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• RNAseq profile of monomorphic epitheliotropic intestinal T-cell lymphoma and enteropathy associated T-cell lymphoma

  Background : Enteropathy-associated T-cell lymphoma (EATL) and monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL) are aggressive malignancies with limited treatment options and poor prognosis. Our research on MEITL has uncovered its genetic portrait including hallmark SEDT2 mutations, expanded its pathological spectrum, and identified molecular biomarkers influencing patients’ outcome. In this study, we aimed to establish and clarify the similar and diverging features of EATL. Methods : A large combined cohort of patients with EATL (n=30) and MEITL (n=52) was assembled and tumor samples were used for whole-exome and RNA sequencing profiling.

  Study EGAS50000001125

• Whole Exome Sequencing of monomorphic epitheliotropic intestinal T-cell lymphoma and enteropathy associated T-cell lymphoma

  Background : Enteropathy-associated T-cell lymphoma (EATL) and monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL) are aggressive malignancies with limited treatment options and poor prognosis. Our research on MEITL has uncovered its genetic portrait including hallmark SEDT2 mutations, expanded its pathological spectrum, and identified molecular biomarkers influencing patients’ outcome. In this study, we aimed to establish and clarify the similar and diverging features of EATL. Methods : A large combined cohort of patients with EATL (n=30) and MEITL (n=52) was assembled and tumor samples were used for whole-exome and RNA sequencing profiling.

  Study EGAS50000001126

• Illumina ExomeChip genotyping data from the Cretan Greek isolate collection HELIC MANOLIS

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina HumanExome Beadchip. The HELIC (Hellenic Isolated Cohorts) MANOLIS (Minoan Isolates) collection focuses on Anogia and surrounding Mylopotamos villages. Recruitment of this population-based sample was primarily carried out at the village medical centres. All individuals were older than 17 years and had to have at least one parent from the Mylopotamos area. www.helic.org **The data may not be used for population genetics analyses.**

  Study EGAS00001000630

• Whole genome and whole transcriptome sequencing of patients diagnosed with angiosarcoma.

  Angiosarcomas are rare, clinically-aggressive tumors with a predilection for the elderly and immunosuppressed, which has incited suspicion of an oncogenic virus. We studied the metagenomic landscape of angiosarcomas and identified reads mapping to human herpesvirus-7 (HHV-7). Overall, HHV-7 was present in two-thirds of angiosarcomas, particularly in cases with low tumor mutation burden and lacking signatures of ultraviolet-induced DNA damage. Transcriptomic profiling revealed the enrichment of tumor inflammation signatures in HHV7-positive angiosarcomas. In conclusion, we identified a distinct “inflammatory” subtype of angiosarcoma associated with HHV-7.

  Study EGAS00001003895

• Leucocyte eQTLs in autoimmune disease and health

  Peripheral blood was taken from healthy controls and patients with active autoimmune disease. CD4 T cells, CD8 T cells, monocytes, neutrophils, and B cells were separated using magnetic-activated cell sorting. RNA and genomic DNA was extracted from cell lysates using Qiagen Allprep kits. Genotyping of healthy controls and patients with inflammatory bowel disease was performed using the Illumina Human OmniExpress12v1.0 BeadChip at the Wellcome Trust Sanger Institute. 200 ng RNA was processed for hybridization onto Affymetrix Human Gene ST 1.1 microarrays. Gene expression and genotyping data was used to perform eQTL mapping.

  Study EGAS00001001251

• DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ.

  DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ. The objective of the study was to introduce methodology for the detection of genomic copy number alterations (CNAs) using high-throughput sequencing data. The samples in this study allow the comparison of the results from the seqCNA R package with those from other methods that detect copy number alterations (CNAs) in tumoural samples, either using SNP-array data or high-throughput sequencing data.

  Study EGAS00001000558

• Illumina Human OmniExpress genotyping data from the Cretan Greek isolate collection HELIC MANOLIS

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina Human OmniExpress BeadChip array. The HELIC (Hellenic Isolated Cohorts) MANOLIS (Minoan Isolates) collection focuses on Anogia and surrounding Mylopotamos villages. Recruitment of this population-based sample was primarily carried out at the village medical centres. All individuals were older than 17 years and had to have at least one parent from the Mylopotamos area. www.helic.org **The data may not be used for population genetics analyses**

  Study EGAS00001000687

• Measurement of SARS-CoV-2 variants fraction in infected alveolar cells

  With the continuous emergence of highly transmissible SARS-CoV-2 variants, the comparison of their infectivity has become a critical issue for public health. However, a direct assessment of the viral characteristic has been challenging due to the lack of appropriate experimental models and efficient methods. Here, we conducted full-length transcriptome sequencing of single human alveolar cells infected by multiple SARS-CoV-2 variants, including GR (B.1.1.119), Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (BA.1). Using unique mutations of each VOC, we calculated the fraction of VOCs in infected cells.

  Study EGAS00001006730

• Single-cell Transcriptome Profiling of Treatment-naïve and Post-treatment Colorectal Cancer: Insights into Putative Mechanisms of Chemoresistance

  Drug resistance remains a major clinical challenge in the treatment of colorectal cancer (CRC) with conventional chemotherapy. Investigation of cancer cells and tumor microenvironment (TME) following chemotherapy is critical for unraveling the mechanisms of resistance. In this study, we analyzed scRNA-Seq data from 56 CRCs including treatment-naïve tumors (25 microsatellite stable (MSS) tumors and 7 tumors with microsatellite instability (MSI)); and tumors treated with standard chemotherapy with the known response status (18 responders and 6 progressors). We observed in treatment-naïve MSS CRC that right-sided tumors are more immunogenic with higher numbers of B cells and CD8+ T memory effector cells than left-sided tumors. MSI CRC were even more immunogenic then MSS CRC and were characterized by elevated Tregs in their TME. In the post-treatment CRC there was a high prevalence of dendritic cells (DC) in the TME in the response group. The DC-derived signature was associated with better survival in a large CRC cohort from the TCGA. We also observed two fibroblast subtypes in CRC, one of which was enriched in progressors and was associated with poor survival in a CRC-TCGA cohort. Progressors also showed elevated exhausted CD8+ T memory cells and monocytes suggesting a pro-inflammatory TME. In tumor cells in progressor group we identified specific expression of chemo-protective markers MTRNR2L1 and CDX1; and their co-expression with stemness-related marker CD24. In summary, scRNA-Seq provides a valuable information for the discovery of prognostic markers, and reveals distinct features of CRC based on location, metastasis status, MSI status and treatment response status.

  Study EGAS50000000830

• Leptomeningeal melanocytic tumour

  This is the first whole exome sequencing analysis of a primary meningeal melanocytic tumour (MMT) alongside the patients germline. Here we report the CRAM files from the tumour and germline.

  Dataset EGAD00001003750