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• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0076_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0076_000 for Triple negative breast cancer sample SA1035X5XB03021

  Dataset EGAD00001011240

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0142_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0142_004 for Triple negative breast cancer sample SA1035X6XB03209

  Dataset EGAD00001011243

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_002 for Triple negative breast cancer sample SA1035X7XB03502

  Dataset EGAD00001011246

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_001 for Triple negative breast cancer sample SA1035X8XB03420

  Dataset EGAD00001011248

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0164_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0164_002 for Triple negative breast cancer sample SA530X3XB03295

  Dataset EGAD00001011250

• 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

• 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