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• Dataset for Sarcoma-WGS linked from study EGAS00001004813

  Sequencing data of 77 sarcoma tumor and control runs, which were uploaded to EGAS00001004813. The sequencing was always paired.

  Dataset EGAD00001010257

• Long-read sequencing identifies a common transposition haplotype predisposing for CLCNKB deletions

  This dataset contains CLCNKA/CLCNKB locus alignment data from 27 patients with Bartter syndrome and structural variants encompassing the CLCNKB gene. Due to data protection regulations and in accordance with the patient consent, only relevant alignments from the following regions are shared: hg19: chr1:16,300,000-16,400,000 hg38 (linked read dataset only): chr1:16,000,000-16,100,000 Methods to generate libaries were: long-range amplicon PCR (24 samples), targeted long-fragment enrichment (Samplix/Xdrop technology, 4 samples), long-read whole genome (PacBio Sequel II HiFi reads, 3 samples), 10X linked read short read whole genome (1 sample).

  Dataset EGAD00001011064

• Organoid Derivation Project - GRCh38 - RNAseq (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011092

• 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

• Decoding Human Endogenous Retrovirus Expression in Liver Metastatic Colorectal Cancers: Implications for Diagnosis and Prognosis

  The association between Human Endogenous RetroVirus (HERV) expression and cancer can be considered to both reflect the epigenetic deregulation of cancer and facilitate oncogenesis through its promoter/enhancer action on genes. More than 50% of colorectal cancers develop liver metastases and HERV has never been studied in this setting. We collected 400 RNAseq samples from more than 200 patients with primary and liver metastases from published and unpublished databases. We corroborated our findings with tandem mass spectrometry from primary colorectal cancer and single-cell RNAseq from liver metastatic colorectal cancer (lmCRC). We identified global stability in HERV expression between liver metastases and primary colorectal cancers, suggesting an early oncogenic footprint. Therefore, we proposed a list of seventeen HERV loci for lmCRC characterization with ERV-derived peptides but no expression in normal tissues. Among them, we discovered six prognostic markers after surgical resection of lmCRC. Four of them, HERVH_Xp22.32a, HERVH_20p11.23b, HERVH_13q33.3, HERVH_13q31.3, showed poor prognostic value when expressed (log-rank p-value 0.028, 0.0083, 9e-4, 0.05, respectively). HERVH_Xp22.2c (log-rank p-value 0.032) and HERVH_8q21.3b (only in multivariate models) were associated with better prognosis when expressed. These markers showed a cumulative effect on survival when expressed. Some HERVs were associated with decreased cytotoxic immune cells and most of them correlated with cell cycle pathways. Our findings provide new insights into lmCRC classification and suggest novel prognostic biomarkers and potential therapeutic targets.

  Study EGAS50000000307

• 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

• 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