanScan III of Asian ancestry from the Shanghai Men's and Women's Health Study (Supplemental Table 10, Wolpin et al. (Nat Genet, 2014)). The control population used in the analysis for the Wolpin et al. manuscript included cancer-free individuals from the prospective cohorts that contributed pancreatic cancer cases to PanScan III and controls from the Spanish Bladder Cancer SBC/EPICURO study that were previously genotyped using the OmniExpress, Omni 1M or Omni 2.5M SNP arrays. The data from these control subjects were posted to dbGaP under the GWAS in which they were initially genotyped and will not be made available in duplicate under this dbGaP study.The summary statistics for PanScan I-III were generated as detailed in Wolpin BM. et al., Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer, Nature Genetics 2014; 46(9):994-1000 (https://www.nature.com/articles/ng.3052), and Klein, A. et al., Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer, Nature Communications, 2018;9(1):556 (https://www.nature.com/articles/s41467-018-02942-5). The dataset includes results from an association study of 5,117 individuals diagnosed with pancreatic ductal adenocarcinoma (PDAC) and 8,845 control individuals, or a total of 13,962 subjects of European ancestry (as compared to the genotype and phenotype information under this project that includes 9,437 individuals (PanScan I and II PDAC case and control individuals and PanScan III PDAC cases only). This is due to the fact that PanScan III “borrowed” GWAS data from control individuals genotyped separately from the PanScan GWAS project and are therefore not included as raw genotypes in phs000206.v5.p3. Association analysis was performed separately for PanScan I-II and PanScan III, followed by a meta-analysis of the two datasets. Results were filtered based on a minor allele frequency (MAF) < 0.01, an imputation INFO score < 0.3 and a heterogeneity P-value < 1x10-10 leaving a total of 9,758,390 variants. Columns in the summary statistics dataset are as follows: ID: variant rsIDChr: chromosome numberPosition: position in the chromosome, genome build GRCh37/hg19MarkerName: variant identifierAllele1: reference alleleAllele2: alternative alleleFreq1: allele frequency for allele2FreqSE: standard error of the allele frequencyMinFreq: the minimal allele frequency across studiesMaxFreq: the max allele frequency across studiesEffect: effect size for allele2StdErr: standard errorP-value: meta-analysis p-valueDirection: summary of effect direction for each studyHetISq: I^2 statistic which measures heterogeneity on scale of 0-100%HetChiSq: chi-squared statistic in simple test of heterogeneityHetDf: degrees of freedom for heterogeneity statisticHetPVal: P-value for heterogeneity statistic

  Study phs000206

• Comprehensive NGS Profiling to Enable Detection of ALK Gene Rearrangements and MET Amplifications in Non-Small Cell Lung Cancer

  We evaluate the analytical performance of the PGDx™ elio™ tissue complete assay, a 505 gene next-generation sequencing (NGS) tissue-based assay, that has now been FDA-cleared for use by physicians to help guide treatment decisions for cancer patients, using a NSCLC cohort of 38 patients.

  Study EGAS50000000010

• CALGB 80303:Genome-Wide Association Study of Advanced Pancreatic Cancer Patients - A Randomized Phase III trial of Gemcitabine Plus Bevacizumab versus Gemcitabine Plus Placebo in Patients with Advanced Pancreatic Cancer

  CALGB 80303 was a randomized, phase III study in advanced pancreatic cancer patients treated with Gemcitabine plus either Bevacizumab or placebo. No difference in overall survival (OS) was observed between the two arms. We prospectively collected germline DNA and conducted a genome-wide association study (GWAS).

  Study phs000250

• Genomic evolution of pancreatic cancer at single-cell resolution

  This project assesses genomic evolution of pancreatic cancer using the Mission Bio Tapestri platform and Whole Exome Sequencing. The Mission Bio Tapestri platform is a single-cell DNA sequencing platform using a targeted gene panel to assess SNV/CNV. Several samples, including primary and metastatic tissue, were used to investigate changes at single-cell resolution.

  Study EGAS50000001351

• Identification of drug resistance genes in cancer cell lines by insertional mutagenesis

  Our aim is to identify genes involved in resistance to anti-cancer therapies. In order to do this we have taken advantage of a lentiviral vector (LV)-based insertional mutagen to mutagenize cancer cell lines. LV-transduced cell lines were then treated with anti-cancer therapies and the emergence of resistant clones scored. DNA from pools of resistant clones was collected, subjected to custom capture by baits designed against the LV sequence, and then sequenced to identify the LV-genomic junction. We hope that the identification of recurrently targeted genes in resistant cell population will allow us to identify genes that mediate drug resistance.

  Dataset EGAD00001002207

• AVENIO Expanded ctDNA panel sequence alignments (BAMs) from plasma DNA of BC, CRC and NSCLC patients

  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 48 plasma samples from patients with breast, colorectal and non-small cell lung cancer. After sequencing 150bp paired-end, reads were aligned to the hg38 genome with the AVENIO Oncology Analysis Software (version 2.0). These files are the deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Dataset EGAD00001006301

• Research on the identification of cancer stem cells for peidatric and adult malignancies.

  In recent years, "cancer stem cells" have been reported to exist in many cancers. Many reports have shown that they are the main cause of cancer recurrence. The aim of this study is to test whether cancer stem cells can be identified using patient samples. We will perform omics analysis of rare pediatric cancers by integrating genomics, transcriptomics, proteomics and metabolomics, including somatic and germline mutations, to deepen our understanding of the biological characteristics of the target disease. Based on the knowledge gained and clinical information from patients, we will conduct preclinical pharmacological studies using mouse models and in vitro models to investigate the therapeutic effects of novel therapeutic agents and novel therapeutic strategies such as cellular therapies.

  Study JGAS000623

• NCI Expanded Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) expanded genome-wide association study (GWAS) of renal cell carcinoma (RCC) was a 2nd GWAS of this cancer performed by NCI to further investigate common genetic variants associated with RCC risk. The GWAS includes 2,781 cases and 2,940 controls of European background from 13 studies conducted in the US and Finland (10 cohorts, 2 case series, 1 hospital biorepository), scanned using the Illumina OmniExpress and Omni2.5 SNP arrays. SNP-level results from this GWAS were combined by meta-analysis with results from the earlier NCI RCC GWAS (phs000351.v1.p1; 1,311 cases and 3,424 controls) and others conducted by the International Agency for Research on Cancer (scan 1: 2,438 cases and 5,071 controls; scan 2: 2,781 cases and 2,940 controls), The University of Texas MD Anderson Cancer Center (893 cases and 556 controls) and the Institute for Cancer Research, UK (944 cases and 4,024 controls). Only data from the second NCI scan are included in this dbGaP submission. Data from 239 cases and 229 controls from this scan will be deposited in dbGaP separately under the Women's Health Initiative (phs000200).

  Study phs001736

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

  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, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure 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.

  Study EGAS00001003520

• PDAC organoid genomic heterogeneity

  The establishment of patient-derived pancreatic cancer organoid culture in recent years creates an exciting opportunity for researchers to perform a wide range of in vitro studies on a model that closely recapitulates the tumor. Among the outstanding questions in pancreatic cancer biology are the causes and consequences of genomic heterogeneity observed in the disease. However, to use pancreatic cancer organoids as a model to study genomic variations, we need to first understand the degree of genomic heterogeneity and its stability within organoids. Here, we used single-cell whole-genome sequencing to investigate the genomic heterogeneity of two independent pancreatic cancer organoids, as well as their genomic stability with extended culture. Clonal populations with similar copy number profiles were observed within the organoids, and the proportion of these clones was shifted with extended culture, suggesting the growth advantage of some clones. However, sub-clonal genomic heterogeneity was also observed within each clonal population, indicating the genomic instability of the pancreatic cancer cells themselves. Furthermore, our transcriptomic analysis also revealed a positive correlation between copy number alterations and gene expression regulation, suggesting the “gene dosage” effect of these copy number alterations that translates to gene expression regulation.

  Study EGAS00001006782

• 300BCG study ATAC-seq data: human population variation of trained immunity

  ATAC-seq dataset for the paper: Title Multi-omics analysis of human population variation in immune function and in vivo response to BCG vaccination Abstract Immune responses are tightly regulated, yet highly variable between individuals. To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live attenuated vaccine induces not only an adaptive immune response against tu-berculosis, but also triggers innate immune activation and memory. We established personal immune profiles and chromatin accessibility maps over a time course of BCG vaccination in 323 individuals. This large resource uncovered genetic and epigenetic predictors of baseline immunity and BCG vaccine response. We found that BCG vaccination enhances the innate immune response only in individuals with dormant immune states at baseline, suggesting that exogeneous induction of trained immunity is not a universal booster of innate immunity, but specifically elevates weak innate immune responses. This study advances our understanding of BCG’s heterologous immune-stimulatory effects and trained immunity in humans. Moreover, our results highlight the value of epigenetic cell states as an “endo-phenotype” that connects immune function with genotype and the environment.

  Dataset EGAD50000000123

• ScRNA-seq of human kidney immune cells of patients with ANCA-associated glomerulonephritis, Lupus Nephritis against a healthy nephrectomy control

  ANCA-associated glomerulonephritis (AGN) associates with a high risk of end-stage kidneydisease. The role of kidney immune cells in local inflammation remains unclear. This study investigates kidney immune cell diversity and function. Kidney tissue from AGN patients (n=5) and a lupus nephritis (LN) patient (n=1) were aquired during a biopsy procedure for a clinical indication. Needle-core biopsies were obtained for histopathological examination, and an additional pass was performed to retrieve kidney tissue for scRNA-seq. Healthy kidney tissue (n=1) was obtained from a kidney that was surgically removed do tue due to a (non-invasive) papillary urothelial carcinoma. Immediately after collection, kidney tissue was processed into a single-cell suspension and sorted using a 4-color flow cytometry panel to isolate living, CD45+immune cells. To aid in the multi-omic characterization, surface markers and T and B cell repertoires were sequenced in 2 samples (1 AGN patient and the nephrectomy control). These samples were incubated with an oligo-antibody TotalSeq-C cocktail containing 130 unique cell surface antigens.

  Dataset EGAD50000000229

• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• Feasibility study of enzymatic methylation sequencing of cell-free DNA from cerebrospinal fluid of pediatric brain tumors for classification

  Array-based DNA methylation profiling is the gold standard for molecular classification of brain tumors. However, it relies on significant amount of input DNA extracted from surgical tissue, thus limiting its use for tumors where biopsy is challenging or limited in quantity. Cell-free tumor DNA (cfDNA) in cerebrospinal fluid (CSF) presents alternative opportunities for brain tumor diagnosis and disease monitoring following treatment. Novel enzymatic DNA methylation sequencing (EM-seq) methods may allow us to overcome input DNA limitations and accurately quantify methylation from cfDNA for tumor classification.

  Study EGAS50000000871

• scRNA seq and scTCR seq data from 5 melanoma patients

  The Chromium Controller and Chromium X platfor of 10X Genomics were used for single cell partitioning and barcoding. Each cell's transcriptome was barcoded during reverse transcription, pooled cDNA was amplified and Single Cell 5' Gene Expression (GEX), V(D)J and Feature Barcode (FB) Libraries were prepared according to the manufacturer's protocols (CG000330 and CG000331, 10X Genomics). All libraries were quantified and normalized on library QC data generated on the Bioanalyzer system according to manufacturer's protocols (G2938-90321 and G2938-90024, Agilent Technologies). Based on the expected target cell counts, a balanced library sub-pool of samples was compsed for SC5'GEX, V(D)J and FB libraries. Library sub-pools were quantified by qPCR, accodring to the KAPA Library Quantification Kit Illumina(R) Platforms protocol (KR0405, KAPA Biosystems). Based on qPCR results a final sequencing pool was composed. Paired end sequencing was performed on a NovaSeq 6000 Instrument (Illumina) using NovaSeq 6000 Reagent Kits v1.5 100 cycles (cat. no. 20028401, 20028319, 20028316 Illumina), using 28 cycles for Read 1, 10 cycles for Read i7, 10 cycles for Read i5 and 90 cycles for Read 2.

  Dataset EGAD50000001155

• M116 scRNA-seq

  scRNA-seq was performed using Chromium Next GEM Single Cell 3’ Kit v3.1 (10X Genomics) according to the manufacturer’s instructions. Briefly, M116's PBMCs were thawed and quantified in order to calculate the number of cells to be loaded. Then, barcoded Single Cell 3ʹ Gel Beads, a master mix containing PBMCs, and Partitioning Oil were combined onto the Chromium Next GEM Chip G to generate Gel Beads-In-Emulsion (GEMs), where polyadenylated mRNAs were reverse transcribed. This way, all generated cDNAs from the same cell shared a common 10X Barcode. Following the reverse transcription, GEMs were broken and cDNAs were amplified and cleaned up with SPRIselect beads (Beckman Coulter®). Next, a portion of these cDNAs were enzymatically fragmented and subjected to adaptor ligation before using them as a PCR template for the incorporation of i5/i7 indexes. Finally, libraries were purified with SPRIselect beads, quantified and quality checked by using the 2200 TapeStation (Agilent®), and subjected to paired-end 150-bp sequencing (Novaseq systems, Illumina®) following standard practices at external facilities (Novogene®). Files types included in this dataset are raw Fastq files.

  Dataset EGAD50000001289

• Ibrutinib induces a global chromatin reorganisation in chronic lymphocytic leukaemia

  Chronic lymphocytic leukaemia (CLL) is the most common haematological malignancy in developed countries. Ibrutinib (PCI-32765), a specific and irreversible inhibitor of Bruton's Tyrosine Kinase (BTK) represents a major step forward in the treatment of CLL. We have undertaken a detailed analysis of the changes happening to the chromatin structure in CLL cells from patients continuously receiving oral doses of ibrutinib. ChIP-seq has been performed for H3K4me3, H3K27ac, H3K27me3 and EZH2 . We observed that Ibrutinib-dependent lymphocytosis correlates with a global and transient recruitment of EZH2 to active cis-regulatory elements and increased H3K27me3.

  Study EGAS00001002827

• Selective advantage of mutant stem cells in human clonal hematopoiesis is associated with attenuated response to inflammation and aging

  In this study we characterised the consequences of DNMT3A- and TET2-mutations in human clonal haematopoiesis. We screened 195 bone marrow samples for mutations by targeted DNA sequencing, and sequenced 99 paired peripheral blood samples to compare mutation detection between bone marrow and blood. We performed single-cell analysis with TARGET-seq+ on 13 samples (4 controls and 9 clonal haematopoiesis samples), which combines single-cell genotyping for targeted mutations with whole transcriptome sequencing on FACS sorted cells. Single-cell genotyping and transcriptomes were sequenced separately and linked by common single-cell identifiers.

  Study EGAS00001007358

• Dr. Fatima Mechta-Grigoriou, PhD, DR1 Head of Stress and Cancer Laboratory Deputy Director Genetic and Biology of Cancer Dpt Institut Curie - Inserm U830

  Dac EGAC00001000581

• ICGC prostate cancer whole genome sequencing

  ICGC prostate cancer whole genome sequencing

  Dataset EGAD00001000306

• Converging and evolving immuno-genomic routes towards immune escape in breast cancer

  Data access committe for the project: Converging and evolving immuno-genomic routes towards immune escape in breast cancer

  Dac EGAC50000000074

• Thoracic Patient-Derived Xenografts

  Targeted capture sequencing of 341 cancer associated genes in thoracic patient-derived xenografts.

  Study phs001192

• scRNAseq of ovarian cancer patient derived organoids

  scRNAseq of ovarian cancer patient derived organoids with or without estradiol

  Dataset EGAD50000002058

• Whole exome sequencing of 103 pairs BLCA-CN

  We sequenced 50M exomes of 103 pairs bladder cancer of chinese

  Study EGAS00001000677

• Genentech gallbladder cancer study - whole genome sequencing

  Genentech gallbladder cancer study - whole genome sequencing

  Dataset EGAD00001004855

• Plasma methylome of metastatic prostate cancer

  The dataset contains plasma DNA methylation data derived from metastatic prostate cancer patients.

  Dataset EGAD00001005433

• Single_cell_ATAC_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008276

• Single_cell_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008275

• Single_cell_RNA_sequencing_of_rhabdomyosarcoma_tumouroids

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008273

• 65 prostate cancer cases wgs sequencing

  65 prostate cancer cases wgs sequencing

  Dataset EGAD00001000983

• 65 prostate cancer cases wgs sequencing

  65 prostate cancer cases wgs sequencing

  Dataset EGAD00001001004

• Premalignant SOX2 in ovarian cancer patients

  Whole Genome Sequencing data set for the study "Premalignant SOX2 in ovarian cancer patients"

  Dataset EGAD00001002734

• "Single nucleotide variant detection in multiple foci of three prostate cancer tumors"

  "Single nucleotide variant detection in multiple foci of three prostate cancer tumors"

  Dataset EGAD00001000035

• "Copy number variant detection in multiple foci of three prostate cancer tumors"

  "Copy number variant detection in multiple foci of three prostate cancer tumors"

  Dataset EGAD00001000036

• Whole_genome_sequencing_of_rhabdomyosarcoma_tumouroids

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008270

• Whole_Genome_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008274

• WGS data of serially passaged TIC-enriched spheres of colorectal cancer

  WGS data of serially passaged TIC-enriched spheres of colorectal cancer

  Dataset EGAD00001006265

• Single cell sequencing of ovarian cancer

  Single cell sequencing of 12 ovarian cancer biopsies from 7 patients.

  Dataset EGAD00001006898

• Exploration of CNV’s and SNV’s in cancers with well-known genetic rearrangements: Identification of additional genetic changes in rearrangements-driven cancer

  Specific cancers are well known to have specific gene rearrangements. Representative cancer is chronic myeloid leukemia (CML) which is famous for BCR/ABL gene rearrangements. By the way, also genetic rearrangements are not infrequently found in acute leukemia, and those include CBFB/MYH11 rearrangements, PML/RARA rearrangements, AML/ETO rearrangements, and BCR/ABL rearrangements. The situation is same is for lung adenocarcinoma of non-smokers and prostate cancers, and ALK and RET gene rearrangements are recently found. However, not all these rearrangements are sufficient to develop cancer, and it is suggested that some genetic aberrations are required for the development and progression of cancer in addition to these genetic rearrangements. In this study, we have a plan to explore the existence of additional genetic changes including single nucleotide variants (SNV’s) and copy number variations (CNV’s) in cancers with specific genetic rearrangements so as to define additional genetic changes that confer full oncogenic potential to cancer cells. So as to look at SNV’s and small indels, we are going to use whole exome sequencing (WES) data. And as for CNV’s, we are going to use array-CGH data. Also, to check the functionality of these genetic changes, we are going to use whole transcriptome data (WTS). In addition, in samples with whole genome sequencing (WGS ) data, we are going to explore genetic changes in intronic regions also. In fact, we sequenced 10 AML samples which are known to have specific genetic rearrangements. Analysis of these WGS, WES and WTS data are under the way. If we have a chance to access WES, array-CGH and WTS data of other cancer samples with specific genetic rearrangements, we would be able to compare additional genetic changes required for oncogenesis in cancer cells with various genetic rearrangements. We hope this result will enlighten our understanding of cancer genetics further.

  Study EGAS00001000673

• Effects of interferon-gamma treatment on human small intestinal organoids generated from healthy donors

  The intestine is vulnerable to interferon-gamma as intestinal epithelial stem cells undergo cell death when exposed to interferon-gamma. Here, we developed a novel human intestinal organoid-based 3D model system to study the effects of interferon-gamma-induced intestinal epithelial damage at the RNA level. We treated organoids with 10 ng/mL for either 6 or 18h. Knowledge generated with this dataset is relevant for a variaty of intestinal pathologies with an immune component, for instance graft-versus-host disease.

  Study EGAS50000000083

• Immune Profiling in Patients with High-Risk Smoldering Myeloma

  Single-cell RNA-sequencing identifies immune biomarkers of response to immunotherapy in patients with high-risk Smoldering Multiple Myeloma (SMM). We conducted a Phase II trial of the immunotherapeutic anti-SLAMF7 antibody, Elotuzumab, in combination with Lenalidomide and Dexamethasone (E-PRISM study), to determine the utility and safety of early immunotherapy in patients with high-risk SMM and develop biomarkers for optimal patient selection and monitoring of response to treatment.There is an overlap in subjects between this study and dbGaP accession phs001323.

  Study phs002476

• NHLBI TOPMed: Children's Health Study (CHS) Integrative Genomics and Environmental Research of Asthma (IGERA)

  The Integrative Genomics and Environmental Research of Asthma (IGERA) Study was proposed to collect immortalized cell lines, RNA, cDNA and DNA from 400 well-characterized subjects who participated in the southern California Children's Health Study (CHS) and to develop an accompanying database for these samples consisting of extensive phenotype, exposure, genome-wide genotype, gene expression, and methylation data. A subset of Hispanic-White participants (n=160) were included in the TOPMed project, including 77 asthma cases and 83 controls.

  Study phs001603

• Metatranscriptomic Sequencing of Pre-Transplant Bronchoalveolar Lavage in Pediatric Stem Cell Transplant Patients

  Children with malignancies, immunodeficiencies, and other life-threatening diseases sometimes receive allogeneic hematopoietic cell transplantation (HCT) as a treatment for their disease. The HCT process can be complicated by the development of lung disease from infection, alloreactivity, or other causes. To identify patients at-risk for post-HCT lung disease, this study uses metatranscriptomic RNA sequencing of bronchoalveolar lavage (BAL) obtained prior to HCT. Sequencing results are associated with the development of post-HCT lung injury. 

  Study phs002208

• UW TAN Study of Metastatic Urothelial Carcinoma

  Patients with metastatic urothelial carcinoma treated at our institution, who elected to undergo rapid autopsy at the time of death, are included in this study. These patients agreed to submit their tissue (normal samples for germline analysis [kidney or liver] as well as primary and metastatic tumor sites [urothelial carcinoma]) and the time of autopsy. Each patient signed consent to allow study of these tissues including histologic, sequencing (DNA/RNA), and implantation in to animals as able for future study.

  Study phs001797

• Single-cell and spatial atlas of steatotic liver disease-related hepatocellular carcinoma

  This study consists of the spatial transcriptomics data generated by : 1. Visium CytAssist Spatial Gene Expression for FFPE (10x) for steatotic liver disease-associated hepatocellular carcinoma (SLD-HCC) (n=7) and non-SLD-HCC (n=5) 2. CosMxTM Human Universal Cell Characterization RNA Panel (1000-plex); NanoString, USA for n=4 SLD-HCC and n=4 non-SLD-HCC. The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Study EGAS50000001034

• Multi-modal single-cell analysis of salivary glands from patients with Sjogren's syndrome collaboration

  Sjogren's syndrome (SS) is an autoimmune disease that causes salivary gland dysfunction due to immune-mediated destruction. While autoantibodies such as anti-SSA and anti-centromere (CENT) are associated with distinct clinical manifestations, the underlying mechanisms remain to be elucidated. In this study, we apply multi-modal single-cell technologies-single-cell RNA sequencing, T- and B-cell receptor sequencing, and spatial transcriptomics-to salivary gland lesions, aiming to uncover common and unique cellular and transcriptional signatures linked to different autoantibody profiles.

  Study JGAS000773

• Longitudinal Transcriptomic Profiling of Endothelial Progenitor Cells in Post-COVID-19 Patients: Insights at 3 and 6-Months Post-SARS-CoV-2 Infection

  Bulk RNA-sequencing analysis of endothelial cells isolated from post-COVID patients at 3 and 6 months post-infection, alongside healthy controls. This study aims to identify differentially expressed genes in endothelial cells from post-COVID patients—at both 3- and 6-month time points—compared to those from healthy individuals. The objective is to uncover upregulated and downregulated pathways potentially associated with long-term consequences of SARS-CoV-2 infection.

  Study EGAS50000000993

• snRNA and snATAC analysis of cocaine use disorder in human caudate nucleus

  We investigated cell type specific changes of gene expression and chromatin accessibility in the caudate nucleus of N=6 individuals with and N=8 individuals without cocaine use disorder using postmortem human brain samples. We performed single-nuclei RNA-sequencing and single-nuclei ATAC sequencing in the same cells using the 10xMultiome platform. The N=14 tissue donors were of African-American ancestry. The cohort consists of N=5 female and N=9 male individuals.

  Study EGAS50000000480

• We performed an integrative analysis to determine genomic aberrations common to sporadic schwannomas.

  Schwannomas are common peripheral nerve sheath tumors that can cause significant debilitating morbidities. We performed an integrative analysis to determine genomic aberrations common to sporadic schwannomas. Exome sequence analysis with validation by targeted DNA-sequencing of 125 samples uncovered, in addition to expected NF2 disruption additional recurrent mutations. RNA sequencing identified a recurrent in-frame SH3PXD2A-HTRA1 fusion in 12/125 (10%) cases, and genomic analysis demonstrated the mechanism as resulting from a balanced 19Mb chromosomal inversion on chromosome 10q.

  Study EGAS00001001886

• OSTEOMICS_RNA

  RNA sequencing of 79 libraries were prepared, from sample of Osteosarcoma tumors biopsied at diagnosis, with TruSeq Stranded mRNA kit following recommendations: the key steps consist of PolyA mRNA capture with oligo dT beads using 1µg total RNA, fragmentation to approximately 400pb, DNA double strand synthesis, and ligation of Illumina adaptors amplification of the library by PCR for sequencing. Libraries sequencing was performed using Illumina sequencers (NextSeq 500 or Hiseq 2000/2500/4000) in 75 bp paired-end mode.

  Dataset EGAD00001008213

• Assessment of genetic and epigenetic variation in human IPS cells-RNA

  In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The transcriptomes of these iPS cells will be compared. Protocol: primary cultures of cells were reprogrammed to iPS cells. RNA was extracted using a standard column extraction kit.

  Dataset EGAD00001000604

• Boson HCV infected liver bulk RNASeq study

  ACE2 is a receptor for the SARS-CoV-2 and differences in its expression may affect susceptibility to infection. In a genome-wide eQTL analysis using hepatitis C virus-infected liver tissue, we discovered that polymorphism in a type III interferon gene (IFNL4), which eliminates IFN-lambda-4 production, is associated with a two-fold increase in ACE2 RNA expression. Conversely, among genes negatively correlated with ACE2 expression, IFN-signalling pathways were highly enriched and ACE2 was downregulated after IFN-alpha treatment.

  Study EGAS00001004996

• Dissecting the Spatial Heterogeneity of Single Circulating Tumor Cells in Hepatocellular Carcinoma

  The dismal outcome of hepatocellular carcinoma (HCC) is closely associated with intra- and extrahepatic metastases, which have been proposed to be initiated by circulating tumor cells (CTCs). However, the plasticity of gene expression and immune evasion mechanisms of CTCs during systemic circulation are not well defined. Here, we determined intra- and inter-vascular transcriptional heterogeneity within the circulatory system using single-cell RNA-sequencing of 113 CTCs isolated from four key vascular sites along their dissemination route in ten HCC patients.

  Study EGAS00001005204

• Single cell sequencing of endoscopic biopsies from Barrett's oesophagus and proximal tissue from the normal GI tract

  Barrett’s oesophagus is a precursor of oesophageal adenocarcinoma. In this common condition, squamous epithelium in the oesophagus is replaced by columnar epithelium in response to acid reflux. Barrett’s oesophagus is highly heterogeneous and its relationships to normal tissues are unclear. We investigated the cellular complexity of Barrett’s oesophagus and the upper gastrointestinal tract using RNA-sequencing of single cells from multiple biopsies from six patients with Barrett’s oesophagus and two patients without oesophageal pathology.

  Study EGAS00001003144

• Novel PARN mutations in Hoyeraal-HReidarsson syndrome patients.

  The deposited data correspond to the sequences of PARN gene obtained by whole exome sequencing in two patients carrying mutations in this gene as described in Benyelles et al. EMBO Mol Med 2019.. PARN is a poly(A)-specific ribonuclease that regulates the turnover of mRNAs and the maturation and stabilization of the hTR RNA component of telomerase. Data represent Sequences with PARN mutations that have been identified in two patients with Høyeraal-Hreidarsson (HH) syndrome, a rare telomere biology disorder.

  Study EGAS00001003623

• scRNAseq of human primary nasal epithelium differentiated at air-liquid interface exposed to SARS-CoV2

  The nasal epithelium is a plausible entry point for SARS-CoV-2, a site of pathogenesis and transmission, and may initiate the host response to SARS-CoV-2. Antiviral interferon responses are critical to outcome of SARS-CoV-2. Yet little is known about the interaction between SARS-CoV-2 and innate immunity in this tissue. Here we applied single-cell RNA sequencing and proteomics to a primary cell model of human primary nasal epithelium differentiated at air-liquid interface.

  Study EGAS00001005633

• Endothelium-derived stromal cells contribute to bone marrow niche formation

  Comprehensive transcriptional characterization of bone marrow stromal cells by RNA sequencing was performed to determine the molecular properties/signatures of endothelium during niche formation.Here, we identify a rare subset of cells in the human fetal BM that co-express endothelial and stromal markers, including low-affinity nerve growth factor receptor (LNGFR/CD271). They display transcriptional reprogramming consistent with endothelial-to-mesenchymal transition (EndoMT), reflected in their potential to generate stromal cells with in vivo BM niche forming capacity.

  Study EGAS00001004946

• Single cell RNAseq of lung adenocarcinoma

  Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing as well as single-cell BCR sequencing of cells from 16 LUADs and 47 multi-region normal lung tissues of defined spatial proximities from the tumors. Our multi-region single-cell sequencing analyses unravel cell populations, states, and phenotypes in the spatial and ecological evolution LUAD from the lung that comprise high-potential targets for early interception.

  Study EGAS00001005021

• Bulk-tissue paired-end RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Profiling of 24 human anterior cingulate cortex samples by bulk-tissue RNA-sequencing. Samples were derived from 5 non-neurological control individuals and 19 individuals with Lewy body disease (Parkinson’s disease = 7 individuals; Parkinson’s disease with dementia = 6 individuals; dementia with Lewy bodies = 6 individuals). Paired-end FASTQ files for each of the human samples are provided and are denoted by the suffixes R1 (read 1) and R3 (read 2). Fastp (v 0.20.0), a fast all-in-one FASTQ pre-processor, was used for adapter trimming, read filtering and base correction. Fastp default settings were used for quality filtering and base correction. Further details on parameters used are available here: https://github.com/RHReynolds/RNAseqProcessing/blob/master/QC/prealignmentQC_fastp_PEadapters.R.

  Dataset EGAD00001007698

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• Duplex sequencing of selected breast cancer patients

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primaty tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000769

• WES of breast cancer patients and controls

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primary tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000770

• Application of organoid culture system of human gastrointestinal and thoracic cancer in genome medicine

  In order to establish preclinical models, we have established three kinds of esophageal tumoroids derived from esophageal cancer patient. We performed whole exome sequencing to analyze genetic background of the tumoroids.

  Study JGAS000749

• Breast_Cancer_Matched_Pair_Cell_Line_Whole_Genomes

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

  Study EGAS00001000166

• Triple_Negative_Breast_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000092

• Transcriptome_Sequencing_of_Cancer_Cell_Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Study EGAS00001000261

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004915

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004910

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004900

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004926

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004913

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004927

• Genome and transcriptome sequence data from a metastatic rectal cancer patient

  Genome and transcriptome sequence data from a metastatic rectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004918

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003613

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003619