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• Sequencing data for oesophageal and related samples - Black et al (WES)

  Data supporting: "Understanding the malignant potential of gastric metaplasia of the oesophagus and its relevance to Barrett’s Oesophagus surveillance: individual-level data analysis" Black et al (WES OACs/BOs/normals)

  Dataset EGAD00001011188

• TXT_Cytof_15B

  Matrix of normal values from 39 marker CyTOF assay performed on longitudinal BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011143

• SNF_CyTOFF_20

  Matrix of normal values from 39 marker CyTOF assay performed on baseline BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011146

• AWI-GEN 2 Microbiome Dataset

  AWI-Gen Phase 2 Microbiome Project for 1820 samples.

  Dataset EGAD00001015449

• Embryonic tumour transmission in monozygotic twins

  We have a case of two siblings (twins) who were born with nodular blue rashes over their body. The first twin had a large periorbital subcutaneous mass which was diagnosed as infantile undifferentiated sarcoma. This baby was too systematically unwell for chemotherapy and died at 12 days of age. The second sibling received two cycles of emergency chemotherapy however died due to disease progression and secondary haemorrhage at 2 months of age. Post-mortem normal and tumour samples have been taken. In addition to placental tissue and parental germline DNA, the goal will be to investigate intra-uterine transfer of sarcoma and the phylogenetic relationship of tumours in both twins.

  Dataset EGAD00001015681

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015712

• 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