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• An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

  As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we developed and validated a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of RNA-Seq to whole genome and exome sequencing revealed that as a standalone assay, RNA-Seq offered the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data were used to develop a novel risk score which, when combined with molecular risk guidelines, allowed for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identified a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase (PTK2), demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.

  Dataset EGAD00001006701

• Myeloid cell programming in patients with non-medullary thyroid carcinoma

  This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

  Dataset EGAD00001008108

• Dataset for the Pearl study

  Biomarkers to identify patients without benefit from adding everolimus to endocrine treatment in metastatic breast cancer (MBC) are needed. We report the results of the Pearl trial conducted in five Belgian centers assessing 18F-FDG-PET/CT non-response (n=45) and ctDNA detection (n=46) after 14 days of exemestane-everolimus (EXE-EVE) to identify MBC patients who will not benefit. Metabolic non-response rate was 66.6%. Median PFS in non-responding patients (using as cut-off 25% for SUVmax decrease) was 3.1 months compared to 6.0 months in those showing response (HR: 0.77, 95% CI: 0.40-1.50, p=0.44). Difference was significant when using a “post-hoc” cut-off of 15% (PFS 2.2 months vs 6.4 months). ctDNA detection at D14 was associated with PFS: 2.1 months vs 5.0 months (HR-2.5, 95% CI: 1.3-5.0, p=0.012). Detection of ctDNA and/or the absence of 18F-FDG-PET/CT response after 14 days of EXE-EVE identifies patients with a low probability of benefiting from treatment. Independent validation is needed.

  Dataset EGAD00001007979

• Sequencing component for the whole genome methylation analysis in PBMCs and cell subsets (pilot study)

  DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

  Dataset EGAD00001000394

• WGS of MPNSTs and ANNUBPs

  Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are highly aggressive soft-tissue sarcomas with a poor prognosis and a lack of therapeutic options. In this study, we analyse the whole genomes of 20 MPNSTs and 7 ANNUBPs to find recurrent genomic alterations that can help us better understand the biology of MPNSTs. Merging this data with another public dataset, we are able to identify three genomic MPNST subgroups with distinct biological and clinicopathological features that can inform management and precision treatments. Published in "Identification of Malignant Peripheral Nerve Sheath Tumor (MPNST) subtypes with distinct genomic identities."

  Study EGAS50000001734

• Discordant_Monozygotic_Twins_ALS(Transcriptomics)

  Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by motor neuron degeneration. Despite known genetic contributions to both familial and sporadic ALS cases, much of ALS heritability remains unexplained, suggesting the involvement of other genetic and epigenetic factors. To address this gap, we used a comprehensive multi-omics approach, in a pair of Italian monozygotic twins discordant for ALS, integrating DNA methylation, transcriptomics, and whole exome sequencing (WES). Here we share transcriptomic data derived from bulk RNA-seq on RNA extracted from PBMCs of the twin pair. This analysis revealed distinct transcriptomic profiles underlying the discordant disease phenotypes.

  Study EGAS50000000909

• Pediatric CNS tumor classification by DNA-methylation dataset

  In this study nanopore sequencing was applied to obtain sparse DNA methylation profiles from pediatric CNS tumor samples. A neural network was used to classify the tumor based on the obtained methylation profile.

  Dataset EGAD00010002599

• Exceptional Outcomes in a Phase Ib Study Combining PARP and MEK Inhibition, With or Without Anti-PD-L1, for BRCA-Wildtype Platinum-Sensitive Recurrent Ovarian Cancer

  To evaluate regimens combining PARP and MEK inhibition, with or without PD-L1 inhibition, for BRCA-wildtype platinum-sensitive recurrent ovarian cancer (PSROC).

  Study EGAS00001007496

• Extracellular RNA Profiling of Serum, Plasma, and Urine of Healthy Subjects

  This study was conducted to generate a reference dataset of extracellular RNA (exRNA) from standard human biofluids. Small RNA-seq data was obtained from plasma, serum, and urine of healthy subjects.

  Study phs003054

• Optimized Polyepitope Neoantigen DNA Vaccines Elicit Neoantigen-Specific Immune Responses in Preclinical Models and in Clinical Translation

  A patient with Lynch syndrome and a neuroendocrine tumor sequenced with exome, whole genome, and bulk RNAseq. Sequence data was used to create a personalized cancer vaccine.

  Study phs002342