Search Results - EGA European Genome-Phenome Archive

Relapse CHL study

Classical Hodgkin Lymphoma (CHL) is characterized by a complex tumor microenvironment (TME) that supports disease progression. While immune cell recruitment by Hodgkin and Reed–Sternberg (HRS) cells is well-documented, the role of non-malignant B cells in relapse remains unclear. Using single-cell RNA sequencing (scRNA-seq) on paired diagnostic and relapsed CHL samples, we identified distinct shifts in B cell populations, particularly an enrichment of naïve B cells and a reduction of memory B cells in early-relapse compared to late-relapse and newly diagnosed CHL. The enrichment of naïve B cells in early relapse biopsies was confirmed in independent validation cohorts using scRNA-seq and immunohistochemistry. Notably, naïve B cells in early-relapse samples exhibited high expression of LGALS9, an immunosuppressive molecule known to interact with T cell immunoglobulin and mucin domain 3 (TIM-3) on regulatory T cells (Tregs). Cell-cell interaction analysis revealed the importance of interactions between LGALS9+ naïve B cells and TIM-3+ Tregs in the early-relapse setting. Spatial analysis by imaging mass cytometry confirmed close proximity of LGALS9+ naïve B cells with TIM-3⁺ CD4⁺ T cells and HRS cells, pointing to their role in shaping an immunosuppressive niche. Our findings highlight a previously unrecognized population of LGALS9⁺ naïve B cells with immunoregulatory potential in early-relapse CHL and provide new insights into the spatial and transcriptional architecture of the relapsed TME in CHL.

Study EGAS00001008222

B cell receptor silencing reveals origin and dependencies of high-grade B cell lymphomas with MYC and BCL2 rearrangements

High-grade B cell lymphomas with MYC and BCL2 rearrangements (HGBCL-DH-BCL2) represent highly aggressive Germinal center (GC) derived B cell malignancies with dismal prognosis and limited therapeutic options. In the present study, we investigated the expression of BCR complex components, including immunoglobulin (IG) heavy (H) and light (L) chains, and CD79A and CD79B signaling subunits in HGBCL-DH-BCL2, scoring 65% of cases with undetectable IGH immunoreactivity (IGHUND). Transcriptomics (bulk RNA-seq) and genetic (whole exome/genome sequencing) analyses indicated that IGHUND and IGH+ HGBCL-DH-BCL2 lymphomas represent distinct biological entities. Specifically, IGHUND HGBCL-DH-BCL2 exhibit a GC DZ-like molecular program, and select subset-specific gene mutations pointing to distinct evolutionary trajectories respect to the IGH+ counterparts. IG profiling revealed that IGHUND HGBCL-DH-BCL2 preserved potentially productive, hypermutated IGH variable (V) gene rearrangements, indicating a selective advantage conferred to the malignant B cells by residual IGH molecules. Accordingly, disruption of the productively rearranged IGHG1 gene in BCRnull HGBCL-DH-BCL2 cell line model confirmed the dependency on IGH expression for optimal fitness. Using transcriptomics and in situ RNA-scope analysis, we reported that IGHUND HGBCL-DH-BCL2 originated from IG-class switched GC B cells, while IGH-expressing tumors were selected for continuous IGM expression. Moreover, while IGH+ HGBCL-DH-BCL2 favor IGM/IG-Kappa expression, IGHUND counterparts complete IG-Lambda light chain rearrangements. Notably, BCR silencing, caused by accelerated IGH turnover and reduced IGH expression, precedes HGBCL-DH-BCL2 onset, inducing RAG1/2-dependent IG light chain editing and eventually facilitating t(8;22)/IGL::MYC translocations. Finally, IGH silencing observed in HGBCL-DH-BCL2 cell models, which leads to intracellular retention/silencing of CD79B, results in reduced sensitivity to the CD79B-targeting antibody-drug conjugate Polatuzumab-vedotin. Collectively, HGBCL-DH-BCL2 originates from isotype-switched t(14;18)+ GC B cells that undergo IG light chain editing fuelling intra-clonal diversification, BCR silencing, and the acquisition of t(8;22) translocation, while preserving IGH dependency.

Study EGAS50000001047

RNA-Seq from PMM2-CDG Patients and Healthy Controls

Besides the predominant neurological involvement of PMM2-CDG patients, around 20% of patient mortality has been linked to severe infections. However, the immunological dysfunction in PMM2-CDG is not well understood. In this study, we aimed to address this gap and study the molecular mechanisms affected behind immunological issues in PMM2-CDG. Primary skin fibroblasts from three PMM2-CDG patients and three healthy controls were stimulated or not with TNF-alpha and their gene expression was assessed by RNA sequencing. The response to TNF-alpha was characterized based on the differential expressed genes and functional enrichment and and compared between PMM2-CDG and healthy individuais. Gene expression alterations and functional enrichment were further validated by several experimental assays by ELISA, Flow Cytometry and Western Blotting.

Study phs003313

Molecular risk stratification in patients with T1 colorectal cancer_WES

The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have 'born-to-be-bad' aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world's largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3' RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

Dataset EGAD00001010890

Multiomic Landscape of Multiple Myeloma Precursor and Relapsed Disease

Multiple myeloma (MM) is a treatable, though incurable, plasma cell malignancy. The molecular mechanisms driving disease onset and the emergence of drug resistance remain elusive. To better characterize the mutational, transcriptional, and epigenetic alterations that accompany MM disease evolution, we accessed molecular data from MM patients treated at Moffitt Cancer Center, with bone marrow biopsies collected between 2011 and 2023.We performed scMultiome (single-cell, paired RNA/ATAC-Seq, 10x Genomics) on 18 CD138+-selected bone marrow aspirate samples, including: 2 healthy donors, 3 patients with monoclonal gammopathy of undetermined significance (MGUS), 4 with smoldering myeloma (SMM), 3 with newly diagnosed MM (NDMM), 1 with early relapse MM (ERMM, 1 to 3 lines of therapy), and 5 with late relapse MM (LRMM, 4 or more lines of therapy). Our dataset includes a sequential sample: a patient with a premalignant condition ("scMultiome_SMM_4") that progressed to active myeloma ("scMultiome_NDMM_3"). These data allow for the assessment of transcriptional and epigenetic dysregulation at the cellular level. Our findings illustrate the dynamic epigenetic and transcriptional landscapes that accompany MM disease progression.We also conducted CUT&Tag analysis on 4 NDMM and 4 LRMM samples to map histone modifications, specifically H3K27ac, to investigate their role in transcriptional reprogramming observed in advanced stages of MM. This analysis revealed sample heterogeneity in terms of super-enhancer-regulated genes associated with active transcription.This cohort also includes samples from the clinical trial NCT04151667, “Daratumumab-Based Response-Adaptive Therapy for Older Adults With Newly Diagnosed Multiple Myeloma.” We performed scRNAseq (single-cell RNA sequencing, 10x Genomics) on 30 CD138+-selected bone marrow aspirate samples and 31 pre-sort samples featuring bone marrow mononuclear cells of various cell types from 5 healthy donors and 11 patients with newly diagnosed MM (NDMM). Our dataset includes sequential samples for all 11 NDMM patients, both prior to induction therapy (denoted by ‘a') with Daratumumab and Dexamethasone, and at cycle 2 day 22 (C2D22, i.e., 60 days after induction therapy start, denoted by ‘b'). For three NDMM patients, we also have samples at relapse (denoted by ‘c'). These data allow for the assessment of transcriptional dysregulation at the single-cell level in both the tumor and immune-tumor microenvironment, associated with Daratumumab treatment in NDMM patients.In addition to the molecular data, demographic, and phenotypic information for all samples is provided.

Study phs003892

BCSA_Exome+SmartSeq3

Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

Dataset EGAD00001009781

RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

Dataset EGAD00001010920

Transcriptomic Analysis of HIV-Infected Cells

Defining the attributes of rare CD4 T cells that harbor latent HIV under therapy with anti-retroviral agents has been challenging due to difficulties in identifying and isolating these cells. These cells represent an important barrier to cure, and characterizing them would aid the design and development of novel HIV cure strategies. In this study, we addressed this challenge using a custom microfluidic technology named Focused Interrogation of cells by Nucleic acid Detection and Sequencing (FIND-seq) that isolates HIV-infected cell transcriptomes, based on HIV DNA detection. We applied this method to HIV DNA+ memory CD4 T cells isolated from blood from five persons with HIV who were receiving anti-retroviral agents. After curating samples based on data quality, we proceeded with bioinformatics analysis from three persons. This analysis identified six transcriptomic pathways that were inhibited in HIV DNA+ cells compared to HIV DNA- cells. These included death receptor signaling, necroptosis signaling, and anti-proliferative G-alpha12/13 signaling. Furthermore, we identified two gene clusters, including 60 and 85 genes, that were significantly associated with HIV DNA+ cells identified by co-expression network analysis. These genes included negative regulators of HIV transcription that were higher in HIV DNA+ cells, positive regulators of HIV transcription that were lower in HIV DNA+ cells, and other genes involved in the negative regulation of mRNA translation, additional RNA processing functions, and the regulation of cellular state and fate. We further examined these signatures in transcriptomic data from CD4 T cell subsets sorted by flow cytometry from nine persons with HIV. We found a partial similarity between the smaller cluster of genes and the signature of CCR6- peripheral TFH cells. Raw sequencing data from all eleven human participant samples included in the study are available. These include samples from two participants who were studied only by FIND-seq, three participants who were studied by both FIND-seq and flow cytometry and six participants who were studied only by flow cytometry.

Study phs003095

Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

Study phs003535

Randomized Phase II 2 x 2 Factorial Trial of the Addition of Carboplatin +/- Bevacizumab to Neoadjuvant Weekly Paclitaxel Followed by Dose-Dense AC in Hormone Receptor-Poor/HER2-Negative Resectable Breast Cancer: DNA Sequencing

This randomized phase II trial studies how well paclitaxel with or without carboplatin and/or bevacizumab followed by doxorubicin and cyclophosphamide works in treating patients with breast cancer that can be removed by surgery. Drugs used in chemotherapy, such as paclitaxel, carboplatin, doxorubicin, and cyclophosphamide, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing. Bevacizumab may stop the growth of tumor cells by blocking blood flow to the tumor. Giving chemotherapy together with bevacizumab before surgery may make the tumor smaller and reduce the amount of normal tissue that needs to be removed. All participants in this study were female. RNA sequencing data from the same patients were published under phs001863. Subject aliases are the same in the two datasets.

Study phs003801

The impact of mutational clonality in predicting the response to anti-PD-L1/PD-L1 in advanced urothelial cancer

The advent of immune checkpoint inhibitors (ICI) has radically changed the management and therapeutic treatment landscape for patients with cancer. It has been shown that the use of these inhibitors can result in long-term complete remissions even in cases with advanced stages of the disease. However, only a small fraction of patients respond to the treatment. A better understanding of which factors could drive this clinical benefit is fundamental to building more accurate predictive biomarkers and developing alternative therapeutic options for patients who are unlikely to benefit. In order to address this issue, we have generated and analyzed whole exome sequencing (WES) and RNA sequencing (RNASeq) data from a cohort of metastatic urothelial carcinoma patients (N = 27) treated with ICI such as anti-PD-(L)1 monoclonal antibodies.

Study EGAS00001007086

DynaTag for efficient profiling of transcription factors in small samples and single cells

Systematic discovery of transcription factor (TF) landscapes in low-input samples and at single cell level is a major challenge in the fields of molecular biology, genetics, and epigenetics. To address this, we present here cleavage under Dynamic targets and Tagmentation (DynaTag), which allows robust mapping of specific TF-DNA interactions via the use of a physiological salt solution during sample preparation. Using this method, we revealed occupancy alterations for 15 different TFs in stem cell and cancer tissue models. Of note, we showcased for NANOG, MYC, and OCT4 differentially occupied genomic loci during stem cell differentiation, both in bulk and at single-cell resolution. DynaTag demonstrated superior signal-to-background ratio and occupancy resolution in comparison to CUT&RUN and ChIP-seq. In addition, a model for small cell lung cancer chemotherapy treatment in vivo showed increased chromatin occupancies of the gain-of-function mutant P53 p.R248Q, FOXA1, and MYC at altered gene pathways, such as epithelial-mesenchymal-transition. Altogether, these results highlight the technical advancement of DynaTag to uncover TF landscapes in cell models and in tissues of a complex disease model.

Study EGAS50000001074

Genomic Profiling of Pediatric Tumors by Cell Free DNA Sequencing

BACKGROUND Analysis of cell-free DNA (cfDNA) from peripheral blood has been studied extensively for detection and monitoring therapy response in adult cancers, but utility in pediatric tumors is unclear. METHODS We studied 233 children with hematologic, solid and brain tumors. cfDNA was extracted from 1 mL of plasma collected at diagnosis. Circulating tumor DNA (ctDNA) in cfDNA was quantified and diverse classes of somatic genomic variants were detected using PeCan-Seq. PeCan-Seq findings were compared with matched tumor whole-genome and whole-exome sequencing data. Minimal residual disease (MRD) status was evaluated by cfDNA PeCan-Seq in 14 patients with B-cell acute lymphoblastic leukemia. RESULTS Plasma cfDNA yields at diagnosis were higher for hematologic malignancies than for solid and brain tumors. Patients with hematologic malignancy were 100% ctDNA-positive, the median ctDNA fraction in cfDNA was 0.77. We detected 97% variants that were present in tumors and covered by the capture panel, and 50 subclonal variants that were present in cfDNA only. Our approach enabled detection of sequence and structural variants in B-ALL ctDNA at varying levels of MRD. Nineteen of 38 patients with solid tumors were ctDNA-positive, with high prevalence in Ewing Sarcoma, liver tumors and osteosarcoma. One of 19 brain tumor patients was ct-DNA positive, indicating lack of utility for plasma-derived cfDNA in this disease. Notably, cfDNA analysis of a single plasma sample identified genomic features in ctDNA derived from B-ALL, concurrent primary neuroblastoma, and a later neuroblastoma relapse, indicating that genomic variations from multiple tumors could be detected simultaneously. CONCLUSIONS Pediatric patients with hematologic malignancy had an abundance of plasma ctDNA at diagnosis. Plasma ctDNA levels varied between different solid tumor types, more studies are needed to determine utility. Panel-based cfDNA sequencing could serve as a non-invasive approach for pediatric cancer diagnosis and disease monitoring.

Study EGAS50000000072

RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting. 117 total samples were sequenced with paired reads on 10 lanes from different flowcells. They were loaded as 2400 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

Dataset EGAD50000002278

ecDNA copy number heterogeneity

Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

Study EGAS50000000509

Count Me In (CMI): The Metastatic Breast Cancer (MBC) Project (CMI-MBCproject)

Count Me In - The Metastatic Breast Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Breast Cancer Research The Metastatic Breast Cancer Project is a research study that directly engages patients with metastatic breast cancer via social media and advocacy groups and empowers them to accelerate cancer research by sharing their samples and clinical information. Our goal is to create a publicly available dataset of genomic, molecular, clinical, and patient-reported data to enable research. Patients in the US or Canada may register online. Registered patients are sent an online consent form that asks for permission to obtain and analyze their medical records, tumor tissue, saliva, and blood samples. Once enrolled, patients are sent a saliva kit and asked to mail back a saliva sample, which is used to extract germline DNA. Study staff contact participants' medical providers and obtain medical records and a portion of their stored tumor biopsies. Patients may be asked to mail in a blood sample, which is used to extract cell free DNA (cfDNA). Whole exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. Clinically annotated genomic data are used to study specific patient cohorts (including outliers) and to identify mechanisms of response and resistance to therapies. All de-identified data, including genomic, clinical, and patient-reported data, are shared via public databases on a pre-publication and recurring basis as it is generated. The latest data release in cBioPortal is available here. Study updates are shared with participants regularly.

Study phs001709

Bulk RNA sequencing of metastatic colorectal cancer patient-derived xenografts with known response to irinotecan

Chemotherapy is the standard-of-care treatment for metastatic colorectal cancer (mCRC) and benefits some patients, but what distinguishes responders from non-responders is unclear. In this study, we expand a pre-existing collection (https://doi.org/10.1158/2159-8290.CD-24-0556) of molecularly annotated patient-derived xenografts to uncover functional predictors of response to 5-FU and irinotecan combination therapy (FOLFIRI) in mCRC. We complemented previous expression profiles with bulk RNAseq for 38 xenografts with known response to irinotecan.

Study EGAS50000001485

Autism Post-Mortem Brain RNA-Sequencing: SRRM4 Splicing Study

Purpose: The goal of this study was to assess the status of splicing changes in microexons in the cortex of individuals with autism. Methods: We performed RiboZero Gold (rRNA depleted) 50bp PE RNA-seq in a larger set of case and control samples to define 12 autism and 12 control samples showing the greatest global differential gene expression change. These samples, which show differential expression of the splicing regulator SRRM4, were used to evaluate global splicing changes. Results: Within these samples, 126 of 504 (30%) detected alternative microexons display, a mean ΔPSI > 10 between ASD and control subjects of which 113 (90%) also display neural-differential regulation. By contrast, only 825 of 15,405 (5.4%) longer (i.e. > 27 nt) exons show such misregulation, of which 285 (35%) correspond to neural-regulated exons. Notably, we also observe significantly higher correlations between microexon inclusion and nSR100 mRNA expression levels across the stratified ASD samples and controls, for those microexons regulated by nSR100 relative to those microexons that are not regulated by this factor (p=1.4x10-7, Wilcoxon Sum Rank test). Conclusions: These data suggest microexon regulation is a potentially important mechanism underlying ASD and likely other neurodevelopmental disorders.

Study phs000872

Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

Rituximab, a CD20+ B cell depletion therapy, is frequently used in the treatment of systemic lupus erythematosus (SLE). However, variability in patient response highlights the need for a deeper understanding of the underlying immune cell dynamics of B cell depletion and repopulation. In this study, we conducted longitudinal single-cell profiling of nine SLE patients treated with rituximab from pretreatment to up to 15 months post-treatment. These were compared to eight healthy controls. We profiled PBMCs via 10X Genomics single-cell RNA, surface protein (CITE-seq), B cell receptor (BCR), and T cell receptor (TCR) sequencing and sequenced bulk BCR repertoires in parallel. For single cell sequencing, 10 pools were created with an equal number of cells from 4 samples each. Samples collected at different timepoints from the same patient were distributed across different pools to allow demultiplexing of individuals using genotypes captured from the scRNA-seq data. Libraries were pooled using a ratio of GEX:CITE:TCR:BCR=9:2:1:1 and were sequenced across two lanes of the NovaSeq 6000. For bulk BCR sequencing, individual samples were demultiplexed using primer barcodes and paired-end BCR amplicon reads were merged prior to submission; data are provided as unmapped single-end reads.

Dataset EGAD00001015817

ChIIP-seq and RNA-seq

epigenome profiling in tumor tissues and paired normal tissues of LUAD patients and transcriptome profiling in tumor tissues of LUAD patients.

Dataset EGAD00001007066

A single-cell atlas of the early COPD lung - Nanopore long-read

Single cell atlas of the human airways from 10 patients suffering of early stage Chronic Obstructive Pulmonary Disease and 12 healthy age matched volunteers. This dataset was sequenced by 10X Genomics 3’ RNA-seq profiling. It is composed of more than 400 000 cells coming from 119 samples total. Sampling was performed by brushings and biopsies from the nose to the 6 th division of the airways. 14 samples were also sequenced using Nanopore long-read sequencing.

Dataset EGAD50000001002

ICARUS-LUNG01 dataset

A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

Dataset EGAD50000001014

Whole genome sequencing of multiple myeloma patient samples.

Tumor (CD138+ plasma cells) and non-tumor (peripheral blood white cells or stem cell harvest) DNA from patients with a plasma cell dyscrasias were sequenced. Whole genome sequencing using high molecular weight DNA was performed using the 10X Genomics Chromium platform on either a HiSeq4000 or NovaSeq (Illumina) using 100 to 150 bp paired-end reads. The dataset consists of 111 patients, and 223 samples in total (matched tumor and control per patient; one patient had 2 tumor samples sequenced). Diseases consisted of 2 MGUS patients, 8 SMM patients, 91 newly diagnosed myeloma patients, 1 previously treated patient, 4 relapsed MM patients, and 5 PCL patients. Paired RNA-seq data are available for 81 of the samples under study EGAS00001003411.

Dataset EGAD00001004452

G-SAM: Transcriptional Evolution of Glioblastomas Treated With Standard of Care

Collection of mostly matching primary and recurrent glioblastoma RNA-seq sample pairs, also matching with an earlier DNA sequencing study

Dataset EGAD00001007860

ScRNA-seq of PBMC and whole blood samples reveales a dysregulated myeloid cell compartment in severe COVID-19

In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

Dataset EGAD00001006550

12215 results for "cancer rna-seq"

in 108.23 milliseconds.