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• NCI COVID-19 in Cancer Patients Study (NCCAPS): A Longitudinal Natural History Study

  NCCAPS is a longitudinal prospective cohort study designed to assess patient, disease and treatment factors associated with short- and long-term outcomes in patients with cancer who develop COVID-19. We also aimed to describe COVID-19 symptoms and treatments, and to describe disruptions in cancer treatment due to COVID-19. The study enrolled patients with cancer on active treatment or with a history of stem cell transplant or CAR-T cell therapy with new, active COVID-19, defined as being within 14 days of their first positive SARS-CoV-2 test. The study found that receipt of chemotherapy and baseline history of stroke, atrial fibrillation or pulmonary embolism were associated with a higher risk of hospitalization for COVID-19. Vaccination for SARS-CoV-2 was associated with a lower risk of hospitalization. Death due to COVID-19 was highest in patients with lymphoma, intermediate in those with acute leukemia and lung cancer, and lowest in those with other solid tumors and other hematologic cancers. Disruptions of cancer treatment were frequent in the first 30 days after SARS-CoV-2 infection.

  Study phs004178

• Adaptive Therapy Exploits Fitness Deficits in Chemotherapy-Resistant Ovarian Cancer to Achieve Long-Term Tumor Control Open Access

  Drug resistance results in poor outcomes for cancer patients. Adaptive therapy is a potential strategy to address drug resistance that exploits competitive interactions between sensitive and resistant subclones. Here, we showed that adapting carboplatin dose according to tumor response (adaptive therapy) significantly prolonged survival of murine ovarian cancer models compared to standard carboplatin dosing, without increasing mean daily drug dose or toxicity. Platinum resistant ovarian cancer cells exhibited diminished fitness when drug was absent in vitro and in vivo, which caused selective decline of resistant populations due to reduced proliferation and increased apoptosis. Conversely fitter, sensitive cells re-grew when drug was withdrawn. Using a bioinformatics pipeline that exploits copy number changes to quantify the emergence of treatment resistance, analysis of cell‐free DNA obtained longitudinally from ovarian cancer patients during treatment showed subclonal selection through therapy, and measurements of resistant population growth correlated strongly with disease burden. These preclinical findings pave the way for future clinical testing of personalized adaptive therapy regimens tailored to the evolution of carboplatin resistance in individual ovarian cancer patients.

  Study EGAS50000001142

• National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III)

  The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) is a nationally representative cross-sectional survey of the U.S. general population, which was sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and conducted in 2012-2013. The NESARC-III's target population was the U.S. noninstitutionalized civilian population, 18 years and older, including residents of selected group quarters (e.g., group homes, workers' dormitories). Multistage probability sampling was used to randomly select respondents. Primary sampling units (PSUs) were individual counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of Census-defined blocks, and tertiary sampling units were households within SSUs. Finally, eligible adults within sampled households were randomly selected. Hispanics, Blacks, and Asians were oversampled and resulted in a total of 36,309 respondents. All respondents provided informed consent for survey participation. Data were adjusted for oversampling and screener - and person-level nonresponse, then weighted through post-stratification to represent the US civilian population based on the 2012 American Community Survey. These weighting adjustments were found to compensate adequately for nonresponse. Interviewer field methods involved initial structured home study, in-person training, ongoing supervision, and random respondent callbacks to verify data. The NESARC-III collected information on alcohol and drug consumption, alcohol use disorder, other substance use disorders (e.g., nicotine, cannabis and opioid), and associated physical and psychiatric adverse consequences. In addition to a full array of sociodemographic characteristics such as race/ethnicity, gender, age, risk and environmental factors including adverse childhood experiences (e.g., sexual, physical abuse and neglect) and family history for alcohol, drug use disorders and other psychiatric disorders (e.g., mood, anxiety, personality disorders and PTSD) were included (phenotypic variables=4,320). As part of the NESARC-III, 22,848 informative samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array (refer to the SNP annotation file). The latter array was selected based on the addiction associated genes, the results of 5 GWAS of alcohol and other psychiatric disorders, and animal models with addiction phenotypes. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data. The 22,848 subjects in this study were all deeply and consistently phenotyped via structured diagnostic interview. Controls group can be selected for specific disorders from a pool of all samples. Here are numbers of cases for major DSM-5 mental disorders in NESARC-III genetic data: Alcohol use disorder (7,075); Nicotine use disorder (6,641); Drug use disorder (2,570); Major depressive disorder (5,214); Persistent depression(1,429); Bipolar I (543); Anxiety disorders (4,226); PTSD (1,674); Personality disorders (4,014); Eating Disorders (457).

  Study phs001590

• Multimodal Analysis for Human Ex Vivo Studies Shows Extensive Molecular Changes from Delays in Blood Processing

  Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMCs up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

  Study phs002280

• Phylogenetic analysis of paired breast carcinomas identifies genetic events associated with clonal recurrence and invasive progression

  Development of ipsilateral breast carcinoma following diagnosis of breast ductal carcinoma in situ (DCIS) has been assumed to represent recurrence of the primary tumour. However, this may not be the case and it is important to know how often recurrences are new tumours. Ipsilateral primary-recurrence pairs (n=78) were sequenced to test their clonal relatedness. Shared genetic events were identified from whole exome sequencing (n=54 pairs) using haplotype-specific copy number and phylogenetic analysis. The remaining pairs were sequenced by a targeted panel or low-coverage whole genome sequencing. We included 32 non-recurrent DCIS to compare recurrent and non-recurrent disease. We found that 7% of DCIS recurrences were non-clonal by whole exome sequencing, indicative of a new breast carcinoma. Lower resolution methods detected a higher non-clonality rate (29%). Comparing primary DCIS with their recurrences found that evolution of DCIS to invasive disease was associated with increased ploidy and copy number events. TP53 mutations were enriched in DCIS with clonal recurrence compared with non-recurrent DCIS. Our results verify that de novo “recurrent tumours” of independent origin occur in patients who may be at high risk. (https://www.biorxiv.org/content/10.1101/2024.05.19.594731v2.full)

  Study EGAS50000001298

• Whole genome sequencing delineates regulatory, structural, and cryptic splice variants in early onset cardiomyopathy

  Cardiomyopathy (CMP) is a heritable disorder. Over 50% cases are gene-elusive on clinical gene panel testing. The contribution of variants in non-coding DNA elements that result in cryptic splicing and regulate gene expression has not been explored. We analyzed whole genome sequencing (WGS) data in a discovery cohort of 209 pediatric CMP patients and 1,953 independent replication genomes and exomes. We searched for protein-coding variants, and non-coding variants predicted to affect the function or expression of genes. Thirty-nine % cases harbored pathogenic coding variants in known CMP genes, and 5% harbored high-risk loss-of-function (LoF) variants in additional candidate CMP genes. Fifteen % harbored high-risk regulatory variants in promoters and enhancers of CMP genes (Odds ratio 2.25, p=6.70×10-7 versus controls). Genes involved in α-dystroglycan glycosylation (FKTN, DTNA) and desmosomal signaling (DSC2, DSG2) were most highly enriched for regulatory variants (Odds ratio 6.7-58.1). Functional effects were confirmed in patient myocardium and reporter assays in human cardiomyocytes, and in zebrafish CRISPR knockouts. We provide strong evidence for the genomic contribution of functionally active variants in new genes and in regulatory elements of known CMP genes to early-onset CMP.

  Study EGAS00001004929

• Genomic catastrophes frequently arise in esophageal adenocarcinoma and drive tumorigenesis.

  Oesophageal adenocarcinoma (EAC) incidence is rapidly increasing in Western countries. A better understanding of EAC underpins efforts to improve early detection and treatment outcomes. While large EAC exome sequencing efforts to date have found recurrent loss-of-function mutations, oncogenic driving events have been underrepresented. Here we use a combination of whole-genome sequencing (WGS) and single-nucleotide polymorphism-array profiling to show that genomic catastrophes are frequent in EAC, with almost a third (32%, n=40/123) undergoing chromothriptic events. WGS of 22 EAC cases show that catastrophes may lead to oncogene amplification through chromothripsis-derived double-minute chromosome formation (MYC and MDM2) or breakage-fusion-bridge (KRAS, MDM2 and RFC3). Telomere shortening is more prominent in EACs bearing localized complex rearrangements. Mutational signature analysis also confirms that extreme genomic instability in EAC can be driven by somatic BRCA2 mutations. These findings suggest that genomic catastrophes have a significant role in the malignant transformation of EAC.

  Study EGAS00001000750

• 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

• Genetic and epigenetic characterization of adenoid cystic carcinoma

  Whole genome sequences of ACC primagrafts, Histone modification maps and transcription factor binding maps for ACC primagrafts and primary tumors. Processed ChIP-seq data is available on GEO under accession number GSE76465.

  Dataset EGAD00001001662

• Untargeted serum metabolomics profiled by Metabolon Inc.

  Raw untargeted metabolomics profiled by Metabolon Inc. for 540 samples from healthy individuals. Files include sample names and run details which can be matched to their metagenomic sequencing samples from PRJEB11532 and PRJEB17643. Information regarding metabolite metadata is also available, including

  Dataset EGAD00001006247

• Bulk RNASeq of metastatic colorectal cancer organoids with ATOH1 knockout

  Bulk RNA sequencing was performed on mCRC organoids subjected to cetuximab treatment, comparing ATOH1 knockout and control conditions. The dataset is intended to elucidate the contribution of ATOH1-regulated secretory cell population to cetuximab persistence mechanisms.

  Dataset EGAD50000002060

• Illumina sequencing of V4 variable region of the 16S rRNA from human feces samples

  The dataset is composed of 62 samples (31 subjects before and after probiotic-like bacteria treatment). Sequencing was performed using Illumina HiSeq 2500. Fastq files are provided.

  Dataset EGAD00001004944

• Cell-Free DNA Genomic and Fragmentomic Features for Early Outcome Prediction in Diffuse Large B-Cell Lymphoma

  Purpose: Diffuse large B-cell lymphoma (DLBCL) patients need an accurate and early risk stratification strategy as prompt therapy escalation may improve outcome. Patients and methods: We evaluated cell free DNA (cfDNA) genomic and fragmentomic features in 190 patients with large B-cell lymphoma from more than 40 hospitals in the Benelux using Whole Genome Sequencing (WGS). We defined a new metric called ACT score (Aberrations, Contribution of short fragments, Terminal motif analyses) by combining four cfDNA signals and evaluated its performance to predict end-of-treatment (EOT) response and survival. Results: Individual cfDNA features and ACT score were altered per EOT response after one cycle of treatment (T1). The ACT score at T1 outperformed all individual cfDNA features in predicting EOT response (AUC = 0.74). Patients with a positive ACT score had an inferior outcome compared to ACT score negative patients [progression-free survival (PFS): HR 5.0 (95% CI 3.1-8.2), log-rank test, p < 0.0001) and overall survival (OS): HR 6.5 (95% CI 3.5-12.2), log-rank test, p < 0.0001]. The 2-year PFS in ACT score positive and negative patients were 29.8% and 78.1%, respectively. The prognostic value of the ACT score is independent of the International Prognostic Index and interim imaging. Conclusions: ACT score computed from a single plasma sample collected after one cycle of treatment can predict clinical outcome. This low-cost and easy-to-interpret test does not require tissue biopsies or a priori knowledge of mutations and has the potential to aid patient selection in interventional clinical trials and risk-adapted treatment strategies.

  Study EGAS50000000412

• Clinical and biomarker dataset

  Clinical &amp; biomarker data from IMagyn050: treatment arm, treatment approach, outcome of surgery, ECOG PS, PD-L1 status, race, age, disease stage, progression free survival (investigator assessed), overall survival, histology, tumor mutation burden and status, genomic loss of heterozygosity, microsatellite status, BRCA1/2 mutation status, tissue of origin. Mutation status based on FoundationOne NGS for the following genes is also being provided: TP53, BRCA1, CCNE1, MYC, NF1, PIK3CA, RAD21, TERC, PRKCI, KRAS, RB1, BRCA2, ARID1A, AKT2, PTEN, KDM5A, NOTCH3, FGF12, ERBB2, CDK12, EMSY, WHSC1L1, BCL2L1, CDKN2A, GNAS, ARFRP1, ZNF217, SOX2, CCND2, FGF6, FGF23, LYN, MUTYH, AURKA, FGFR1, MCL1, MLL2, MYCL1, ZNF703, BRAF, MAP2K4, CREBBP, TSC2

  Dataset EGAD00001009797

• Transcriptomic profiling of primary tumor and paired hepatic oligometastasis of PDAC

  The dataset was generated for studying metastatic mechanism of pancreatic ductal adenocarcinoma (PDAC). It is consisted of pair-end raw RNA sequencing reads of 33 fresh froze PDAC specimens, which includes 6 tumor-adjacent normal tissues (N), 13 primary tumors (PT), and 14 hepatic metastases (HM) from 14 PDAC patients (6 N-PT-HM trios, 7 PT-HM paires, and 1 HM).

  Dataset EGAD00001006598

• Final results and ctDNA analyses from the randomized phase 3 IMpassion031 trial evaluating peri-operative atezolizumab for early-stage triple-negative breast cancer

  In IMpassion031, adding atezolizumab to neoadjuvant chemotherapy significantly improved pathologic complete response (pCR) rate (primary endpoint) for stage II/III triple-negative breast cancer (TNBC). Patients with stage II/III TNBC were randomized 1:1 to neoadjuvant chemotherapy plus peri-operative atezolizumab or pre-operative placebo. Descriptive secondary endpoints included event-free, disease-free, and overall survival. Long-term outcomes favored the atezolizumab group (event-free survival HR 0.76, 95% CI: 0.47–1.21). Among patients without pCR, 14/70 (20%) atezolizumab-treated and 33/99 (33%) placebo-treated patients received additional adjuvant therapy, frequently capecitabine. In exploratory analyses, pCR was prognostic for long-term outcome. Patients with baseline ctDNA-negative status (6%) had excellent long-term outcomes. Most patients (87%) had cleared ctDNA at surgery. ctDNA-positive status at surgery identified a subset of non-pCR patients with poorest prognosis. Long-term safety was consistent with primary results. Adding atezolizumab to chemotherapy for stage II/III TNBC is associated with more favorable long-term outcomes. ctDNA dynamics provide prognostic value beyond pCR. ClinicalTrials.gov identifier: NCT03197935

  Study EGAS50000000974

• 503 genotypes from Inner Asia used in 'Close inbreeding and low genetic diversity in Inner Asian human populations despite geographical exogamy' publication

  Inner Asia is particularly interesting to understand human history and evolution, as two groups presenting contrasting cultural traits (notably their language, their social organisation and matrimonial system) cohabit. We sampled 503 individuals from these two groups, belonging to 17 populations from 11 distinct ethnic groups (AltaiKizhi, Kazakh, Khakas, Kyrgyz, Mongolian, Shore, Tajik, Telengit, Tubalar, Turkmen and Uzbek). The samples were then genotyped with 5 different DNA-arrays and, after quality-control, the 253,532 autosomal SNPs present in all the arrays were merged together in the present dataset.

  Study EGAS00001002951

• PAGE: Prenatal Assessment of Genomes and Exomes

  The Prenatal Assessment of Genomes and Exomes (PAGE) study is a multicentre prospective trial, performing exome sequence analysis on samples from 1000 families with structural anomalies in prenatal ultrasound screening but normal aneuploidy results. The data will enable discovery of novel genetic disorders and increase the diagnostic yield. Where appropriate, results will be reported back to the families at the end of the pregnancy, after thorough clinical review. Ultimately, the translation of the acquired know-how into cost-effective prenatal diagnostic sequencing will improve genetics-derived prognoses and allow more informed parental counselling as well as management of pregnancy and childbirth.

  Study EGAS00001001713

• Alterations in the gut microbiome implicate key taxa and metabolic pathways across inflammatory arthritis phenotypes

  Musculoskeletal diseases affect up to 20% of adults worldwide. The gut microbiome has been implicated in inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, the Inflammatory Arthritis Microbiome Consortium investigated 440 stool shotgun metagenomes comprising 221 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis and 219 healthy controls and individuals with joint pain without an underlying inflammatory cause. Diagnosis explained about 2% of gut taxonomic variability, which is comparable in magnitude to inflammatory bowel disease. We identified several candidate microbes with differential carriage patterns in patients with elevated blood markers for inflammation. Our results confirm and extend previous findings of increased carriage of typically oral and inflammatory taxa and decreased abundance and prevalence of typical gut clades, indicating that distal inflammatory conditions, as well as local conditions, correspond to alterations to the gut microbial composition. We identified several differentially encoded pathways in the gut microbiome of patients with inflammatory arthritis, including changes in vitamin B salvage and biosynthesis and enrichment of iron sequestration. Although several of these changes characteristic of inflammation could have causal roles, we hypothesize that they are mainly positive feedback responses to changes in host physiology and immune homeostasis. By connecting taxonomic alternations to functional alterations, this work expands our understanding of the shifts in the gut ecosystem that occur in response to systemic inflammation during arthritis.

  Dataset EGAD50000000567

• Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

  We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

  Dataset EGAD00001001869

• Khoe-San genomes reveal unique variation and confirm deepest population divergence in Homo sapiens

  The southern African indigenous Khoe-San populations harbor the most divergent lineages of all living peoples. Exploring their genomes is key to understanding deep human history. We sequenced 25 full genomes from five Khoe-San populations, revealing many novel variants, that 25% of variants are unique to the Khoe-San, and that the Khoe-San group harbors the greatest level of diversity across the globe. In line with previous studies, we found several gene-regions with extreme values in genome-wide distributions, potentially caused by natural selection early in the modern human lineage and more recent in time. These gene-regions included immunity-, sperm-, brain-, diet- and muscle-related genes. When accounting for recent admixture, all Khoe-San groups display genetic diversity approaching the levels in other African groups and a reduction in effective population size starting around 100,000 years ago. Hence, all human groups show a reduction in effective population size commencing around the time of the Out-of-Africa migrations, which coincides with changes in the paleoclimate records, changes that potentially impacted all humans at the time.

  Study EGAS00001004459

• DAC for Central African ancient demography processes NGS dataset

  Title DAC Ancient tree-topologies and gene-flow processes among human lineages in Africa Contacts: Paul Verdu +33144057317 paul.verdu@mnhn.fr CNRS-MNHN-Université de Paris UMR7206 Eco-anthropology Short description The Data Access Committee for acess to genotype and sample information used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa" by Gwenna Breton et al. 2025 ensures that data-access requests comply with the Informed Consent provided by donors, and with ethical and deontological guidelines with respect to privacy. DNA samples from individuals were collected with the subjects’ informed consent following the Declaration of Helsinki guidelines and approved by the following Ethics committees: Institut de Recherche pour le Développement (IRD, France); Cameroon Ministry of Scientific Research and Technology; Central African Republic Ministère de l’Enseignement Supérieur et de la Recherche Scientifique; France Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation (Comité de Protection des Personnes DC-2016-2740); French Commission Nationale Informatique et Liberté CNIL (declaration n°1972648); Uganda National Council for Science and Technology; Institutional Review Board of the University of Chicago Biological Sciences Division and the Pritzker School of Medicine University of Chicago Hospitals (protocol number 16986A); Committee for the Protection of Human Subjects of the Trustees of Dartmouth College and the Dartmouth-Hitchcock Medical Center (protocol number 22410); Human Research Ethics Committee (Medical) at the University of the Witwatersrand, Johannesburg (Protocol Numbers: M980553, M050902, M090576, M10270, M180654); Working Group of Indigenous Minorities in Southern Africa (WIMSA); South African San Council (SASC); and the Swedish Ethical Review Authority (Dnr 2019-05174). Requests for accessing all or part of the Central African data used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa", by Gwenna Breton et al. 2024 (doi - PENDING), should be addressed to the DAC providing: 1) Data can only be used to explore human genetic evolution, evolutionary ecology and population history 2) The research institution where data will be stored and were analyses will be conducted. 3) The detailed coordinates of the researcher responsible for data storage and analyses. 4) A description (max 20 sentences) of the scientific finality and context of the project and classes of methodological analyses that will be performed to achieve it using the requested data. 5) When applicable, mention also other previously published data sets that will be used jointly with the requested datas et For accessing any or all the Central African genetic data used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa", by Gwenna Breton et al. 2024 (doi - PENDING), the requester hereby ensures that: 1) Individual donor privacy should be respected at all times. Data cannot be made publicly available under any circumstances. 2) Data cannot be shared nor transferred to a third party without re-applying for eGA access to the DAC. 3) No direct or indirect commercial use of the data can be made 4) No individual medical genetics or disease diagnostics can be performed with the data 5) No medical or legal forensic investigations can be conducted with the data 6) No genealogical research can be conducted with the data (e.g. no paternity nor maternity testing, no genetic identification, no search of relatives using other datasets) 7) Appropriate citation of the article and data set used for any scientific communication using the data 8) Data is destroyed after the completion of the project. Any further re-use of the data is subject to a novel application to the DAC.

  Dac EGAC50000000447

• deep-learning-powered tissue deconvolution for cfDNA

  Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

  Study EGAS00001007213

• Spatially resolved antigen receptor and gene expression data from breast cancer patients

  The dataset includes spatially-resolved and single-cell antigen receptor, as well as gene expression, data from two different HER2+ breast cancer patients. The tumor piece obtained during surgery from each patient was divided into several regions and tissue sections were used for spatial transcriptomics (Visium, 10x genomics). As indicated, some tissue sections were analyzed by a new method (Spatial VDJ) to spatially resolve antigen receptor sequences (target capture), which was developed in our publication. In parallel, tissue pieces from the same tumor were dissociated for single-cell gene expression analysis (10x genomics GEX, VDJ, and feature barcoding/Hash Tag Oligonucleotide). The deposited data is in the form of fastq files. All processed data, metadata, micrographs of the tissue sections (of those used for spatial transcriptomics), and scripts used for the analysis are publicly available at Zenodo (DOI: 10.5281/zenodo.7961605). Final libraries were sequenced on NextSeq2000 (Illumina) or NovaSeq6000 (Illumina) and analyzed with Cell Ranger, Seurat, Space Ranger, and STutility pipelines.

  Dataset EGAD00001011061

• PopCol 16S gut microbiome sequencing

  PopCol is a cohort study in Stockholm, Sweden that includes a data-rich set of individuals with data available from bowel symptoms questionnaires, gastroenterology visits and biospecimens (genotype and 16S sequencing from blood and stool samples, respectively). Genotyping was carried out using the Illumina HumanOmniExpressExome-8v1 arrays at the SciLifeLab NGI facility in Uppsala, Sweden. Fecal DNA was extracted from samples kept at -80°C using Qiagen 5 QIAamp DNA Stool Mini Kits and analyzed using 16S rRNA gene amplicon sequencing (in the V1-V2 hypervariable region). This was performed on the Illumina MiSeq platform at the Institute of Clinical Molecular Biology (IKMB) in Kiel, Germany. Of these, six PopCol participants were PPI users and 12 used antibiotics. The study was approved by the local Committee of Research Ethics (Forskningskommitté Syd) at Karolinska Institutet, Stockholm, in November 2001. Written informed consent was obtained from all participants

  Dataset EGAD00001007071