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• Preferential infiltration of unique Vγ9Jγ2‐Vδ2 T cells into glioblastoma multiforme

  Glioblastoma multiforme (GBM) is clinically highly aggressive as a result of evolutionary dynamics induced by cross-talk between cancer cells and a heterogeneous group of immune cells in tumor microenvironment. The brain harbors limited numbers of immune cells with few lymphocytes and macrophages; thus, innate‐like lymphocytes, such as γδ T cells, have important roles in antitumor immunity. Here, we characterized GBM‐infiltrating γδ T cells, which may have roles in regulating the GBM tumor microenvironment and cancer cell gene expression. V(D)J repertoires of tumor‐infiltrating and blood‐circulating γδ T cells from four patients were analyzed by next-generation sequencing-based T-cell receptor (TCR) sequencing in addition to mutation and immune profiles in four GBM cases. In all tumor tissues, abundant innate and effector/memory lymphocytes were detected, accompanied by large numbers of tumor‐associated macrophages and closely located tumor‐infiltrating γδ T cells, which appear to have anti-tumor activity. The immune-related gene expression analysis using the TCGA database showed that the signature gene expression extent of γδ T cells were more associated with those of cytotoxic T and Th1 cells and M1 macrophages than those of Th2 cells and M2 macrophages. Although the most abundant γδ T cells were Vγ9Vδ2 T cells in both tumor tissues and blood, the repertoire of intratumoral Vγ9Vδ2 T cells was distinct from that of peripheral blood Vγ9Vδ2 T cells and was dominated by Vγ9Jγ2 sequences, not by canonical Vγ9JγP sequences that are mostly commonly found in blood γδ T cells. Collectively, unique GBM‐specific TCR clonotypes were identified by comparing TCR repertoires of peripheral blood and intra‐tumoral γδ T cells. These findings will be helpful for the elucidation of tumor-specific antigens and development of anticancer immunotherapies using tumor-infiltrating γδ T cells.

  Dataset EGAD00001004862

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006309

• Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics

  Single-cell transcriptomics (scRNA-seq) has enabled the characterization of cell state heterogeneity and recapitulation of differentiation trajectories. However, since proteins are the main functional entities in cells, the exclusive use of mRNA measurements comes at the risk of missing important biological information. Here we leverage recent technological advances in single-cell proteomics by Mass Spectrometry (scp-MS) to generate the first scp-MS dataset of an in vivo differentiation hierarchy encompassing over 2,500 human CD34+ hematopoietic stem and progenitor cells. Through integration with scRNA-seq, we identify proteins that are important for stem cell quiescence, which were not indicated by their mRNA transcripts, and demonstrate functional expression covariance during differentiation that is only detectable on protein level. Finally, we show that modeling translation dynamics can infer cell progression during differentiation and explain 45% more protein variation from mRNA than linear correlation. Our work serves as a framework for future single-cell multi-omics studies across biological systems.

  Study EGAS00001007930

• The genomic landscape of relapsed infant and childhood KMT2A-rearranged acute leukemia

  To study the mechanisms of relapse in KMT2A-rearranged (KMT2A-r) acute lymphoblastic (ALL) and acute myeloid leukemia (AML), we performed whole-genome and exome sequencing of infants and children with relapsed ALL/AML (n=36), and longitudinal deep-sequencing of 257 samples in 30 patients. Somatic alterations in drug-response genes, most commonly in TP53 and IKZF1 (64%), were highly enriched in early relapse ALL (79%, 9-36 months after diagnosis), but rare in very early relapse ALL (<9 months, 9%). A marked chemotherapy-exposure signature was detected for mutations in early relapse ALL but not in very early ALL or AML relapse, in line with different mechanisms of relapse. Longitudinal analyses could track residual leukemia cells, clonal drug responses, and the upcoming relapse. These results highlight that KMT2A-r ALL and AML evade therapy differently and provide new insights into the mechanisms of relapse in this highly lethal form of pediatric acute leukemia.

  Study EGAS00001008197

• Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes

  DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N=190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P<1x10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions.

  Study EGAS00001007118

• The genetic history of the southern Andes from present-day Mapuche ancestry

  We generate genome-wide data from 64 participants from three Mapuche populations in Southern Chile: Pehuenche, Lafkenche, and Huilliche. Broadly, we describe three main ancestry blocks with a common origin, which characterize the Southern Cone, the Central Andes, and Amazonia. Within the Southern Cone, ancestors of the Mapuche lineages differentiated from those of the Far South during the Middle Holocene, and did not experience further migration waves from the north. We find that the deep genetic split between the Central and Southern Andes is followed by instances of gene flow, which may have accompanied the southward spread of cultural traits from the Central Andes, including crops and loanwords from Quechua into Mapudungun (the language of the Mapuche). Our findings add new perspectives on the genetic (pre)history of South America, from first settlement through to the present-day indigenous presence. Follow-up fieldwork took these results back to the indigenous communities to contextualize the genetic narrative alongside indigenous knowledge and perspectives.

  Study EGAS00001007200

• Immune landscape of oncohistone-mutant gliomas reveals diverse myeloid populations and tumor-promoting behavior

  Histone H3-mutant gliomas are deadly brain tumors characterized by a dysregulated epigenome and stalled differentiation. In contrast to the extensive datasets available on tumor cells, limited information exists on their tumor microenvironment (TME), including the immune infiltrate. Here, we characterize the TME of H3.3K27M and G34R/V-mutant gliomas, and multiple H3.3K27M mouse models, using transcriptomic and proteomic, including spatial single-cell approaches. Resolution of immune lineages indicates uniform high-infiltration of H3-mutant gliomas with diverse myeloid populations, high-level expression of immune checkpoints, and scarce lymphoid cells, findings uniformly reproduced in all H3.3K27M models tested. We show these myeloid populations communicate with H3-mutant cells mediating immunosuppression and sustaining tumor formation and maintenance. Dual inhibition of myeloid cells and immune checkpoints showed significant therapeutic benefit in pre-clinical syngeneic models. Our findings provide valuable characterization of the TME of oncohistone-mutant gliomas, and insights into means to modulate the myeloid infiltrate for the benefit of patients.

  Study EGAS00001007510

• Sensitive and Frequent Identification of High Avidity Neo-epitope Specific CD8 + T-cells in Immunotherapy-naïve Ovarian Cancer

  Immunotherapy directed against private tumor neo-antigens derived from non-synonymous somatic mutations is a promising strategy of personalized cancer immunotherapy. However, feasibility in low mutational load tumor types remains unknown. Comprehensive and deep analysis of circulating and tumor-infiltrating lymphocytes (TILs) for neo-epitope specific CD8 + T cells allowed prompt identification of oligoclonal and polyfunctional such cells from most immunotherapy-naïve patients with advanced epithelial ovarian cancer studied. Neo-epitope recognition was discordant between circulating T cells and TILs, and was more likely to be found among TILs, which displayed higher functionalavidity and unique TCRs with higher predicted affinity than their blood counterparts. Our results imply that identification of neo-epitope specific CD8 + T cells is achievable even in tumors with relatively low number of somatic mutations, and neo-epitope validation in TILs extends opportunities for mutanome-based personalized immunotherapies to such tumors.

  Study EGAS00001002803

• Disease specific alterations in the olfactory mucosa of patients with Alzheimer’s disease

  OOlfactory dysfunction manifests early in several neurodegenerative disorders. Olfaction is orchestrated by olfactory mucosal cells located in the upper nasal cavity. However, it is unclear how this tissue reflects key neurodegenerative features in Alzheimer’s disease. Here we report that Alzheimer´s disease olfactory mucosal cells secrete toxic amyloid-beta. We detail cell-type-specific gene expression patterns, unveiling 147 differentially expressed disease-associated genes compared to the cognitively healthy controls, and 5 distinct populations in globose basal cell -, myofibroblast-, and fibroblast/ stromal – like cells in vitro. Overall, coordinated alteration of RNA and protein metabolism, inflammatory processes and signal transduction were observed in multiple cell populations, suggesting a key role in pathophysiology. Our results demonstrate the potential of olfactory cell cultures in modelling Alzheimer´s disease. Moreover, for the first time we provide single cell data on olfactory mucosa in Alzheimer´s disease for investigating molecular and cellular mechanisms associated with the disease.

  Study EGAS00001006019

• ARHGAP11A Maintains Cortical Progenitor Identity Through RHOA–ROCK Signalling During Human Brain Development

  Mammalian brain development involves coordinated progenitor amplification, migration, and differentiation. Apical progenitors (APs) establish the ventricular zone (VZ) and are key determinants of brain size and complexity. Rho-family guanosine triphosphatases (Rho GTPases) regulate cytoskeletal dynamics and AP behaviour, but how specific Rho GTPase-activating proteins (Rho GAPs) influence progenitor identity and VZ architecture remains unclear. Using human forebrain organoids, we investigated the Rho GAP ARHGAP11A in human corticogenesis. CRISPR/Cas9-mediated ARHGAP11A knockout revealed its essential role in maintaining VZ integrity. Loss of ARHGAP11A impaired neuroepithelial organisation and randomised mitotic cleavage plane orientation via the RHOA–ROCK–actin axis. This led to premature AP delamination, AP depletion, and reduced cell density and glial numbers. Pharmacological inhibition of RHOA or ROCK rescued these defects, highlighting ARHGAP11A’s role in cytoskeletal remodelling to maintain cortical progenitors. Our findings establish ARHGAP11A as a critical regulator of AP identity and VZ integrity, with broad implications for human corticogenesis.

  Study EGAS00001008322

• Privacy Notice for the Account User

  Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-user-account

• Exome sequencing reveals pathogenic variants in known and novel candidate genes for severe sperm motility disorders

  STUDY QUESTION: What are the causative genetic variants in patients with male infertility due to severe sperm motility disorders? SUMMARY ANSWER: We identified high confidence disease-causing variants in multiple genes previously associated with severe sperm motility disorders in 9 out of 21 patients (43%). We also identified variants in novel candidate genes in 8 additional patients (38%). WHAT IS KNOWN ALREADY: Severe sperm motility disorders are a form of male infertility characterised by vital, but immotile sperm often in combination with a spectrum of structural abnormalities of the sperm flagellum. Examples of this spectrum of disorders include dysplasia of the fibrous sheath / multiple morphological abnormalities of the sperm flagella (DFS-MMAF) and severe forms of asthenozoospermia associated to non-specific structural defects. These disorders frequently recur in families and may include chronic respiratory disease. As such, genetic causes are suspected and many genes have recently been reported. Currently, depending on the clinical sub-categorisation, up to 50% of causality in patients with severe sperm motility disorders can be explained by pathogenic variants in at least 21 known genes. STUDY DESIGN, SIZE, DURATION: We performed exome sequencing in patients with severe sperm motility disorders from two different clinics, aiming to identify the underlying genetic defects and establishing a diagnostic yield in both. PARTICIPANTS/MATERIALS, SETTING, METHOD: Two groups of infertile men, one from Argentina (n= 9) and one from Australia (n=12), with clinically defined sperm motility disorders were included. All patients in the Argentine cohort were diagnosed with DFS-MMAF, based on transmission electron microscopy. Exome sequencing was performed in all 21 patients and variants with an allele frequency of <1% in the gnomAD population were prioritised and interpreted. MAIN RESULTS AND ROLE OF CHANCE: In 9/21 patients (43%), we identified pathogenic variants in known sperm motility disorder genes: CFAP43 (3 patients); CFAP44 (2 patients), QRICH2 (2 patients), DNAH1 (1 patient) and DNAH6 (1 patient). The diagnostic rate did not differ markedly between the Argentinian and the Australian cohort (44% and 42%, respectively). Furthermore, we identified patients with variants in the novel candidate sperm motility genes CFAP58, DNAH12, DRC1, MDC1, PACRG, SSPL2C and TPTE2. One patient presented with two possibly damaging variants in four candidate genes and it remains unclear which variants were responsible for the severe sperm motility defect in this patient. LIMITATIONS, REASONS FOR CAUTION: In this study, we described patients with potential bi-allelic variants in known and novel candidate genes for severe sperm motility disorders. Due to unavailability of parental DNA, we have not assessed de novo or maternally inherited dominant variants and could not phase the mutations to establish in all cases that the mutations occur on both alleles. WIDER IMPLICATIONS OF THE FINDINGS: Our results confirm an important role for five known genes for sperm motility and we demonstrate that exome sequencing is an effective method to diagnose patients with severe sperm motility defects (9/21 diagnosed; 43%). Furthermore, our analysis revealed seven novel candidate genes for severe sperm motility disorders. Genome-wide sequencing of additional patient cohorts and re-analysis of exome data of currently unsolved cases may reveal additional variants in these novel candidate genes.

  Study EGAS00001005018

• Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype

  The metabolic profile of dendritic cells (DCs) shapes their phenotype and functions. Carboxylestrase 1 (CES1) enzyme is highly expressed in mononuclear myeloid cells however its exact role in DCs is elusive. We used a CES1 inhibitor (WWL113) and genetic overexpression to explore the role of CES1 in DCs differentiation in inflammatory models. CES1 expression was analyzed during CD14+ monocytes differentiation to DCs (MoDCs) using quantitative PCR. CES1 Inhibitor (WWL113) was applied during MoDCs differentiation. Surface markers, secreted cytokines, lactic acid production, phagocytic and T cell polarization capacity were analyzed. Transcriptomic and metabolic profile were assessed with RNA-sequencing and mass spectrometry. Cellular respiration was assessed with seahorse respirometry. Transgenic mice were used to assess CES1 overexpression in DCs in inflammatory models. CES1 expression peaks early during MoDCs differentiation. Pharmacological inhibition of CES1 led to higher expression of CD209, CD86 and MHCII. WWL113 treated MoDCs secreted higher quantities of IL6, IL8, TNF and IL10 and demonstrated stronger phagocytic ability and higher capacity to polarize Th17 differentiation in autologous DCs-T cells co-culture model. Transcriptomic profiling revealed enrichment of multiple inflammatory and metabolic pathways. Functional metabolic analysis shows impaired maximal mitochondrial respiration capacity, increased lactate production and decreased intracellular amino acids and TCA intermediates. Transgenic human CES1 overexpression in murine DCs generated less inflammatory phenotype and increased resistance to T cell mediated colitis. In conclusion, CES1 inhibition directs DCs differentiation towards more inflammatory phenotype, that shows stronger phagocytic capacity and supports Th17 skewing. This is associated with disrupted mitochondrial respiration and amino acids depletion.

  Study EGAS50000000230

• A Single Cell Transcriptomic Analysis of Human Neocortical Development

  Defining the number, proportion, or lineage of distinct cell types in the developing human brain is an important goal of modern brain research. We produced single cell transcriptomic profiles for 40,000 cells at mid-gestation to define deep expression profiles corresponding to all known major cell types at this developmental period and compare this with bulk tissue profiles. We identified multiple transcription factors (TFs) and co-factors expressed in specific cell types, including multiple new cell-type-specific relationships, providing an unprecedented resource for understanding human neocortical development and evolution. This includes the first single-cell characterization of human subplate neurons and subtypes of developing glutamatergic and GABAergic neurons. We also used these data to deconvolute single cell regulatory networks that connect regulatory elements and transcriptional drivers to single cell gene expression programs in the developing CNS. We characterized major developmental trajectories that tie cell cycle progression with early cell fate decisions during early neurogenesis. Remarkably, we found that differentiation occurs on a transcriptomic continuum, so that differentiating cells not only express the few key TFs that drive cell fates, but express broad, mixed cell-type transcriptomes prior to telophase. Finally, we mapped neuropsychiatric disease genes to specific cell types, implicating dysregulation of specific cell types in ASD, ID, and epilepsy, as the mechanistic underpinnings of several neurodevelopmental disorders. Together these results provide an extensive catalog of cell types in human neocortex and extend our understanding of early cortical development, human brain evolution and the cellular basis of neuropsychiatric disease.

  Study phs001836

• Whole-genome and transcriptome versus panel sequencing in precision oncology: A translational-clinical comparison

  Precision oncology offers new cancer treatment options. While the use of whole-genome (WGS) and transcriptome (TS) sequencing remains often confined to specific clinical programs, molecular analysis with gene panels is more common clinical practice. Methods: Twenty patients with rare or advanced tumors sequenced by WGS/TS within the DKFZ/NCT/DKTK-MASTER program from 2015 to 2020 (MASTER 1) were additionally sequenced with the TSO500 DNA and TST170 RNA Assay by Illumina. Original Molecular Tumor Board (MTB) therapy recommendations (TR) were juxtaposed with TR from NGS panel data analysis (comparison 1). To mitigate temporal differences between the two sequencings, WGS/TS was bioinformatically reanalyzed (MASTER 2), and new TR were again compared (comparison 2). Results: In comparison 1, 47.1% of the MASTER 1’s TR and 62.8% of the panel’s TR were identical, as were 45.9% of the TR of MASTER 2 and 54.9% of the panel in comparison 2. In both MASTER 1 and MASTER 2, 26.5% and 36.1% of TR, respectively, relied on Biomarkers (BM) which were not covered by the panel. Eight of the ten MTB-derived therapy implementations were also supported in the panel, the two remaining ones being based on BM absent from the panel. Conclusions: About half of the TR in WGS/TS and panel sequencing were identical. Around a third of TR issued by WGS/TS were based on BM which are not covered by the panel, leading to therapy implementations. The presented data underscores the clinical value of comprehensive molecular analyses in individuals with advanced cancers.

  Study EGAS50000000431

• Analysis of recent shared ancestry in a familial cohort identifies coding and noncoding autism spectrum disorder variants

  Autism spectrum disorder (ASD) is a collection of neurodevelopmental disorders characterized by deficits in social communication and restricted, repetitive patterns of behavior or interests. ASD is highly heritable, but genetically and phenotypically heterogeneous, reducing the power to identify causative genes. We performed whole genome sequencing (WGS) in an ASD cohort of 68 individuals from 22 families enriched for recent shared ancestry. We identified an average of 3.07 million variants per genome, of which an average of 112,512 were rare. We mapped runs of homozygosity (ROHs) in affected individuals and found an average genomic homozygosity of 9.65%, consistent with expectations for multiple generations of consanguineous unions. We identified potentially pathogenic rare exonic or splice site variants in 12 known (including KMT2C, SCN1A, SPTBN1, SYNE1, ZNF292) and 12 candidate (including CHD5, GRB10, PPP1R13B) ASD genes. Furthermore, we annotated noncoding variants in ROHs with brain-specific regulatory elements and identified putative disease-causing variants within brain-specific promoters and enhancers for 5 known ASD and neurodevelopmental disease genes (ACTG1, AUTS2, CTNND2, CNTNAP4, SPTBN4). We also identified copy number variants in two known ASD and neurodevelopmental disease loci in two affected individuals. In total we identified potentially etiological variants in known ASD or neurodevelopmental disease genes for ~61% (14/23) of affected individuals. We combined WGS with homozygosity mapping and regulatory element annotations to identify candidate ASD variants. Our analyses add to the growing number of ASD genes and variants and emphasize the importance of leveraging recent shared ancestry to map disease variants in complex neurodevelopmental disorders.

  Study EGAS00001006058

• Characterization of a human iPSC-derived islet differentiation model

  To explore the contribution of islet development to T2D pathogenesis, we characterised the transcriptomes of 3 human iPSC lines (from independent donors) differentiated along the islet development lineage. Whole transcriptome RNA-seq was performed at 7 developmental stages: definitive endoderm, primitive gut tube, posterior foregut (PF), pancreatic endoderm, endocrine progenitors, endocrine-like cells, and beta-like cells (BLC). Differentially-expressed (ΔExp) genes were assigned to the stage in which they were most upregulated (versus baseline iPSC profile), and used to assess the enrichment of T2D GWAS genes, as well as to predict the upstream transcription factors at each developmental stage.We found 9409 ΔExp genes across all stages, including known markers of islet development (NEUROG3, INS). Genes ΔExp in the most-differentiated (BLC) stage were significantly enriched for genes within the 99% credible sets of T2D GWAS loci. Despite this enrichment in BLC only, over 70% of genes mapping within the credible sets were ΔExp before this stage, highlighting the relevance of key T2D GWAS genes in islet development: e.g. expression of TCF7L2 peaked during the PF stage (log2FC=1.2; q=8.5×10-10). REST and LMNA are also highlighted by the analyses as having a potential function in islet development, considering their pattern of expression and those of the genes they regulate. Transcriptomic signatures derived from this iPSC differentiation model highlight T2D-associated GWAS loci, monogenic diabetes genes and potential master regulators of gene networks with plausible function in islet development. All these provide clues for developmental mechanisms contributing to T2D diabetes pathology.

  Study EGAS00001002721

• CentralAfricanCMC_Pemberton

  The CentralAfricanCMC_Pemberton dataset encompasses 153,798 SNPs from the Illumina Cardio-MetaboChip (Voight et al. 2012) genotyped in 406 individuals from 19 Central African Populations from Gabon, Cameroon, Centralafrican Republic and Uganda). Individual phenotypic and cultural information at the individual level for this data set encompass gender, lifestyle (hunter-gatherer or farmer), and, when available, stature phenotype (standing height in cm, sitting-height in cm, and weight in kg). Other cultural, linguistic, and geographical location information about the sampled populations can be found in Pemberton et al. , Human Genetics, 2018 (https://doi.org/10.1007/s00439-018-1902-3).This dataset can only be accessed and used for non-commercial research purposes with a finality complying with the informed consent provided by Central African donors for the study of human evolutionary history only.

  Dataset EGAD00010001584

• Lipomatous tumors with 12q amplification

  The project concerns whole genome sequencing (short-read and long-read) and RNA-sequencing of lipomatous tumors with 12q-amplification. A subset of lipomatous tumors is driven by amplification of genes mapping to chromosome arm 12q, including the MDM2 gene. The goals of the study were to compare expression levels of genes mapping to 12q in tumors with amplification in rod-shaped or circularized chromosomes as well as to assess and compare the structural variants in those tumors. In total, 20 samples were analyzed, and the data were correlated with genomic data on bulk and single cell DNA from the same tumors. The fastq files from the tumors were uploaded to EGA.

  Dataset EGAD50000000087

• Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE)

  The STRRIDE study is the combination of three interventional trials to evaluate dose and intensity of physical activity on cardiometabolic health. The three component studies are Peripheral Effects of Exercise on Cardiovascular Health (STRRIDE I, ClinicalTrials.gov Identifier: NCT00200993), Effects of Resistence and Aerobic Exercise on Cardiovascular Health (STRRIDE II, ClinicalTrials.gov Identifier: NCT00275145) and Exercise Dose-Response Effects in Prediabetes (STRRIDE-PD, ClinicalTrials.gov Identifier: NCT00962962).

  Study phs001855

• A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy

  In this prospective study, custom genome-wide exome and whole transcriptome sequencing (NGS) was used to identify genomic events and associated expression changes in advanced Small Cell Lung Cancer (SCLC) and attempt to prescribe systemic therapy based on the results. Tumor/normal pairs were sequenced from 12 patients with advanced SCLC for this study.

  Study phs001366

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• Mutational signatures in normal tissues of patients treated with clinical stage G-quadruplex binder CX5461

  Drug induced photoreactions following exposure to UVA have been documented for several therapeutic compound classes, including psoralens and fluoroquinolones. We used deep (~80X) whole genome sequencing to examine the mutagenic spectrum of CX5461, quinolone-derived small molecule, in normal tissues of cancer patients undergoing treatment. We compared the distribution of somatic base substitutions and short indels from skin biopsies taken from non-sun exposed areas pre and post CX5461 exposure of patients. To further characterize the mutational pattern of CX5461 photoreactivity, we compared mutational profiles of human retinal pigment epithelial cells exposed to UVA, CX5461, or a combination of both UV and CX5461.

  Dataset EGAD50000001640

• Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

  This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

  Dataset EGAD50000001557

• scRNAseq - Notch Signaling Maintains a Progenitor-Like Subclass of Hepatocellular Carcinoma

  To clarify the cellular composition and the mechanism of efficacy following JAG1/NOTCH2 inhibition, we performed single-cell sequencing of LIV78 tumors isolated from control animals or following inhibition of JAG1 or NOTCH2. The results suggest that sensitive tumors consist of heterogeneous populations of cells in distinct transcriptional states and that Notch signals emerge from ligand-receptor co-expressing cells.

  Study EGAS50000000517

• Data access to Small RNA-Seq of MicroRNA's in Tear EV's of Ushers Syndrome patients

  Via this DAC you can get access to Small RNA-Seq dataset of MicroRNA's in Tear EV's of Ushers Syndrome patients. The study involved genetically confirmed USH1B patients and their healthy relatives, with additional fibroblast samples from Spanish collaborators, to ensure a robust comparison of small non-coding RNAs (sncRNAs). Tear and blood samples were collected using non-invasive methods, and extracellular vesicles (EVs) were isolated from both tears and hiPSC-derived retinal pigment epithelium (RPE) cells. RNA was extracted from these EVs and assessed for quality before preparing libraries using the TruSeq Small RNA Library Preparation Kit. Sequencing was performed on the Illumina NextSeq 2000 platform, generating data for comparative analysis of sncRNA profiles between patients and controls.

  Dac EGAC50000000711

• Transcriptomic profiling of T cells following ABHD11 inhibition

  This dataset contains paired-end RNA sequencing data from human T cells treated with ML226, a selective ABHD11 inhibitor, and matched vehicle controls. The experiment was designed to investigate the role of ABHD11 in sterol metabolism and its impact on T cell effector function and autoimmunity. Samples were collected across biological replicates following 24-hour treatment, and RNA was extracted for high-throughput sequencing. Sequencing was performed using an Illumina platform. The dataset supports analysis of differentially expressed genes, alternative transcript usage, and pathway-level effects of ABHD11 inhibition. This dataset is part of the study titled "ABHD11 inhibition drives sterol metabolism to modulate T cell effector function and alleviate autoimmunity".

  Dataset EGAD50000001845

• Differential expression in clear cell renal cell carcinoma

  To investigate the levels of gene expression in clear cell renal cell carcinoma (ccRCC), we performed an RNA-seq analysis in 786-O, A-498, UM-RC-2 clear cell renal carcinoma cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq files and csv files with the differential expression results. Differential expression was calculated by the RNAflow pipeline (DEseq2), and log fold changes are calculated with respect to the normal cell line (HK-2), with separate results between normoxic and hypoxic datasets.

  Dataset EGAD50000001883

• SCANDARE HNSCC 3' Tag RNA-seq

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 264 FFPE samples at baseline from 90 HNSCC patients using 3'-tag RNA-seq technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001655

• SCANDARE TNBC WES data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 247 frozen samples at baseline and 138 germline DNA from 139 TNBC patients using WES technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001661

• SCANDARE TNBC WGS data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 108 FFPE samples at baseline and 108 germline DNA from 108 TNBC patients using WGS technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001662

• Summarized somatic variant calls from CMMRD-associated high-grade gliomas

  This dataset contains summarized somatic variant call data derived from paired tumor–blood whole-exome sequencing of human samples. Access to the dataset is controlled and granted only upon submission and approval of a formal data access request. Requests are reviewed by the Data Access Committee led by the Principal Investigator to ensure compliance with applicable legal, ethical, and data protection requirements. Users must not attempt to re-identify study participants and must comply with all relevant confidentiality and data protection regulations. In accordance with local legal and ethical requirements, individual-level raw sequencing data are not shared.

  Dataset EGAD50000002180

• scMethylation data of 5 regionally sampled GBM tissue for 2 patients

  This dataset contains snRNA-seq data of 5 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed in an unbiased manner without any sorting procedure. Nuclei dissociation was performed following the nuclei isolation for single-cell ATAC-seq (10x Genomics; CG000169) with matched peri-tumoral and tumor core samples. Subsequent single-cell methylation sample preparation followed Scale Biosciences single-cell methylation kit protocol v1.0. mplification adaptors through ligation and adding a second barcode though indexed PCR reaction following Scale Biosciences single-cell methylation kit protocol v1.0. We employed the TWIST human methylome panel for targeted enrichment of informative methylation sites.

  Dataset EGAD50000001837

• SCANDARE TNBC shallow WGS data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 251 frozen samples at baseline from 143 TNBC patients using shallow WGS technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001849

• ICARUS-LUNG01 dataset

  A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

  Dataset EGAD50000001014

• Personalized IGM, IGK, IGL V(D)J repertoire sequencing of four Influenza A exposed individuals

  Peripheral blood mononuclear cells were used to produce paired, full-length IGM, IGK and IGL V(D)J libraries from HA-binding single memory B cells using the ISCAPE (Individualized Single Cell Analysis of Paired Expressed antigen receptors) technique. Locus-specific multiplexed nested PCR with primer sets targeting the 5’ UTR/leader and 3’ constant region was performed before well and plate indexing and paired chain sequencing with an Illumina MiSeq instrument. Expressed total IGM, IGK and IGL V(D)J libraries from each donor were acquired and analyzed to define personalized IG allele content. The fastq file names include the donor and target for expressed IGM, IGK or IGL V(D)J libraries.

  Dataset EGAD50000002018

• RNA-seq of iPSC-derived oligodendrocytes of individuals with and without t(1;11) translocation

  This dataset contains high-throughput RNA-sequencing of 14 samples, each sample comprising oligodendrocytes derived from human induced pluripotent stem cells, from individuals with and without a balanced t(1;11) translocation which substantially increases risk of major mental illness. 5 samples derive from 2 control individuals, and 9 samples from 3 individuals carrying the translocation. Libraries were prepared from each total-RNA sample using the TruSeq Stranded Total RNA with Ribo-Zero kit. Libraries were then sequenced using the NextSeq 500/550 High-Output v2 (150 cycle) Kit on the NextSeq 550 platform. Raw paired-end sequencing data is stored in two FASTQ files per sample.

  Dataset EGAD00001006341

• Reconstruction of complex rearrangement patterns causing the initiation of clear cell renal cell carcinoma.

  The genomic hallmark of clear cell renal cell carcinoma is the loss of the short arm of chromosome three. This appears to be the earliest genomic event in the formation of these cancers. Often chromosome 3 is lost at the same time as part of chromosome 5 is duplicated via an unbalanced translocation, often with features consistent with focal chromothripsis. In this study, we sought to reconstruct the chromothriptic event that underlies the initiation of kidney cancer. We used long read sequencing (promethION, Oxford Nanopore Technologies) of patient tumour-derived DNA to elucidate how a single cell division error can generate cancer genome complexity.

  Dataset EGAD00001005495

• ATAC-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015509

• scRNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015510

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 3 Diamond-Blackfan anemia cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 3 Diamond-Blackfan anemia (DBA) cases. This data set, comprising 3 DBA cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 4 Shwachman-Diamond syndrome (SDS) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition, this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002661

• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• sWGS on cfDNA and matching tumor DNA in pediatric cancer

  This dataset contains shallow whole genome sequencing data from paired cfDNA - tumor DNA samples of various pediatric cancer entities (total 215 samples). Files are provided in fastq format. Samples were sequenced on an Ion Proton sequencer (Thermo Fisher Scientific) or a Hiseq3000 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Dataset EGAD00001007508

• Detection of cancer cell transcriptomes

  Single cell transcriptomes, generated using chromium 10X 3' sequencing, for two tumour types (AT/RT, and Ewing's sarcoma). For each individual, tumour and normal whole genome sequencing was also obtained using Illumina short read sequencing to an average depth of 30X. These data were used to validate the accuracy of a method for identifying cancer cell transcriptomes based on the allelic shift produced by copy number changes.

  Dataset EGAD00001009005

• The BEACCON study: tumour sequencing

  This dataset consists of paired-end DNA sequencing (whole exome and targeted-capture) of tumours for the BEACCON study. There are 240 unique samples consisting of 92 matched tumour-germline pairs and 56 unmatched tumours totalling 148 patients. There are 33 paired and 6 unpaired tumours sequenced using the Agilent SureSelect All Human Exon v6 libraries, 1 paired and 8 unpaired tumours sequenced using Agilent SureSelect All Human Exon v7 libraries and 48 paired and 3 unpaired tumours sequenced using Twist Bioscience Comprehensive Human Exome v1 libraries totalling 176 whole exome samples. There are 3 paired and 58 unpaired tumours sequenced using a custom Agilent SureSelectXT library totalling 64 targeted capture samples.

  Dataset EGAD00001009299

• Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild type primary glioblastoma

  We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.

  Dataset EGAD00001010156

• MPM cell lines

  RNA-sequencing data for 12 MPM cell lines treated with 0.1% DMSO or 1 µM palbociclib for 9-10 days. Experiment was performed in duplicates for sensitive cells (MPM08, MPM21, MPM38, MPM57, MPM59, Meso11, Meso13, Meso34 and Meso56) and only once for resistant cells (MPM31, MPM34 and MPM36) except for Meso11 which was done in triplicates. For Meso11, Meso13, Meso34 and Meso56, a drug washout of 48 hours was also performed. 4 MPM cell lines (MPM31, MPM34, MPM59 and MPM66) were also analyzed in untreated condition. 2 FASTQ files for each sample (n=56) (paired)

  Dataset EGAD00001008741

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 4 Shwachman-Diamond syndrome cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 4 Shwachman-Diamond syndrome (SDS) cases. This data set, comprising 4 SDS cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 3 Diamond-Blackfan anemia (DBA) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002660

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Dataset EGAD00001007978

• Identification of differentially expressed protein-coding genes in HCC and adjacent non-cancerous tissues

  Twenty samples were collected in pairs, i.e., HCC tissue and adjacent non-cancerous tissue. The collected tissue samples were stored in liquid nitrogen. First, 50 mg of tissue was lysed in TRIzol (Invitrogen) to extract RNA following the manufacturer’s instructions. Next, ribosomal RNA was depleted using a RiboZero Gold kit (Epicentre Bio-technologies). RNA integrity was assessed with an Agilent Bioanalyzer 2100. An RNA-Seq library was generated with the rRNA-depleted samples using an Illumina standard RNA Sample Prep kit according to the manufacturer’s instructions. The library was subsequently sequenced on an Illumina HiSeq2500 as 125-bp paired-ends with approximately 300-bp size selection.

  Dataset EGAD00001003397