11976 results for "cancer rna-seq"

in 25.15 milliseconds.

• A Comprehensive Platform for Analyzing Longitudinal Multi-Omics Data

  PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for analyzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type or user defined groups. It allows to infer stable and variable features in a given donor and each cell type or a user defined group. The outlier analysis can be performed to identify technical/biological perturbed samples in a donor or a participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type. The data that is available in the dbGaP is the demo longitudinal samples used in the study, which includes hashed raw fastq files for single-cell RNA-sequencing (scRNA-seq) and non-hashed fastq files for single-cell ATAC-sequencing (scATAC) experiment.

  Study phs003203

• Single-cell Profiling of an In Vitro Model of Human Interneuron Development Reveals Temporal Dynamics of Cell Type Production and Maturation

  GABAergic interneurons are essential for neural circuit function and their loss or dysfunction is implicated in human neuropsychiatric disease. In vitro methods for interneuron generation hold promise for studying human cellular and functional properties and ultimately therapeutic cell replacement. We used a protocol for generating cortical interneurons from hESCs and analyzed the properties and maturation timecourse of cell types using single-cell RNAseq (data available at GEO under: GSE93802 on March 10 2017). Transcriptomic profiles of the hESC-derived interneurons were compared to several different populations of cells from mid-gestation human neocortex that showed differing levels of PAX6 and SOX2 expression. For this study, 104 samples of 100 human neocortical cells each, have been sorted based on SOX2 and PAX6 expression, mRNA recovered from the fixed cells by FRISCR, and transcriptomic profiles generated by SmartSeq2. The RNA-seq data from the 104 100-cell samples is included in this dbGaP study.

  Study phs001276

• Functional Dynamics of the Elderly Gut Microbiome During Probiotic Consumption

  A mechanistic understanding of the health benefits conferred by consumption of probiotic bacteria has been limited by our knowledge of the resident gut microbiota and its interaction with the host. We used fecal samples from a study of twelve healthy individuals aged 65-80 to characterize the structure and functional dynamics of the gut microbiota associated with consumption of the single-organism probiotic, Lactobacillus rhamnosus GG ATCC 53103 (LGG). Samples were collected prior to probiotic consumption (day 0), on day 28 immediately after consuming 10^10 CFU of LGG twice daily for 28 days and day 56, one month after stopping LGG consumption. Our integrative approach incorporated bacterial 16S rRNA gene sequencing, whole-community expression profiling using RNA-seq, and metagenomic sequencing. We highlight the value of combinatorial 'omics methods and concomitant high-resolution informatics to probe the role that probiotics may play on the structure and function of the resident microbiota.

  Study phs000896

• Multi-Ethnic Study of Atherosclerosis (BioLINCC)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics).

  Study phs003288

• Integrative Somatic and Germline Computational Biology to Redefine Clinical Actionability in Solid Tumors

  Neuroendocrine tumors (NETs) are rare cancers that arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic NETs (GEP-NETs) growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we performed single-cell RNA-sequencing (scRNA-seq) of fresh resections of GEP-NETs, including four pancreatic NETs, three small intestinal NETs, and one perigastric NET. We used single-cell sequencing to investigate the tumor and immune cellular landscapes of GEP-NET patients. Malignant GEP-NET gene and regulon expression was compared with normal, gastrointestinal endocrine cell differentiation and fate determination stages. We further characterized immune-immune and immune-tumor interaction networks within GEP-NETs, identifying novel therapeutic opportunities in the myeloid compartment of the microenvironment. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

  Study phs003141

• Genome sequencing identifies splice-disrupting variants in childhood heart disease

  We used genome sequencing (GS) to identify cardiac specific splice disrupting variants that were subsequently validated in a subset of participants. In turn, we developed a heart-specific model for canonical and non-canonical splice variants, which was applied to patients with congenital heart disease (CHD). These included patients with two of the most common forms of cyanotic CHD i.e. tetralogy of Fallot (TOF) and dextro-transposition of the great arteries (TGA). In addition to identifying canonical splice-disrupting variants in known CHD-related genes in 1% cases, this approach identified putatively damaging non-canonical splice-disrupting variants in 11% of isolated CHD, with deeply intronic variants representing 53% of non-canonical splice-disrupting variants in CHD genes. GS was critical for the identification of variants that would not be captured by routine clinical genetic tests including exome sequencing, while cardiac RNA-Seq allowed for high specificity in the interpretation of splice-disrupting effects in the heart.

  Study EGAS50000000586

• Spatial atlas of human atherosclerosis highlights role of the microvasculature in disease

  Atherosclerosis is a pervasive contributor to ischemic heart disease and stroke. Despite the advance of lipid lowering-therapies and antihypertensive agents, the residual risk of an atherosclerotic event remains high and developing therapeutic strategies has proven challenging. This is due to the complexity of atherosclerosis with a spatial interplay of multiple cell types within the vascular wall. Here we generate an integrative high-resolution map of human atherosclerotic plaques combining single-cell RNA-seq from multiple studies and spatial transcriptomics data from 12 human specimens, with different stages of atherosclerosis. We show cell-type and atherosclerosis-specific expression changes and spatially constrained alterations in cell-cell communication. We highlight the possible recruitment of lymphocytes via ACKR1 endothelial cells of the vasa vasorum, the migration of vascular smooth muscle cells towards the lumen by transforming into fibromyocytes, and cell-cell communication in the plaque region, indicating an intricate cellular interplay within the adventitia and the subendothelial space in human atherosclerosis.

  Study EGAS50000000660

• Single Cell Transcriptional Analysis of Human Adenoids Identifies Molecular Features of Airway Microfold Cells

  We aimed to characterize the cellular composition and molecular features of the human adenoid, a mucosa-associated lymphoid tissue located in the upper airway, with a focus on epithelial populations involved in immune surveillance. To this end, we performed single-nucleus RNA sequencing (snRNA-seq) on adenoid tissue obtained from 6 human donors (age 2 – 14; 3 males and 3 females) undergoing routine adenoidectomy. The donor cohort includes clinically annotated samples with no known immunodeficiency or chronic airway disease.Our analysis uncovered distinct epithelial populations, including transcriptionally defined immature and mature microfold (M) cells, and a previously unrecognized interferon-stimulated epithelial population enriched for antiviral response genes, which we term WISP cells (Waldeyer's ring Interferon-Stimulated Population). We validated key transcriptomic findings through multiplex immunofluorescence microscopy in independent donor tissues, confirming the spatial localization of WISP and M cells and their predicted interactions with specific immune subsets.

  Study phs004103

• Transcriptome alterations underlying metabolic dysfunction and liver disease in myotonic dystrophy type 1

  Myotonic dystrophy type 1 (DM1) is a multisystem disorder affecting various organs, including the skeletal muscles, eyes, heart, central nervous system, and endocrine system. Liver dysfunction and lipid metabolism abnormalities are frequently observed in DM1 but are not fully understood. To explore the molecular basis of these abnormalities, transcriptome analysis was performed on postmortem liver samples from DM1 patients DM1 patients (n = 11) and disease control patients (n = 9) using bulkRNA sequencing (RNA-seq) on the MGI DNBSEQ-G400RS. Differential gene expression and alternative splicing analyses revealed significant transcriptomic changes associated with lipid metabolism, liver fibrosis, and glucose homeostasis. Interestingly, transcriptome changes in DM1 livers also revealed partial resolution of sexual dimorphism in gene expression, along with unique sex-specific pathway alterations. A correlation between serum GGT levels and splicing abnormalities in DM1 patients was identified, suggesting a link between transcriptomic changes and clinical outcomes. This dataset provides valuable insights into the molecular mechanisms underlying DM1-related liver dysfunction and metabolic abnormalities.

  Study JGAS000814

• Searching for variants associated with endometriosis

  We explored regulatory mechanism of a SNP on chromosome 9p21 associated with endometriosis by leveraging “allele-specific” functional genomic approaches. By re-sequencing 1.29 Mb of 9p21 region and scrutinizing DNase-seq data from the ENCODE project, we prioritized rs17761446 as a candidate functional variant that was in perfect linkage disequilibrium with the original GWAS SNP (rs10965235) and located on DNase I hypersensitive site. Chromosome conformation capture followed by high-throughput sequencing revealed that the protective G allele of rs17761446 exerted stronger chromatin interaction with ANRIL promoter. We demonstrated that the protective allele exhibited preferential binding affinities to TCF7L2 and EP300 by bioinformatics and chromatin immunoprecipitation (ChIP) analyses. ChIP assays for histone H3 lysine 27 acetylation and RNA polymerase II reinforced the enhancer activity of the SNP site. The allele specific expression analysis for eutopic endometrial tissues and endometrial carcinoma cell lines showed that rs17761446 was a cis-regulatory variant where G allele was associated with increased ANRIL expression.

  Study EGAS00001001741

• RNA_seq_of_Toxoplasma_gondii_response_in_human_macrophages

  Toxoplasmosis is a zoonotic disease caused by a ubiquitous protozoan parasite called Toxoplasma gondii, which caninfect all mammal and bird species throughout the world. seroprevalence varies widely between countries. Studieshave estimated that between 7-34% of people in the UK have been infected with T. gondii. The vast majority of thesepeople will not have noticed any symptoms, however about 10% of people develop a mild to moderate self limitingflu-like illness. Following the acute active stage of the infection the parasite persists in the body in the form of cysts,particularly in heart and skeletal muscle and nervous system tissues, for many years, and usually for life. Inimmunocompetent persons these cysts do not pose a health risk. We will use RNA-seq to quantify the transcriptionalresponse of macrophages to T gondii infection.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001708

• Single_Cell_RNAseq_at_various_stages_of_HiPSCs_differentiating_toward_definitive_endoderm_and_endoderm_derived_lineages

  When comparing the differentiation capacities of pluripotent stem cell lines that have different genetic backgrounds, batch to batch experimental variablility poses a significant challenge, especially when trying to identify smaller effects. One way to address this issue is to differentiate several different lines in the same culture dish, thereby elimating experimental variation. In addition, it allows researchers to analyze many more lines with less experiments. Parallel single cell RNA-Seq exploits that individual cells are tagged and hence each cell can be reliably assigned to the donor of origin based on the genetic variants it contains. In addition, analyzing the genetic signature of single cells within a differentiating population can reveal differentation stages that are not easily detected in bulk RNAseq data. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002278

• Myoepithelial progenitors as founder cells of hyperplastic human breast lesions upon PIK3CA transformation

  The myoepithelial (MEP) lineage of human breast comprises bipotent and multipotent progenitors in ducts and terminal duct lobular units (TDLUs). We here assess whether this heterogeneity impacts on oncogenic PIK3CA transformation. Single cell RNA sequencing (scRNA-seq) and multicolor imaging reveal that terminal ducts represent the most enriched source of cells with ductal MEP markers including a-smooth muscle actin (a-SMA), keratin K14, K17 and CD200. Furthermore, we find neighboring CD200high and CD200low progenitors within terminal ducts. When sorted and kept in ground state conditions, their CD200low and CD200high phenotypes are preserved. Upon differentiation, progenitors remain multipotent and bipotent, respectively. Immortalized progenitors are transduced with shp53 and mutant PIK3CA. Upon transplantation, CD200low MEP progenitors distinguish from CD200high by the formation of multilayered structures with a hyperplastic inner layer of luminal epithelial cells. We suggest a model with spatially distributed MEP progenitors as founder cells of biphasic breast lesions with implications for early detection and prevention strategies.

  Study EGAS00001005933

• Oncogenic cooperation in a human de novo T-ALL model

  We previously modelled T-cell acute lymphoblastic leukemia (T-ALL) by over-expressing four oncogenes (activated NOTCH1, LMO2, TAL1, and BMI1) in healthy human umbilical cord blood cells through lentiviral transduction (Kusakabe et al, Nat Commun 10, 2913 (2019). https://doi.org/10.1038/s41467-019-10510-8). We have now tested individual effects of the four oncogenes by transducing human cells with all possible combinations of one, two, three, and four oncogenes. We also tested the effects of additional known T-ALL oncogenes including HOXA9, LYL1, MEF2C, NXK2.1, TLX1, and TLX3. In addition to culture in vitro on OP9-DL1 feeders, we also injected transduced cells into immunodeficient NSG mice. We observed differing abilities of the various oncogene combinations to support growth in vitro and frank leukemia in vivo. This study includes RNA-seq data from samples of transduced cells cultured in vitro as well as cells harvested from clinically moribund mice after development of leukemia in vivo.

  Study EGAS00001006055

• A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

  Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. The determination of TM-interconnectivity in individual tumors has been challenging and the impact on patient survival unresolved. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells has been established using a dye uptake methodology, confirmed with recording of cellular calcium epochs and validated with clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, network connectivity correlated with the mesenchymal subtype and dismal patient survival. CHI3L1 has been identified and validated as a robust molecular marker of connectivity with functional relevance. The connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients’ prognosis, and serves as a robust prognostic biomarker.

  Study EGAS00001007611

• 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

• 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

• Dataset for cancer_of_unknown_primary-RNA

  Rare cancer sequencing data of 58 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008857

• Integrative analysis of exome-seq, RNA-seq, ATAC-seq (bulk and single-cell), and Hi-C data generated from 3-D spatially mapped samples acquired during surgical resection from 10 patients diagnosed with IDH-WT glioblastoma

  Glioblastoma (GBM), the most common primary brain cancer in adults, remains incurable with no targeted therapies approved despite decades of investigation into its molecular landscape. Treatment failure is attributed to intratumoral heterogeneity in the GBM genome and epigenome, which foster tumor evolution and selection of resistant clones. However, tumor evolution and intratumoral heterogeneity remain poorly understood on the level of the whole tumor as most studies are based on single samples per patient and lack spatial context. Here, we have used 3-D neuronavigation during surgical resection for 10 primary IDH-WT GBM patients to collect 102 samples representing maximal tumor diversity, each mapped by 3-D spatial coordinates. We have applied a strategic set of genomic and epigenomic assays spanning multiple levels of resolution to discover, orthogonally validate, and functionally assess drivers of tumor evolution and intratumoral heterogeneity. These include extrachromosomal DNA amplifications, chromothripsis events, inversions, and translocations that disrupt both the GBM genome and epigenome while generating fusion transcripts and opportunities for therapeutic intervention. We define epigenomic programs that contribute to GBM evolution and intratumoral heterogeneity, revealing their 3-D spatial patterning within whole tumors and their cell type(s) of origin in single-cell data from the same tumor samples. Notably, we distinguish neuronal, glial, and immune programs aberrantly active in tumor cells from their counterparts in normal cells and discover NEUROD1, JUN/FOS, and NF1 transcription factors as key drivers of GBM evolution and growth. Collectively, these data provide unprecedented insight into GBM evolution and intratumoral heterogeneity from single-cell to whole-tumor resolution, redefining current understanding and providing a rich resource of targets for therapeutic investigation.

  Study EGAS00001006785

• Interactions between the tumor and the systemic response of breast cancer patients

  Breast cancer (BC) research has largely focused on the molecular properties of the tumor proper. However, to understand how cancer progresses and ultimately modulates patient outcome, we also require an understanding of the molecular changes in the patient systemic response (SR). Toward this end, we generated and analyzed RNA profiles from tumor and matched blood samples in 173 BC patients. We designed a system (MIxT) to explore and link tightly co-expressed gene sets (modules) across matched tissues. The gene composition of modules, and their expression, largely vary across tissues. Distinct patterns of expression in the SR are predominantly detected in highly immunogenic BC subtypes. We also find that the expression pattern of a module in one tissue is correlated to the expression pattern of a module in the other tissue in a fashion that depends on subtype. For example, systemic immunosuppression is detected in basalL patients in a fashion that is proportional to the level of expression of several tumor modules highlighting immune evasion mechanisms active in these particular cancers.

  Study EGAS00001001804

• MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

  Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer (CRC) and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their DNA methylation profiles. MethCORR was applied to methylation profiles from 877 fresh-frozen and FFPE samples and comparative analysis identified the same two major subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicted relapse-free survival (HR=2.66, 95% CI [1.67-4.22], P<0.001) than TNM staging and MSI status were identified and validated using DNA methylation-specific PCR assays. The MethCORR approach is general, and may be similarly successful for other cancer types.

  Study EGAS00001004293

• Endocrine therapy reprogramming of breast cancer facilitates metastatic escape via upregulation of P-Rex1/Rac1 signalling

  The estrogen receptor (ER) drives growth in ~70% of breast cancers, and endocrine therapies prevent recurrence. However, 30% of patients recur, with many fatal cases occurring late (after >5 years), presenting a challenge due to their often non-proliferative nature and limited options. To study this, we generated slow-growing resistant cells that form small primary tumours but readily metastasize. Single-cell RNA sequencing (scRNAseq) revealed that endocrine therapy reprograms these cells, notably upregulating the Rac1 signalling component P-Rex1. We found in clinical cohorts that P-Rex1 in high in ER+ breast cancer. Intravital imaging demonstrated that Rac1 signalling is active in ER+ cells following endocrine therapy. Targeting the Rac1 pathway with small molecule inhibitors (NSC23766, R-ketorolac) reduced survival and motility in resistant cells, inhibited in vivo Rac1 activity, and reduced tumour burden when combined with tamoxifen in a drug-refractory patient-derived xenograft. This work identifies the P-Rex1/Rac1 axis, as a potential therapeutic target for late recurring ER+ breast cancer.

  Study EGAS00001008353

• mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

  RNA sequencing is widely used to study gene abundance patterns, but less frequently to assess structural alterations such as fusion transcripts. In this study, we assess the performance of messenger RNA (mRNA) capture sequencing to identify fusion transcripts in formalin-fixed paraffin-embedded (FFPE) tissue of different types of sarcoma, followed by orthogonal confirmation using RT-qPCR. To validate our workflow, we used the TruSight RNA Pan-Cancer Panel to analyze a first cohort of 6 positive control tumors for which the diagnostic workup demonstrated the presence of a specific chromosomal rearrangement. Fusion transcript calling by FusionCatcher confirmed all known aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole transcriptome TruSeq RNA Exome sequencing was applied to a second cohort of 17 patients, diagnosed with fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS), for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. Remarkably, for 6 out of 17 patients, mRNA capture sequencing readily detected a pathognomonic fusion transcript, i.e. PAX3-FOXO1 in 2 ARMS patients, and EWSR1-FLI1, EWSR1-ERG or EWSR1-NFATC2 in 4 URCS patients. These data show that RNA capture sequencing may enhance the detection rate of pathognomonic fusion genes in sarcoma. For the 11 patients with no known pathognomonic fusion transcript, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2 and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in two patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53 and UBE2F-ALS2). Our results provide new insights into the underlying genetic causes of these malignancies.

  Study EGAS00001005202

• HuBMAP: A Spatially Resolved Molecular Atlas of Human Endothelium

  The human circulatory system plays a vital role in the proper functioning of every organ in the human body. Because vascular related diseases, such as atherosclerosis, do not occur homogeneously throughout the vascular tree, differences in the endothelium of various organs must exist. There is even evidence of heterogeneity of adjacent endothelial cells. We are studying normal endothelium throughout the body and across individuals of different ages to characterize these differences. The first step will be to procure normal tissue samples from a wide range of organs. From disaggregated samples of these tissues, we will perform single cell combinatorial indexing (sci-) to generate chromatin accessibility (sci-ATAC-seq) and transcriptome (sci-RNA-seq) data from millions of single cells across hundreds of samples.  Molecular heterogeneity might correlate with multiple facets of the anatomical distribution of endothelium, including vascular vs. lymphatic, arteries vs. veins, capillaries vs. larger vessels, differences between organs, organ zonation, cell-to-cell differences, etc. Based on heterogeneous markers defined from deep profiling of disaggregated cells, we will employ seqFISH to spatially relate the distinct endothelial subpopulations arising from the single nuclei data to histologic preparations. For example, this will allow us to identify subpopulations with particular markers as arterial, capillary, venous, or lymphatic. The end product will include multiparameter images in which the complete gene expression and chromatin accessibility profile can be interactively visualized for every cell.

  Study phs002267

• 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

• 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

• Genomic Characterization CS-MATCH-0007 Arm N

  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 N is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PTEN mutation, or deletion with PTEN expression on IHC, are treated with the drug GSK2636771. 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 phs002151

• Adjuvant nivolumab in resected esophageal or gastroesophageal junction cancer: exploratory biomarker analyses from CheckMate 577

  Adjuvant nivolumab demonstrated a significant improvement in disease-free survival (DFS; primary endpoint) versus placebo in patients with resected esophageal or gastroesophageal junction cancer and residual pathologic disease following neoadjuvant chemoradiotherapy (CRT) in the phase III CheckMate 577 study, leading to global approval and widespread adoption. Exploratory biomarker analyses were performed using whole-exome sequencing, RNA sequencing, and immunohistochemistry. Hazard ratios for DFS favored nivolumab versus placebo in patients with higher inflammation and proliferation gene expression signature scores; lower M2 macrophage, endothelial, and stromal GES scores; and higher densities of CD3+/CD8- T cells and natural killer cells. Assessments of pre-CRT and post-CRT tumor tissue found post-CRT increases in programmed death ligand 1 combined positive score in 51% of patients, which appeared to be associated with greater DFS benefit. Through these analyses, we identified patient subpopulations that appear to derive improved DFS benefit from adjuvant nivolumab in this setting.

  Study EGAS50000001663

• ATAC-seq/ChIP part

  Epigenetics: ATAC-seq and ChIP-seq data

  Study EGAS00001006520

• 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

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• RNA-seq data from 164 advanced prostate tumors generated by the West Coast Dream Team including 42 paired samles

  164 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node. 42 pairs prior to enzalutamide treatment and at progression from 21 patients are included.

  Dataset EGAD00001009065

• 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

• 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

• 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

• Differential expression in clear cell renal cell carcinoma

  To investigate the levels of gene expression in clear cell renal cell carcinoma (ccRCC), we performed an RNA-seq analysis in 786-O, A-498, UM-RC-2 clear cell renal carcinoma cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq files and csv files with the differential expression results. Differential expression was calculated by the RNAflow pipeline (DEseq2), and log fold changes are calculated with respect to the normal cell line (HK-2), with separate results between normoxic and hypoxic datasets.

  Dataset EGAD50000001883

• 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

• ATAC-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015509

• 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

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514

• RNAseq of blood, fat and muscle samples from 45,X, 46,XX, 46,XY and 47,XXY

  Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. The RNA-seq libraries were multiplexed paired-end sequenced on an Illumina Novaseq 6000 (100 bp) and subjected to initial quality control using FastQC (BAbraham Bioinformatics). In addition to trimming of low-quality ends, adaptor removal was conducted using Trim Galore with default settings (BAbraham Bioinformatics).

  Dataset EGAD00001010052

• 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 dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015510

• 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

• 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

• 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

• 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

• 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

• Bulk RNASeq of metastatic colorectal cancer organoids treated with crenigacestat alone or in combination with cetuximab

  Bulk RNA sequencing was performed on mCRC organoids cultured under untreated conditions or treated with crenigacestat alone or in combination with cetuximab. This dataset was generated to investigate the transcriptional changes associated with combination therapy and to compare these profiles with the adaptive responses observed following cetuximab monotherapy in the corresponding ATOH1 wild-type and knockout organoid models.

  Dataset EGAD50000002061