11750 results for "cancer rna-seq"

in 17.86 milliseconds.

• Dana-Farber Cancer Institute (DFCI) Brown Lab CLL Sequencing Study

  Chronic Lymphocytic Leukemia (CLL) is a hematological malignancy characterized by accumulation of CD5+CD19+ B cells in peripheral lymphoid organs, bone marrow and blood. In this study we analyze matched whole genome sequencing and RNA-seq data from CLL patients to characterize the mutational processes operative throughout tumor evolution. Source of tumor and normal DNA used is patient PBMC or B cells and saliva respectively.

  Study phs000879

• Pathogenesis and Immunity in Endemic Burkitt Lymphoma

  This genomic landscape of Burkitt lymphoma represents a multimodal sequencing of tumors and control tissues and individuals to better understand the etiology, and molecular pathogenesis of Burkitt lymphoma including the roles of the associated Plasmodium falciparum malaria and EBV infections. Comprehensive sequencing set includes genomic, transcriptomic, and epigenomic datasets in concert with variable clinical phenotypes and outcome information such as anatomical presentation site, in-hospital survival rates, and EBV genome type. This deposit includes additional small RNA-seq data from endemic BL (eBL) tumors and RNA-sequencing data from sorted NK cell subsets from the peripheral blood of eBL patients. The additional small RNA-seq data are from tumor specimens from 17 eBL cases, of the previously deposited polyA RNA-seq data from 28 eBL cases (phs1282.V1). The additional RNAseq data from Fluorescence-activated cell sorting (FACS) of NK cell subsets, isolated from the peripheral blood of 7 eBL cases. The additional RNAseq data are from eBL tumor samples of 5 eBL cases, BL cell lines established from these tumor samples and also NSG mouse tumors created by implanting the established BL cell lines into NSG mice. The dataset also includes RNAseq data of the NSG mouse tumors after treatment with Rituximab (RIT) and Phosphate buffered saline (PBS). The fifth batch of data includes mRNA-seq from different passages of a single eBL cell line that have variable EBV phenotypes (low passage with lytic EBV and high passage with latent EBV). This batch also includes lytic and latent lymphoblastoid cell line (LCL) clones from a single blood donor generated through infection with the strain of EBV isolated from the aforementioned eBL cell line. For initial transcriptome analysis see: Kaymaz et al. "Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-specific Difference." Molecular Cancer Research, 2017, PMID: 28465297. For initial microRNA analysis see: Oduor et al. "Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma." Frontiers in Microbiology 8, 2017, PMID: 28400759. For initial NK subsets RNA expression analysis see: Forconi et al. "A new hope for CD56negCD16pos NK cells as unconventional cytotoxic mediators: an adaptation to chronic diseases." Frontiers in Cellular and Infection Microbiology, 2020, PMID: 32373555.For initial eBL cell line and mouse avatar RNA expression analysis see: Saikumar et al. "Endemic Burkitt lymphoma avatar mouse models for exploring inter-patient tumor variation and testing targeted therapies." Life Science Alliance, 2023, PMID: 36878637. For general overview of cohort study see: Buckle et al. "Factors influencing survival among Kenyan children diagnosed with endemic Burkitt lymphoma between 2003 and 2011: A historical cohort study." Int J Cancer. 15:1231, 2016, PMID: 27136063.

  Study phs001282

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169

• RNA-seq of Ewing sarcoma tumors (ICGC)

  Ewing sarcoma (ES) is a primary bone tumor initiated by an EWSR1-ETS gene fusion. To characterize the transcriptome of Ewing sarcoma, RNA-seq was performed.

  Study EGAS00001003333

• Bulk and single-cell AML RNA-seq post ex vivo culture

  Bulk and single-cell RNA-seq performed on primary AML blasts cultured ex vivo for 3 days in standard or niche-like conditions.

  Study EGAS00001006265

• Verification of BCR reconstruction from single-cell RNA-seq using BraCeR

  This dataset was made to verify the computational reconstruction of B cell reseptors from single-cell RNA-seq using BraCeR. The dataset contains BCR-derived reads from single-cell RNA-seq from 13 cells using the Smart-seq2 protocol, as well as targeted BCR-sequencing data from the same cells.

  Dataset EGAD00001004199

• RNAseq of 12q-amplified osteosarcomas

  RNA-seq of 12q-amplified osteosarcomas for detection of gene fusions and gene expression analysis. RNA-seq was used to look for novel gene fusions and promoter swapping events, and study the expression levels of identified 3' partners. Additionally, global gene expression patterns were used to separate cases into clusters.

  Study EGAS50000000494

• Paired RNA-Seq of fCAB treated and bisulfite treated VDH01, partly depleted for NSUN3

  Paired RNA-seq of bisulfite treated VDH01 samples control or depleted for NSUN3 (4 replicates each). The samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of fCAB treated vdh01 samples control or depleted for NSUN3(4 replicates each). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of fCAB treated VDH01 samples (3). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of bisulfite treated VDH01 samples (3). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq.

  Dataset EGAD00001008742

• Nrf2 transcript alterations

  WGS and RNA-seq data for Nrf2 study

  Study EGAS00001001740

• RNA-seq

  RNA-seq

  Dataset EGAD00001008995

• The Role of ZEB2 during Human Neural Crest Cell Formation

  This study examined the role of ZEB2 during human neural crest cell formation. Human neural crest cells were differentiated from WiCell H1 human embryonic stem cells (WA01). Genome-wide transcriptional analysis (RNA-seq) was performed at day-3 and day-5 of human neural crest cell formation following siRNA knockdown of ZEB2 and using an N-terminal ZEB2 mutant H1 human embryonic stem cell line generated using CRISPR genome editing. RNA-seq was also performed on edited and unedited H1 human embryonic stem cells. ATAC-seq analysis was performed at day-3 and day-5 human neural crest differentiated from the N-terminal ZEB2 mutant embryonic stem cell line. Together, these data reveal the regulatory role of ZEB2 in the human neural crest gene regulatory network. We provide raw sequencing files for all RNA-seq and ATAC-seq samples.

  Study phs002701

• Epigenomic data of Human muscle stem cell

  To profile the epigenomic landscape of Human muscle stem cell, ChIP-seq of histone marks , WGBS and RNA-seq data were generated.

  Study EGAS00001006159

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  This dataset consists of RNA-seq CRAM raw-data files of 1063 primary colorectal cancer and 120 adjacent normal tissue samples. The expression profiles for these samples can be found at the ArrayExpress with accession number E-MTAB-12862.

  Dataset EGAD50000000169

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441

• Additional RNA-seq, ChIP-seq, and ATAC-seq files for PCGP SJERG

  This dataset contains RNA-seq, ATAC-seq, and ChIP-seq samples from the SJERG cohort. We applied ChIP-Seq for Dux4 on two B-cell ALL cell-lines(REH, Nalm6) along with INPUT. ATAC-Seq on two B-cell ALL cell-lines(REH, Nalm6) and xenograft of a B-cell ALL patient(ERG000016).

  Dataset EGAD00001002654

• RNA-seq data for NRF2 study

  RNA-seq data for clinical samples

  Dataset EGAD00001002243

• WES and RNA-seq of triple-negative breast cancers from the MyBrCa cohort

  The dataset contains a genomics characterization of 35 triple-negative Asian breast tumours from the Malaysian Breast Cancer cohort. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a NovaSeq 6000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a NovaSeq 6000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001009311

• Sputum RNA-Seq from Asthmatic Patients for Microbes and Genes

  RNA-seq files and other data associated with an investigation of the relationship between microbes, genes and immune cells present in the sputum of humans with asthma.

  Study phs002224

• Short-read (RNA-seq)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006596

• Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

  Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

  Study phs003749

• RNA-Seq of response to Tozinameran vaccination in individuals with KTx/dialysis or healthy controls.

  Low-input RNA-Seq (~200 cells per sample) of CD4+ T cells in patients with kidney transplants, dialysis, or healthy controls after the second dose of Tozinameran COVID-19 vaccine. RNA-Seq was performed using the Smart-Seq v4 ultra-low input protocol. The dataset includes 4 healthy control samples, 3 kidney transplant recipients, and 4 patients undergoing dialysis.

  Dataset EGAD00001007689

• RNA-seq in insulinomas

  RNA-seq datasets in human insulinoma samples

  Dataset EGAD50000000462

• Transcriptome of insulinomas

  Characterization of the transcriptome of insulinomas by RNA-seq.

  Study EGAS50000000320

• RNA-Seq data for Juvenile Pilocytic Astrocytomas

  RNA-Seq data for 9 JPA samples.

  Dataset EGAD00001009043

• A phase II trial of the aurora kinase A inhibitor alisertib for patients with castration resistant and neuroendocrine prostate cancer: efficacy and biomarker evaluation

  Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may develop de novo or as a mechanism of treatment resistance. N-myc is capable of driving NEPC progression. Alisertib inhibits the interaction between N-myc and its stabilizing factor Aurora-A, inhibiting N-myc signaling, and suppressing tumor growth. In this single arm, multi-institutional open label phase 2 clinical trial of alisertib, sixty men were treated with alisertib 50mg twice daily for 7 days every 21-days. Eligibility included metastatic prostate cancer and at least one: small cell neuroendocrine morphology; ≥50% neuroendocrine marker expression; new liver metastases without PSA progression; elevated serum neuroendocrine markers. The primary endpoint was six-month radiographic progression free survival. Pre-treatment biopsies were evaluated by whole exome and RNA-seq.

  Study phs001666

• Recurrent DNMT3B gene rearrangements are associated with unfavorable outcome in dicentric (9;20)-positive pediatric BCP-ALL

  The dicentric chromosome dic(9;20)(p11∼13;q11), occurs in 2% of pediatric acute lymphoblastic leukemia (ALL) cases. However, the prognostic significance of the dic(9;20) alterations and the mechanism in which these alterations drive leukemogenesis remains elusive. Our study describes the demographic, clinical, prognostic, and molecular characteristics of the dic(9;20)-positive ALL in a cohort of 57 pediatric BCP-ALL patients. Targeted RNA-seq and Array CGH analysis unraveled heterogeneous breakpoints on chromosomes 9 and 20 and frequent deletions of the IKZF1 gene. Together with the intrinsic susceptibility for deletions in CDKN2A, CDKN2B, and PAX5 genes in the dic(9;20)-positive ALL, these patients are eligible for treatment escalation in the AIEOP-BFM ALL 2017 clinical study. Survival analysis revealed poor 5-year event-free survival (pEFS) of 69% in dic(9;20)-positive ALL cases, compared to BCP-ALL patients enrolled in modern treatment studies. Strikingly, we identified six dic(9;20)-positive cases with rearrangements involving the DNMT3B gene, and poor 5-year pEFS of 25% (SE = 20%), compared to 79% (SE = 9%) for the remaining cohort (P = 0.011). Despite the loss of the methyltransferase domain of the DNMT3B gene in most cases with DNMT3B rearrangements, we did not observe major changes in the global methylation patterns. Differential gene expression analysis of DNMT3B-rearranged ALL unraveled a dysregulation of genes involved in hematopoiesis, lymphocyte maturation, and the PI3K/AKT signaling pathway. After confirmation in an independent cohort, DNMT3B-rearranged ALL cases should be considered high-risk for relapse and treated accordingly. We provide clinical data sets of Array CGH, targeted RNA-seq, total RNA-seq, whole genome bisulfite (WGBS) and whole genome DNA sequencing (WGS) obtained from bone marrow (BM) or peripheral blood (PB) mononuclear cells of 57 pediatric patients with dicentric chromosome dic(9;20) positive Acute lymphocytic leukemia (ALL), from which in 6 cases DNMT3B gene rearrangement was identified. This data is complemented by total RNA-seq and WGBS of samples from 4 additional ALL patients with a t(12;21) translocation and ETV6-RUNX1 gene fusion. DNA was isolated from BM or PB lymphocytes using Qiagen QIAamp DNA Blood Midi Kit to perform i) Array CGH of 58 dic(9;20) positive samples by hybridizing 500ng DNA using a Agilent 400K SurePrint G3 Custom CGH Human Genome Microarray (e-Array design 84704) ii) WGBS of 6 DNMT3B rearrangement positive samples and 4 ETV6-RUNX1 positive samples using Tecan TrueMethyl oxBS-Seq module for library preparation and Illumina NovaSeq 6000 platform to run 2x151 cycles iii) WGS of DNMT3B rearrangement positive samples using Illumina Lotus DNA Library Prep Kit followed by sequencing running 2x160 cycles on an Illumina NovaSeq 6000 platform. RNA was isolated from PB lymphocytes using the PerkinElmer Chemagic 360 instrument, followed by i) targeted RNA-seq of 56 dic(9;20) positive samples prepared using Illumina TruSight RNA Pan-Cancer Panel and sequenced on an Illumina MiSeq platform running 2x75 cycles ii) total RNA-seq of 6 DNMT3B rearrangement positive samples and 4 ETV6-RUNX1 positive samples utilizing TruSeq Stranded Total RNA Library Prep Gold kit and running 2x100 cycles on an Illumina NovaSeq 6000 platform.

  Study EGAS00001007383

• Low-input RNA-seq libraries from FFPE samples using TaKaRa SMARTer kit

  Using the TaKaRa SMARTer Stranded Total RNA-Seq Kit v2, RNA-seq libraries were generated from 5 ng of RNA extracted from FFPE tissue. A low-input workflow was applied with 5 PCR cycles for the first amplification and 16 for the second. Library quality was assessed by Bioanalyzer and Qubit, and libraries were sequenced (2×150 bp) on the Illumina NextSeq 550 platform.

  Dataset EGAD50000001552

• Complex-I stratification of Parkinson's disease in the prefrontal cortex - bulk RNA seq

  Dataset corresponding to the bulk RNA seq dataset from prefrontal cortex for a total of N=98 samples. Tissue samples correspond to patients with idiopathic Parkison's disease (PD) with varying levels of Complex-I activity (N=79) and neurologically healthy controls (N=19). RNA seq was carried out using ribosomal depletion. A subset of these samples was additionally sequenced using single nucleus RNA seq and is available in the same Study as an additional Dataset.

  Dataset EGAD50000000433

• bulk Exome-seq of the 5 HCC patients which also have the single cell T cell RNA-seq data

  bulk Exome-seq data of the 5 HCC patinets. Single cell RNA seq data of these patients was under the accession number EGAD00001003337

  Dataset EGAD00001004149

• bulk RNA-seq data

  a total number of 99 bulk RNA-seq lymphoma samples

  Dataset EGAD50000000631

• RNA-seq Revision

  RNA-seq Revision

  Dataset EGAD00001008951

• Immune Determinants of Resistance to PD-1 Blockade in Renal Cell Carcinoma

  We performed an integrated bulk and single-cell transcriptomic analysis of tumors from 102 advanced renal cell carcinoma patients enrolled in a phase II clinical trial of frontline nivolumab (NCT03117309) to investigate determinants of response to anti-PD1 monotherapy. The present study includes 112 archival or pre-treatment tumors of clear cell and non-clear cell histologies from 90 patients that underwent bulk RNA sequencing (RNA-seq). For 76 patients, 74 of whom had matched RNA-seq, whole exome sequencing (WES) was also performed on tumor samples as well as matched peripheral blood. Additionally, 19 fresh tumor samples from 17 patients, including pre and post-treatment samples and mixed histologies, were locally cryopreserved and centrally processed for single cell RNA (scRNA-seq) and TCR (scTCR-seq) sequencing. 7 patients had matched scRNA/scTCRseq, RNAseq, and WES.

  Study phs003618

• single cell RNA-seq data of circulating tumor cells from three small cell lung cancer patients

  This dataset contains raw 10x Genomics single-cell RNA sequencing data from a total of eight runs of circulating tumor cells from three small cell lung cancer patients. Each run represented by four FASTQ files (R1, R2, I1, I2) generated using the Illumina NextSeq 2000 platform. These files include read pairs as well as sample and cellular barcode indices. Circulating tumor cells were enriched from the blood of three SCLC patients using the CTC-iChip followed by magnetic depletion of RBCs. The enriched samples were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system.

  Dataset EGAD50000002035

• Analyses of RNAseq data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors

  The dataset includes RNA-seq expression R data, RNA-seq gene counts matrix, and RNA-seq gene FPKM matrix from 21 NEN tumors or metastases and matched PDTOs. The sequencing was done with either a Nextseq 2000 or a NovaSeq 6000 instrument.

  Dataset EGAD00001009994

• RNA-seq iNKT, T and C1R cells

  RNA-seq (Ribodepleted Directional -75 PE- Hiseq 4000) data of purified and expanded iNKt and T cells from normal donor, and RNA-seq (poly-A 100-PE Hiseq 2500) data from C1R cell line. Data set consist of 3 pairs of fastq files, one pair per sample

  Dataset EGAD00001004331

• Enhancer profiling identifies epigenetic markers of endocrine resistance and reveals therapeutic options for metastatic castration-resistant prostate cancer patients (LuCaP cell line data)

  Androgen Receptor (AR) signaling inhibitors, including enzalutamide, are treatment options for patients with metastatic castration-resistant prostate cancer (mCRPC), but resistance inevitably develops. Using metastatic samples from a prospective phase II clinical trial, we epigenetically profiled enhancer/promoter activities with H3K27ac chromatin immunoprecipitation followed by sequencing, before and after AR-targeted therapy. We identified a distinct subset of H3K27ac-differentially marked regions that associated with treatment responsiveness. These data were successfully validated in mCRPC patient-derived xenograft models (PDX). In silico analyses revealed HDAC3 as a critical factor that can drive resistance to hormonal interventions, which we validated in vitro. Critically, we identified the pan-HDAC inhibitor, vorinostat to be effective in decreasing tumor cell proliferation both in vitro and in vivo. Moreover, we uncovered evidence for HDAC3 working together with Glucocorticoid Receptor (GR) as a potential mechanism for this therapeutic effect. These findings demonstrate rationale for new therapeutic strategies including HDAC inhibitors to improve patient outcome in advanced stages of mCRPC. Project Goal: We identified H3K27ac regions associated with resistance in patient samples. Extensive analysis of these regions suggested that HDAC3 may play a role in resistance. To test this, we analyzed ChIP-seq and RNA-seq from cell lines generated from PDX LuCaP samples (recapitulating resistant and non-resistant) to validate findings in patient samples. ChIP-seq samples were used to verify the signals identified from specific factors, such as H3K27ac, AR, FOXA1, GR and HDAC3, their association with resistance and possible mechanisms of action. RNA-seq samples were analyzed to determine the effect of AR signaling in these samples in specific genes in the H3K27ac resistance-associated regions.

  Study EGAS50000000917

• Multi-omics analysis of cocaine use disorder in postmortem brain tissue of the ventral striatum [Proteomics data to study EGAS50000000623]

  We performed a multi-omics analysis of cocaine use disorder in postmortem human brain tissue of the ventral striatum in N=41 individuals (N=20 CUD cases, N=21 non-affected individuals). From the postmortem brain tissue samples, we generated miRNA-seq, RNA-seq, proteomics, and snRNA-seq data. The miRNA-seq, RNA-seq and snRNA-seq datasets can be found in the EGA under study ID EGAS50000000623. Proteomics data is deposited under study ID EGAS00001007945 (this study). The proteomic dataset was obtained using TMT-labeling. Measurement was performed on an Orbitrap Fusion Lumos device.

  Study EGAS00001007945

• RNA-seq of human astroblastomas

  RNA-seq for fusion gene discovery of human astroblastomas

  Dataset EGAD00001009664

• Glucose Binds and Activates NSUN2 to Promote Translation and Epidermal Differentiation

  This study was undertaken to determine the role of NSUN2 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. NSUN2 was found to promote epidermal differentiation and alter translation using the methods of RNA-seq, CLIP-seq and Ribo-seq.

  Study phs003767

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011192

• NSD2 E1099K Drives Relapse in Pediatric Acute Lymphoblastic Leukemia by Disrupting 3D Chromatin Organization

  NSD2 p.E1099K (EK) is a mutation shown to be enriched in patients that relapse with pediatric Acute Lymphoblastic Leukemia (ALL). This work aims to uncover 3D chromatin architecture-related mechanisms responsible for drug resistance or therapy failure in these patients. We investigated this by performing Hi-C, ATAC-Seq, and RNA-Seq on three B-ALL cell lines heterozygous for EK either expressing a NSD2 targeting small RNA (sRNA) or a non-targeting small hairpin RNAs (shRNA). We also performed RNA-Seq on three matched diagnosis/relapse B-ALL samples with the relapse enriched EK mutation.

  Study phs003195

• RNA-seq

  RNA sequencing files that were used in our study. The cohort was composed of 39 cases of RNA sequencing data. RNA-seq library was prepared with rRNA depletion method, and the sequence was performed using DNBSEQ sequencer.

  Dataset EGAD50000000971

• Transcriptome Sequencing PPGL (2)

  RNA-Seq data (n=81) library preparation was performed as previously reported by Calsina et al 2023 using QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015). The prepared libraries were subsequently sequenced on NovaSeq™ system (Illumina). To combine the new CNIO samples (n=81) with the CNIO+TCGA dataset generated in Calsina et al., 2023, RNA data were processed using ComBat-seq as described in that same article.

  Study EGAS50000000013

• Delineating pediatric brain tumor progression using single-nuclei sequencing

  Pediatric brain cancers are the most common solid tumors in children with varying survival rates depending on molecular features of cancer cells and associated microenvironment. Several studies have used single-cell RNA sequencing to define transcriptional programs active in cancer cells and highlighted supportive roles of non-cancerous cells embedded in these tumors. Although application of single-cell RNA sequencing technology has expanded our understanding of intratumoral heterogeneity and underlying transcriptional mechanisms in brain tumors at diagnosis, mechanisms of disease remains elusive. Therefore, the purpose of this proposal is to characterize cellular and transcriptional states of malignant and non-malignant compartments at primary diagnosis and at relapse. In this study, we performed single-nuclei sequencing of 42 patient samples taken at various disease stages (initial diagnosis, progressive disease, and relapsed disease) from 20 patients with low-grade glioma or Atypical Teratoid Rhabdoid Tumor (ATRT). Bulk whole genome and RNA-seq data for these samples are available from the Children’s Brain Tumor Network and the Gabriella Miller Kids First Data Resource Center. Findings from our study will help define the mechanistic shifts of tumor and non-cancerous cells over course of disease progression. Collectively with the single-cell Pediatric Cancer Atlas funded, this project lays the foundation of an important data set focused on lethal relapsed cancers that can continue to be expanded to identify cancer-intrinsic and extrinsic microenvironmental factors supporting recurrence of pediatric brain tumors.

  Study EGAS50000001288

• Postmortem Single Nuclei and Bulk RNA-seq data of the Motor Cortex and Spinal Cord for Healthy, C9ALS and sALS Patients

  This dataset contains both snRNA-seq and bulk RNA-seq data from 19 different patients, comprising of 9 healthy controls (4 Spinal Cord, 5 Motor Cortex) as well as 5 C9ALS patients and 5 sporadic ALS patients, each with paired data from the spinal cord and motor cortex. For the snRNA-seq data, fastq files containing the raw reads are provided, many of these samples were pooled for sequencing and subsequently require demultiplexing using SNPs using a tool such as freemuxlet. The paired bulk RNA-seq data (raw fastq files) can be used to acquire the ground truth per patient - a list of pooled samples can be found in map.txt. snRNA-seq data was produced using the 10X Genomics 3' v3 kit and bulk RNA-seq was produced using the Illumina TruSeq v2 kit.

  Dataset EGAD00001009686

• Transcriptomic profiling of lymphedema

  RNA-seq of skin from human subjects with and without lymphedema

  Study EGAS00001004516

• RNA-seq

  RNA-seq data

  Dataset EGAD00001008959

• CD4 T-Cell RNA-Seq

  CD4 T-Cell RNA-Seq

  Dataset EGAD00001002687

• LGG Epilepsy Cohort RNA-Seq

  LGG Epilepsy Cohort RNA-Seq

  Dataset EGAD00001001666

• Adeno-associated virus in the liver: natural history and consequences in tumor development

  Adeno-associated virus (AAV) is a defective mono-stranded DNA virus, endemic in human population (40-80%). AAV infection has long been considered as non-pathogenic1, however few years ago we reported for the first time recurrent clonal AAV2 insertion in the pathogenesis of human hepatocellular carcinoma (HCC) developed on normal liver. These clonal viral insertions target cancer driver genes, including CCNA2, CCNE1, TERT, TNFSF10 and MLL4, leading to their overexpression. The viral inserted sequences involved in almost all the cases the 3’ inverse tandem repeat (ITR) of AAV2, which is important for virus integration in host DNA and exhibits a promoter/enhancer activity. Here, we used RNA sequencing (RNA-seq) to investigate their functional impact on the tissue, such as fusion transcript generation events.

  Study EGAS00001003310