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• Single-Cell Mitochondrial Mutation Lineage Tracing of Non-Dysplastic and Dysplastic Barrett's Esophagus

  This study addresses a critical knowledge gap in understanding Barrett's esophagus (BE), a common metaplastic condition and precursor to esophageal adenocarcinoma, by identifying lineage connections and cell states underlying its development and malignant transformation. We collected biopsies from 13 Barrett's esophagus patients undergoing routine surveillance endoscopy, sampling metaplastic tissue alongside normal squamous esophagus and gastric cardia tissues when clinically appropriate. Our novel approach integrated single-cell RNA sequencing of nearly 180,000 cells with mitochondrial DNA mutation analysis for lineage tracing, coupled with spatial transcriptomics and comprehensive whole-exome sequencing. For one patient with high-grade dysplasia, we performed detailed whole-exome sequencing analysis at 100x coverage on dissociated Barrett's esophagus cells alongside matched normal esophagus and gastric cardia tissues. This genomic profiling revealed critical genetic drivers of malignant transformation, including a truncating mutation in the mutation cluster region of APC (a negative WNT regulator), mutations in the tumor suppressor genes CDKN2A and TP53, and significant copy number alterations including loss of CDKN2A on chromosome 9. These genetic alterations corresponded with the transcriptional changes observed in our single-cell data, particularly WNT pathway dysregulation and the expansion of LGR5-expressing stem cells, providing molecular evidence for how single clones can initiate the dysplastic transformation. Data deposited in dbGaP consist specifically of the whole-exome sequencing raw files, processed variant calls, and copy number analyses from the single patient with high-grade dysplasia and matched normal esophagus and stomach control tissue. Whole exome sequencing was performed on an Illumina NovaSeq 6000. Sequencing data was preprocessed following the Genome Analysis Toolkit's (GATK) Best Practices. Sequencing data was analyzed with Mutect2 (GATK, v4.2.5.0) to identify short somatic mutations including single-nucleotide polymorphisms and insertions and deletions. The Barrett's esophagus sample was run with the two matched normals, as well as the publicly available germline resource somatic-hg38_af-only-gnomad.hg38.vcf.gz (GATK). Somatic variant calls were filtered using FilterMutectCalls (GATK) and loaded into the Integrative Genomics Viewer (v2.12.3) for identification of high-quality variants in known esophageal adenocarcinoma regulators. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9). CNV, Mutect2, and SVC analyses will be made available through dbGAP. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9) with the default run settings; a pooled reference was generated from the normal esophagus and stomach samples. Copy number results were plotted directly within CNVkit using the function scatter.

  Study phs003949

• Targeted sequencing of candidate regions on chromosome 22q predisposing to multiple schwannomas

  Constitutional LZTR1 or SMARCB1 pathogenic variants have been found in ~86% of familial and ~40% of sporadic schwannomatosis cases. Hence, we performed massively parallel sequencing of the entire LZTR1, SMARCB1 and NF2 genomic loci in 35 individuals with schwannomas negative for constitutional first-hit pathogenic variants in the LZTR1/SMARCB1/NF2 coding sequences, however with 22q deletion and/or a different NF2 pathogenic variant in each tumor, including six cases with only one tumor available. Furthermore, we verified whether any other LZTR1/SMARCB1/NF2 (likely) pathogenic variant(s) could be found in 16 cases carrying a SMARCB1 constitutional variant in the 3’ untranslated region (3’-UTR) c.*17C>T, c.*70C>T or c.*82C>T. As no additional variants were found, functional studies were performed to clarify the effect of these 3’-UTR variants on the transcript. The 3’-UTR variants c.*17C>T and c.*82C>T showed pathogenicity by negatively affecting SMARCB1 transcript level. Two novel deep intronic SMARCB1 variants, c.500+883T>G and c.500+887G>A, resulting in out-of-frame missplicing of intron 4, were identified in two unrelated individuals. Further resequencing of the entire repeat - masked genomics sequences of chromosome 22q in individuals negative for pathogenic variants in the SMARCB1/LZTR1/NF2 coding- and non-coding regions revealed five potential schwannomatosis-predisposing candidate genes, i.e. MYO18B, NEFH, SGSM1, SGSM3 and SBF1, pending further verification.

  Study EGAS00001005680

• Tumor Profiler Project - AML scRNA data

  The dataset contains single-cell RNA seq data from 23 patients with Acute Myeloid Leukemia (AML). Samples were collected from bone marrow or blood. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000000823

• 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

• Genomic characterization of CNA-quiet oral cancer

  Low-coverage whole genome sequencing and targeted (30 gene panel) deep sequencing of oral cancer. Note that the targeted deep sequencing is not actually amplicon sequencing but hybrid capture sequencing, which was not available as on option.

  Dataset EGAD50000000790

• RNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  Bulk RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 4), critical COVID-19 (n = 12) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001405

• miRNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  micro RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 6), critical COVID-19 (n = 13) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001406

• prostate cancer plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 180 different human donors: 132 prostate cancer patients (PRAD) and 48 cancer-free controls. Samples were sequenced on a NovaSeq X and sequencing data is provided in FASTQ format.

  Dataset EGAD50000001805

• CD8+ Tumor-Infiltrating Lymphocyte Abundance is a Positive Prognostic Indicator in Nasopharyngeal Cancer

  This retrospective tissue study explores the prognostic significance of tumour-infiltrating lymphocyte (TIL) populations in NPC, using a combination of RNA sequencing and immunohistochemistry.

  Study EGAS00001006396

• Whole-genome sequencing of BCR-ABL1 lymphoblastic leukemia

  This dataset is derived from whole-genome sequencing (WGS) of DNA from 57 BCR-ABL1 lymphoblastic leukemias (53 diagnostic, 4 relapse) and 53 germline samples.

  Dataset EGAD00001010323

• Illumina sequencing of V4 variable region of the 16S rRNA from human feces samples

  The dataset is composed of 62 samples (31 subjects before and after probiotic-like bacteria treatment). Sequencing was performed using Illumina HiSeq 2500. Fastq files are provided.

  Dataset EGAD00001004944

• Comparison of 133/144bp dominant phenotype vs 166bp dominant phenotype.

  The sequencing results provided in this study is enriched through liquid phase hybridization capture. The data set shows 35 clinical cfDNA samples showing a dominant peak at 166bp and 35 clinical cfDNA samples showing a dominant peak at 134/144bp.

  Dataset EGAD00001005798

• Sporadic Parathyroid Carcinoma

  This dataset is compromised of 5 sequencing experiments from a single patient with sporadic and recurring parathyroid carcinoma. The samples include whole genome sequence of the primary tumor, the first recurrent tumor and peripheral blood. Whole transcriptome sequence of the first and second recurrent tumors are also included.

  Dataset EGAD00001000370

• Human Skin Cancer Atlas, Medical University of Vienna Data Access Policy

  Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. Here, we elucidate the yet unresolved intra-tumoral CAF variety in three skin cancer types at molecular and spatial single-cell resolution in a large cohort. We show that two out of three CAF subtypes contribute to tumor immune surveillance with distinct mechanisms. Matrix CAFs (mCAFs) ensheath tumor nests and synthesize extracellular-matrix to prevent T cell invasion. Immunomodulatory CAFs (iCAFs), which express proinflammatory and immunomodulatory factors, are only detected in high abundance in aggressive tumors. Strikingly, iCAFs but not tumor cells are (apart from immune cells) the exclusive cell type producing chemokines and, thus, play a key role in immune cell recruitment and activation. Mechanistically, we show that cancer cells transform adjacent healthy fibroblasts into cytokine-expressing iCAFs, which subsequently recruit immune cells and modulate the immune response. In conclusion, targeting CAF variants holds promise for improved efficacy of immunotherapy.

  Dac EGAC50000000154

• Single-cell RNA sequencing of sorted regulatory T cells

  Single-cell RNA sequencing of flow cytometry enriched CD4+ CD127- CD25+ regulatory T cells from 8 systemic lupus erythematosus patients (SLE_001 to SLE_007, and SLE_009) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform (incl. generation of TCR libraries). Samples from patients SLE_001, SLE_002, SLE_004, SLE_006 were collected and processed on the first day of experiment (Day 1), and samples from patients SLE_003, SLE_005, SLE_007, SLE_009 on the second day of experiment (Day 2). On each day, samples were pooled and distributed to four lanes on the chromium controller. Run ID 245269 and ID 245270 identify samples sequenced on separate flow cells. Provided are raw sequencing files.

  Dataset EGAD50000000663

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

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

  Dataset EGAD50000000831

• Single cell RNA sequencing of mononuclear cells from synovial fluid of patients with rheumatoid arthritis

  Mononuclear cells were collected from synovial fluid of anti-citrullinated positive antibodies (ACPA)-positive rheumatoid arthritis patients (n=8) and ACPA-negative RA patients (n=8). Global cell types (i.e., no enrichment) were obtained from these cryopreserved synovial fluid mononuclear cells (SFMC) samples and immediately fixed and processed using the GEM-X Flex Gene Expression Reagent Kits (10x Genomics) according to protocol. Following Gel Bead-in Emulsion (GEM) generation, samples were processed using the standard manufacturer’s protocol. Once sequencing libraries passed standard quality control metrics, libraries were sequenced on an Illumina NextSeq2000 P4 100 cycle reagent kit with the following read structure: R1: 28, R2: 90, I1: 10, I2: 10. Libraries were sequenced to obtain a read depth greater than 10,000 reads/cell for gene-expression (GEX). FASTQ files are made available. More detailed information can be obtained in Argyriou A. et al, Annals of the Rheumatic Disease, 2025.

  Dataset EGAD50000001801

• Identification of therapeutic target molecules for prostate cancer by using next generation sequencer

  Comprehensive transcriptional characterization of cancer tissues can reveal important molecular signatures associated with the disease progression. Long non-coding RNA (LncRNA) has a diversity of functions such as transcription, epigenetic and gene regulation in cancer cells including prostate cancer cells. Here, we performed directional RNA-sequence (RNA-seq) on clinical samples obtained from prostate cancer (PC) and lethal castration-resistant PC (CRPC) patients to identify novel molecular signatures including protein coding genes and non-coding RNAs induced in CRPC tissues.

  Study JGAS000198

• Targeted panel data for newly diagnosed myeloma patients.

  Genomic abnormalities in MM are common and can affect a patients outcome. Here we have performed targeted sequencing on xx patient tumor samples and matched control DNA. The targeted panel consists of ~160 genes and copy number regions, as well as key regions of chromosomal translocation including IGH, IGK, IGL and MYC. Using mutation, copy number, and translocation information we have been able to identify abnormalities that affect prognosis including bi-allelic inactivation of TP53 and rearrangements involving MYC.

  Study EGAS00001002859

• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Whole exome and targeted DNA sequencing data for formalin-fixed paraffin embedded tissue from de novo small cell prostatic carcinoma cases

  This dataset consists of 44 compressed paired fastq files, 15 of which are generated from whole exome sequencing, and 29 of which are generated from DNA sequencing using a targeted gene panel capturing the exonic regions of 73 prostate cancer driver genes. Targeted DNA sequencing was performed on an Illumina MiSeq (v3 600 cycle kit), and exome sequencing was done using an Illumina HiSeq 2500 (v4 250 cycle kit) machine. The fastq files are named in accordance with the sample aliases provided, which reflect the pathology of interest to this study (small cell prostatic carcinoma--SCPC), whether it was sequenced using an exome or targeted gene panel, whether the FFPE sample was sourced from tumor or benign tissue (labeled T or B, respectively), and whether there exists multiple samples belonging to a single patient.

  Dataset EGAD00001004139

• Undifferentiated sarcomas develop through distinct evolutionary pathways

  Undifferentiated sarcomas (USARC) of adults are diverse, rare and aggressive soft tissue cancers. Recent efforts have confirmed that USARC exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the genomic basis of this structural complexity by integrating whole genome sequencing, ploidy analysis and methylation profiling of 53 USARC. We identified whole genome doubling as a prevalent and pernicious force in USARC tumourigenesis. Deconvolution of the complex copy number and rearrangement landscapes show distinct signatures associated with chromothripsis, early-haploidy, and successive whole-genome-doubling events, suggesting four divergent models of sarcoma development. We show similar distinct evolutionary tumourigenic pathways in different sarcoma subtypes from the Cancer Genome Atlas. Thirteen percent of tumours exhibited a hypermutator phenotype, opening new avenues for clinical management such as immunotherapy, whilst the period prior to and between genome doubling events may represent clinically relevant interventional points in USARC.

  Dataset EGAD00001004162

• Chromosome Segregation Errors Promote a Diverse Spectrum of Simple and Complex Genomic Rearrangements

  Cancer genomes are frequently characterized by numerical and structural karyotypic abnormalities. Here we combined an inducible centromere-specific inactivation approach with selection for a conditionally essential gene, a strategy we term ‘CEN-SELECT’, and show that single-chromosome missegregation during cell division can directly drive a broad spectrum of structural rearrangement types. Cytogenetic profiling revealed that missegregated chromosomes are 120-fold more susceptible to developing seven major categories of structural variants, including translocations, insertions, deletions, and reassembly into chromothriptically rearranged chromosomes. Whole-genome sequencing of clones with genetically propagatable derivative chromosomes identified complex rearrangements and copy-number alterations that can result in gene inactivation or extrachromosomal gene amplification. We conclude that chromosome segregation errors are sufficient to drive extensive structural variation that recapitulates those commonly associated with human cancers.

  Dataset EGAD00001004163

• Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma

  Atezolizumab (anti–programmed death-ligand 1 [anti-PD-L1]) and bevacizumab (anti-vascular endothelial growth factor [anti-VEGF]) combination therapy has become the new standard of care in patients with unresectable hepatocellular carcinoma. However, potential predictive biomarkers and mechanisms of response and resistance remain less understood. We report integrated molecular analyses of tumor samples from 358 patients enrolled in the GO30140 phase 1b or IMbrave150 phase 3 trials who were treated with atezolizumab combined with bevacizumab, atezolizumab alone, or sorafenib. Pre-existing immunity assessed by high expression of CD274 (PD-L1 mRNA), T-effector signature, and intratumoral CD8+ T cell density were associated with response and better clinical outcomes with the combination treatment. Less clinical benefit was associated with high regulatory T cell (Treg) to effector T-cell ratio and high expression of oncofetal genes such as GPC3 and AFP. Improved outcomes from the combination vs atezolizumab alone appeared to be associated with high expression of KDR (VEGFR2), Treg, and myeloid inflammation signatures, indicating anti-VEGF may contribute by targeting these axes. These findings were further validated by transcriptome analysis of paired pre- and post-treatment biopsies, in situ analysis by multiplex IHC and digital pathology, and in vivo study of an immunogenic hepatocellular carcinoma mouse model. Our findings highlight that anti-VEGF therapy might augment antitumor immunity and enhance anti–PD-L1 immunotherapy by targeting VEGF-mediated angiogenesis, Treg proliferation, and myeloid cell inflammation. Furthermore, our study identified candidate biomarkers for predicting response and resistance to anti–PD-L1 and anti-VEGF combination therapy.

  Study EGAS00001005503

• Inferring causal genes at type 2 diabetes GWAS loci through chromosome interactions in islet cells

  Resolving causal genes for type 2 diabetes at loci implicated by genome-wide association studies (GWAS) requires integrating functional genomic data from relevant cell types. Chromatin features in endocrine cells of the pancreatic islet are particularly informative and recent studies leveraging chromosome conformation capture (3C) with Hi-C based methods have elucidated regulatory mechanisms in human islets. However, these genome-wide approaches are less sensitive and afford lower resolution than methods that target specific loci. Methods: To gauge the extent to which targeted 3C further resolves chromatin-mediated regulatory mechanisms at GWAS loci, we generated interaction profiles at 23 loci using next-generation (NG) capture-C in a human beta cell model (EndoC-βH1) and contrasted these maps with Hi-C maps in EndoC-βH1 cells and human islets and a promoter capture Hi-C map in human islets. Results: We found improvements in assay sensitivity of up to 33-fold and resolved ~3.6X more chromatin interactions. At a subset of 18 loci with 25 co-localised GWAS and eQTL signals, NG Capture-C interactions implicated effector transcripts at five additional genetic signals relative to promoter capture Hi-C through physical contact with gene promoters. Conclusions: High resolution chromatin interaction profiles at selectively targeted loci can complement genome- and promoter-wide maps.

  Dataset EGAD50000000517