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• PROMETEO

  The SOLTI-1503 PROMETEO trial was a single-arm, preoperative, window-of-opportunity phase II study conducted at four sites in Spain between December 2018 and February 2022. It enrolled female patients with operable HER2-negative breast cancer (triple-negative or Luminal B-like) and residual disease after neoadjuvant chemotherapy. Tumor biopsies were collected at five time points (baseline, post-NAC screening, C2D1, C3D1, and surgery) for translational research. This dataset includes raw paired-end RNA sequencing data (~110M reads per library) generated from the 113 biopy samples, archived in FASTQ format.

  Study EGAS50000001499

• scRNA-seq using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data for 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert). Dissociated cells from each tumor sample have been sorted to isolate live cells from the 3 compartments: tumor, immune and stromal. Each of the compartments has been analyzed separately by scRNAseq, excluding some desert tumors for which cells from the stromal and immune compartments have been pooled. Sequencing was performed using 10X Genomics Chromium Single Cell platform (v2 Chemistry).

  Dataset EGAD00001006974

• NOTCH-mutations drive immune-escape mechanisms in B cell malignancies

  Here we provide access to MCL expression data that were used for interrogating the molecular functions of NOTCH1 and NOTCH2, which are two of the most commonly mutated genes in CLL and MCL and associated with a poor clinical outcome. The mechanisms underlying how NOTCH1 contributes to disease progression, resistance to treatment and Richter’s transformation remain largely unknown. The main goal of this study is to compare the gene expression profile of primary MCL cells transduced with the intracellular part of NOTCH1 or NOTCH2 lacking of the PEST domain vs cells transduced with an empty vector.

  Study EGAS00001005793

• Transcriptomic and Clonal Characterization of T Cells in the Human Central Nervous System

  The cerebrospinal fluid (CSF) is thought to be a main route for immune surveillance in the central nervous system (CNS). Understanding the composition and state of CSF in healthy individuals may provide insight into perturbations present during neuroinflammation. Here, we have used single-cell RNA and TCR sequencing to profile CSF and peripheral blood mononuclear cells (PBMCs) from healthy individuals and patients with relapsing-remitting multiple sclerosis (MS), a chronic autoimmmune disease. In addition, with the goal of understanding how transcriptional artefacts are introduced in transcriptomics experiments, we have performed single-cell and TCR sequencing to profile PBMCs from a healthy individual that were processed with the same enzymatic digestion used for tissues (such as the brain) in the presence or absence of transcription inhibitors. 

  Study phs002222

• SEARCH for Diabetes in Youth Study - Genetic Risk Score

  Genetic risk scores (GRS) quantify polygenic disease risk into a single measure and can aid in disease classification. GRS studies have focused primarily on adult populations of recent European ancestry. We aimed to assess the utility of GRS in classification of diabetes type among racially/ethnically diverse youth in the United States. We used data from SEARCH baseline visits and follow up visits for which key data elements were available. 2260 participants are included. Phenotypic Data to be submitted here include: Self-reported sex, race and ethnicity Diabetes type determined by provider Etiologic diabetes type T1D (antibody positive, or antibody negative/missing and insulin sensitive) T2D (antibody negative and insulin resistant) Diabetes duration (years) Age at diagnosis (years) Measures from baseline, SEARCH 3 (follow-up) and SEARCH 4 (follow-up): Age Height Weight Waist circumference HbA1c Fasting/non-fasting glucose C-peptide Triglycerides HDL LDL Systolic Blood Pressure Diastolic Blood Pressure Measures from SEARCH 3 and 4:Arterial stiffness as characterized by PWVRetinopathy Measures from SEARCH 4 only: LV structure and diastolic function measurements from echocardiogram GAD autoantibody IAD autoantibody ZnT8 autoantibody We performed genotyping using the Illumina Multi-Ethnic Global Array (MEGA) array with 1,697,069 genotyped variants including 748,291 with minor allele frequency <0.01. Genotyping and preliminary quality control checks were performed at the Colorado Center for Personalized Medicine. After additional quality control, 2,238 samples and 900,743 variants remained for analyses. Samples genotyped on the MEGA array were categorized using SEARCH etiologic type and consisted of predominantly type 1 diabetes cases (n=2,051) but also those with other diabetes (n=133 type 2 diabetes, n=52 other diabetes including monogenic diabetes; genetic confirmation with either a genetic clinical test or test performed as an ancillary study to SEARCH). The median reported age at DNA collection was 11.2 years (interquartile range 7.6 – 14.1) with a minimum age of 1.9 years and maximum of 21.9 years. We used additional data genotyped on the Affymetrix 500K imputation scaffold chip with 239,279 genotyped variants. This cohort consisted of predominantly type 2 diabetes cases (n=417) but also those with type 1 (n=104), and other diabetes types (n=16). After additional quality control, 537 samples and 235,967 variants remained. The median reported age at collection was 11.2 years (quartile range 8.1 – 14.2) with a minimum of 2.0 years and a maximum of 21.1 years. About 100 type 2 diabetes cases were also genotyped using the MEGA chip to ensure concordance between the data sets and facilitate strand alignment between the two chips before genotypic imputation. The data sets had n=230,228 genotyped variants in common and concordance between the genotypes was high (mean correlation r2 for SNPs used in GRS=0.95). We used the 1000 Genomes reference panel to impute each data set separately, resulting in a total of 34.5M and 27.8M well-imputed variants (r2>0.8) for the MEGA and Affymetrix data sets respectively. We combined high quality imputed variants for analysis.

  Study phs002703

• 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

• Exome Sequencing of Multiple Localised Spiradenoma and Spiradenocarcinoma

  Tumor samples were microdissected from formalin-fixed, paraffin-embedded tissue and genomic DNA was extracted. DNA libraries were generated using xGen ssDNA & Low-Input DNA Library Preparation Kit (IDT). The libraries were enriched for the exome using xGen Exome Hyb Panel (IDT) and sequenced on DNBSEQ G400RS.

  Dataset EGAD50000000788

• Interruption of BTK Inhibitor Improves Response to SARS-CoV-2 Booster Vaccination in Patients with Chronic Lymphocytic Leukemia

  This study investigates the effect of booster SARS-CoV-2 vaccination and Bruton tyrosine kinase inhibitor (BTKi) interruption on antibody response to vaccination. Patients with chronic lymphocytic leukemia (CLL) are immunocompromised, at increased risk of infection, and have historically poor response to immunization. BTKi therapy is a standard treatment for CLL in frontline and salvage settings and further suppresses antibody vaccine responses.

  Study phs003319

• Karyotype Evolution in Response to Chemoradiotherapy and Upon Recurrence of Esophageal Adenocarcinomas

  The genome of esophageal adenocarcinoma (EAC) is highly unstable and might evolve over time. Here, we track karyotype evolution in EACs in response to treatment and upon recurrence through multi-region and longitudinal analysis. To this end, we introduce L-PAC, a bio-informatics technique that allows inference of absolute copy number aberrations (CNA) of low-purity samples by leveraging information of high-purity samples from the same cancer. Quantitative analysis of matched absolute CNAs reveals that the amount of karyotype evolution induced by chemoradiotherapy (CRT) is predictive for early recurrence and depends on the initial level of karyotype intra-tumor heterogeneity. We observe that CNAs acquired in response to CRT are partially reversed back to the initial state upon recurrence. CRT hence alters the fitness landscape to which tumors can adjust by adapting their karyotype. Together, our results indicate that karyotype plasticity contributes to therapy resistance of EACs.

  Study EGAS00001007711

• Bibliography Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue Here we expose in a yearly and cumulative manner, the publications, citations, publishers journals and impact factor of EGA related studies. Publications citing data stored at the EGA The studies that use EGA datasets are requested to cite the EGA into their bibliography. This fact allows for a faster spreading of the role and purpose of the EGA, being the availability of their studies for testability and reusability purposes. In order to track the studies we use the unique study accession, provided by the EGA when submitting a new study, and comprised of the keyword EGAS followed by 11 digits such as EGAS00000000001. We use the Europe PMC RESTful Web Service in order to query, and index studies where the EGAS accession was used. Below, you can find a chart showing the journal publishers of the studies citing data stored in the EGA being cited: Publications Citing Data Stored in the EGA pieChart('publishers-citations', 'https://stats.ega-archive.org/publishers/citations', 'Publishers') Number of publications citing data stored in the EGA by year Here, you can find a chart showing the number of publications citing data stored in the EGA by year. These publications could have deposit, or re-used the data. The study acession can be found in the publication. The default values are non-cumulative. You can see cumulative values by clicking "Cumulative". Number of Publications Citing Data Stored in the EGA by Year barChart('publications-by-year', 'https://stats.ega-archive.org/publications/year', ['Number of Publications by Year', 'Publications by Year']) Journal Impact Factor of Publications Citing Data Stored in the EGA Here, you can find a chart showing the journal impact factor of publications citing data stored in the EGA. We have used Scimago Journal Rank for this purpose. Low impact treshold was defined between 0.0 and 5.0 excluding; Medium impact treshold was defined between 5.0 and 10.0 excluding; High impact range was established from values equal to or higher than 10.0; Journal Impact Factor of Publications Citing Data Stored in the EGA pieChart('citations-publication-impact-factor', 'https://stats.ega-archive.org/citations/publication/impact/factor', 'Publication Impact Factor') Publications citing a publication containing a EGA study accession The publications, stating a EGA study accession in the bibliography, can be cited for testibility or reusability purposes. Below, you can find a chart showing the publishers of the publications being cited: Publications Citing a Publication Containing a EGA Study Accession pieChart('publications-citations', 'https://stats.ega-archive.org/publications/citations', 'Publishers') Number of publications citing a publication containing a EGA study accession by year Here, you can find a chart showing the number of publications citing a publication containing a EGA study accession by year by year. The values are non-cumulative: Number of published citations by year barChart('citations-year', 'https://stats.ega-archive.org/citations/year', ['Number of Publications', 'Citations by Year'])

  Documentation about/statistics/bibliography

• Transcriptional data of human isogenic iPSCs

  This dataset contains bulk RNA-seq data from 12 autosomally isogenic human iPSCs. Three biological replicas from XXY (sample ID 419295-7), XX (sample ID 419298-419300), XY (sample ID 419302, 419305-6), and XO (sample ID 419308, 419310, 419312) hiPSC. RNA for this dataset was collected using Trizol method, and polyA library type was implemented. The libraries were sequenced using Illumina device. The sample reads are deposited as fastq files. Analysis have been done using reference alignment to GRCh38 reference genome.

  Dataset EGAD50000001361

• WGS of NPC268_Tumor and NPC268_Cell_line

  This dataset contains WGS data in the form of BAM files for NPC268 - "Tumor" derived from snap-frozen tissue while "Cell line" derived from late passage NPC268 cell line. Extracted DNA was sent for 100x and 60x WGS with Novogene via Apical Scientific Sdn Bhd.

  Dataset EGAD00001010292

• Whole exome sequencing of an invasive diffuse intrinsic pontine glioma sampled from different sites

  The lateral ventricle subventricular zone (SVZ) is a frequent site of high-grade glioma (HGG) spread and tumor invasion of the SVZ is a predictor of a worse clinical prognosis. A range of HGG types invade the stem cell niche of the SVZ, including both adult glioblastoma and pediatric high-grade gliomas such as diffuse intrinsic pontine glioma (DIPG). The cellular and molecular mechanisms mediating this frequent invasion of the SVZ are poorly understood. Here we demonstrate that neural precursor cell (NPC):glioma cell communication underpins the propensity of glioma to colonize the SVZ. SVZ NPCs secrete chemoattractant signals toward which glioma cells home. Biochemical and proteomic analyses of factors secreted by SVZ NPCs revealed a discrete list of candidate proteins. Necessity and sufficiency testing implicated the neurite outgrowth-promoting factor pleiotrophin, along with three required binding partners (secreted protein acidic and rich in cysteine (SPARC), SPARC-like protein 1, and heat shock protein 90B), as key mediators of this chemoattractant effect. Pleiotrophin protein expression is strongly enriched in the SVZ, and knockdown of pleiotrophin expression starkly reduced glioma invasion of the SVZ in the adult murine brain. Pleiotrophin, in complex with the three binding partners, activated the Rho/ROCK pathway in DIPG cells, and inhibition of ROCK resulted in decreased DIPG invasion toward SVZ neural precursor cell-secreted factors. These findings demonstrate a pathogenic role for neural precursor cell – glioma interactions and potential therapeutic targets to limit glioma invasion.

  Study EGAS00001002326

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Study EGAS00001007327

• Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas

  Spitzoid melanoma is a specific morphologic variant of melanoma that most commonly affects children and adolescents and ranges on the spectrum of malignancy from low-grade to overtly malignant. These tumors are generally driven by fusions of ALK, RET, NTRK1/3, MET, ROS1 and BRAF. However, in approximately 50% of cases, no genetic driver has been established. Clinical whole genome and transcriptome sequencing (RNA-Seq) of a spitzoid tumor from an adolescent revealed a novel gene fusion of MAP3K8, encoding a serine−threonine kinase that activates MEK. The patient who had exhausted all other therapeutic options was treated with a MEK inhibitor and underwent a transient clinical response. We subsequently analyzed spitzoid tumors from 49 patients by RNA-Seq and found in-frame fusions or C-terminal truncations in 33% of cases. The fusion transcripts and truncated genes all contained MAP3K8 exons 1-8 but lacked the autoinhibitory final exon. Data mining of RNA-Seq from the Cancer Genome Atlas (TCGA) uncovered analogous MAP3K8 rearrangements in 1.5% of adult melanomas. Thus, MAP3K8 rearrangements - uncovered by comprehensive clinical sequencing of a single case - are the most common genetic event in spitzoid melanoma, are present in adult melanomas, and could be amenable to MEK inhibition.

  Study EGAS00001003430

• Single Cell Genotypic and Phenotypic Analysis of Measurable Residual Disease in Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) is a group of blood cancers with high mortality. Even though complete remission is often achieved, majority of the AML patients still relapse. Measurable residual disease (MRD), defined as the population of cancer cells which persists following chemotherapy, is responsible for AML relapse. Understanding the biology enabling MRD clones to resist therapy is necessary to guide the development of curative treatments more effectively. Discriminating residual leukemic clones, preleukemic clones, and normal precursors remains a challenge with current MRD tools. We developed a single cell MRD (scMRD) assay by combining flow cytometric enrichment of the targeted precursor/blast population with integrated single cell DNA sequencing (scDNA-seq) and immunophenotyping (Tapestri, Missionbio). The platform utilizes a custom amplicon panel covering 109 amplicons across 31 genes frequently mutated in AML and a panel of 42 oligo-conjugated antibodies against surface makers. We applied our scMRD assay to sequence 30 MRD samples (multiplexed into 6) from 29 AML patients to study the clonal architecture and protein correlation. In addition, 2 MRD samples were sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. Five patients with AML at diagnosis were also sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. In order to establish the sensitivity of our scMRD assay, we spiked AML cells into normal bone marrow cells. We sequenced 12 such spiked samples after multiplexing.

  Study phs003233

• Colon Cancer Organoid Cultures and Tumors Whole Genome Sequencing Data

  Five hundred nanograms of genomic DNA was fragmented by Covaris S2, the fragmented DNAs were performed end-repair, A-tailing at the 3 prime end, adaptors ligation with an IDT dual-indexed UMI adaptor system at the terminal ends. The adapter ligated library with size range 300-750bp were selected by dual-SPRI method. Twenty percent of the size selected PCR-free libraries were enriched by 5 PCR cycles prior to library size assessment by Bioanalyzer Fragment Analyzer. The PCR-free libraries were quantified by qPCR.The PCR-free libraries were denatured and diluted to optimal concentration. Illumina NovaSeq 6000 was used for Pair-End 151bp sequencing.

  Dataset EGAD00001005759

• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• Mutation_analysis_in_human_iPS_cells_

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced by MiSeq. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000359

• The Spatio-Temporal Evolution of Multiple Myeloma from Baseline to Relapse-Refractory States

  In multiple myeloma, the spatio-temporal evolution patterns of cancer cells in the bone marrow remain largely unknown. Here, we applied spatial-longitudinal sequencing, including a total of 179 samples collected from 25 patients during a follow-up of up to 14 years. Our study highlights focal bone lesions (FL) as hotspots of tumor evolution and provides possible explanations for their negative prognostic impact. We show a close phylogenetic relationship between baseline FL and relapse clones. In patients with ≥3 FDG-PET-positive FL at diagnosis, relapse was driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion was typically seen (p<0.01). Applying imaging-guided sampling, we identified a novel evolutionary pattern with unique treatment-resistant sub-clones at distinct locations. We observed multiple selective clonal sweeps, resistant clones that can be hidden over years, and epigenetic modifier mutations as a new class of relapse aberrations. Here we show that imaging can enhance tumor evolution studies and response assessment. The sophisticated evolution mechanisms in myeloma and presence of single cells that can drive relapse even after 10 years of remission suggest that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy.

  Study phs002625

• Pediatric Papillary Thyroid Carcinoma Whole Exome Sequencing

  BACKGROUND: Pediatric papillary thyroid carcinoma (PPTC) is distinct from adult-onset disease. Despite higher rates of regional and distal metastases and more frequent recurrence, there is, paradoxically, a highly favourable prognosis. Historically, only 40-50% of childhood PTC are driven by genomic variants common to adult PTC, while the oncogenic drivers in the remainder are unknown. METHODS: Fifty-two PPTCs were genotyped by candidate gene testing, followed, in a subset (n=32), by whole exome (WES) and transcriptome sequencing (RNASeq) to identify oncogenic variants in driver-unknown tumors and to explore gene expression patterns. FINDINGS: Thirty-one tumors (60%) carried variants identified by candidate gene testing, specifically: BRAFV600E(22%), NRASQ61R(2%), RET-CCDC6(19%), RET-NCOA4(15%) and PAX8-PPARG. Among the 21 remaining tumors with negative first-line genotyping, oncogenic variants were identified in 19 (90%). These were enriched with oncogenic fusions, with 11 non-recurrent fusion transcripts identified, including two that had not been previously described: STRN-RET and TG-PBF. Most fusions were associated with 3’ receptor tyrosine kinase (RTK) moieties: RET, MET, ALK and NTRK3. Gene expression analysis defined three distinct clusters, which demonstrated differing expression of genes involved in thyroid differentiation and MAPK signaling. INTERPRETATION: Exome and transcriptome-wide sequencing identify genomic drivers of PPTC in 98% of tumors, whereas conventional genotyping leaves many tumors genetically unexplained. PPTC is driven, in the majority of cases, by oncogenic fusion transcripts involving one of a limited number of RTKs. These observations have broad implications for diagnostic testing and for therapeutic options in children with advanced disease.

  Study EGAS00001005187

• Neoantigen-Targeted CD8+ T-Cell Responses 1 With PD-1 Blockade Therapy

  Background: The primary target of T-cell responses induced against cancer cells are peptides derived from non-synonymous mutations presented by HLA (neoantigens). However, the large diversity of HLA alleles and restricted availability of clinical samples have limited the study of the specificity and the evolution over time of the neoantigen-specific T cell responses induced after treatment with immune checkpoint blockade (ICB) immunotherapy. Methods: We applied a newly developed neoepitope-specific T cell isolation technology to perform a longitudinal landscape analysis of the neoepitope-specific T cells in peripheral blood and tumor from 11 patients with metastatic melanoma; 7 with response and 4 with no response to ICB. Briefly, first using computational prediction, the putative neoantigens in each patient were ranked based on affinity for the patient's HLA and expression levels. Then hundreds of barcoded capture reagents consisting of the patient HLA class I subtypes loaded with the corresponding predicted neoantigen were made and used to isolate neoepitope-specific T cells. Once isolated, the TCRs and the barcodes were sequenced. Finally, the tumor reactivity of the isolated neoepitope-specific TCRs (neoTCRs) was assessed upon co-culture of autologous melanoma cell lines from each patient with primary human T cells expressing the neoTCRs generated using a CRISPR-based non-viral gene editing to replace the endogenous TCRs. Results: The tumor mutation burden ranged between 3507 and 177 for patients with response to therapy and 977 to 31 for patients without response to therapy. We screened a median of 172 predicted neoantigen-HLA per patient across their 6 HLA molecules and isolated neoTCRs in all 11 patients. The number of mutations targeted ranged between 13 and 1. We assessed the neoTCR-tumor reactivity in samples from 3 patients with response and 3 patients without response. 39 of the 62 neoTCRs demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Multiple T cell clonotypes recognized a limited number of mutations in 7 patients with response (median of 41 different neoTCR clonotypes per patient), and the T cell specificities were recurrently detected in the blood and the tumor over time. Samples from 4 patients without response to therapy also demonstrated neoepitope-specific T cell responses in blood and tumor to a similarly restricted number of mutations, but lacked TCR polyclonality (median 6.5 neoTCR clonotypes per patient) and were not recurrently detected in sequential samples. Conclusion: Effective ICB therapy is associated with polyclonal neoepitope-specific T-cell responses in the tumor and blood that recognize a limited number of immunodominant mutations and are recurrently detected over time.

  Study phs003153

• A reference map of potential determinants for the human serum metabolome

  The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

  Study EGAS00001004512

• WGS_of_healhy_mesothelial_cells_and_primary_mesothelima_cell_lines

  Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, here we aim at performing WGS of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

  Study EGAS00001005559

• Dataset for transcriptome sequencing of forebrain organoids from Lissencephaly patients

  This dataset contains transcriptome sequencing for 16 samples of forebrain organoids from Lissencephaly patients. The sequencing was performed on Illumina NextSeq 6000 . The sequencing was always paired.

  Dataset EGAD00001015688