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• 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

• Colorectal cancer organoids expressing BRAF (fusion) genes

  Fusion genes may be oncogenic drivers and potential targets for personalized therapies in a variety of cancer types. The BRAF gene is frequently involved in oncogenic fusions, with fusion frequencies of 0.2-3% throughout different cancers. BRAF can be fused to a wide variety of genes, however, BRAF fusions rarely occur in the exact same gene configuration, making assessment of the fusion relevance and decision for drug treatment challenging. Here, we devised a colorectal cancer organoid-based platform to functionally characterize diverse BRAF fusions, containing various partner genes (AGAP3, DLG1 and TRIM24). We compared these BRAF fusions with respect to cellular behaviour, downstream signaling activation and response to targeted therapies. We found that 5’ partner choice of BRAF affects cellular localization and intracellular signaling capacities of the fusion genes. The DLG1-BRAF fusion gene showed distinct localization to the plasma membrane and exhibited increased levels of MAPK pathway activation under unperturbed conditions. Furthermore, the different BRAF fusions showed varying sensitivities to the targeted inhibition of ERK and BRAF, with the DLG1-BRAF fusion being the most sensitive. Additionally, RNA-sequencing identified distinct subsets of genes affected by the DLG1-BRAF fusion gene. Importantly, all fusion genes conveyed resistance to the clinically relevant EGFR/HER2/HER4-inhibitor afatinib, suggesting that BRAF fusions should be screened alongside other MAPK pathway alterations to identify mCRC patients amenable to cetuximab treatment. In summary, we developed a platform to efficiently assess molecular and cellular effects of fusion genes, and revealed that differential drug responses and distinct gene expression profiles can be induced by different BRAF fusions .

  Study EGAS00001003558

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

  Dataset EGAD00001004938

• sWGS of HGSOC samples for fixative comparison study

  Shallow whole-genome sequencing of samples from the study "Methanol-based fixation is superior to buffered formalin for next-generation sequencing of DNA from clinical cancer samples". DNA from each sample (100ng) was sheared on Covaris S220 (Covaris): duty cycle - 10%, intensity -5.0, bursts per sec - 200, duration - 300 sec, mode - frequency sweeping, power - 23V, temperature -5:5 C to 6 C, water level - 13. Libraries were prepared with the TruSeq Nano DNA LT Sample Prep Kit (Illumina) using a modi?ed protocol - Sample Puri?cation Beads were replaced by Agencourt AMPure XP beads (Beckman Coultier) and size selection after the End Repair was done to remove only the short fragments. Quality and quantity for contructed libraries were assessed with DNA 7500 kit on Agilent 2100 Bioanalyzer and with Kapa Quanti?cation kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations, respectively. Libraries from 18 barcoded samples were pooled together in equimolar amounts and each pool was loaded on a single lane of a HiSeq Single End Flowcell (Illumina), followed by cluster generation on a cBot (Illumina) and sequencing on a HiSeq 2500 (Illumina) in a single-read 50bp mode. Reads were aligned using bwa-mem v0.7.12-r1039 to the 1000 genomes version of human genome build GRCh37. Picard (http://picard.sourceforge.net) was used to remove duplicate reads.

  Dataset EGAD00001001938

• Knoll et al.: The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Following the demonstration of its life-saving effect in clinical trials, dexamethasone quickly became standard-of-care in the treatment of severe COVID-19. Beneficial effects were reported for patients requiring supplemental oxygen or invasive mechanical ventilation. Yet, a substantial proportion of patients still progressed to a critical condition or succumbed to the disease, despite timely initiation of glucocorticoid treatment. No molecular or cellular correlate of this beneficial treatment response has been defined. Here, we identify distinct cellular and molecular changes in circulating immune cells in patients with COVID-19 elicited in response to dexamethasone treatment. The most profound transcriptional changes in response to dexamethasone treatment were noted in monocytes and in B cells. In monocytes, we observed a reversal of hallmark signatures previously associated with COVID-19 severity, and the induction of a specific monocyte substate enriched in glucocorticoid response gene expression which we here refer to as dexamethasone response cluster. Molecular responses to dexamethasone treatment were directly linked to clinical outcome, since the reversal of pathogenic signatures and induction of glucocorticoid response genes were enriched in patients who survived the disease in response to dexamethasone treatment. Cellular responsiveness of circulating monocytes was thus identified as a correlate of clinical response to dexamethasone treatment. Changes in monocyte transcriptomes could also be linked to epigenetic alterations highlighting early differences in monocytes of dexamethasone responders and non-responders. Further, monocyte single-cell transcriptome-derived signatures were enriched in whole blood transcriptomes from patients with fatal outcome in two independent cohorts, highlighting the potential clinical value for early identification of non-responders who are refractory to dexamethasone treatment. Overall, our findings indicate that the life-saving effects of dexamethasone in COVID-19 patients are linked to a specific immunomodulatory effect based on the reversion of monocyte dysregulation. Our study elucidates the potential mechanism of action of one of the most efficient and cost-effective drugs for the treatment of COVID-19. It further highlights the potential of single-cell omics for monitoring target engagement of immunomodulatory drugs and for the stratification of patients for precision medicine approaches.

  Study EGAS00001007461

• Differentiation-associated ISG expression of NK cells in chronic viral hepatitis

  Little is known about the effects of ISGs on NK cell responses in chronic viral hepatitis. Here, we determined the expression, regulation and function of ISGs in NK cells with respect to phenotype and function, we performed high-throughput single cell RNA sequencing of circulating CD3-CD56+ NK cells from healthy donors (HD) and patients with chronic HBV or HCV infections.

  Dataset EGAD50000001623

• Tumor Profiler Project - MEL scRNA data

  The dataset contains 10x Chromium single-cell transcriptomics data from 65 samples from 62 different patients with melanoma. Samples were collected from the tumor. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000000853

• Tumor Profiler Project - MEL scDNA data

  The dataset contains 10x Chromium single-cell DNA sequencing data from 63 samples from 60 different patients with melanoma. Samples were collected from the tumor. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000000852

• Targeted DNA sequencing on bulk bone marrow and peripheral blood

  Targeted DNA sequencing was performed on 195 bone marrow samples to identify cases of clonal haematopoiesis, and on 99 paired peripheral blood samples. The SeqCap EZ HyperCap protocol was followed, and targeted capture performed against a panel of 97 genes recurrently mutated in myeloid malignancies and clonal hematopoiesis. One BAM file (mapped to the hg38 reference genome) is provided per sample.

  Dataset EGAD00001011083

• Characterization of the cellular microenvironment in fibrostenotic Crohn’s disease

  Crohn's disease (CD) is marked by recurring intestinal inflammation and tissue injury, often resulting in fibro-stenosis and bowel obstruction, necessitating surgical intervention with high recurrence rates. To elucidate to the mechanisms underlying fibro-stenosis in CD, we analysed the transcriptome of cells isolated from the transmural ileum of CD patients, including a trio of lesions from each patient: non-affected, inflamed, and stenotic ileum samples, and compared them with samples from non-CD patients. Our computational analysis revealed that pro-fibrotic signals from a subset of monocyte-derived cells induced a disease-specific fibroblast population, resulting in chronic inflammation and tissue fibrosis. Our findings suggest that the myeloid-stromal axis may offer a promising therapeutic target to prevent fibro-stenosis in CD.

  Study EGAS50000000382

• A novel recurrent mutation in MITF predisposes to familial and sporadic melanoma

  We conducted whole-genome sequencing of probands from several melanoma families, identifying one individual carrying a novel germline variant (c.G1075A, NM_000248.3; p.E318K, NP_000239.1; rs149617956) in the melanoma lineage-specific oncogene MITF. While the variant cosegregated with melanoma in some, but not all cases in the family, linkage analysis of 31 families subsequently identified to carry the variant generated a LOD score of 2.7 under a dominant model, suggesting E318K as a possible intermediate risk variant. Consistent with this, E318K was significantly associated with melanoma in a large Australian case-control sample, giving an odds ratio (OR) of 2.33, 95% CI 1.21-4.70 (case and control carrier frequency, 0.0165 and 0.0072, respectively; P=0.008). Likewise, it was similarly associated in an independent case-control sample from the United Kingdom (UK P=0.012; combined P=0.0003, OR 2.19, 95% CI 1.41-3.45). In the Australian sample, the variant allele was significantly over-represented in cases with a family history of melanoma (OR 2.95, 95% CI 1.23-6.92), multiple primary melanomas (OR 4.22, 95% CI 1.52-10.91), or both (OR 8.37, 95% CI 2.58-23.80). The variant allele was also associated with increased nevus count (combined P=0.002, OR 2.54, 95% CI 1.42-4.55) and non-blue eye color (combined P=0.008, OR 2.01, 95% CI 1.11-3.81). Functional analysis of E318K showed that MITF encoded by the variant allele had impaired sumoylation and differentially regulated several MITF targets. These data indicate that MITF is a melanoma predisposition gene and highlights the utility of whole-genome sequencing to identify novel rare variants associated with disease susceptibility.

  Study phs000419

• NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Asthma): Genetic variants affecting susceptibility and severity

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The exome sequencing asthma project includes 200 African-Americans with asthma from the NHLBI multicenter Severe Asthma Research Program (SARP). SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al., Am J Respir Crit Care Med, 2010. PMID: 19892860). Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. All subjects were carefully characterized using the standardized SARP protocol which included spirometry (medication withheld), maximum bronchodilator reversibility, hyper-responsiveness to methacholine (not performed in subjects with low baseline FEV1), skin-tests to common allergens, questionnaires on health care utilization and medication use and sputum, lung imaging and bronchoscopy in a subset. In addition GWAS data are available (phs000355, Illumina platform).

  Study phs000422

• T1DGC GWAS 1958 British Birth Cohort controls

  T1DGC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort as controls. The cases for this study are made available from the NCBI dbGAP.

  Study EGAS00000000038

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Dac EGAC00001001718

• Degradation of Cyclin K/CDK12 is a druggable vulnerability of colorectal cancer (H012)

  Study EGAS00001004517

• Increased trunk fat is associated with altered gene expression in breast tissue of normal weight women

  Study EGAS00001005138

• Studying Glioblastoma in a Human Organoid Tumor Transplantation Model

  This study comprises two complementary investigations that leverage innovative human model systems and cutting-edge molecular profiling to dissect glioblastoma (GBM) heterogeneity and tumor-microenvironment interactions. The first study uses a novel Human Organoid Tumor Transplantation (HOTT) model, in which freshly dissociated GBM tumor cells from five patients were transplanted into human embryonic stem cell-derived cortical organoids. This system enables the interrogation of tumor and microenvironment interactions in a human-specific, developmentally relevant context. Using single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq), the authors profiled over 216,000 cells, analyzing tumor heterogeneity across multiple media conditions. Ligand-receptor analysis (CellChat), immunofluorescence, and RNAScope were used to validate findings. The study revealed that the HOTT model faithfully recapitulates primary GBM cell types and microenvironmental components, and uncovered a novel bidirectional signaling axis mediated by PTPRZ1 that influences both tumor migration and cell fate in a context-dependent manner. PTPRZ1 is identified to be important for intercellular communication between tumor and microenvironmental cells, while PDGFRB, NOTCH3, HOPX, FAM107A, CLDN5, RGS5, FOXC1, SOX18 are key markers of the neurovascular progenitor that we identify to be a multipotent, restricted progenitor in GBM. Related datasets include the inclusion of immune cells in the HOTT system, termed “iHOTT”. The second study focuses on identifying and characterizing a rare but functionally potent neurovascular progenitor (NVP) population within GBM tumors. By generating a meta-atlas from seven publicly available GBM scRNA-seq datasets, the authors identified a unique tumor-derived cell population co-expressing neural progenitor and vascular markers. This population was validated in situ and in vivo through immunostaining and lineage tracing via DNA barcoding in the HOTT system. Functional knockdown of NVPs in a murine GBM model resulted in reduced cycling cells, altered tumor composition, and increased survival. Clonal analysis showed NVPs have dual potency to give rise to both neuronal and vascular-like tumor cells, contributing significantly to tumor cell diversity. Molecular technologies used across the studies include: Single-cell and single-nucleus RNA sequencing DNA barcoding and clonal lineage tracing (CellTag) Population information: Tumor samples were obtained directly from multiple GBM patients (all IDH1 wild-type, adult), including core and peripheral tumor regions. Human cortical organoids derived from human embryonic stem cells (hESCs) served as the microenvironment in the HOTT model. Principal findings include: HOTT recapitulates the heterogeneity and cell type fidelity of GBM, while enabling the study of tumor–microenvironment signaling. PTPRZ1 has opposing roles in tumor and microenvironment, influencing GBM cell migration and fate via non-catalytic mechanisms. A novel GBM neurovascular progenitor population (NVP) was identified, validated, and shown to contribute clonally to distinct tumor cell types. Elimination of NVPs in vivo reduces tumor aggressiveness and improves survival. Data to be available through dbGaP: Raw and processed single-cell and single-nucleus RNA-seq data (HOTT model and NVP studies) CellTag barcode-labeled scRNA-seq clonal lineage data Associated metadata including patient of origin, experimental condition, and sample annotations.

  Study phs003936

• Study on the consequences of prenatal famine exposure on DNA methylation.

  The potential of the epigenome to undergo environmentally-induced changes during early development is central to its postulated role in human disease. Here, we report a genome-scale view of DNA methylation differences after early gestational malnutrition that was caused by the Dutch Hunger Winter, a severe famine at the end of World War II. We adopted an annotation guided analysis of reduced-representation bisulfite sequencing data generated in 24 middle-aged individuals who had been exposed to famine in utero and 24 unexposed sibling controls. We observed differential DNA methylation primarily at genomic regions with regulatory potential, including enhancers active during early development. In-depth annotation of 181 prenatally-induced differentially methylated regions (P-DMRs) showed that they were predominantly located in gene bodies and co-occurred with histone marks denoting an active state. In line with the early gestational timing of the exposure, the P-DMRs mapped to genes that were enriched for differential expression patterns during blastocyst development and early organogenesis. Validation and further explorative analyses of 6 P-DMRs mapping to SMAD7, CDH23, INSR, RFTN1, CPT1A and KLF13 highlighted the critical role of gestational timing, indicated that differential methylation extended along pathways involved in growth, development and metabolism, and suggested associations with birth weight and serum LDL cholesterol in adulthood and confirmed an enhancer function for the INSR and CPT1A P-DMRs. Our results point toward a link between prenatal malnutrition and epigenetic modulation of growth and lipid metabolism that may underlie the adverse metabolic phenotype of exposed individuals in later life.

  Study EGAS00001000668

• Targeting TRIP13 in Wilms Tumor with Nuclear Export Inhibitors

  Wilms tumor (WT) is the most common renal malignancy of childhood. Despite improvements in the overall survival, relapse occurs in ~15% of patients with favorable histology WT (FHWT). Half of these patients will succumb to their disease. Identifying novel targeted therapies in a systematic manner remains challenging in part due to the lack of faithful preclinical in vitro models. We established ten short-term patient-derived WT cell lines and characterized these models using low-coverage whole genome sequencing, whole exome sequencing and RNA-sequencing, which demonstrated that these ex-vivo models faithfully recapitulate WT biology. We then performed targeted RNAi and CRISPR-Cas9 loss-of-function screens and identified the nuclear export genes (XPO1 and KPNB1) as strong vulnerabilities. We observed that these models are sensitive to nuclear export inhibition using the FDA approved therapeutic agent, selinexor (KPT-330). Selinexor treatment of FHWT suppressed TRIP13 expression, which was required for survival. We further identified in vitro and in vivo synergy between selinexor and doxorubicin, a chemotherapy used in high risk FHWT. Taken together, we identified XPO1 inhibition with selinexor as a potential therapeutic option to treat FHWTs and in combination with doxorubicin, leads to durable remissions in vivo.

  Study EGAS00001007389

• TF ChIP-seq of human acute leukemias

  CEBPA/PU.1/TCF7 ChIP-seq of 6 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). Low-coverage whole genome sequencing (ChIP input) of the same samples is also included as a control to be used in peak calling.

  Dataset EGAD00001015358

• Whole genome sequencing of Cas9 repaired cystic fibrosis organoids description

  Three SpCas9-ABE (R785X/R785X) and three xCas9-ABE-repaired organoid clones (F508del/R553X) and their respective unrepaired control organoids were paired-end whole genome sequenced using Illumina Novaseq 6000 system. The reads were mapped to hg19 genome assembly and data is provided as BAM files.

  Dataset EGAD00001005427

• Health Effects of Arsenic Longitudinal Study

  The Health Effects of Arsenic Longitudinal Study (HEALS), a multidisciplinary and large prospective cohort study in Araihazar, Bangladesh, was established to evaluate the effects of full-dose range arsenic (As) exposure on various health outcomes. We applied array-based genotyping technologies to baseline DNA samples from a subset of the HEALS study and linked those genotypes to data on arsenic species measured in urine. We used these data to identify regions influencing arsenic metabolism (AS3MT and FTCD). We also applied array-based DNA methylation technologies to baseline DNA samples from a subset of individuals from HEALS. These data were linked to data on arsenic concentration (in both urine and drinking water) to identify regions of the genome where DNA methylation is impacted by arsenic exposure.

  Study phs003839

• Elevated cfDNA after exercise is derived primarily from mature polymorphonuclear neutrophils, with a minor contribution of cardiomyocytes

  Study EGAS00001007157

• Epigenomics of Human CD8 T cell Differentiation and Aging

  The efficacy of the adaptive immune response declines dramatically with age, but the cell-intrinsic mechanisms driving the changes characteristic of immune aging in humans remain poorly understood. One hallmark of immune aging is the loss of self-renewing naive cells and the accumulation of differentiated but dysfunctional cells within the CD8 T cell compartment. Using ATAC-seq, we first inferred the transcription factor binding activities that maintain the naive and central and effector memory CD8 T cell states in young adults. Integrating our results with RNA-seq, we determined that BATF, ETS1, Eomes, and Sp1 govern transcription networks associated with specific CD8 T cell subset properties, including activation and proliferative potential. Extending our analysis to aged humans, we found that the differences between memory and naive CD8 T cells were largely preserved across age, but that naive and central memory cells from older individuals exhibited a shift toward a more differentiated pattern of chromatin openness. Additionally, aged naive cells displayed a loss in chromatin openness at gene promoters, a phenomenon that appears to be due largely to a loss in binding by NRF1, leading to a marked drop-off in the ability of the naive cell to initiate transcription of mitochondrial genes. Our findings identify BATF- and NRF1-driven gene regulation as targets for delaying CD8 T cell aging and restoring T cell function.

  Study phs001187

• Upper respiratory microbiome of COVID-19 patients

  Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 microbiome studies by analyzing the upper respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We found that time in the intensive care unit and the type of oxygen support explained the most variation within the upper respiratory tract microbiome, dwarfing (non-significant) effects from viral load, disease severity, and immune status. Specifically, mechanical ventilation was linked to altered community structure, lower species- and higher strain-level diversity, and significant shifts in oral taxa previously associated with COVID-19.

  Study EGAS00001004951