7188 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

in 84.20 milliseconds.

• Bulk RNAseq of mCRC organoids

  6 organoids transcriptomic profiles

  Dataset EGAD00001009691

• SF12199 Primary diffuse astrocytoma G3

  Primary diffuse astrocytoma G3 Male, 74

  Dataset EGAD00001006020

• Prediction of Resistance and Sensitivity to HER2 Targeted Therapy in the Neoadjuvant Setting

  Women with breast cancers that overexpress HER2 are at greater risk for disease progression and death than women whose tumors do not overexpress HER2. Trastuzumab, a recombinant humanized monoclonal antibody against the extracellular domain of the HER2 protein blocks downstream signaling of HER2 and substantially improves the efficacy of chemotherapy in women with metastatic and early-stage HER2-positive breast cancers. Because resistance to trastuzumab eventually results in progressive disease in the metastatic setting and contributes to recurrence following adjuvant trastuzumab-based therapy, it is important to develop agents other than trastuzumab that target HER2 signaling through different mechanisms of action. Lapatinib is an oral, small molecule, dual tyrosine kinase inhibitor of HER2 and EGFR. Lapatinib has shown a lack of cross-resistance with trastuzumab in preclinical studies and activity in women with HER2-positive, metastatic breast cancer that has progressed during trastuzumab treatment. Trastuzumab blocks the downstream signaling of HER2 by binding to the extracellular domain of the receptor. Lapatinib binds to the intracellular domains of HER2 and EGFR and prevents activation of downstream signaling pathways. Because of this different mechanism of action, lapatinib may be effective in trastuzumab-resistant disease. The study will also provide important safety information on trastuzumab and lapatinib combinations immediately following anthracycline exposure, and also provide an initial direct comparison of cardiac effects of trastuzumab and lapatinib when incorporated into a standard sequential adriamycin and cyclophosphamide (AC) followed by weekly paclitaxel neoadjuvant regimen. Availability of a second agent that can interrupt HER2-signaling pathways through completely different mechanisms than those of trastuzumab offers the potential for further improvement in the management of patients with HER2-overexpressing breast cancer in both the adjuvant and metastatic setting. Co-administration of both trastuzumab and lapatinib with chemotherapy may be important in improving outcomes in subsets of HER2-positive breast cancers. However, use of two inhibitors of the HER2 pathway will increase costs and may increase toxicity, so it will be important to identify the subsets of patients who would benefit from the dual therapy. Inhibition of HER2 with a single agent clearly is sufficient for many patients as evidenced by the results of the trastuzumab trials. Therefore, co-administration to unselected populations of women with HER2-positive breast cancers would not represent an optimal approach. Given the activity of lapatinib, it is likely that it will also be sufficiently active in inhibiting HER2-pathway activation in some patients to allow for its use as the sole inhibitor of the HER2 pathway. Different populations may also derive greater benefit from one of the HER2-blocking agents relative to the other. Identification of potential predictive factors for pathologic complete response to the combination or to either agent administered alone in neoadjuvant trials would provide important information for adjuvant trials designed to definitively address these important issues. This study will compare 3 combined chemotherapy regimens: AC followed by paclitaxel plus trastuzumab and lapatinib, AC followed by paclitaxel plus lapatinib, and AC followed by paclitaxel plus trastuzumab given before surgery to patients with HER2-positive breast cancer.Tumor samples were collected prior to and post-treatment, and RNA sequencing was performed with this version.

  Study phs003275

• Development of Precision Neoadjuvant-Adjuvant Therapies

  In clinical trials assessing neoadjuvant androgen deprivation therapy plus next-generation androgen receptor axis inhibitors, a subset of patients fail to demonstrate a complete pathologic response following treatment and radical prostatectomy. We performed exome and transcriptome analyses on laser capture microdissected foci of residual tumor from these patients.

  Study phs001399

• Molecular Characterization of Clinical Renal Tumors

  We performed comprehensive molecular profiling of renal tumors, including whole exome sequencing and transcriptome sequencing, derived from patient samples. This project additionally explores mechanisms of response and resistance to existing and emerging therapies in this disease, as well as mechanisms of tumor evolution in the context of treatment.

  Study phs001018

• Single-cell transcriptomics of PBMC’s from healthy, acute decompensated (AD) and acute chronic liver failure (ACLF) patients.

  This dataset contains the raw sequencing data (fastq-files) of 10 sample libraries. These are 10x genomics single-cell transcriptome libraries of human peripheral blood mononuclear cells (PBMC’s). The samples are taken from healthy, acute decompensated (AD) and acute chronic liver failure ACLF patients. The sequencing was performed on an Illumina NovaSeq6000. This data are related to the paper: "Distinct immunometabolic signatures in circulating immune cells define disease outcome in acute-on-chronic liver failure"

  Dataset EGAD50000000574

• Transcriptome sequencing of neuroendocrine tumors of the small intestine

  This dataset contains 206 RNASeq samples from a cohort of patients with neuroendocrine tumors of the small intestine. Libraries were prepared using a Illumina TruSeq Stranded mRNA kit following the manufacturer’s recommendations. Sequencing was performed on Illumina Novaseq6000 machine with a 2x75bp paired-end fashion. This dataset contains data for 169 tumors, 22 mesenteric nodules, 8 liver metastases, 2 adenomas, 1 lymph node and 4 normal ileum samples.

  Dataset EGAD50000000906

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Study EGAS50000000182

• Transcriptome analysis of human iPSC-derived microglia in a novel human 3D cortical tissue model

  scRNA-seq analysis of human iPSC-derived microglia in a novel, human in vitro 3D cortical tissue model. Samples include three distinct conditions (each as biological duplicates): wild-type microglia extracted from cultures after 1 month (WT_1mo) and 3 months (WT_3mo) of culturing, as well as knock-in microglia extracted from cultures carrying three familial AD mutations in the APP gene (Swedish, Iberian, Arctic; introduced by CRISPR/Cas9-mediated knock-in) after 3 months of culturing (KI_3mo).

  Dataset EGAD50000000677

• Profiling of Peritoneal Metastases from Gastric Adenocarcinoma Identified Molecular Subtypes

  Peritoneal carcinomatosis (PC) occurs frequently in gastric adenocarcinoma (GAC) patients and confers poor prognosis. Multiplex profiling of primary GACs has been insightful but the underpinnings of PC’s development/progression remain largely unknown. Here we characterized exome/transcriptome/immune landscapes of PC cells from 43 patients.

  Study EGAS00001003180

• DKFZ-HIPO Project H021/NCT MASTER

  Clinical genome and transcriptome sequencing in younger adults with advanced-stage cancer across all histologies: DKFZ-HIPO Project H021 (http://www.hipo-heidelberg.org/hipo2/index.php/menu-item-2/32-021-prospective-genetic-characterization-of-tumors-from-individual-patients-of-special-interest) / NCT MASTER (http://www.nct-heidelberg.de/forschung/nct-master.html)

  Study EGAS00001000948

• Integrated molecular analysis of adult T-cell leukemia/lymphoma

  This study is an integrated molecular study of adult T-cell leukemia/lymphoma which includes whole-exome (n = 81), whole-genome (n = 48), and transcriptome sequencing data (n = 57) as well as methylation (n = 109) and SNP array data (n = 426)

  Study EGAS00001001296

• Genetic heterogeneity and dynamics of transcriptional subtypes in matched primary and recurrent head and neck squamous cell carcinomas

  To get a better understanding of different HNSCC subtypes, whole-exome (matched tumor-normal paits) and whole transcriptome sequencing to to elucidate underlying molecular processes. Here, we present the matched whole-exome sequencing data from 28 patients (normal tissue, tumor tissue, relapse).

  Study EGAS00001005005

• The genomic landscape of lung adenocarcinoma in East Asians

  We performed exome sequencing of 210 and transcriptome sequencing of 181 LUADs of Chinese patients. For more details, please see publication "Genomic landscape of lung adenocarcinoma in East Asians" by Chen J. et. al. in Nature Genetics 2020. https://www.nature.com/articles/s41588-019-0569-6.

  Study EGAS00001002941

• CITEseq data

  Single-cell whole transcriptome and antibody expression for bone marrow samples from Cohorts A and B. CITEseq protocol was followed. 37 and 77 surface markers were measured in each cohort, respectively (see Supplementary Table 1). For details on cell sorting prior scRNAseq see the methods section of the manuscript.

  Dataset EGAD00001010187

• scRNA-seq dataset of patient with immune dysregulation

  scRNA-seq dataset on a patient (P_IKZF2-het) presenting with immune dysregulation. This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are three paired-end (75 bp) fastq files (I1, R1, R2) and three processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (scrnaseq_P_IKZF2-het_barcodes.tsv.gz, scrnaseq_P_IKZF2-het_features.tsv.gz, scrnaseq_P_IKZF2-het_matrix.mtx.gz).

  Dataset EGAD00001008443

• TARGET-seq+ single-cell genotyping

  Single-cell genotyping data for bone marrow samples from 9 cases with clonal hematopoiesis and 1 control sample. The TARGET-seq+ protocol was used to generate plate-based 3' transcriptome data. For details on cell sorting and the TARGET-seq+ protocol see the methods section of the manuscript. One FASTQ file is provided per cell. Cells are named with their plate and well IDs and the subject ID. Empty wells (no-cell controls) are named "blank". Corresponding transcriptome files use the same naming with the "_transcriptome" suffix.

  Dataset EGAD00001011150

• Single cell RNA seq of breast cancer stem cells

  RNA sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations' mRNA will be detected. With respect to breast cancer, it has been also reported that cancer cells can sub-gropued into cancer stem cells and non-cancer stem cells. Although the mRNA expressions' difference between this two groups has been profoundly investigated, whether each group is composed by unique cell or not is yet to be elucidated. Since cancer stem cells are the thought to be the major contributor of metastasis and/or recurrence, we focused on cancer stem cells in this study. We separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. Thereafter, we sequenced mRNA of cancer stem cells in single cell resolution. From this result, we examined whether these cells can be sub-grouped or not.

  Study JGAS000305

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• RNA-seq of M-CSF differentiated human peripheral monocyte-derived macrophages (MDMs) - Validation macIDR

  Macrophages represent multifunctional leukocytes defined by their stimulus-specific transcriptional reprogramming. As in vivo macrophages are often difficult to obtain, in vitro macrophage models are often used. We aggregated public expression data to define consensus expression profiles for eight commonly-used in vitro macrophage models and built the classifier macIDR, capable of distinguishing macrophage subsets with high accuracy (>0.95). Classification of in vivo macrophages suggested that alveolar macrophages resembled interleukin-10 activated macrophages in general whereas chronic obstructive pulmonary disease patients displayed decreased similarity to interferon-γ stimulated macrophages. Adipose tissue-derived macrophages were classified as unstimulated macrophages, but would resemble LPS-stimulated macrophages more in diabetic-obese patients. Rheumatoid arthritic synovial macrophages were similar to macrophages stimulated with interleukin-10 or interferon-γ. Altogether, our results suggest that macIDR is capable of identifying in vitro macrophages. By projecting in vivo macrophages onto the in vitro macrophages, we were capable of elucidating macrophage-specific changes as a result of tissue and disease.

  Study EGAS00001003451

• Genetic investigation of 12q-amplified osteosarcomas

  Genetic investigation of 12q-amplified osteosarcomas using both whole genome short- and longread and transcriptome sequencing.

  Dac EGAC50000000340

• MiRNA_Validation

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002752

• MiRNA_TrainTest

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002754

• A single cell view on host immune transcriptional response to in vivo BCG-induced trained immunity

  Study EGAS00001006990

• SF10320

  SF10320 Unknown.

  Dataset EGAD00001006314

• GATCI RNAseq fastqs

  Raw RNA sequence data (fastq) for the GATCI project

  Dataset EGAD00001005810

• TEST3 Dataset

  TEST3 dataset containing 1 FASTQ file with mRNA reads.

  Dataset EGAD00001001920

• Transcriptome Sequencing Data of High Grade Serous Ovarian Cancer

  Study EGAS00001004714

• Identification_of_drug_resistance_genes_in_melanoma_by_mRNA_gene_expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistanceThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000815

• Transcriptome analysis of samples derived from GBM tumors, and relevant cell lines established and maintained at 5% or 20% oxygen.

  The goal of the study was to compare the transcriptome of patient-derived serum-free GBM cell lines to that of parental GBM tumors. For each patient, three samples were analyzed: GBM tumor, cell line growing at 5% oxygen, and cell line growing at 20% oxygen. Analysis demonstrated the enrichement in cell cycle and DNA repair gene expression in cell lines when compared to parental tumor sample. Moreover, cells cultured at 5% oxygen maintained hypoxia, carbon metabolism and tumor progression transcriptional pattern characteristic for GBM.

  Study EGAS00001006267

• A transcriptome atlas of human skeletal muscles

  We generated a large transcriptome atlas of human skeletal muscles by collecting biopsies from 6 different muscles to determine molecular signatures that may be distinct between leg muscles. The biopsies were collected from gracilis (GR), semitendinosus (ST), vastus lateralis (VL), vastus medialis (VM), rectus femoris (RF), and gastrocnemius lateralis (GL) muscles. We also investigated molecular differences within the muscle by including two biopsies from the middle and distal sides of the semitendinosus muscle (STM and STD, respectively). In total, 128 samples from 20 individuals (aged 25 ± 3.6 yr) were analyzed.

  Study EGAS00001005904

• Sebaceous carcinoma tumor/normal exome sequencing and transcriptome sequencing. Transcriptome sequencing of

  Sebaceous carcinomas (SeC) are cutaneous malignancies that, in rare cases, metastasize and prove fatal. Here we report whole exome sequencing on 32 SeC, revealing distinct mutational classes that explain both cancer ontogeny and clinical course. A UV-damage signature predominated 10/32 samples, while 9 were instead defined by microsatellite instability (MSI) mutations. UV-damage SeC exhibited poorly differentiated, infiltrative histopathologycompared to MSI signature SeC (p = 0.003), features previously associated with dissemination. Strikingly, UV-damage SeC transcriptomes and anatomic distributionclosely resembling those of cutaneous squamous cell carcinomas (SCC), implicating sun-exposed keratinocytes as a cell of origin. Like SCC, this UV-damage subclass harbors a high somatic mutation burden with >50 mutations/Mb, predicting immunotherapeutic response. In contrast, ocular SeC acquire far fewer mutations without a dominant signature, but show frequent truncating mutations in the ZNF750 epidermal differentiation regulator. Our data exemplify how different mutational processes convergently drive histopathologically related but clinically distinct cancers.

  Dataset EGAD00001004016

• TSO500 on RNA

  TruSight Oncology 500 RNA probes panel on case 521

  Dataset EGAD50000000271

• QuantSeq 3'-mRNAseq of pathogen-stimulated PBMCs

  5 donors, 4 stimuli, 2 time points

  Study EGAS50000000007

• The BAF chromatin remodeling complex is a novel target of spliceosome dysregulation in SF3B1-mutated chronic lymphocytic leukemia

  Study EGAS00001006771

• RNAseq data

  RNAseq data for 10 patients: 10 tumors and 10 cell lines

  Dataset EGAD00001002691

• PCa RNASeq data

  RNASeq data from paired malignant/benign prostate tissues

  Dataset EGAD00001005931

• RNAseq

  RNAseq of pancreatic cancer organoids.

  Dataset EGAD00001010834

• LCNEC study - RNAseq data set

  RNAseq Data set

  Dataset EGAD00001003801

• Spatial Transcriptomic BC ILC

  Fastq files from 4 Visium spatial transcriptomic ILC sections

  Dataset EGAD50000002494

• Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

  We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

  Study EGAS00001001659

• Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma

  Dataset EGAD00001003324

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_2020

  Dataset EGAD00001006003

• Dataset for study EGAS00001004946 (Endothelium-derived stromal cells contribute to bone marrow niche formation)

  Dataset EGAD00001006914

• RNAseq for 190 AML patients

  This dataset contains 190 fastq files sequenced with Illumina HiSeq500.

  Dataset EGAD50000000490

• Single nuclei sequencing (snRNA-seq) of patient tumours

  snRNA-seq was performed on patient samples

  Study EGAS50000000617

• ORIENT study

  scRNAseq dataset containing 5 healthy donors and 4 asthmatic donors.

  Dataset EGAD00001009687

• Bulk RNAseq

  Bulk RNAseq from 183 premalignant gastric biopsies

  Dataset EGAD00001010131

• Characterization of HCV-specific CD4 T cells during DAA-Therapy

  To be added...

  Dataset EGAD00001005432

• IRF5 HL RNASeq dataset

  bam files associated with the study EGAS00001001205

  Dataset EGAD00001001417

• Pipeline study - RNAseq dataset

  Fernandez-Cuesta et al., RNAseq data Pipline

  Dataset EGAD00001000746

• PTA_thyroid__RNA_

  Exploring the somatic mutations in single cells derived from the thyroid

  Study EGAS00001007946

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• Complete sequencing dataset of study EGAS00001002795

  Dataset EGAD00001004572

• Whole transcriptome and 850k methylome profiling of human MBM

  Assessment of methylation status of ~850,000 sites

  Dataset EGAD00010002281

• SCANDARE MACARON 78 bulk-RNAseq HGSOC

  78 bulk-RNAseq from HGSOC patients from SCANDARE MACARON

  Dataset EGAD50000000205

• COVID-19 PBMC single-cell transcriptomics, multiplexed

  COVID-19 PBMC single-cell transcriptomics, multiplexed

  Dataset EGAD50000000188

• RNAsequencing

  RNAsequencing from 271 samples.

  Dataset EGAD50000000312

• RNAseq for 4 pdx and 1 cell-line

  RNAseq for #1049, #111, #1217, #206, COV362

  Dataset EGAD50000000032

• CRISPR_perturbations_IRF4_PRDM1_Bcells

  CRISPR perturbations of IRF4, PRDM1, and AAVS1 (within PPP1R12C gene) in activated B cells

  Dataset EGAD50000002113

• IPF Core Biopsy Study Gene Expression Data

  Matrix of gene x sample RNAseq read count data.

  Dataset EGAD00001007566

• RNAseq samples

  20 RNAseq samples of Human CD4+ cells

  Dataset EGAD00001010182

• Molecular effects of TYK2 inhibition

  Transcriptomic profiling of skin biopsies from psoriasis patients following treatment with deucravacitinib

  Dataset EGAD00001008417

• DSRCT RNAseq

  Desmoplastic small round cell tumor (DSRCT) RNAseq data. 14 tumor samples.

  Dataset EGAD00001003980

• Centroblast Cohort

  miRNA-seq Cohort of 15 Benign Centroblasts

  Dataset EGAD00001001075

• RNA Sequence-Based Analysis Used to Compare Breast Primary and Metastatic Tumor Pairs

  The goal of this study is to capture the transcriptome landscape of luminal and basal-like metastatic breast tumors. We will aim to show the importance of using the most up-to-date cancer biopsy for detecting cancer drivers that were often not present in the primary tumor.

  Study phs001866

• Epigenomic timecourse of brain organoid development

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. At each time point used scCut&Tag to profile histone modifications (H3K27me3, H3K27ac, H3K4me3) as well as multiome-seq (10X) to jointly profile transcriptome and chromatin accessibility from the same cell suspension. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000222

• Human CMV-specific CD8+ T cells

  In this study we established a comprehensive workflow to collect multi-omics single-cell data using a commercially available micro-well based platform. This included whole transcriptome, cell surface markers (targeted sequencing-based cell surface proteomics), T cell specificities, adaptive immune receptor repertoire (AIRR) profiles and sample multiplexing. With this technique we identified novel paired T cell receptor sequences for three prominent human CMV epitopes. In addition, we review the ability of dCODE dextramers to detect antigenspecific T cells at low frequencies by estimating sensitivities and specificities when used as reagents for single-cell multi-omics.

  Dataset EGAD50000000894

• Spatio-temporal evolution of the primary glioblastoma genome (newly added after 2015)

  Since our genomic analysis of 38 GBM patients, we recruited more cases to further study spatial and temporal evolution of glioblastoma with international collaboration of multiple institutes. The cases in this study includes the whole exome and transcriptome of GBM patients newly recruited in Samsung Medical Center.

  Study EGAS00001001800

• Molecular profiles and urinary biomarkers of upper tract urothelial carcinomas associated with aristolochic acid exposure

  This study present a molecular analysis of upper urinary tract urothelial tumours (UTUC) and urines of patients with past exposure to carcinogenic aristolochic acid (AA). Tumor exome and transcriptome sequencing revealed the AA-specific mutations in UTUC and identified deleterious mutations at both the gene and transcript levels.

  Study EGAS00001005363

• Growth Hormone (GH) -secreting Pituitary Adenoma

  We profiled the somatic landscape of 21 growth hormone (GH) -secreting pituitary adenomas using somatic copy-number alteration (SCNA), whole-genome sequencing (WGS), bisulfate sequencing, and transcriptome approaches. See details in Valimaki et al. Genetic and epigenetic characterization of growth hormone (GH) - secreting pituitary tumors. Manuscript in preparation, 2019.

  Study EGAS00001003488

• Multi-omics of Richter syndrome

  Richter syndrome (RS) is the aggressive transformation of Chronic Lymphocytic Leukemia, mostly with Diffuse Large B-Cell Lymphoma histology. While histologically similar, RS and de novo DLBCLs present with different clinical courses. We characterized the RS epigenome by combining genome-wide DNA methylation with transcriptome-sequencing on a large RS cohort.

  Study EGAS00001005495

• Development and Validation of a Prognostic and Predictive 32-Gene Signature for Gastric Cancer

  We applied this signature to a 567-patient GC cohort to establish genomic-based molecular subtypes and then used a support vector machine to build a molecular subtype-based risk-scoring model. Both source code and supplementary datasets for risk score prediction are available at https://github.com/hwanglab/Yonsei_gastric_cancer_32genes.

  Dataset EGAD00001008091

• Single cell sequencing of human normal breast myoepithelial cells

  The dataset includes 6 FASTQ files with single cell transcriptome sequencing data of normal breast myoepithelial cells from ducts and TDLUs derived from reduction mammoplasties from three patients. Chromium Single Cell 3’ Reagent Kit v2 or v3 (10x Genomics) were used for processing of cells, whereafter sequencing was performed using the Illumina® NextSeq500/550 High Output Kit v2. Cell Ranger was used for generating FASTQ files and files from different lanes were concatenated prior to uploading the data to EGA.

  Dataset EGAD00001008468

• Molecular and phenotypic data for patients enrolled in the IMmotion150 trial

  Tumor transcriptome and whole exome sequencing data (matched tumor/normal for somatic mutation calling) along with key phenotypic information are provided for patients enrolled in the phase 2 IMmotion150 trial, assessing efficacy of atezolizumab monotherapy or combination of atezolizumab and bevacizumab versus standard of care (sunitinib) in 1L renal cell carcinoma. This data set accompanies the respective Nature Medicine publication (PMID: 29867230).

  Dataset EGAD00001004183

• Genome and transcriptome sequence data from a colorectal adenocarcinoma patient (Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer)

  Genome and transcriptome sequence data from a colorectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study. These data are included in the manuscript entitled, "Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer".

  Dataset EGAD00001001876

• scRNA-seq of glioblastoma cells alone or after co-culture with cerebral organoid cells

  Dataset EGAD00001005315

• README-for-EGAS00001004349-linking-HIPO-K09R-RNA-files

  Dataset EGAD00001006785

• RNA-sequençing of 21 inflammatory hepatocellular adenomas and 1 non-tumoral sample

  Dataset EGAD00001005284

• RNAseq for 8 PDX

  RNAseq for #111, #1177, #206, #201, #29, #931, WO-19, WO-2

  Dataset EGAD50000000116

• COVID-19 whole blood bulk trasncriptomics multi-center

  COVID-19 whole blood bulk trasncriptomics multi-center

  Dataset EGAD50000000187

• Single cell RNAseq of PBMC in chimeric twins

  scRNAseq data generated with 10x genomics

  Dataset EGAD50000000132

• Pilot data of PDiamond Lung Cancer Data

  RNAseq pilot data of PDiamond Korean lung cancer data

  Dataset EGAD50000000843

• EGAS00001006863

  Targeted DNA-sequencing, whole genome sequencing and whole transcriptome sequencing data on childhood leukaemia patients enrolled on to UK clinical trials (specifically UKALL2003 and UKALL2011).

  Dac EGAC50000000342

• ADARIO Dataset

  RNA editing analyses of BRCA-isogenic cell lines and patient-derived xenografts (PDX)

  Dataset EGAD50000000739

• PBMC_dual_10X_kit

  Dual snRNAseq and ATACseq of replicate PBMC samples for 10X beta testing.

  Study EGAS00001004834

• HCA_Muscle_Adult_Wellcome_RNA_Managed_Access

  Transcriptomic analysis of skeletal muscle, to understand the mechanisms of muscle ageing.

  Study EGAS00001007495

• RNAseq of U251 and two ID1 gene knockouts

  RNAseq of U251 and two ID1 gene knockouts

  Dataset EGAD00001005089

• Dataset of PPB

  Whole exome sequencing and miRNA-seq data of PPB.

  Dataset EGAD00001000822

• DATA FILES FOR GRUBER SJAMLM7 RNASEQ

  DATA FILES FOR GRUBER SJAMLM7 RNASEQ

  Dataset EGAD00001003135

• snRNA-seq of two samples of ATCWGS42

  This dataset contains snRNA-seq data of two samples of ATCWGS42

  Dataset EGAD50000002146

• Single cell sequencing in D425

  Single cell sequencing aligned BAM files for the D425 cell line

  Dataset EGAD50000002304

• Conserved interferon-gamma signaling and decreased immune exclusion programs in responses to immune checkpoint blockade therapy

  We analyzed baseline and on-therapy tumor biopsies from 101 patients with advanced melanoma treated with nivolumab (anti-PD-1) alone or combined with ipilimumab (anti-CTLA-4). Analysis of whole transcriptome data showed that T cell infiltration and interferon-gamma signaling signatures corresponded most highly with clinical response to therapy, with a reciprocal decrease in cell cycle and WNT signaling pathways in responding biopsies. Clinical outcome differences were likely not due to differential melanoma cell responses to interferon-gamma, as 57 human melanoma cell lines exposed in vitro to this cytokine showed a conserved interferon-gamma transcriptome response unless they had mutations that precluded signaling from the interferon-gamma receptor. Therefore, the magnitude of the antitumor T cell response and the corresponding downstream interferon-gamma signaling are the main drivers of clinical response or resistance to immune checkpoint blockade therapy.

  Study EGAS00001004545

• Short read sequencing dataset of pathogen-stimulated PBMCs

  QuantSeq 3'-mRNAseq. 5 donors, 4 stimuli, 2 time points

  Dataset EGAD50000000012

• Normalized read counts for 84 PDAC samples

  Bulk RNAseq analysis of 84 PDAC samples : Normalized read counts

  Dataset EGAD50000000537

• RNAseq dataset

  RNAseq experiment after DIS3 ASO or Control ASO treatment on human cells under plasmablast differentiation.

  Dataset EGAD50000001243

• Neutrophils infected with leishmania donovani at timepoint 6h

  Neutrophils infected with Leishmania donovani at timepoint 6h

  Dataset EGAD00001006808

• Genomic Analysis of Mucinous Tumours (GAMuT) - RNA

  RNASeq for Genomic Analysis of Mucinous Tumours (GAMuT)

  Dataset EGAD00001005190

• Gene expression from human iPSC derived motor neurons.

  Gene expression from human iPSC derived motor neurons.

  Dataset EGAD00001005216

• RNA sequence of HUB_5 cell culture

  RNA sequence data for conditionally reprogrammed cells from patient HUB_5

  Dataset EGAD00001001923