11754 results for "cancer rna-seq"

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• Transcriptome Sequencing PPGL

  RNA library preparation of samples with RNA Integrity Number (RIN) > 5.5 (median 7.1; range 5.6-8.9) was performed as described in the TruSeq Stranded mRNA Library Prep Kit (Illumina, RS-122-2101). Briefly, 0.7-1 µg total RNA PolyA+ fraction was purified and randomly fragmented, converted to double stranded cDNA and processed through subsequent enzymatic treatments of end-repair, dA-tailing, and ligation to adapters. Adapter-ligated library was completed by PCR with Illumina PE primers. The resulting purified cDNA library was applied to an Illumina flow cell for cluster generation and sequenced on an Illumina HiSeq2500 on a 51bp single-read format following manufacturer's protocols. cDNA libraries from FFPE tumors and low integrity RNA’s (RIN<5.5) from FF tumors (median 2.4; range 1-5.5) but % of fragments > 200 nucleotides higher than 20% (median 57.5; range 20-96) were prepared using QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015) with a UMI Second Strand Synthesis Module for QuantSeq FWD (Lexogen, 081), vendor’s protocol for low input/ low quality/ FFPE RNA using 200-500 ng of total RNA, according to availability, was used as starting material. PCR Add-on Kit for Illumina (Lexogen, 020) was used to adjust the library amplification number of cycles. Libraries were applied to an Illumina flow cell for cluster generation and sequenced on NovaSeq6000. Image analysis, per-cycle basecalling and quality score assignment was performed with Illumina Real Time Analysis software. Demultiplexing of BCL files to FASTQ format was performed with the bcl2fastq Software (Illumina).

  Study EGAS00001006044

• CCMA-RNA

  This dataset has the raw RNA sequencing data for the cancer models in CCMA.

  Dataset EGAD00001010034

• RNA sequencing

  RNAseq of 45 high-grade serous ovarian cancer tumour samples. Libraries were generated using the NEB Ultra II Directional RNA library Prep kit with polyA enrichment. Libraries were sequenced as paired-end 50 or 100bp on an Illumina NextSeq or NovaSeq.

  Dataset EGAD00001009844

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139

• Healthy control cfMeDIP-seq

  This dataset comprises 46 raw fastq files derived from 23 plasma cfDNA samples from 23 healthy (CTL) cancer-free donors. For each sample, 10ng of cfDNA was used for library preparation utilizing the cfMeDIP-seq technology based on the 5mC antibody-immunoprecipitation strategy. Libraries were validated via Bioanalyzer trace analysis and sequenced on the Illumina NovaSeq 6000 platform with paired-end 150-bp model for ~100 million reads per sample.

  Dataset EGAD50000000652

• Chromatin accessibility of clear cell renal cell carcinoma

  To investigate chromatin accessibility in ccRCC, we performed ATAC-seq in 3 ccRCC cell lines (786-O, A498, UMRC-2), and 1 normal kidney epithelium cell line (HK-2), cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions

  Study EGAS50000001325

• Derivation and Investigation of The First Human Cell-Based Model of Beckwith-Wiedemann Syndrome

  Beckwith-Wiedemann Syndrome (BWS) is the most common human imprinting disorder, and phenotypes include hepatomegaly and hepatoblastoma development. In approximately 20% of patients, this syndrome is caused by uniparental isodisomy of the paternal allele across chromosome 11p15 (pUPD11). From fibroblasts cultured from 2 BWS patients with pUPD11, we derived induced pluripotent stem cells (iPSC) and differentiated to hepatocytes to study a model of the BWS liver transcriptome through RNA-Seq. Compared to 2 similarly derived controls, we observed differential expression in insulin signaling, cell proliferation, and cell cycle pathways, indicating their potential importance in the liver overgrowth and oncogenesis associated with BWS.

  Study phs002365

• Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

  Background: Glioblastoma (GBM) harbors a highly immunosuppressive tumor microenvironment (TME) which influences glioma growth. Major efforts have been undertaken to describe the TME on a single-cell level. However, human data on regional differences within the TME remain scarce. Goals: we performed single-cell RNA sequencing (scRNAseq) on paired biopsies from the tumor center, peripheral infiltration zone and blood of five patients with primary GBM Details: This EGA study includes raw data sequencing files for the scRNA-seq samples. The processed data (output from Alevin, UMI count matrix and cell metadata) are available from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE197543

  Study EGAS50000000302

• Bulk RNAseq - Calprotectin in vitro effects on human early hematopoiesis

  To explore the effects of calprotectin (CAL) on early hematopoiesis, we incubated CD34+ cells from four healthy donors for 7 days in the presence of stem cell factor (SCF), FLT3-ligand and thrombopoietin (TPO) without and with CAL, interleukin-6 (IL6) and the IL6_CAL combination before collecting cells. We performed the same experiment with CD34+ cells collected from three patients with JAK2-V617F-mediated myelofibrosis (MF). A total of 135,545 cells from healthy donors and 111,725 cells from myelofibrosis patients were analyzed by single-cell RNA sequencing (scRNA-seq) using the 10X Chromium droplet-based platform. Bulk RNAseq 4 conditons : -Control - Calprotectin - IL-6 - Calprotectin+IL-6

  Study EGAS50000000454

• Investigating immunopathological signatures associated with COVID-19 severity post Omicron

  The aim of this study was to investigate the type and duration of protective immunity alongside immunopathological signatures associated with COVID-19 severity. RNA sequencing was performed using the Illumina Stranded mRNA Prep Ligation kit to investigate the protein coding transcriptome of PBMC cells. T cell receptor (TCR) repertoire profiling was performed with the TakaraBio SMART-Seq Human TCR (with UMIs) on PBMC cells to investigate the depth and persistence of SARS-CoV-2 targeting TCRs. The cohort (n=20) consisted of 10 non-hospitalised and 10 Hospitalised individuals with samples analysed 3 months post positive SARS-CoV-2 PCR.

  Study EGAS50000000926

• Human Epilepsy Genetics: Mosaic Mutations in Focal Epilepsy

  This study investigates the role of somatic mosaic mutations in human focal epilepsies, including focal cortical dysplasia (FCD) and mesial temporal lobe epilepsy (mTLE). It leverages genomic and single-cell transcriptomic data from surgically resected brain tissue to identify pathogenic variants and characterize their effects on specific cell types and molecular pathways. The study employs methods such as deep whole-exome and targeted sequencing, single-nucleus RNA sequencing (snRNA-seq), and integrated genotype-transcriptome profiling (e.g., GO-TEN) to define the cellular architecture and functional consequences of mosaic mutations. Data generated under this project aim to elucidate mechanisms of epileptogenesis and support discovery of potential therapeutic targets.

  Study phs004124

• Feasibility Study to Identify the Optimal Adjuvant Combination Scheme of Ipilimumab and Nivolumab (OpACIN) in resectable stage III melanoma patients

  OpACIN is a feasibility study including 20 patients with palpable stage III melanoma that were 1:1 randomized to receive ipilimumab 3mg/kg and nivolumab 1mg/kg, either 4 courses after surgery (adjuvant arm), or 2 courses prior to surgery and 2 courses post-surgery (neoadjuvant arm). WES and RNA-seq was performed on baseline biopsy material and correlated with outcome of the patients (relapse free survival). TCRseq from baseline tumor samples was used to analyse the top 100 tumor resident clones and analyse their change in PBMC comparing baseline versus week 6 of immunotherapy.

  Study EGAS00001003099

• Mongolia Western HCC

  Mongolia has the world’s highest incidence of hepatocellular carcinoma (HCC), with ~100 cases/105 inhabitants. We molecularly characterize the Mongolian (n=192) compared to Western HCCs (n=187) by RNA-seq and WES. Mongolian patients were predominantly younger, female, with HBV-HDV non-cirrhotic livers. Mongolian HCCs had higher rates of protein-coding mutations (121 vs 70 mut /tumor in West), and mutations in known (i.e. APOB) and putative HCC drivers (TSC2). A novel mutational signature (SBS Mongolia) was identified in 25% of cases associated with the carcinogenic DMS genotoxic signature. Two unique molecular classes enriched in HBV-HDV infection, female gender and inflamed tumors are described.

  Study EGAS00001005364

• Single-cell roadmap of immune cell responses in chronic myeloid leukemia

  To study the innate and adaptive immune responses in CML, we profiled 25 samples from CML patients including samples at diagnosis (n = 7, N = 9, where n is the number of subjects and N the number of samples if different from n) and before and after TKI-cessation with imatinib (n = 6, N = 15) with paired single-cell RNA and T cell receptor (TCR) αβ chain sequencing (scRNA+TCRαβ-seq) and compared our data to different cancers (n = 29) and healthy donors (n = 7). This dataset contains the samples from before and after TKI-cessation, please see the manuscript for info related to the other datasets.

  Study EGAS00001005044

• raw RNA-seq data from patients infected with COVID-19 or influenza

  Dataset consists of fastq files from bulk RNA-seq done on peripheral blood acquired from two well characterised hospitalised cohorts, a cohort of patients infected with influenza and a cohort of patients infected with SARS-CoV-2 during the first wave of the pandemic and prior to availability of COVID-19 treatments and vaccines.

  Dataset EGAD00001008505

• Transcriptome analysis of endometrial organoids derived from patients with Mayer-Rokitansky-Küster-Hauser syndrome

  The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. The cause of the disease is still enigmatic. Here, we developed organoid cultures from endometrium found in uterine rudiment horns of MRKH patients. Phenotypically they share great similarity between healthy control organoids and are fully hormone responsive. Transcriptome analysis using RNA-seq identified possible disease-causing pathways altered in MRKH patients during development of the female reproductive tract. Thus, the organoid cultures provide a powerful research model for further insight into disease-causing alterations.

  Study EGAS00001005908

• Preclinical Modeling of Leiomyosarcoma Identifies Susceptibility to Transcriptional CDK Inhibitors through Antagonism of E2F-Driven Oncogenic Gene Expression

  Leiomyosarcoma (LMS) is a smooth muscle-derived mesenchymal cancer commonly found to have recurrent loss of tumor suppressor genes and a poorly defined oncogenic program. Empiric cytotoxic chemotherapy is the standard systemic treatment for LMS, and while more targeted and effective therapies are urgently needed, insights into therapeutic vulnerabilities in LMS have been limited by available preclinical models. We generated a panel of LMS patient-derived xenograft (PDX) models and evaluated fidelity to their tumors of origin using RNA sequencing and ultra-low passage whole-genome sequencing (ULP-WGS). Data available at dbGaP include RNA sequencing and ULP-WGS of primary tumors and early and late passages of PDX. 

  Study phs002587

• scRNA-seq of patient-derived PDAC organoids and matched CAFs

  We established direct three-dimensional (3D) co-cultures of primary PDAC organoids and patient-matched CAFs. Single-cell RNA sequencing was performed for three organoid/CAF pairs in mono- and co-culture to uncover transcriptional changes induced by tumor-stroma interaction. Single-cell RNA sequencing data evidenced induction of a pro-inflammatory phenotype in CAFs in co-cultures. Organoids showed increased expression of genes associated with epithelial-to-mesenchymal transition (EMT) in co-cultures and several potential receptor-ligand interactions related to EMT were identified, supporting a key role of CAF-driven induction of EMT in PDAC chemoresistance.

  Study EGAS00001006661

• Single-cell atlas of the human healthy airways

  Single cell atlas of human airways from 10 healthy volunteers by 10X Genomics 3’ RNA-seq profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12th division of the airway tree, either by forceps (46,791 cells), or brush biopsies (31,178 cells).

  Dataset EGAD00001005714

• Human T-bet governs innate and innate-like adaptive IFN-g immunity against mycobacteria.

  We report a patient with mycobacterial disease due to inherited deficiency of the transcription factor T-bet. PBMCs from the patient and his heterozygous father were analyzed with scRNA-seq. these represent 2 single cell RNA samples generated using the 0xGenomics technology and being processed through cell ranger.

  Dataset EGAD00001006623

• RNA-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

  Study describing the differentiation trajectory of atypical teratoid rhabdoid tumors (ATRTs) at single-cell level. This study describes how the differentiation trajectory differs per subtype of ATRTs, and how those findings could contribute to develop so-called "maturation therapy" tailored towards ATRTs.

  Dataset EGAD00001015544

• (sn)RNA-seq dataset of Multi-modal analysis of pediatric pilocytic astrocytomas reveals tumor location-associated cellular and transcriptional heterogeneity

  Aim: to comprehensively characterize the cellular and transcriptional landscape of pediatric pilocytic astrocytomas across anatomical tumor locations

  Dataset EGAD00001015705

• BAM Files MBD-SEQ

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001668

• BS-seq in plasma of CRC patients

  We performed whole genome bisulfite sequencing of plasma DNA in 11 colorectal cancer patients to study the colonic DNA in plasma.

  Dataset EGAD00001004568

• Integrative analysis of non-small cell lung cancer patient-derived xenografts identifies unique proteotypes associated with patient outcomes

  Non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths worldwide. Only a fraction of NSCLC harbour actionable driver mutations and there is an urgent need for patient-derived model systems that will enable the development of new targeted therapies. NSCLC and other cancers display profound proteome remodelling compared to normal tissue that is not predicted by DNA or RNA analyses. We generated NSCLC patient-derived xenografts (PDXs) that recapitulate the histology and molecular features of primary NSCLC. Here, we completed whole exome sequencing on 122 NSCLC PDXs.

  Study EGAS00001006068

• scRNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Fresh peripheral blood mononuclear cells of four human donors were cultured together with either lung adenocarcinoma A549 cancer cells or A549-expressing H1N1 Sialidase cancer cells. These treatments induced the differentiation of donor cells into immunosuppressive MDSC-like cells, which were further subjected to single-cell RNA sequencing.

  Dataset EGAD50000000351

• Transcriptomic Profiling of Oropharyngeal Squamous Cell Carcinoma

  The study is a retrospective transcriptomic profiling of oropharyngeal squamous cell carcinoma. The pathologic database was queried for squamous cell carcinoma tumors originating from the anatomic oropharynx (tonsil or tongue base) with available samples from surgical archives. This retrospective RNA sequencing cohort included cases dating prior to the routine implementation of p16 immunohistochemistry (IHC) testing at our institution, therefore, p16 status was not required for inclusion in this study. Formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center (LCCC) Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer's protocol (Promega 9FB167). After a pathology review of a hematoxylin and eosin (H&E) stained slides to identify tumor area, RNA was extracted from unstained slides using macrodissection. Total RNA quality was measured using a NanoDrop spectrophotometer (Thermo Scientific ND-2000C) and a TapeStation 4200 (Agilent G2991AA). Total RNA concentration was quantified using a Qubit 3.0 fluorometer (Life Technologies Q33216). Libraries were prepared with Illumina TruSeq Stranded Total RNA with Ribo-Zero protocol. Libraries were sequenced on an Illumina HiSeq2500 sequencer. Paired end read data, with read lengths of 75 were collected.

  Study phs002935

• Gene expression profile of mesothelial-derived carcinoma-associated fibroblasts

  RNA-sequencing was carried out on ascetic fluid-isolated mesothelial cells from low-grade serous ovarian cancer patients, high-grade serous ovarian cancer patients, chemotherapy-treated high-grade serous ovarian cancer patients and control mesothelial cells obtained from non-oncologic patients to identify differentially expressed genes associated to mesothelial-to-mesenchymal transition process. The dataset contains 18 samples: - Control mesothelial cells: 4 samples - Group 1, high-grade serous ovarian cancer patients: 3 samples - Group 2, chemotherapy-treated high-grade serous ovarian cancer patients: 5 samples - Group 3, low-grade serous ovarian cancer patients: 6 samples

  Dataset EGAD00001005133

• Single-cell RNA sequencing of 16 NPM1 mutated AML patients

  NPM1 mutated AML is the largest class in WHO classification, however several subtypes within NPM1 were already reported. Here, we sequence 16 NPM1 mutated AML samples with single-cell RNA-sequencing and multi-color flow cytometry from three major NPM1 subtypes we previously identified, totaling more than half a million cells. We show that the differences among three NPM1 subtypes are mainly driven by cell composition, and these differences are also reflected at cell surface protein level. With the re-analysis of CITE-seq data from another cohort and single cell variant calling on our data, we also report two distinct stem cell phenotypes: one with leukemic (CD34dimCD38-CD45RA+) and another with pre-leukemic (CD34+CD38-CD45RA-) origin. We believe that our data and findings provide novel insights regarding the etiology of NPM1 mutated AML.

  Study EGAS50000000332

• Mapping regulatory variation in sensory neurons using IPS lines from the HIPSCI project

  Sensory neurons are nerve cells that are activated by sensory input such as heat, light and convey information to the brain. Although a key cell type in complex organisms, human sensory neurons are challenging to study because they are impossible to obtain from living donors. We have collaborated with the Neucentis Pharmaceutical Research Unit to differentiate sensory neuron like cells from human induced pluripotent stem cells derived as part of the Human Induced Pluripotent Stem Cells Initiative. We will sequence RNA from 100 IPS lines derived from healthy individuals and perform RNA-seq on the differentiated cells to identify noncoding variants that alter gene expression in human sensory neurons.

  Dataset EGAD00001003145

• Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

  Gastric cancer (GC) is a major cause of global cancer mortality with high levels of heterogeneity, and intratumoral heterogeneity (ITH) represents a significant barrier to GC patient outcomes. In this study, we applied GeoMx DSP technology to identify ITH in GC. We found spatially colocalized RNA-based intratumor subgroups within samples, each correlated with distinct spatially oriented TME and immune profiles. The findings broadening our understanding of the spatial and molecular complexity of GC ITH and offering a valuable data resource for future exploration and discovery.

  Study EGAS50000000345

• Transcriptome sequencing of Gingivo-buccal Cancer - ICGC India Project YR03

  This dataset pertains to transcriptome sequencing of paired RNA samples.RNA was isolated from the tumor and adjacent normal tissues of 12 patients (24 samples). We have performed rRNA removal followed by total RNA sequencing in Illumina HiSeq platform.We have uploaded TopHat2 aligned BAM files.

  Dataset EGAD00001003981

• RNAseq dataset of ovarian cancer patients

  Dataset of transcriptomics data from a cohort of individuals diagnosed with ovarian cancer. This dataset includes RNAseq sequencing data from 68 individuals. A total of 109 tumor samples were sequenced. Samples were prepared with the Illumina TruSeq Stranded RNA library. Sequencing data are paired end.

  Dataset EGAD50000001556

• Diversity of U1 small nuclear RNAs and Evaluation of Diagnostic Methods for their Mutations

  U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various malignancies, including medulloblastoma, yet their identification has proven challenging due to their repetitive nature. To establish a robust DNA-based, and RNA-based method for detecting U1 snRNA mutations, we performed targeted DNA sequencing using our original gene panel for medulloblastoma and RNA-sequencing. As an RNA-based method, we developed a random forest classifier employing splicing patterns which were massively altered as a result of U1 snRNA mutations. By using both methods, we successfully detected U1 snRNA mutation in five DNA samples and four RNA samples.

  Study EGAS50000000693

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  The dataset for the study “Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer” includes 173 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 32 individuals with esophageal/gastroesophageal junction cancer, who received immunotherapy-containing regimens.

  Dataset EGAD00001011822

• Chip_seq_oesophageal_adenocarcinoma_

  There is complex interplay between underlying genetic sequence and epigenetic factors, however this interplay is still illusive. Massively reconstructed cancer genomes can be used in order to better understand this relationship. Six oesophageal adenocarcinoma organoids will be sequenced using long read sequencing technologies and will be profiled for a range of epigenetic marks. Combination of genetic and epigenetic data will allow the thorough characterisation of reference cancer genomes and will provide novel insights into mechanisms of gene regulation. Description: Chip-seq Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger.

  Study EGAS00001007180

• scRNA-seq of HGSC tumor and ascites

  Immune regulatory metabolites are key features of the tumor microenvironment (TME), yet with a few notable exceptions, their identities remain largely unknown. We uncovered the immune regulatory metabolic states and metabolomes of sorted tumor and stromal, CD4+, and CD8+ cells from the tumor and ascites of patients with high-grade serous ovarian cancer (HGSC) using high-dimensional flow cytometry and metabolomics supplemented with single cell RNA sequencing. Flow cytometry revealed that tumor cells show a consistently greater uptake of glucose than T cells, but similar mitochondrial activity. Cells within the ascites and tumor had pervasive metabolite differences, with a striking enrichment in 1-methylnicotinamide (MNA) in T cells infiltrating the tumor compared to ascites. Despite the elevated levels of MNA in T cells, the expression of nicotinamide N-methyltransferase, the gene encoding the enzyme that catalyses the transfer of a methyl group from S-adenosylmethionine to nicotinamide, was restricted to fibroblasts and tumor cells. Treatment of T cells with MNA resulted in an increase in T cell-mediated secretion of the tumor promoting cytokine tumor necrosis factor alpha. Thus, the TME-derived metabolite MNA contributes to an alternative and non-cell autonomous mechanism of immune modulation of T cells in HGSC. Collectively, uncovering the tumor-T cell metabolome may reveal metabolic vulnerabilities that can be exploited using T cell-based immunotherapies to treat human cancer.

  Study EGAS00001004829

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_YR03

  Transcriptome Sequencing of Gingivo-buccal Cancer: ICGC-India ProjectAs a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Transcriptome sequencing of paired RNA samples – isolated from the tumor and adjacent normal tissues of 12 patients – have been performed. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from adjacent normal and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Sequencing is being performed at the National Institute of Biomedical Genomics, Kalyani.

  Study EGAS00001002851

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_Batch05

  Transcriptome Sequencing of Gingivo-buccal Cancer: ICGC-India ProjectAs a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Transcriptome sequencing of paired RNA samples – isolated from the tumor and adjacent normal tissues of 28 patients – have been performed. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from adjacent normal and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Sequencing is being performed at the National Institute of Biomedical Genomics, Kalyani.

  Study EGAS00001003285

• ICARUS-BREAST01-RNAseq

  Efficacy, safety and biomarker analysis of ICARUS-BREAST01: a phase 2 Study of Patritumab Deruxtecan in patients with HR+/HER2- advanced breast cancer. RNA-squencing is available for 44 samples comprising 22 samples collected at entry into the trial and 22 samples collected during treatment (cycle 1 day 3, cycle 1 day 19, or cycle 2 day 3) from 22 patients.

  Study EGAS50000000543

• Clinical Activity of Combined Telomerase Vaccination and Pembrolizumab in Advanced Melanoma: Results from a Phase I Trial

  Thirty patients with advanced melanoma were recruited to a clinical trial investigating the therapeutic cancer vaccine, UV1, in combination with pembrolizumab. Whole exome sequencing was performed on melanoma biopsies to determine tumor mutational burden and association with response to therapy. RNA sequencing of matched tumor biopsies to evaluate gene expression profiles at baseline and post-treatment.

  Study EGAS00001007210

• Genomic and Transcriptomic Data in GBM Patients Undergoing anti-PDL1 Therapy

  This dataset comprises whole exome sequencing data from 29 tumor-normal pairs and RNA-seq data from 39 tumors of newly diagnosed IDH-wt GBM patients. It includes analyses such as variant calls, copy number variations, the transcriptomic expression matrix, and patient metadata and outcomes.

  Dataset EGAD50000001154

• Phenotype, genotype, and transcriptome data from three South Eastern Bantu groups in the SABR study

  Phenotypic data, whole genome sequencing, blood RNA-seq, imputed variant calls, cell type estimates, gene expression levels, splicing measurements, and analysis covariates from South African Blood Regulatory (SABR) resource participants, which includes South Eastern Bantu-speaking groups.

  Dataset EGAD50000001477

• 10Xchromium 3' RNA-seq of 21 samples from human embryonic heart

  21 samples were taken from human embryonic heart of PCW 5.5-14 of a total of 13 fetuses. Samples were subject to 10Xgenomics chromium single cell 3' sequencing version 2 or 3. Data was analyzed using STARSolo version 2.7.10a, using human genome GRCh38.p12 and transcript annotations from ENSEMBL release 93 from reference package GRCh38-3.0.0 as available from 10Xgenomics.

  Dataset EGAD50000001499

• Standard epigenome mapping in human epithelial cells of the digestive and urogenital organs [RNA-Seq ]

  The aim of this study is to participate in International Human Epigenome Consortium (http://ihec-epigenomes.org/), through disclosure of quality reference epigenome profiles in normal and diseased cells obtained from multiple Japanese people.

  Study JGAS000080

• Standard epigenome mapping in human epithelial cells of the digestive and urogenital organs [RNA-Seq ]

  The aim of this study is to participate in International Human Epigenome Consortium (http://ihec-epigenomes.org/), through disclosure of quality reference epigenome profiles in normal and diseased cells obtained from multiple Japanese people.

  Study JGAS000081

• Extraembryonic tissue and cytotrophoblast epigenome mapping

  Maps of H3K27ac from normal 2nd- and 3rd-trimester cytotrophoblasts, preterm severe preeclampsia cytotrophoblasts, and 2nd-trimester amnion. Maps of H3K27me3, H3K27me3, H3K36me3, and H3K4me1 from 2nd- and 3rd-trimester cytotrophoblast. Maps of H3K9me3 from 2nd- and 3rd-trimester cytotrophoblast, smooth chorion, and basal plate. RNA-seq from 2nd- and 3rd-trimester cytotrophoblasts.

  Dataset EGAD00001006066

• MSC_busulfan_small_intestine_organoids

  This dataset represent the RNA-seq, which was done on untreated small intestinal organoids; small intestinal organoids treated with chemotherapeutic, busulfan; untreated small intestinal organoids co-cultured wth mesenchymak stromal/stem cells (MSCs; busulfan treated small intestinal organoids co-cultured with MSCs. The same set of samples was done for 3 different primary bone marrow MSC donors.

  Dataset EGAD00001011176