7197 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

in 22.19 milliseconds.

• Deciphering Maternal-Fetal Crosstalk in the Human Placenta During Parturition Using Single-Cell RNA-Sequencing

  Labor is a complex physiological process requiring a well-orchestrated dialogue between the mother and fetus. However, the cellular contributions and communications that facilitate maternal-fetal crosstalk in labor have not been fully elucidated. In this latest version (#5), scRNA-seq was applied to decipher maternal-fetal signaling in the human placenta and chorioamniotic membranes during term labor. Samples were obtained from women who underwent spontaneous labor (n = 24) or who were delivered in the absence of spontaneous labor (n = 18) at term. Samples from previous versions (#1-3) of this study include the placental villous tree, basal plate, and chorioamniotic membranes of women across a range of pregnancy physiologic and pathologic conditions, including the processes of labor (term labor and preterm labor), and COVID-19 (version #3). Version #4 includes samples from the human myometrium during spontaneous term labor.

  Study phs001886

• IFN-γ and TNF-α drive a CXCL10+ CCL2+ Macrophage Phenotype Expanded in Severe COVID-19 Lungs and Inflammatory Diseases with Tissue Inflammation

  We explored how the human macrophages response to different inflammatory factors, focusing particularly on the effects of antiviral interferons (IFN-β and IFN-γ), pro-inflammatory cytokines such as TNF-α, and other mediators like IL-4. Co-cultured fibroblasts were a component in some conditions to generate factors produced by resident stroma. We used a single-cell antibody-based hashing strategy to multiplex samples from different stimulatory conditions in one sequencing run. This macrophage transcriptomic data reveals distinct macrophage activation states and polarizations shaped by different tissue-related inflammatory conditions at single-cell resolution. We further performed an unbiased integration between tissue-level macrophages and this stimulated human blood-derived macrophages, which pinpoint an IFN-γ and TNF-α synergistically driven inflammatory macrophage phenotype expanded in severe COVID-19 lungs and other inflamed disease tissues.

  Study phs002780

• A Multimodal Atlas of Human Brain Cell Types

  "A multimodal atlas of human brain cell types" includes sample data targeting two cell types that show species differences between mouse and human. First, it includes a detailed transcriptomic, morphological, and electrophysiological characterization of cell types in layer 1 of human middle temporal gyrus, focusing primarily on different inhibitory cell types. This project also includes gene expression data collected from nuclei in layer 5 of human fronto-insula, with a goal of identifying transcriptomic signatures of Von Economo neurons. Control samples collected as part of the same experiment are also included in the data set. This study was conducted as part of a collaboration between the Allen Institute for Brain Science, the University of Szeged, and the J. Craig Venter Institute. Collaborators request that publications resulting from these data cite their original publication: Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type (PMID: 30150662).

  Study phs001791

• DNA and RNA sequencing of single human haploid germ cells

  Our goal was to look at allele-specific gene expression in single spermatids from two human donors. We first genotyped and phased each donor using a combination of linked-read sequencing (one sample per donor, 10X Chromium), and single haploid whole genome sequencing (53 spermatids for the first donor, and 19 for the second). We then sequenced mRNA from single spermatids (302 from the first donor, and 164 from the second), using the Smart-Seq2 protocol. We used these gene expression data, in combination with the haplotype data, to look for gene products that exhibit allele-specific bias reflecting the haploid genotype of the cell. We find a large class of human genes that show such allele-specific bias in spermatids, indicating that these gene products are not fully shared across the cytoplasmic bridges that connect spermatids. We term these genes “genoinformative markers” (GIMs).

  Study phs002279

• Anaplastic oligodendroglioma exome and RNA sequencing data

  Anaplastic oligodendrogliomas (AOs) are rare primary brain tumors which are generally incurable, with heterogeneous prognosis and few treatment targets identified. Most oligodendrogliomas have chromosome 1p/19q co-deletion and IDH mutation. We analyzed 51 AOs by whole-exome sequencing, identifying previously reported frequent somatic mutations in CIC and FUBP1. We also identified recurrent mutations in TCF12 and in an additional series of 83 AO. Overall 7.5% of AO are mutated for TCF12, which encodes an oligodendrocyte-related transcription factor. 80% of TCF12 mutations identified were in either the bHLH domain, which is important for TCF12 function as a transcription factor, or were frame shift mutations leading to TCF12 truncated for this domain. We show that these mutations compromise TCF12 transcriptional activity and are associated with a more aggressive tumor type. Our analysis provides further insights into the unique and shared pathways driving AO.

  Study EGAS00001001209

• RNA sequencing CYLD cutaneous syndrome

  Patients with CYLD cutaneous syndrome (CCS; syn. Brooke-Spiegler syndrome) carry germline mutations in the tumor suppressor CYLD and develop multiple skin tumors with diverse histophenotypes. We comprehensively profiled the genomic landscape of 42 benign and malignant tumors across 13 individuals from four multigenerational families. Novel recurrent mutations were found in epigenetic modifiers DNMT3A and BCOR in 29% of benign tumors. Multi-level and microdissected sampling strikingly reveal that many clones with different DNMT3A mutations exist in these benign tumors, suggesting that intra-tumor heterogeneity is common. Integrated genomic, methylation and transcriptomic profiling in selected tumours suggest that isoform specific DNMT3A2 mutations are associated with dysregulated Wnt/ß-catenin pathway signaling. Phylogenetic and mutational signature analyses confirm cylindroma pulmonary metastases from primary skin tumours. These findings add novel dimensions to existing paradigms of cutaneous tumorigenesis and metastasis.

  Study EGAS00001003841

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• Title: Divergent levels of CD112 and INKA1 define a distinct subset of human long-term hematopoietic stem cells

  The data provided here was critical in establishing that human long-term hematopoietic stem cells (LT-HSC), previously described as the most primitive HSC population, is actually composed of distinct subsets that can be prospectively isolated. Via mechanistic studies centering around the Rho-GTPase effector kinase PAK4 and its inhibitor INKA1, we identified the immune checkpoint ligand CD112 as a marker for hematopoietic stem and progenitor cells, that is highest expressed on LT-HSC. More importantly, CD112 can be used to stratify functionally distinct subsets within LT-HSC: In response to regeneration-mediated stress, the CD112low subset exhibits a transient restraint (termed latency) before contributing to hematopoietic reconstitution, while the CD112high subset is primed to respond rapidly. High resolution RNA-seq of the CD112 surface expression spectrum within rare LT-HSC subsets (human umbilical cord blood) demonstrated that more genes are differentially upregulated in the deeper quiescent and less metabolic active subset. Genes enriched in this subset centre around cell adhesion and Rho-GTPase signaling. This is in agreement with the scRNAseq data from human G-CSF mobilized peripheral blood (mPB) generated here that was used as an model of in vivo activation/priming revealing via RNA-velocity and pseudo-time analysis that INKA1high versus PAK4high, CDK6high and CD112high enrichment are either detected early or late in diffusion pseudotime indicative of quiescent versus primed cell status, respectively. RNAseq following INKA1 overexpression in LT-HSC and ST-HSC revealed by GSEA an overall stemness preserving phenotype and particularly in LT-HSC, but not in short-term HSC (ST-HSC), suppression of transcriptional programs linked to activation. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir.

  Dataset EGAD00001006541

• Dual targeting of polyamine synthesis and uptake in diffuse intrinsic pontine gliomas

  Bulk RNA-seq data of tumour data.

  Dataset EGAD00001006794

• A Phase I Study of the Treatment of Recurrent Malignant Glioma with CAN-3110 (AKA rQNestin34.5v.2), a Genetically Engineered HSV-1 Virus

  This study is a "first-in-human" phase 1 trial of recurrent, IDH wild-type glioblastoma (rGBM) patients treated with CAN-3110 (aka rQNestin34.5v.2), a genetically modified oncolytic herpes simplex virus 1 (HSV-1). The study was a 3+3 dose-escalation study starting at a single intra-tumoral injection of 106 PFU CAN-3110 going up to 1010 PFU in half-log increments (cohorts 1-9). An expansion cohort (cohort 10) was treated with 109 PFU injected into up to 5 sites within a single tumor. Principal findings of the study conclude that:CAN-3110 was safe at all tested doses (no dose-limiting toxicities reached)HSV-1 seropositive patients survived significantly longer than HSV-1 seronegative patients in this study - longer than expected based on historical rGBM controlsHSV-1 seropositive patients were significantly more likely to clear CAN-3110 (HSV-1) antigen from their tumors based on immunohistochemical stainingCAN-3110 treatment-induced CD8+/CD4+ T-cell recruitment to injected tumor sites altered TCR beta diversity in both tumor infiltrating leukocytes (TILs) and PBMCs, and initiated changes in specific TCR beta clonotypes and immune gene signatures which were associated with post-treatment survival.Data provided in dbGaP for this study include:Bulk RNA-Seq data for 13 pre/post-treatment pairs of rGBM tumors corresponding to 12 unique patients (patient 28 was treated with CAN-3110 at two different timepoints). This data is provided as raw sequencing reads (.fastq), kallisto pseudoalignment transcript-level read counts (abundance.tsv files), gene-level abundance matrix (Gene_Level_Expression_Matrix.tsv), and immune gene signature scores matrix (Immune_Gene_Signatures_Matrix.tsv). Sequencing was performed as paired 150bp sequencing on NovaSeq6000 S4 Illumina flow cells. Library preparation varied by batch as described in the included RNAseq_Metadata.xlsx table.TCR beta DNA sequencing performed by Adaptive Biotechnologies for 21 pre/post-treatment pairs of rGBM tumors and PBMCs representing 20 unique patients (patient 28 was treated with CAN-3110 at two different timepoints). Note that all tumor pairs with TCR beta sequencing data also have available bulk RNA-Seq data. The TCR beta sequencing data is provided as an excel spreadsheet (TCRbeta_Sample_Overview.xslx), which provides a broad level summary of the sequencing on a per-sample basis (# of TCRbeta templates, T cell fraction, TCR beta diversity metrics, etc.) and as a large tab separated value file (Full_TCRbeta_Rearrangement_Details.tsv), which provides information per sample at the level of each unique TCR beta sequence (amino/nucleic acid sequence, VDJ gene usage, etc.).An excel table of de-identified metadata for the patients involved in this study.

  Study phs003378

• CPTAC: Proteogenomic Studies of Ovarian Tumor Responses to Agents Targeting the DNA Damage Response

  There is a critical unmet need for predictors of chemo-refractory High-grade serous ovarian cancer (HGSOC). Despite over 3 decades of research on platinum responses in cancer, no predictive biomarker has been translated into clinical use. Predictors of refractory disease could spare these patients the unnecessary toxicity of a platinum-based regimen and provide a means to triage these patients to clinical trials to identify effective therapies for refractory disease. This study has approached the development of a predictor in a novel way enabling detection of a multi-analyte panel biomarker capable of detecting a subset of refractory HGSOCs with high specificity and implicating potential treatment vulnerabilities for refractory disease. We reported the first proteogenomic analysis of platinum refractoriness in HGSOC and made the novel dataset available as a resource to the community, including a ProTrack portal: http://ptrc.cptac-data-view.org/. Detailed proteogenomic profiles were generated for this study from a retrospective cohort of 242 treatment-naive HGSOCs with enriched representation of "exceptional non-responders" (i.e., patients with chemo-refractory disease). Whole genome sequence (WGS) and RNA seq FASTQ files are available through dbGaP. Proteomic data are available through the NCI Proteomic Data Commons (PDC): https://pdc.cancer.gov/pdc/.

  Study phs003152

• Somatic Mutation Profile by Next Generation Sequencing in HER2+ Breast Cancer

  The HER pathway is the driving force behind 30% of human breast cancers. It is important to understand how targeted therapies block different cellular pathways, and mechanisms of escape from this blockage. Therapies directed at HER2 establish a successful treatment paradigm, but de novo and acquired resistance exist. The HER signaling system is a complex network with four receptors and eleven ligands, a phosphorylation signaling cascade, and many transcription factors, all complicated by both positive and negative feedback circuits. Analysis of genomes, exomes and transcriptomes by next generation sequencing is aimed at uncovering the genetic factors responsible for patient responses to HER2-directed therapies. We are sequencing HER2-overexpressing cancers, in order to identify potential somatic changes that may better select patients who will benefit from therapy, to determine new targets that may overcome resistance, and to improve outcomes with known current HER2-targeted therapies. Whole exome capture sequencing will determine somatic mutation profiles in HER2-overexpressing tumors, to comprehensively characterize the somatic alterations, with the goal of identifying those patients most likely to respond, as well as discovering new targets that may overcome resistance to HER2-directed therapy. We augment the whole exome data with RNA-seq data to determine expression levels of somatic mutations we discover.

  Study phs000770

• An RCOR1 loss-associated gene expression signature identifies a prognostically significant DLBCL subgroup

  Effective treatment of diffuse large B cell lymphoma (DLBCL) is plagued by heterogeneous responses to standard therapy, and molecular mechanisms underlying unfavorable outcomes in lymphoma patients remain elusive. Here, we profiled 148 genomes with 91 matching transcriptomes in an R-CHOP-treated DLBCL cohort to uncover molecular subgroups linked to treatment failure. Systematic integration of high-resolution genotyping arrays and RNA-seq data revealed novel deletions in RCOR1 to be associated with unfavorable progression free survival (P = 0.001). Integration of expression data from the clinical samples with data from RCOR1 knockdowns in the lymphoma cell lines KM-H2 and Raji yielded an RCOR1 loss-associated gene signature comprising of 233 genes. This signature identified a subgroup of patients with unfavorable overall survival (OS) (P = 0.023). The prognostic significance of the 233-gene signature for OS was reproduced in an independent cohort comprising of 195 R- CHOP treated patients (P = 0.039). Additionally, we discovered that within the IPI low risk group, the gene signature provides additional prognostic value that was independent of the cell-of-origin phenotype. Taken together, we present a novel and reproducible molecular subgroup of DLBCL, impacting risk-stratification of R- CHOP treated DLBCL patients and revealing a new avenue for therapeutic intervention strategies.

  Study EGAS00001001000

• Molecular determinants of response to PD-L1 blockade across tumor types

  Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

  Study EGAS00001004343

• Adult-type Granulosa Cell Tumour of the Ovary

  A recurrent mutation in FOXL2 (c.402C>G; p.C134W) is present in over 95% of adult-type granulosa cell tumours (AGCTs). In contrast, various loss-of-function mutations in FOXL2 lead to the development of blepharophimosis, ptosis and epicanthus inversus syndrome (BPES). BPES is characterized by an eyelid malformation often accompanied with primary ovarian insufficiency but not granulosa cell tumours. Two recent studies suggest that FOXL2 C402G is a gain or change-of-function mutation with altered DNA-binding specificity. Another study proposes that FOXL2 C402G is selectively targeted for degradation inducing somatic haploinsufficiency suggesting its role as a tumour suppressor. The latter study relies on data indicative of an FOXL2 allelic imbalance in AGCTs. Here we present RNA-seq data as genetic evidence that no real allelic imbalance is observed at the transcriptomic level in AGCTs. Additionally, there is no loss of protein expression in tumours harboring the mutated allele. These data and other features of this mutation as compared to other oncogenes and tumour suppressor genes argue strongly against FOXL2 being a tumour suppressor in this context. Given the likelihood that FOXL2 C402G is oncogenic, targeting the variant protein or its downstream consequences is the most viable path forward to identifying an effective treatment for this cancer.

  Study EGAS00001005414

• Stereotyped B-cell responses are linked to IgG constant region polymorphisms in multiple sclerosis

  Clonally related B cells infiltrate the brain, meninges, and cerebrospinal fluid of multiple sclerosis (MS) patients, but the mechanisms driving the B-cell response and shaping the immunoglobulin repertoires remain unclear. Here, we used single-cell full-length RNA-seq and B-cell receptor reconstruction to simultaneously assess the phenotypes, isotypes, constant region polymorphisms, and the paired heavy- and light-chain repertoires in intrathecal B cells. We detected extensive clonal connections between the memory B cell and antibody-secreting cell compartments and observed clonally related cells of different isotypes, including IgM/IgG1, IgG1/IgA1, IgG1/IgG2, and IgM/IgA1. There was a strong dominance of the G1m1 allotype constant region polymorphisms in antibody-secreting cells, but not in memory B cells. Tightly linked to the G1m1 allotype, we found a preferential pairing of the immunoglobulin heavy-chain variable (IGHV)4 gene family with the κ variable (IGKV)1 gene family. The IGHV4-39 gene was most used and showed the highest frequency of pairing with IGKV1-5 and IGKV1(D)-33. These results link IgG constant region polymorphisms to stereotyped B-cell responses in MS and indicate that the intrathecal B-cell response in these patients could be directed against structurally similar epitopes.

  Study EGAS00001005745

• Characterization of a New Case of XMLV (Bxv1) Contamination in the Human Cell Line Hep2 (Clone 2B) Using High-Throughput DNA- and RNA-Seq

  We have sequenced DNA and RNA from the Hep2 (clone 2B) cell line (Sigma-Aldrich catalog number: 85011412-1VL) using short read Illumina sequencing. We show that this cell line is indistinguishable from the HeLa cell line (as mentioned on the Sigma-Aldrich website) by mapping integrations of the human papillomavirus 18. We also show that the cell line is contaminated by the Bxv1 xenotropic murine leukemia virus. This contamination has to be taken into account when using the cell line in future experiments.

  Study phs001944

• Cancer and germline exomes, and cancer RNA-seq consisiting of FASTQ paired-end reads from melanoma, lung and colon cancer samples

  Discovery of patient-specific tumor antigens usually requires in vitro-expanded autologous tumor infiltrating lymphocytes (TILs), among which tumor antigen-specific T cells are however often rare, thus limiting sensitivity. We designed in vitro culture conditions to improve the identification of rare tumor antigen-specific CD8 TILs. This innovative yet accessible pipeline allows highly-sensitive identification of tumor antigens and cognate T cell receptors (TCRs), greatly improving the selection of candidates for personalized cancer vaccines and TCR-based cellular immunotherapies.

  Study EGAS00001005513

• RNA-seq analysis of metastatic prostate cancer solid tumor biopsies

  The prevalence and features of treatment-emergent small-cell neuroendocrine prostate cancer (t-SCNC) are not well characterized in the era of modern androgen receptor (AR)–targeting therapy. We sought to characterize the clinical and genomic features of t-SCNC in a multi-institutional prospective study. Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy and were followed for survival. t-SCNC is present in nearly one fifth of patients with mCRPC and is associated with shortened survival.

  Study EGAS00001006369

• 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/

  Dataset EGAD00001005741

• Alignment BAM files and gene count files of the Illumina Sequencing Data (10 tumor samples)

  Reads were processed with the RNA-seq workflow 1.3.0 developed by the DKFZ Omics IT and Data Management Core Facility (https://github.com/DKFZ-ODCF/RNAseqWorkflow). First, FASTQ reads were aligned via two-pass alignment using STAR 2.5.3a. The STAR index was generated from the 1000 Genomes assembly and GENCODE Version 19 gene models with a sjdbOverhang of 200. Duplicate marking of the resultant main alignment file was done with sambamba 0.6.5. Gene-specific read counting was performed using featureCounts (from Subread 1.5.1) over exon features based on GENCODE Version 19 gene models. Both reads of a paired fragment were used for counting, and the quality threshold was set to 255, indicating that STAR found a unique alignment. Strand-specific counting was also used. For RPKM and TPM calculations, all genes on chromosomes X and Y, the mitochondrial genome, as well as rRNA and tRNA genes were omitted as they are likely to introduce library size estimation biases.

  Dataset EGAD00001008969

• NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

  The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.

  Study phs003047

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Exceptional Responders Initiative

  The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

  Study phs001145

• Identification of Somatic Changes in Tumors from Fanconi Anemia Patients

  This study focused on the identification of genomic signatures present in tumors from Fanconi anemia patients. Fanconi anemia is a rare hereditary disease caused by defects in DNA interstrand crosslink repair. The primary patient phenotypes are bone marrow failure and cancer predisposition. We concentrated on squamous cell carcinomas and used whole genome Illumina sequencing (22 tumor samples and 12 normal samples) , whole exome sequencing (37 tumor samples and 33 normal samples), PacBio long-read whole-genome (nine tumor and four normal samples),10X linked-read whole-genome sequencing, 10x single-cell/nuclei 3’ RNA sequencing (three tumor samples), 10x Visium spatial transcriptomics (one tumor sample), EPIC 850K methylation array (six samples), and bulk RNAseq (six tumor samples) to identify somatic changes present in tumors. The study aimed to identify changes that drive tumorigenesis in Fanconi anemia, give insight into the early development and aggressive nature of these tumors, and suggest therapeutic avenues for these patients. Another goal was to compare the genomic changes identified in tumors from Fanconi anemia patients with sporadic head and neck cancers. This study demonstrated that the tumors from Fanconi anemia individuals are generally not driven by HPV. Instead, they acquire mutations in the p53 tumor suppressor. The main characteristic of the tumors is the presence of a high number of structural variants in the form of small deletions, unbalanced translocations, and fold-back inversions, which often form complex rearrangements. These rearrangements result in amplifications and deletions of a multitude of oncogenes and tumor suppressors, respectively. The study also shows that lack of the Fanconi anemia DNA repair pathway leads to an epithelial-to-mesenchymal transition in a mouse model and in human samples that may influence the behavior of tumors in Fanconi anemia. Finally, comparing genomic changes in Fanconi anemia and sporadic tumors of the head and neck, we propose that the structural variants present in sporadic cancer result in a functional deficiency of the Fanconi anemia DNA repair pathway.

  Study phs002652