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• Systematic Growth Factor Profiling Platform for 3D Tumor Models Reveals EstradiolResponsive Cellular Mechanisms of Immunotherapy Resistance

  Epithelial ovarian cancer (EOC) exhibits significant molecular heterogeneity, which is thought to be influenced by the tumor microenvironment (TME). However, the specific factors driving this heterogeneity remain poorly understood. In this study, we integrated growth factoromics and genomic data to identify TME factors contributing to EOC heterogeneity and immunosuppression. Our analysis revealed distinct subgroups of EOC samples with differential responsiveness to specific growth factors, particularly estradiol and R-spondin. Notably, samples with high responsiveness to estradiol and Wnt (C1 cluster) were enriched in the Mesenchymal (MES) molecular subtype, while samples with high responsiveness to R-spondin (C2 cluster) were associated with the Differentiated (DIF) and Immunoreactive (IMR) subtypes. We discovered that the G protein-coupled estrogen receptor (GPER), rather than the classical estrogen receptor alpha (ERα), was the key mediator of estrogen responsiveness and a determinant of molecular subtype classification. Single-cell sequencing analysis identified subsets of estrogen-responsive malignant cell (MAL.PDCD5) and cancer-associated fibroblast (FB.TNFSF10), which were associated with immunosuppressive patterns in the TCGA cohort. Importantly, the interaction between these cell populations significantly increased upon estrogen treatment, suggesting a potential mechanism by which estrogen signaling may contribute to the development of an immunosuppressive TME. Our findings highlight the critical role of estrogen signaling in shaping the molecular heterogeneity and immunosuppressive TME of EOC and provide novel insights into potential therapeutic targets for overcoming immunosuppression in this malignancy.

  Study EGAS50000000422

• Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

  Introduction: Concurrent non-serous endometrial and ovarian tumours are often managed clinically as two separate primary tumours, but almost all exhibit evidence of a genomic relationship. Methodology: This study investigates the extent of relatedness using whole exome sequencing, which was performed on paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours in a cohort with detailed clinicopathological annotation. Four whole exome sequencing-derived parameters (mutation, mutational burden, mutational signatures and mutant allele tumour heterogeneity scores) were used to develop a novel unsupervised model for the assessment of genomic similarity to infer genomic relatedness of paired tumours. Results: This novel model demonstrated genomic relatedness across all four parameters in all tumour pairs. Mutations in PTEN, ARID1A, CTNNB1, KMT2D and PIK3CA occurred most frequently and 24 of 27 (89 %) tumour pairs shared identical mutations in at least one of these genes, with all pairs sharing mutations in a number of other genes. Ovarian endometriosis, CTNNB1 exon 3 mutation, and progression and death from disease were present across the similarity ranking. Mismatch repair deficiency was associated with less genomically similar pairs. Discussion: Although there was diversity across the cohort, the presence of genomic similarity in all paired tumours supports the hypothesis that concurrent non-serous endometrial and ovarian carcinomas are genomically related and may have arisen from a common origin. Keywords: Co-existing; Concurrent; Endometrial carcinoma; Genomics; Mutation; Ovarian carcinoma; Paired tumours; Tumour mutational burden.

  Study EGAS00001008259

• Defining the metastasome in colorectal cancer: Implications for hypotheses on metastasis evolution and personalized therapy (HIPO-032)

  Personalized cancer therapy aims at individual genetic changes characterizing primary cancers. Still, however, metastasis is the major clinically unmet problem, also due to an incomplete understanding of its molecular evolution.This study is the first to define the metastasis-specific whole genome landscape of human colorectal primary vs. matched metastatic lesions.Protein coding, ncRNA genes and 3’UTRs harbored about a third each of single nucleotide variations (SNVs)/indels, 19% of them being metastasis-specific. We found novel mutational hills among ncRNAs and 3’UTRs, copy number changes able to explain changes in microRNA expression in metastases, and novel metastasis-specific mutations in the 3’UTRs on important cancer signalling genes. Some metastatic lesions showed targetable mutations not detected in the primaries. Analysis of mutual exclusivity patterns supported a model that has progressive alterations in important colorectal cancer genes and revealed new partners. Metastatic lesions were enriched in SNVs, specific structural variations, and alterations in genes affecting cell adhesion and extracellular matrix interaction.Furthermore, a hepatic stellate activation cascade was enriched in metastases, suggesting genetic programs for site-specific colonization. Allele frequency distribution and mutational signature analysis suggests a common ancestor clone to both the primary tumor and the metastasis, with additional mutagenesis ongoing in both sites independently. Taken together, our results significantly add to hypothesis generation on metastasis evolution, and suggest novel metastasis-specific genomic changes which would be missed by current personalized therapy concepts. (HIPO-032)

  Study EGAS00001002717

• Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary with Neuroendocrine Differentiation

  PURPOSE: Cancer of unknown primary (CUP) is a group of metastatic tumors in which the standard diagnostic work-up fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large since their tumors might have actionable driver mutations that can provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomics analyses could inform on the origin of the tumor. PATIENT AND METHODS: Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a PDX mouse model and bioinformatics was used to identify an actionable mutation, predict resistance development to the targeted therapy, and to correctly diagnose the origin of the tumor. The Cancer Genome Atlas was used to benchmark the bioinformatics workflow. RESULTS: Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatics workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from The Cancer Genome Atlas. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION: Comprehensive genomics analyses could inform on the origin of tumors in patients suffering from CUP.

  Study EGAS00001003026

• Single-cell ATAC-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006559

• Single-cell RNA-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006560

• InterPregGen-GWAS-KAZ-1

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. This dataset includes lllumina 2.5-8 genotyping of maternal and fetal PE cases and controls from Kazakhstan. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator).

  Dataset EGAD00010001945

• InterPregGen-GWAS-KAZ-2

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. This dataset includes OmniExpress genotyping of maternal and fetal PE cases and controls from Kazakhstan. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator).

  Dataset EGAD00010001947

• InterPregGen-GWAS-KAZ-3

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. This dataset includes Infinium GSA genotyping of maternal, paternal and fetal PE cases and controls from Kazakhstan. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator).

  Dataset EGAD00010001949

• PRADO trial - Personalized response-directed surgery and adjuvant therapy after neoadjuvant ipilimumab plus nivolumab in stage III melanoma

  The dataset includes WES sequencing data on PRE- treatment biopsies of lymph node metastasis (n=79) The technology used for sequencing is llumina HiSeq. The PRADO trial tested a personalized response-directed treatment approach based on the pathologic response after neoadjuvant ipilimumab plus nivolumab in stage III melanoma patients. In patients achieving a major pathologic response, in their index lymph node (the largest lymph node metastasis at baseline), therapeutic lymph node dissection (TLND) and adjuvant therapy were omitted. Patients with partial response underwent TLND only, whereas patients with pathologic non-response underwent TLND and adjuvant systemic therapy ± synchronous radiotherapy.

  Dataset EGAD50000000393

• Synchronous patterning of hiPSC-derived CNS progenitors generates comprehensive axial spinal cord organoids (CASCOs) containing diverse motor neuron population

  Dataset includes scRNA-sequencing data of cells isolated by dissociation of ~20 BJ WT day 20 hiPSC-derived MN embryoid bodies generated in ULA 96w plates following the protocol described in Rodriguez-Muela et al., JCI 2018). Droplet-based scRNA-seq was performed using 10X Genomics scRNA-sequencing was performed using 10X Genomics Chromium Single Cell Kit v3. The resulting sequencing reads were processed as described in Buchner et al 2024. Analysis of the count matrices was performed using the R toolkit for single cell genomics, Seurat v5.1.0, with R v3.3.3 “Angel Food Cake.”

  Dataset EGAD50000001301

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• RNAseq and T cell receptor (TCR) profiling of PBMC cells 3 months post Omicron exposure

  This dataset contains RNA-seq and T cell receptor (TCR) sequencing files from a cohort (n=20) 3 months post positive PCR for SARS-CoV-2. A total of 10 hospitalised (samples H1-10) and 10 non-hospitalised (samples NH1-10) are contained within this dataset. RNA sequencing was performed using the Illumina Stranded mRNA Prep Ligation kit to investigate the protein coding transcriptome of PBMC cells. T cell receptor (TCR) repertoire profiling was performed with the TakaraBio SMART-Seq Human TCR (with UMIs) on PBMC cells to investigate the depth and persistence of SARS-CoV-2 targeting TCRs.

  Dataset EGAD50000001356

• Genotyping microarray data of molecular tumorboard patients in the context of the HRD-manuscript published in IJC

  Intensity files (.idat) derived from the Infinium CytoSNP-850K BeadChip microarray (Illumina) were used to analzye a possible Homologous-Recombination-Repair Deficiency (Molecular Rationale for a PARP-Inhibitor therapy) of n= 39 tumor patients (each n= 39 .idat files of the green and red chanel respectively) presented in the Molecular Tumorboard at the University Hospital Erlangen. Using these files a Genomic Instability Score was bioinformatically deducted (R-based scripts, e.g. ASCAT, scarHRD) based upon the presence of three parameteres "Loss of Heterozygosity, LOH", "Large Scale Transitions, LST" and "Telomeric Allelic Imbalances, TAIs". The associated manuscript is published in International Journal of Cancer, IJC.

  Dataset EGAD00010002736

• Complex-I stratification of Parkinson's disease - single nucleus RNAseq

  Single nucleus RNA seq dataset for CI stratification of Parkinson's disease Single nucleus RNA seq dataset of prefrontal cortex tissue from a total of N=18 samples. Tissue samples correspond to patients with idiopathic Parkison's disease (PD) with varying levels of Complex-I activity (N=12) and neurologically healthy controls (N=6). Single nucleus RNA seq was carried out using 10X Genomics Chromium. This dataset corresponds to a subset of the samples sequenced using conventional bulk tissue RNA seq and available within this Study as a separate Dataset.

  Dataset EGAD50000000432

• TSO500 sequencing of ovarian tumour samples

  This dataset consists of 8 ovarian cancer DNA sample libraries prepared using the Illumina TruSight Oncology 500 Kit (Illumina, cat no. 20076480) following the manufacturer's protocol. Library quality and quantity were assessed with High Sensitivity/D5000 Screentape Assay (Agilent Technologies, cat no. 5067-5592) on 4150/4200 Tapestation Quant-IT/Qubit dsDNA HS (Qiagen, cat no. Q32851) assay according to the supplier’s recommendations. Libraries were then pooled together in equal ratios and sequenced using PE-150bp mode on NovaSeq S1 flow cell 300 cycles kit (Illumina, 20028317) or S4 flow cell 300 cycles kit (Illumina, 20028312) aiming for 100 million reads per sample. The dataset contains sequence reads in fastq file format.

  Dataset EGAD50000001451

• Single cell atlas of large B-cell lymphoma

  The dataset comprises multi-omics profiles from 232 biopsies, including 217 from patients with large B-cell lymphoma (114 newly diagnosed and 103 relapsed/refractory) and 15 benign control samples. Specifically: single-nucleus RNA sequencing (snRNA-seq) was performed on all 232 biopsies; single-nucleus ATAC sequencing was conducted on 96 biopsies; bulk RNA sequencing was generated for 208 biopsies; whole-exome sequencing (WES) was performed on 174 tumor biopsies with 118 matched germline samples; Low-pass whole-genome sequencing (lpWGS) was performed on 174 tumor biopsies with 41 matched germline samples. All raw data files are provided in FASTQ format.

  Dataset EGAD50000001491

• Single cell RNA-seq of 24 samples from 13 individual human embryonic meninges of PCW 5.0-13.0 using 10X chromium technology

  A total of 24 samples of meninges from 13 normal human embryos of post-conceptional week (PCW) 5.0-13.0 were dissected and subject to 10Xgenomics chromium single cell RNA sequencing with the purpose of identifying cell types and gene expression programs for normal meninges development. All libraries were sequenced on an Illumina NovaSeq 6000 using S4 to a target sequencing depth of 100,000 reads/cell. Final data after processing with STARSolo 2.7.10a, using human genome GRCh38.p12 and transcript annotations from ENSEMBL release 93 from reference package GRCh38-3.0.0 as available from 10Xgenomics, consists of 24 BAM files.

  Dataset EGAD50000001434

• Sequence data to study genomic CNVs that drive apoptotic resistance and relapses on immune checkpoint inhibitors

  The dataset consists of bulk whole exome sequencing (WES) and whole genome sequencing (WGS) data from baseline and disease-progressed tumors after immune checkpoint inhibitor (ICI) treatment, derived from patients, human cell lines, and mouse models. Whole exome sequencing includes 17 clinical cases and one human cell line model with parental and acquired resistant cell lines (n = 5). Whole genome sequencing encompasses the YUMMER mouse model, including vehicle-treated controls (n = 2) and acquired resistant tumors (n = 3). The sequence reads have been aligned to hg19 and mm9 reference genomes, with mapped files (BAM) made available for analysis.

  Dataset EGAD50000001537

• (ChIP-seq) Shifted assembly and function of mSWI/SNF family subcomplexes underlie targetable dependencies in endometriod carcinomas

  ChIP-seq data of 18 samples from the VOA1066 undifferentiated endometrial carcinoma cell-line with various pulldowns: BRG1 (abcam, ab110642, GR3255117-11), BRD9 (CST, E4Q3F, Lot 1), ARID1A (CST, D2A8U, Lot 4), SS18 (CST, D6I4Z, Lot 1), PBRM1 (CST, D3F70, Lot 3), GLTSCR1 (CST, E6I3A, Lot 1), H3K27ac (CST, C36B11, Lot 16), or none. Sample were either untreated or received doxycycline-induced ARID1A treatment. Samples were sequenced on Illumina NextSeq 500 using 37 bp single-end sequencing parameters. Raw fastq files, along with processed bigwig files containing normalized genomic coverage, and called narrow peaks, are included for each sample.

  Dataset EGAD50000001473

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  The ccRCC-ITH study WES dataset is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. It contains whole exome sequencing data of 18 tumor and 2 adjacent normal samples from 2 UTSW patients, who have consented to depositing their genomic data to public repository. Tumor samples come from different tumor sites, including primary tumor, thrombus and metastases. WES was performed using 75bp paired-end fragments at an average read depth > 50x on a NovaSeq 6000 platform (Illumina, San Diego, CA, USA). The raw data is in fastq format.

  Dataset EGAD50000001550

• Reference Panel for Imputation Analysis Based on Whole Genome Sequencing Data of 3,256 Japanese Individuals(BioBank Japan genotype data)

  This reference panel was constructed using whole genome sequencing data from 3,256 Japanese individuals and the 1000 Genomes Project. It provides high accuracy and utility in analyzing genetic polymorphisms, while also reflecting the genetic diversity specific to the Japanese population. This dataset is expected to contribute to the advancement of genetic research and personalized medicine.

  Study JGAS000746

• Evidence for Enhancer Activity in Intron 1 of TNFRSF1A Using CRISPR/Cas9 in Human Induced Pluripotent Stem Cell-derived Macrophages

  Use of CRISPR/Cas9 technology to study the TNFRSF1A gene, which plays a key role in autoimmune diseases such as ankylosing spondylitis, multiple sclerosis, and inflammatory bowel disease. By editing a specific regulatory element within the TNFRSF1A locus, we have identified the role of an enhancer element that is not well understood.

  Study EGAS50000000703

• PARADIGM: Combined ctDNA and serum PSA for dynamic monitoring of metastatic prostate cancer starting first-line treatment

  The prognosis of newly-diagnosed metastatic prostate cancer is highly variable. The PARADIGM prospective cohort study evaluated predictors of survival in blood collected at the start of each of the first six treatment cycles from 114 high-volume metastatic patients starting androgen deprivation therapy combined with docetaxel or an androgen receptor pathway inhibitor.

  Study EGAS50000001357

• SCANDARE HNSCC DNA targeted panel sequencing

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 232 FFPE samples at baseline from 83 HNSCC patients using DNA targeted panel sequencing, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001654