Search Results - EGA European Genome-Phenome Archive

RNA-seq analysis of CCO+/CCO- hepatocytes in normal human liver

RNAseq data from Passman et al 2023. Clonal CCO-deficient hepatocyte patches and nearby CCO-proficient hepatocytes were identified in morphologically normal human livers and sampled at varying distances along the PT-CV axis. Samples are characterised according to their location within the liver lobule, with "PT" denoting samples abutting the portal triad, "CV" denoting samples abutting the central hepatic vein, and "Mid" sampled acquired midway between these structures. Analysis was performed on an Illumina Nextseq using a high output kit and 100 single-end cycles.

Dataset EGAD00001010033

Application of short-RNA-seq in post-mortem human hippocampi from the Calgary Brain Bank (CBB) to assess transcriptome-wide deregulation in processing of SINE Alu RNAs in Alzheimer’s disease

Here, we investigate through short-RNA_seq in human hippocampi from the Calgary Brain Bank (CBB) whether Alu RNAs are processed in human brains, and whether their processing ratio is deregulated in brains of AD patients compared to healthy aging individuals.

Study EGAS00001004973

Sex Chromosome Aneuploidy Effects on Human Gene Expression

Sex chromosome aneuploidy (SCA) syndromes are defined by the presence of a sex chromosome complement other than the typical XX for females and XY for males. SCAs are collectively common and increase risks for diverse immune, metabolic, and neuropsychiatric illnesses. Understanding genome-wide transcriptomic changes in SCAs is critical for clarifying the biological underpinnings of their clinical phenotypes. Assessments of sex chromosome dosage (SCD) effects on gene expression in humans have often been confined to the use of a few SCA subtypes (e.g., XO or XXY) - precluding analysis of the same SCD change in different contexts. Our study used RNA-seq data from lymphoblastoid cell lines in 197 individuals representing diverse SCA karyotypes (49 XX, 24 XXX, 39 XY, 39 XXY, 23 XXYY, 23 XYY) to assess expression changes for 25,075 genes in multiple pairwise SCD group comparisons. The paper reporting our findings has been cited below.

Study phs003278

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has killed hundreds of thousands of people, including >23,000 in New York City (NYC) alone. The pandemic's sudden emergence highlights the clinical need to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we provide large-scale shotgun metatranscriptomics (total-RNA-seq) for host, viral, and microbial profiling. In version 1, we sequenced a total of 732 clinical specimens (nasopharyngeal (NP) swabs) gathered from 669 unique patients in New York City during the first two months of the outbreak. In version 2, we sequenced an additional 168 clinical specimens from autopsy tissues (lung, heart, kidney, liver, and lymph node) from 60 patients, yielding a broad molecular portrait of the emerging COVID-19 disease across 900 clinical specimens and 729 patients.

Study phs002258

Transcriptome of human trophoblast stem cells derived from normal and HDP placentas

Hypertensive disorders of pregnancy (HDP) is a disease driven by abnormal placenta formation, which is a leading cause of maternal and fetal death. For investigation of genetic and epigenetic regulation of human trophoblast differentiation, we have previously established human trophoblast stem cells (hTSCs) from first-trimester placentas. Those hTSCs were able to differentiate into extravillous trophoblasts (EVTs) and syncytiotrophoblasts (STs), and their transcriptome was similar to that of cytotrophoblasts in human placenta. However, since HDP happens in the second half of pregnancy, the conventional hTSC derivation method was not enough to investigate the nature of HDP trophoblasts. In this analysis, we improved the derivation method and successfully established the hTSCs from normal and HDP term placentas after delivery. We performed RNA-seq of normal and HDP hTSCs, and HDP hTSCs recapitulated abnormalities in gene expression reported in HDP placentas.

Study JGAS000660

Longitudinal single-cell transcriptomic study in patient-derived xenografts of pediatric T-ALL

In this study, we conducted single cell full length total RNA sequencing (VASA-seq) on 13 matched pediatric T-ALL PDX samples at initial diagnosis and relapse, along with 5 non-relapsing PDX samples collected at initial diagnosis. We identified a subpopulation of T-ALL cells with stem-like cell features that expands substantially at relapse indicating resistance to first-line therapy. Chemotherapy resistance was further validated through functional testing: Two samples were subjected to in-vitro drug testing, treated with Cytarabine for three days, followed by single-cell transcriptomic analysis using 10x Genomics. Additionally, in-vivo drug testing was conducted on one sample, involving re-engraftment into mice and treatment with a combination of Vincristine, Doxorubicin, and Dexamethasone. Single-cell transcriptomic analysis using 10x Genomics was performed after 0, 15 and 30 days of treatment.

Study EGAS50000000582

Transcriptomic profiles of tumor samples from patients with stage I-III TNBC treated with anthracycline-taxane chemotherapy plus fasting-mimicking diet plus/minus metformin in the context of the BREAKFAST trial (NCT04248998)

BREAKFAST is a randomized, non-comparative, phase II trial enrolling stage I-III (cT>1cm) TNBC pts treated with neoadjuvant doxorubicin-cyclophosphamide q3w for 4 cycles, followed by weekly paclitaxel for 12 cycles. Pts were randomized 1:1 to receive: CT + triweekly 5-day FMD cycles (arm A), or CT + FMD + daily metformin (1700 mg) (arm B). The primary study objective was to investigate if one or both experimental treatments were able to increase pCR rates when compared to anthracycline-taxane CT alone according to historical data. Secondary/exploratory endpoints included biomarker analyses based on tumor transcriptomics analyses. Specifically, we collected fresh-frozen tumor samples at baseline and 14-21 days after the first treament cycle and we analyzed the RNA-seq profiles to identify early predictors of treatment activity.

Study EGAS50000000690

Network-based systems pharmacology identifies heterogeneity in LCK and BCL2 signaling and differential vulnerability of T-cell acute lymphoblastic leukemia to targeted therapy

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and novel therapeutics are much needed. Profiling patient leukemia’ drug sensitivities ex vivo, we discovered striking inter-patient variability in T-ALL response to a panel of targeted agents. Applying network-based systems pharmacology analyses, by integrating ex vivo pharmacotyping, bulk and single-cell RNA-seq, genomics, phospho-proteomics, and genome-wide CRISPR screening data, to examine signal circuitry, we identified the pharmacogenomic basis of T-ALL drug response and revealed a therapeutic vulnerability that is directly related to the developmental stage of leukemia cells. In conclusion, our results indicate that heterogeneity in the differentiation of T-ALL drives activation of key signaling pathways in this leukemia, providing unique opportunities for targeted therapy.

Study EGAS00001004700

Single cell RNAseq of PBMC from RCC patients

Frozen PBMC samples containing at least 1 million cells were thawed for 1 minute at 37C and washed twice with RPMI complete media (10% FBS with glutamate and Pen/Strep). All of the samples had &gt;80% viable cells. Sample processing for single-cell RNA-seq was done using Chromium Single Cell 3’ Library and Gel bead kit v2 (PN-120237) following manufacturer’s user guide (CG00052, 10x Genomics, Pleasanton, CA). The total cell density was used to impute the volume of single cell suspension needed in the reverse transcription (RT) master mix, aiming to achieve ~ 6,000 cells per sample. cDNAs and libraries were prepared following manufacturer’s user guide (10x Genomics). cDNA amplification and indexed libraries were prepared using 12 and 14 cycles of PCR, respectively. Libraries were profiled, quantified, and sequenced as 5’ single-cell gene expression libraries.

Study EGAS00001004451

The endometrial transcription landscape of MRKH syndrome

The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute to the pathogenic unfolding, too, the etiology of the syndrome has remained largely enigmatic. A comprehensive understanding of gene activity in the context of the disease is crucial to identify etiological components and their potential interplay. So far, this understanding is lacking, primarily due to the scarcity of samples and suitable tissue. In order to close this gap, we profiled endometrial tissue of uterus rudiments in a large cohort of MRKH patients using RNA-seq and thereby provide a genome-wide view on the altered transcription landscape of the MRKH syndrome.

Study EGAS00001004601

single nuclei RNASeq of 5 regions of the human prenatal brain

Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

Study EGAS00001006537

WXS and RNA-seq raw sequence data for TG project

WXS sequence data from 112 samples, RNA-seq sequence data from 117 samples, all sequence data are raw sequence data in fastq format, sequenced by Illumina platform.

Dataset EGAD00001007989

Long-read whole genome sequencing of gastric cancer

Gastric cancer (GC) remains a significant health challenge globally, with a particularly high incidence in Asia, including Singapore. Understanding the genomic landscape of normal gastric and the different GC subtypes along with its precursor lesions such as intestinal metaplasia (IM) as well as GC metastatic sites is crucial for advancing diagnostics, prognostics, and therapeutics. Long-read sequencing technologies offer an opportunity to delve deeper into the genomic and epigenetic alterations underlying these conditions and to complement existing short-read omics data. By integrating these data with previously generated in-house multi-omics data (such as RNA sequencing and whole exome sequencing), we hope to better elucidate the molecular mechanism underlying GC initiation and progression.

Study EGAS50000001607

Super enhancers define regulatory subtypes and cell identity in neuroblastoma - RNA-seq

Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

Study EGAS00001004552

Type 1 Diabetes Genetics Consortium (T1DGC): Case-only RNA-Seq Study

Peripheral blood mononuclear cells (PBMC) from 82 T1D cases from the T1DGC study were fractionated by positive selection on magnetic beads into CD4+ T cells, CD8+ T cells and CD19+ B cells. RNA purification, library preparation and sequencing to an average of 50 million reads per sample were performed by the HudsonAlpha Genome Services Laboratory. The resulting dataset includes 82 subjects with data from at least one cell type; sequence data from all 3 cell types is available from 79 subjects. The individuals in this study can be linked to the phs000911 T1DGC ImmunoChip study via subject ids to obtain both genotypic and phenotypic information, including genotypes used for expression quantitative trait locus analysis.

Study phs001426

Resilience and Susceptibility Patterns in the Viral Immune Response Using RNA-Seq (ReSP VIRUS Study)

This is a cross sectional study to investigate the relationship between nasal mucosa gene expression and clinical outcomes in infants with critical Respiratory Syncytial Virus (RSV) infection. We collected nasal mucosa samples from infants admitted to the pediatric intensive care unit with polymerase chain reaction confirmed RSV bronchiolitis. Samples were obtained by mucosal scrape biopsy of the inferior turbinate using a sterile plastic curette and bulk RNA-sequencing of mRNA was performed. Clinical data was extracted from the electronic health record including: demographics, medical history, duration of symptoms, time from admission to sample collection, hospital and intensive care unit length of stay, and type and duration of respiratory support.

Study phs003053

Single-cell RNA-seq data of the tumor microenvironment of lymphocyte-rich Hodgkin lymphoma and other Hodgkin lymphoma subtypes

Lymphocyte-rich classic Hodgkin lymphoma (LR-CHL) is a rare subtype of Hodgkin lymphoma. Recent technical advances have allowed for the characterization of specific crosstalk mechanisms between malignant Hodgkin Reed-Sternberg (HRS) cells and different normal immune cells in the tumor microenvironment (TME) of CHL. However, the TME of LR-CHL has not yet been characterized at single cell resolution. Here, using single cell RNA sequencing, we examined the immune cell profile of 8 cell suspension samples of LR-CHL in comparison to 20 samples of the mixed cellularity (9 cases) and nodular sclerosis (11 cases) subtypes of CHL, as well as 5 reactive lymph node controls.

Study EGAS00001005541

Single cell transcriptomics to characterize the tumor microenvironment of prostate cancer fusion biopsies

The primary objective of this study was to characterize the tumor microenvironment in fusion-guided transperineal biopsy samples from patients undergoing PC diagnosis. For each patient, one biopsy was taken from a suspected tumor region and another from a non-suspicious area, which were later classified as high- or low-tumorigenicity based on anatomopathological analysis. Using scRNA-seq data, we performed cancer-oriented cell annotation, differential expression analysis, and functional pathway enrichment studies across key cellular subpopulations. Additionally, differential abundance analysis was conducted to identify cell groups representative of different tumorigenicity levels. Finally, classification models were developed using gene expression data to differentiate high- vs. low-tumorigenicity samples, with the long-term goal of establishing a diagnostic classifier for PC stratification.

Study EGAS50000000888

RNA-seq profiling of NKX6.1 reporter iPSC lines for isolation and analysis of functionally relevant neuronal and pancreas populations

We generated human induced pluripotent stem cell (iPSC) lines with a GFP reporter inserted in the endogenous NKX6.1 locus. Characterisation of the reporter lines demonstrated faithful GFP labelling of NKX6.1 expression during pancreas and motor neuron differentiation. We performed three independent in vitro differentiations towards the pancreatic endocrine lineage. We FACS-purified GFP positive and negative cells from stage 7 cultures, and generated Smart-Seq2 RNA-sequencing libraries for the pre-sorted cells, as well as the two GFP-sorted cell populations. Gene expression profiling by RNA-sequencing reveals that the NKX6.1-positive population closely resembles mature human beta cells and the functional evaluation of purified populations shows that the glucose-responsive beta-like cells are enriched within the NKX6.1-positive population. These reporter lines provide a valuable resource to the scientific community for the derivation of functional relevant pancreas and neuronal cell subtypes.

Study EGAS00001002802

KRT17High/CXCL8+ Tumor Cells Display Both Classical and Basal Features and Regulate Myeloid Infiltration in the Pancreatic Cancer Microenvironment

Recent studies have uncovered the co-existence of basal and classical subtypes within pancreatic ductal adenocarcinoma (PDAC). We sought to characterize these intermediary cells using single-cell RNA sequencing of PDAC. We performed subtyping on 18 single-cell RNA sequencing human PDAC samples to identify multiple intermediary subtypes. We compared single-cell profiling of patient-matched blood and tumor samples to measure changes in the local and systemic immune microenvironments in CXCL8-high tumors vs. CXCL8-low tumors. Finally, we leveraged longitudinally patient-matched blood over the course of chemotherapy. In our studies we identified a cluster of KRT17high intermediary cancer cells that uniquely express high levels of CXCL8 and other cytokines which in turn influence the myeloid compartment both locally and systemically. We utilized sequencing data from dbGaP study accession phs002070. In addition to that, we included sequencing from new specimens which are deposited to this submission, consisting of one additional tumor specimen and 5 PBMC samples, sequenced after chemotherapy (longitudinally matched to PBMC samples in phs002071.v1.p1). FASTQ files of these sequencing runs are available through this dbGaP submission.

Study phs003436

Molecular investigation of BCC HHI-ICI combination therapy

We collected skin biopsies and PBMCs of patients with advanced BCC who underwent HHI-ICI combination therapy. We analyzed the skin biopsies with STx and the PBMCs with scRNA-seq to characterize the response of the immune cells, tumor cells and the tumor microenvironment to this therapy. We were interested in immune activation upon HHI and how that synergises with subsequent ICI.

Study EGAS50000001481

De novo detection of somatic variants

The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

Dataset EGAD50000001292

ScRNA-seq of PBMC and whole blood samples reveals 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.

Study EGAS00001004571

RNA-sequencing of ex vivo exhausted human antigen-specific T cells

Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level. Four human healhy donor CD8+ T cells were isolated, transduced with an NY-ESO-1 TCR lentivirus construct, stimulated in four different conditions (Trested, Ttumor, Tex, Teff) with T2 tumor cells and specific peptides over 12 days. Cells were then sorted for TCR Vbeta 13.1+ (NY-ESO-1 TCR) CD8+ CD3+ CD56- CD4- DAPI- cells. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode (2x51bp) on 2 lanes of an Illumina NovaSeq 6000 flow-cell. FASTQ sequence files were generated with the Illumina RTA version 3.4.4 and Base-calling Version bcl2fastq-2.20.0.422.

Dataset EGAD00001009754

EPITREAT pilot cohort

Benchmark data set containing five tumor/normal pairs of non-small cell lung cancer (NSCLC) patients. Tissue pairs were screened with bisulfite (BS) sequencing, MeDIP methylation enrichment sequencing and RNA sequencing in order to identify differentially methylated and expressed spots in the genomes.

Dataset EGAD00001003116

Single cell RNA sequencing of colorectal cancer patients (KUL5)

All libraries were sequenced on Illumina NextSeq or NovaSeq6000 until sufficient saturation was reached.

Dataset EGAD00001008585

Sensitive and robust liquid biopsy-based detection of PIK3CA mutations

Over the last years, the treatment of hormone receptor-positive metastatic breast cancer patients has dramatically changed. Combination strategies attempting to overcome resistance to endocrine therapy such as targeting the PI3 kinase pathway are gaining importance. The phase III SOLAR-1 trial demonstrated the benefit of the addition of alpelisib to fulvestrant, thereby providing further clinical evidence of the increasing importance of PIK3CA testing. Here, we performed a comparison of liquid biopsy and tissue-based detection of PIK3CA mutations in HR-positive metastatic breast cancer patients. Plasma samples and the latest available tumor tissue from 69 patients with metastatic hormone-receptor positive breast cancer were analyzed for PIK3CA hotspot mutations. A high-resolution NGS assay (SiMSen-Seq) was used for plasma samples covering 11 recurrent PIK3CA mutations, used for stratification in SOLAR-1. Additionally, mFAST-SeqS was used to estimate the tumor fractions in the plasma samples. For tumor tissue samples, targeted Ion Torrent NGS was employed. Matched tissue and plasma samples were available from 63 patients. PIK3CA mutations were detected in 46.1% of the tissue samples and in 50.7% of the plasma samples. The variant allele frequency (VAF) ranged from 4.36% to 72.93% with a median of 28.60% in tissue samples, and from 0.28% to 49.85% with a median of 1.17% in plasma samples. The most frequent variants in tissue and plasma were H1047R, E545K, and E542K. We detected at least one of 11 PIK3CA mutations from the SOLAR-1 trial in 51/63 patients, both in tissue and plasma. In 7 patients, such mutations were found only in plasma. In 5 patients, PIK3CA mutations found in tissue were not detectable in ctDNA, 2 of which had a low tumor fraction.Together, in 33/67 plasma samples without detectable PIK3CA mutations, 18 samples had elevated tumor fraction, implicating true negative results. In the remaining 15 patients with low tumor fraction, additional tissue analysis was needed. SiMSen-Seq-based detection of PIK3CA mutations in plasma shows advantageous concordance with the tissue analyses. A combination with an untargeted, mutation-independent approach for detecting ctDNA fractions may confirm a negative PIK3CA result and thereby enhance the performance of the SiMSen-Seq test. This combinatory approach for selecting suitable patients for alpelisib treatment should be validated in larger patient cohorts.

Study EGAS00001004940

AC-ICAM: An Atlas and Compass of Immune-CAncer-Microbiome Interactions in Colon Cancer

Fresh frozen tumor samples and matched normal colon specimens from chemotherapy naïve, consecutive patients with a histological diagnosis of colon adenocarcinoma at Leiden University Medical Center (LUMC) were subjected to multi-omics profiling at Sidra Integrated Genomics Services, part of Sidra Medicine, Doha, Qatar. This resulted in a high-quality dataset of samples collected between 2001 and 2015. Multi-step QC was performed, including assessment of the quality of the nucleic acid extraction, sequencing, and genetic concordance between DNA/RNA sequences from the same patient. After QC, this resulted in RNA sequencing on 348 tumor samples, whole exome sequencing (WES) on 281 tumor-normal sample pairs (n=562 samples), TCR sequencing of the TCR β locus (TRB) for 114 tumor and 10 matched normal samples, and 16S rDNA sequencing on 246 tumor-normal sample pairs (n=492 samples) and 42 tumor only samples, and 167 WGS non human-aligned reads of the tumor samples. Extensive clinicopathological and survival data of the cohort are available. The median follow-up time for this cohort is 4.6 years, and the distribution of gender and pathological stage are within expected ranges for this patient population with a mean age of 68. We refer to this resource as the Sidra-LUMC (SILU) colon adenocarcinoma (COAD) Atlas and Compass of Immune-Colon cancer-Microbiome interactions (AC-ICAM)."Reprinted from Nature Medicine,Roelands, J., Kuppen, P.J.K., Ahmed, E.I. et al. An integrated tumor, immune and microbiome atlas of colon cancer. Nat Med (2023). https://doi.org/10.1038/s41591-023-02324-5, with permission from Nature."

Study phs002978

Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

The extensive primary and secondary drug resistance in many cancer types requires rational approaches to design personalized and selective combinatorial therapies that do not only show synergistic effect in overall cancer cell killing but also result in minimal toxic side effects on non-malignant cells. To address the combinatorial explosion in the number of relevant combinations, we implemented a machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA-sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory AML patient cases, each with a different genetic background, our integrated approach accurately predicted patient-specific combinations that were shown to result not only in synergistic cancer cell co-inhibition but were also capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our data-driven approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of non-malignant cells, and highlight the relevance of considering cell heterogeneity for personalized cancer therapy.

Study EGAS00001004614

INTEGRATIVE MOLECULAR ANALYSIS OF SKIN TUMORS FROM CYLD CUTANEOUS SYNDROME PATIENTS

CYLD cutaneous syndrome (CCS) is a rare autosomal dominant disorder characterized by germline CYLD mutations and by multiple benign skin tumors dependent on NF-kB pathway. We assembled a large cohort of CCS rare skin tumors that was profiled with whole exome or genome sequencing, RNA sequencing and methylation arrays to better understand genetic mechanisms of CCS tumorogenesis.

Study EGAS50000000247

PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

HSPCs were sorted as CD34+ cells from bone marrow of patients with Hodgkin Lymphoma (HL). Control samples were isolated before initiating treatment.These were compared to samples from two additional HL patients who had relapsed and were being treated with nivolumab. Nivolumab was administered at a dose of 240 mg every two weeks, with BM samples collected the day before the scheduled dose. The patients receiving nivolumab were in remission at the time of BM collection. RNA was extracted using Arcturus™ PicoPure™ RNA Isolation Kit (Thermo Fisher Scientific, #12204-01) ` instructions. Paired-end sequencing was reads were generated for each sample in the Illumina Novaseq 6000 system.

Dataset EGAD00001015403

Integrated Single-Cell Genetic and Transcriptional Analysis Suggests Novel Drivers of Chronic Lymphocytic Leukemia

Intratumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells leading to increased understanding of driving events in malignancy. Reprinted from Genome Research, with permission from Publisher.

Study phs001372

Systems Analysis of the PfSPZ Vaccine in Kenyan Infants

The PfSPZ vaccine is a candidate vaccine targeting the Plasmodium falciparum parasite, which is the cause of the most lethal type of human malaria. This study used de-identified blood samples collected from 316 infants aged 5 to 12 months (inclusive) enrolled in a Phase 2, randomized, placebo-controlled trial (NCT02687373) of the PfSPZ malaria vaccine, conducted in a region of western Kenya where malaria transmission is high and perennial. The study began in July, 2016, after peak malaria transmission, and was completed in August, 2018. In this study, three doses of the PfSPZ Vaccine (4.5x105 PfSPZ, 9.0x105 PfSPZ, and 1.8x106 PfSPZ) were tested against a normal saline placebo comparator. In all four groups, doses were administered in 3 doses at 0, 8, and 16 weeks by direct venous inoculation. Vaccine efficacy was determined at 3, 6, and 12 months of follow-up after the third immunization. RNA was extracted from whole blood collected in PAXgene tubes before PfSPZ immunization, and two weeks after the third (final) dose, from 262 children for which sufficient material was available at both time points (82% of 316 enrolled children; 525 samples). RNA was depleted of globin and ribosome transcripts before library generation and sequencing on the Illumina NovaSeq platform. RNA-seq expression data was analyzed to determine blood transcriptional signatures, before and after PfSPZ vaccine immunization, that predicts sterile protection from naturally occurring P. falciparum infection or delayed parasitemia at 3 months post-immunization. Gene expression data will also be correlated to P. falciparum-specific IgG antibody and cellular responses to identify possible molecular correlates of vaccine-induced immunogenicity

Study phs002196

Biallelic variants in the non-protein coding minor spliceosome components RNU6ATAC and RNU6ATAC cause syndromic monogenic autoimmune diabetes

Non-protein coding genes are emerging as critical contributors to the aetiology of rare diseases, providing key insights into human biology and uncovering novel disease mechanisms. We identified 7 individuals from 4 families with early-onset diabetes (diagnosed <5 years) and immune dysregulatory features caused by biallelic variants in RNU6ATAC. RNU6ATAC encodes a small nuclear RNA (snRNA) acting as a catalytic component of the minor spliceosome, a protein-RNA complex mediating splicing of ~700 genes containing U12/minor-type introns. Variant screening of the other 64 minor spliceosome genes in 276 infants with diabetes identified 12 unrelated individuals with biallelic disease-causing variants in RNU4ATAC. Biallelic pathogenic RNU4ATAC variants are known to cause a variable spectrum of clinical features, which until now did not include diabetes. Clinically, 12/19 RNU6ATAC/RNU4ATAC patients had additional immune dysregulatory features, and 50% of patients tested were islet-autoantibody positive, strongly supporting an autoimmune aetiology for their diabetes. RNA-seq in 3 individuals with biallelic RNU6ATAC variants showed a pattern of intron retention in U12 intron-containing genes similar to that seen in RNU4ATAC-individuals (n=3), supporting a shared disease mechanism. Analysis of patients’ transcriptomic, methylation and immune data revealed impaired B cell development and maturation. We conclude that biallelic RNU6ATAC variants cause a novel syndrome of early-onset autoimmune diabetes and immune dysregulation. We further show that infancy-onset diabetes is a previously unrecognised feature of RNU4ATACopathy. Our work highlights the important role of two snRNAs critical to minor spliceosome function in immune system regulation, providing novel insights into the pathogenesis of autoimmune diabetes.

Study EGAS50000001565

Long Read sequencing data from 4 tumor/germline samples with non muscle invasive bladder cancer

A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). Additionally, tumor/germline samples from 4 patients were sequenced using Oxford Nanopore technology. This dataset contains 8 BAM files corresponding to the Long read sequencing data.

Dataset EGAD50000000731

WES data from 438 tumor/germline samples with non muscle invasive bladder cancer

A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 876 BAM files corresponding to the full WES dataset. Tumor and matched germline DNA were sequenced to a mean coverage of 132x (35x-338x) and 128x (31x-302x), respectively.

Dataset EGAD50000000730

Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

Dataset EGAD50000000559

Long-term organoid culture of a small intestinal neuroendocrine tumor rna-seq

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and highly heterogeneous neoplasms whose incidence has markedly increased over the last decades. A grading system based on the tumor cells' proliferation index predicts high-risk for G3 NETs. However, low-to-intermediate grade (G1/G2) NETs have an unpredictable clinical course that varies from indolent to highly malignant. Cultures of human cancer cells enable to perform functional perturbation analyses that are instrumental to enhance our understanding of cancer biology. To date, no tractable and reliable long-term culture of G1/G2 NET has been reported to permit disease modeling and pharmacological screens. Here, we report of the first long-term culture of a G2 metastatic small intestinal NET that preserves the main genetic drivers of the tumor and retains expression patterns of the endocrine cell lineage. Replicating the tissue, this long-term culture showed a low proliferation index, and yet it could be propagated continuously without dramatic changes in the karyotype. The model was readily available for pharmacological screens using targeted agents and as expected, showed low tumorigenic capacity in vivo. Overall, this is the first long-term culture of NETs to faithfully recapitulate many aspects of the original neuroendocrine tumor.

Study EGAS00001007108

WXS and RNA-seq for 22 patients treated with radiation + immunotherapy

Over 500 active clinical trials are investigating combination radiation (RT) and immune checkpoint blockade (ICB) as a cancer treatment; however, the majority of trials have found no positive interaction. We performed a comprehensive molecular analysis of a randomized phase I clinical trial of patients with non-small cell lung cancer (NSCLC) treated with concurrent or sequential ablative RT and ICB. Concurrent treatment was superior to sequential treatment in augmenting local and distant tumor responses and improving overall survival in a subset of patients with highly aneuploid tumors, but not in those with less aneuploid tumors. Our analysis suggested that concurrent treatment eliminated immunologically cold aneuploid tumors better than sequential treatment and improved patient outcomes. In addition, we report that RT alone decreased intratumoral cytotoxic effector T cell and adaptive immune gene expression signatures, in contrast to upregulation of key immune pathways after concurrent administration of RT and ICB. Our findings distinguish the differential genomic and transcriptomic effects of RT versus RT and ICB and challenge the prevailing paradigm that local ablative RT beneficially stimulates the immune response. We propose the use of tumor aneuploidy as a novel biomarker and therapeutic target in personalizing treatment approaches for patients with NSCLC treated with RT and ICB.

Study EGAS00001006212

Genomic Characterization CS-MATCH-0007 Arm B

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH clinical trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with HER2- activating mutations are treated with Afatinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002028

Genomic Characterization CS-MATCH-0007 Arm Z1I

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRCA1, BRCA2 mutations are treated with AZD1775. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002058

PDAC Prognosis Biomarkers in Genomic and Transcriptomic Molecular Data

Our study was designed to identify biomarkers related to the prognosis of Pancreatic Ductal AdenoCarcinoma (PDAC) patients using genomic variants and gene expression in coding regions of the human genome (exome). PDAC is the 7th cause of cancer deaths and is among types of cancer having the poorest prognosis. To improve treatment outcomes of PDAC, biomarkers related to PDAC prognosis are needed. The goals of our study are to find genomic and transcriptomic biomarkers, which can classify prognosis subtype of PDAC patients, and eventually to predict subtypes or prognosis for each patient. In this study, we generated Whole Exome Sequencing (WES) and exome capture RNA sequencing data of 450 tumor and matched normal samples from 150 PDAC patients. Our data may be useful for understanding genomic and transcriptomic features, prognosis prediction, and precision medicine for PDAC.

Study phs002347

Genomic Characterization CS-MATCH-0007 Arm Z1A

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1A is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NRAS mutations are treated with Binimetinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs001973

Genomic Characterization CS-MATCH-0007 Arm W

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm W is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with FGFR fusions, mutations, amplifications are treated with AZD4547. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including tumor tissue and whole blood.

Study phs001948

Genomic Characterization CS-MATCH-0007 Arm S2

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S2 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with GNAQ or GNA11 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002178

Genomic Characterization CS-MATCH-0007 Arm R

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm R is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRAF fusions, non-V600K or non-V600E mutations, are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002029

Genomic Characterization CS-MATCH-0007 Arm S1

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NF1 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002153

Genomic Characterization CS-MATCH-0007 Arm I

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PIK3CA mutations (without KRAS Mutation or PTEN Loss) are treated with Taselisib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002181

Genomic Characterization CS-MATCH-0007 Arm U

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm U is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NF2 loss are treated with Defactinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002179

Genomic Characterization CS-MATCH-0007 Arm C1

The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm C1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with MET amplification are treated with Crizotinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

Study phs002177

12304 results for "cancer rna-seq"

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