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• Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

  In this study, we demonstrate that aberrant expression of SLAMF6 on acute myeloid leukemia (AML) cells serves as a novel immune escape mechanism that can be inhibited by antibodies against the SLAMF6 dimerization site. This constitutes a novel mechanism of checkpoint inhibition, which paves the way for immunotherapy in AML and other SLAMF6-expressing cancers. This study utilizes single cell sequencing data from the AML cell line HNT-34 co-cultured with normal T cells, with and without antibody targeting SLAMF6, as well as single cell data of 38 primary AML samples.

  Study EGAS50000001085

• Spatial predictors of response to immunotherapy in microsatellite stable metastatic colorectal cancer

  Microsatellite stable (MSS) colorectal cancers (CRC) are largely unresponsive to immune checkpoint inhibition (ICI), prompting investigation into strategies to enhance sensitivity. The MAYA trial, which utilized temozolomide (TMZ) in MGMT-silenced MSS mCRC, hypothesized that TMZ-induced hypermutation could sensitize tumors to ICI. This phase II trial met its primary endpoint, demonstrating durable clinical responses with TMZ combined with ipilimumab and nivolumab. To elucidate factors in uencing response heterogeneity, we conducted multi-omic spatial pro ling of samples from patients who participated in the MAYA trial, including baseline and on-treatment tissue and blood specimens. While increased neoantigen load following TMZ exposure did not consistently predict for deep responses, spatial profiling revealed key determinants. Lymphocyte proportions, particularly CD8+KI67+ cells, within stromal and tumor compartments, along with macrophage composition (CD68+CD163+ cells) at the tumor-stromal interface, were predictive of response. Treatment pressures dynamically altered the tumor microenvironment composition and activated peripheral immune cells. This study is the first to identify spatial predictors of response to this promising novel treatment approach for MSS CRC.

  Dataset EGAD50000002244

• TSO500 STJAN33, BRAF mutated CUP

  The data set contains FASTQ files (filetype) of a NEXTSEQ550DX run (instrument). De FASTQ files are from DNA and RNA sample. The Library prep is a NGS TSO500 library prep (Illumina) (technology). A Study to Examine the Clinical Value of Comprehensive Genomic Profiling Performed by Belgian NGS Laboratories: a Belgian Precision Study of the BSMO in Collaboration With the Cancer Centre (BALLETT) This 2-year study involves the consortium of 9 cooperating Belgian NGS laboratories and will enroll 936 metastatic or locally advanced cancer patients coming from 13 different Belgian hospitals and cancer centers. Upon inclusion, all cancer patients will be offered 'comprehensive genomic profiling' (CGP) using Illumina's TSO500 NGS panel. This targeted NGS panel of 523 genes allows for the detection of single nucleotide variants, small indels, copy number variations and fusions, as well as for the determination of the 'tumor mutational burden' (TMB) and the 'microsatellite-instability' status (MSI). Both the wet lab execution of the CGP as well as the biological and clinical classification of the variants will be performed in a fully standardized way among the 9 participating Belgian local NGS laboratories.

  Dataset EGAD50000000689

• Fecal microbiome of T2D patients undergoing semaglutide or empagliflozin treatment

  The gut microbiome has been shown to be affected by the use of many human-targeted medications, and the interaction can be bidirectional. This has been clearly demonstrated for type 2 diabetes medications that have been in clinical use for several decades. However, the bidirectional effects of novel type 2 diabetes drugs semaglutide, empagliflozin, and the gut microbiome have yet to be clearly described. We investigated the effect of semaglutide and empagliflozin initiation on the gut microbiome of type 2 diabetes patients. In addition, we analyzed whether the pre-treatment gut microbiome can predict the treatment efficacy. Twenty subjects (10 women and 10 men) were enrolled in the study between November 2019 and January 2023 from the University of Tartu Hospital, Tartu, Estonia. All participants had been diagnosed with type 2 diabetes. The study group taking semaglutide included 6 women and 4 men, and the group prescribed empagliflozin included 4 women and 6 men. Gut microbiome fecal samples donated at four timepoints (Baseline, Month 1, Month 3; Month 12) were studied using 16S ribosomal RNA gene sequencing and analysis.

  Dataset EGAD50000000756

• Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease

  Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. We now define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. We leverage the insulin response heterogeneity and use transcriptomics and proteomics to identify molecular pathways of specific nutrient responsiveness. Surprisingly, we find robust insulin secretion to fatty acid stimulus in ~8% of donors, challenging the idea that fat has negligible effects on insulin release. Distinct islet proteomes with differences in metabolic signalling networks convey this hyper-responsiveness to fat relative to carbohydrate. By comparing human islets to human embryonic stem cell-derived islet clusters, we show that, unlike glucose-responsiveness, fat hyper-responsiveness is equivalent and may be a hallmark of functionally immature cells. Our study represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people’s islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition.

  Dataset EGAD50000000519

• RNA sequencing data of pediatric T-cell acute lymphoblastic leukemia

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy accounting for approximately 15–25% of pediatric and adult ALL cases. Despite significant therapeutic improvements over the last decade, the prognosis of T-ALL remains less favorable than that of B-ALL, with 5-year EFS and OS of around 76–82% and 80–88%, respectively, depending on the treatment protocol used. T-ALL patients often suffer from failure of induction therapy or early relapse, which is associated with a dismal prognosis. Approximately 10–15% of T-ALL patients experience relapse, and survival after relapse is poor.

  Study EGAS50000001800

• Whole genome sequencing in 1038 index cases reveals novel causative genes in pulmonary arterial hypertension

  Pulmonary arterial hypertension (PAH) is a rare disorder with a poor prognosis. Deleterious variation within genes encoding components of the transforming growth factor-ß pathway underlie the majority of heritable forms of PAH. Identifying the missing genetic contribution is challenging, even with genes of large effect size, since it likely involves mutations in genes confined to small numbers of PAH cases. In this study, we performed whole genome sequencing, comparing 1038 PAH index cases to 6385 subjects with other rare diseases. Rare variant analysis identified mutations in novel causal genes, namely ATP13A3, AQP1 and SOX17, and provided independent validation of a critical role for GDF2 in PAH. We detected mutations predicted to be disruptive of function in most, but not all, previously reported PAH genes. Taken together these findings provide new insights into the molecular basis of PAH, and support a central role for endothelial dysregulation in disease pathogenesis.

  Dataset EGAD00001003423

• Raw DNA and RNA data from breast cancer organoids, control samples and biopsies

  Whole genome sequencing data for primary tumors, matching control material from blood and their corresponding organoid. Whole transcriptome data for organoids.

  Dataset EGAD00001003751

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004193