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• 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

• Exome sequencing identifies mutation of the ribosome in T-cell acute lymphoblastic leukemia

  Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy and responds well to therapy in children, but not in adults. We used exome sequencing of 67 T-cell ALL (T- ALL) samples to gain insight in the mutational spectrum and age related differences of these leukemias. We detected protein-altering mutations in 508 genes, with an average of 8.2 mutations in pediatric and 21.0 in adult T-ALL. Based on stringent filtering, we predict 15 of these genes to be drivers, including 7 genes that were not previously implicated in T-ALL. We identify CNOT3 as a new tumor suppressor, as it is mutated in 12.2 % of adult T-ALLs and its knock-down causes de novo tumors in a sensitized drosophila eye tumor model. In addition, we identify mutations in RPL5 and RPL10, proteins of the 60S ribosomal complex2, in 18.2 % of pediatric T-ALLs. Mutation of arginine 98 in the X-linked RPL10 gene was most frequent. Yeast cells expressing the Rpl10 R98S mutant showed a clear ribosome biogenesis defect, excluding that this mutation is a passenger mutation. Our data provide insights in the mutational landscape of pediatric and adult T-ALL and identify the ribosome as a potential oncogenic factor in cancer.

  Study EGAS00001000296

• The Genomic Landscape of Core-Binding Factor Acute Myeloid Leukemias

  Pediatric de novo acute myeloid leukemia (AML) is a heterogeneous disease that can be divided into clinically distinct subtypes based on the presence of specific chromosomal abnormalities or gene alterations. One of the best characterized subtypes of AML involves leukemias with alterations of the core-binding factor (CBF)-complex, which comprises the FAB subtypes M2 and M4Eo and associates with a favorable outcome. Patients with the AML M2 subtype harbor a translocation between chromosomes 8 and 21 [t(8;21)] that yields the chimeric fusion gene RUNX1(AML1)-RUNX1T1(ETO), while patients with AML M4Eo express the chimeric fusion gene CBFβ-SMMHC(MYH11) as a result of an inversion/translocation event of chromosome 16 [inv(16)/t(16;16)]. In an effort to define the total complement of genetic changes in CBF-leukemia, we performed paired-end whole genome sequencing (WGS) on diagnostic leukemia blasts and matched germ line samples from 17 pediatric CBF-leukemia patients using the Illumina platform. Somatic alterations, including single nucleotide variations (SNVs) and structural variations (SVs), including insertions, deletions, inversions, and inter- and intra-chromosomal rearrangements, were detected using complementary analysis pipelines (Bambino, CREST and CONSERTING). Recurrent screening of identified mutations will be performed in a cohort of approximately 94 cases of CBF-leukemias.

  Study EGAS00001000349

• Whole genome sequencing of tumour and normal paired samples of diffuse intrinsic pontine gliomas

  Diffuse intrinsic pontine glioma (DIPG) have a universally dismal prognosis (median 9-12 months), with neither chemotherapeutic nor targeted agents showing any substantial survival benefit in clinical trials in children with these tumours. DIPG are highly infiltrative malignant glial neoplasms of the ventral pons, which due to their location within the brain, make them unsuitable for surgical resection and consequently have a universally dismal clinical outcome. Recent high-throughput sequencing approaches have revealed a striking prevalence of K27M mutations in the genes encoding the histone variants H3.3 (H3F3A) or H3.1 (HIST1H3B) in the childhood brain tumour DIPG. This K-to-M substitution confers a trans-dominant ablation of global H3K27 trimethylation, which likely profoundly alters gene expression through de-repression of polycomb repressive complex 2 (PRC2) target genes. Despite these advances in our understanding of the distinct biology of these tumours, approaches for specific novel therapeutic interventions are not clear, and little has been reported of the secondary mutations accompanying these changes. We carried out whole genome sequencing on a series of 20 tumour normal pairs of pre-treatment biopsy samples of DIPG, for which the patients underwent a safe stereotactic procedure, and whole exome sequencing on a further six tumour normal pairs obtained at autopsy.

  Study EGAS00001000572

• DAC Admixture histories of São Tomé e Príncipe

  Contacts: Paul Verdu +33144057317 paul.verdu@mnhn.fr CNRS-MNHN-Université de Paris UMR7206 Eco-anthropology Jorge M. Rocha jrocha@cibio.up.pt CIBIO Short description The Data Access Committee for acess to genotype and sample information used in the article "Nested admixture during and after the Trans-Atlantic Slave Trade in the island of Sao Tome" by Ciccarella M 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. Research sampling protocols followed the Declaration of Helsinki guidelines and written informed consent was obtained from all volunteer participants involved in the sampling in São Tomé e Príncipe. The study of the São Tomé e Príncipe sample was undertaken with the support and permission of the Provincial Government of the Ministry of Health of the Democratic Republic of São Tomé e Príncipe, and the Provincial Government of Príncipe. Research sampling protocols also followed the French laws of scientific research deontology (Loi n° 2016-483 du 20 avril 2016) and were approved by the French ethics committees and CNIL (Declaration n°1972648).

  Dac EGAC50000000437

• A practical guide for mutational signature analysis in hematological malignancies

  Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.

  Dataset EGAD00001005028

• Comparison of single/pooled CTCs and bulk exome sequencing

  Single cell technologies allow the interrogation of tumor heterogeneity, providing insights into tumor evolution and treatment resistance. To better understand whether circulating tumor cells (CTCs) could complement metastatic biopsies for tumor genomic profiling, we characterized 11 single CTCs and 10 pooled CTC samples at the mutational and copy number aberration (CNA) levels, and compared these results with matched synchronous tumor biopsies from 3 metastatic breast cancer patients with triple-negative (TNBC), HER2-positive and estrogen receptor-positive (ER+) tumors. Similar CNA profiles and the same patient-specific driver mutations were found in bulk tissue and CTCs for the HER2-positive and TNBC tumors, whereas different CNA profiles and driver mutations were identified for the ER+ tumor, which presented two distinct clones in CTCs defined by mutations in ESR1 Y537N and TP53, respectively. Furthermore, de novo mutational signatures derived from CTCs described patient-specific biological processes. These data suggest that tumor tissue and CTCs provide complementary clinically relevant information to map tumor heterogeneity and tumor evolution.

  Dataset EGAD00001009052

• Transcriptional consequences of SETBP1 variants in developmental disorders and malignancies

  The SETBP1 gene encodes a DNA-binding nuclear protein that regulates gene expression across multiple tissues. Precise control of SETBP1 dosage is essential for normal cellular function, as both loss- and gain-of-function variants of SETBP1 can lead to severe phenotypic consequences. De novo germline gain-of-function point mutations that prolong SETBP1 half-life result in Schinzel-Giedion syndrome (SGS), an ultra-rare and severe congenital disorder associated with extensive developmental abnormalities and health complications. These SGS-associated variants cluster within a hotspot in the SKI-homology domain of SETBP1, overlapping with somatic mutations recurrently observed in myeloid leukaemia with poor prognosis. Thus far, the precise mechanisms by which these SETBP1 mutations drive disease remain largely unclear. Here, through single-cell and single-nucleus mRNA sequencing of a rare collection of primary patient samples with SGS and myeloid leukaemia, we examined the transcriptional consequences of SETBP1 gain-of-function variants in haematopoietic cells, comparing their impacts when acquired in the germline and somatically in malignancies.

  Dataset EGAD00001015482

• Genomic Analyses of Germline and Somatic Variation in High-Grade Serous Ovarian Cancer

  The goal of this study was to identify and characterize germline and somatic genetic variation in women with high grade serous ovarian cancers treated at a single cancer center and their associations with relapse-free and overall survival. We conducted paired tumor/normal targeted next-generation sequencing of 577 genes in pathways of DNA repair, response to DNA damage, cell-cycle regulation, programmed cell death, MAPK, and P13K/AKT/MTOR signaling in 114 tumors from 71 women. In addition, we investigated single copy number alterations (SCNAs) and loss of heterozygosity in a subset of 61 tumors. We validated our results with data from ovarian tumors in TCGA. Our results were similar to other studies of high-grade serous carcinomas. As an example, we found that approximately one third of the tumors harbored loss of function variants in homologous recombination genes and that >90% had TP53 somatic mutations. Through GISTIC analysis of the OncoScan data on tumor DNA from 61 cases, we identified several regions of high copy number alterations including including NOTCH3 and PIK3R2 that were significantly associated with an increase in cancer recurrence and a reduction in overall survival. We identified few changes in mutation profiles where we had multiple tissues, either from multiple surgeries or from the primary site to metastatic sites within the same surgery. However, we did not investigate copy number alterations in multiple tissues from the same individuals, and so it may be that copy number alterations are more important. Data available through dbGAP will be the BAM files and the phenotypic data on the tumor samples, the age, race, ethnicity of the participants and their outcomes, and the Oncoscan OSCHP files.

  Study phs003198

• Modifier Genes in 21-hydroxylase Deficiency

  CAH is a genetic steroidogenesis disorder. The most common form, 21OHD, leads to cortisol deficiency and, in turn, an excess of androgen, a hormone that promotes the development and maintenance of male sex characteristics. As a result of this androgen excess, prepubescent males and newborn, prepubescent, and grown females exhibit mature masculine characteristics. The symptoms and severity of 21OHD vary among individuals with the disease and in adults versus children. The reasons for these differences are not yet known. Current therapy for 21OHD consists of administration of glucocorticoids to replace cortisol and suppress excessive pituitary function. With more information about what genes or factors contribute to the severity of 21OHD, researchers may be able to better treat children and adults with the disease. This study will examine participants' DNA to determine what other genes may affect the severity of 21OHD and may make the disease milder in adults than in children This is a 3-day inpatient study. Once eligibility is confirmed through physical exam and blood analysis, eligible participants are admitted to the study site in the morning on the first study day. A blood sample is taken and participants receive one 10-mg pill of hydrocortisone. Heart rates and blood pressures are taken every 4 hours throughout the day. In the morning of Day 2, a blood sample will be obtained and a 24 hour urine collection will begin. On the morning of Day 3, another blood sample is obtained. Participants then receive intravenous cosyntropin, a synthetic form of a hormone that the body makes. About 1 hour after this, participants provide a final blood sample. Participants receive a pill of hydrocortisone prior to the end of the study.

  Study phs001313

• The Human Pancreas Analysis Program (HPAP)

  The past decade has seen a dramatic improvement in our ability to phenotype and molecularly profile human tissues with unprecedented resolution at the genomic, epigenomic, protein, and functional levels. The Human Pancreas Analysis Program (HPAP), part of the Human Islet Research Network and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) through multiple NIH grants, is performing deep phenotyping of the human endocrine pancreas to better understand the cellular and molecular events that precede and lead to beta-cell loss and/or dysfunction in type 1 diabetes (T1D) and type 2 diabetes (T2D) as well as to accumulate, analyze, and distribute high-value data sets to the diabetes research community through the HPAP PANC-DB database (and additional details provided at that site). To this end, HPAP employs state-of-the-art technologies to perform comprehensive analyses of pancreas biology as it pertains to organ donors with T1D, autoantibody-positive donors without diabetes, donors with T2D, and control donors. Pancreas procurement and analyses take advantage of the expertise and extensive network of Organ Procurement Organizations (OPOs) and autoantibody screening centers established through the JDRF/The Lenona M. and Harry B. Helmsley Charitable Trust (HCT) – funded nPOD program. In contrast to nPOD, the major product provided by HPAP is not archived biomaterial subject to broad distribution, but rather, the delivery of extensive and high-quality molecular data sets to the diabetes research community in order to facilitate further discovery. Together, nPOD and HPAP are complementary programs that assist the diabetes community and afford the maximal opportunity for advancing knowledge about the pathogenesis of T1D and T2D.

  Study phs002465

• A Personalized Neoantigen Vaccine Generates Anti-Tumor Immunity in High-Risk Renal Cell Carcinoma

  Personalized cancer vaccines (PCVs) can generate circulating immune responses against predicted neoantigens. However, whether such responses can target cancer driver mutations, lead to immune recognition of a patient's tumor, and result in clinical activity are largely unknown, particularly in patients with lower mutation burden tumors. We conducted a phase I trial testing a neoantigen-targeting PCV in patients with high-risk, fully resected clear cell renal cell carcinoma (RCC; stage III or IV), with or without ipilimumab administered adjacent to the vaccine. At a median follow-up of 40.2 months from surgery, none of the 9 initial participants experienced a recurrence of RCC. No dose-limiting toxicities were observed. All patients generated T cell immune responses against PCV antigens, including RCC driver mutations in VHL, PBRM1, BAP1, KDM5C, and PIK3CA. Following vaccination, there was a durable expansion of peripheral T cell clones, and T cell reactivity against autologous tumor was detected in 7 of the 9 patients. Our results demonstrate that neoantigen-targeting PCVs in high-risk RCC are highly immunogenic, capable of targeting key driver mutations, and induce anti-tumor immunity. These observations, in conjunction with the absence of recurrence in all 9 vaccinated patients, highlights the promise of PCV as effective adjuvant therapy in RCC. We are submitting WES data from whole blood samples and tumor FFPE samples, and RNA-Seq data from tumor FFPE samples. We are also submitting RNA-Seq data from purified tumor samples. scRNA-seq data will be submitted for skin samples (vaccine site biopsies at Weeks 0, 4, and 13), tumor samples (including resected metastatic tumor samples for two patients), and normal kidney samples. Bulk TCR-seq data will be submitted for blood samples.

  Study phs003710

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• CPTAC Proteogenomic Study

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.) The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein=protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the third phase of the CPTC initiative in September 2016. As the Clinical Proteomic Tumor Analysis Consortium, CPTAC continues to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach was to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. In this third phase of CPTAC, the program aims to expand on CPTAC II and genomically and proteomically characterize over 2000 samples from 10 cancer types (Lung Adenocarcinoma, Pancreatic Ductal Adenocarcinoma, Glioblastoma Multiforme, Acute Myeloid Leukemia, Clear cell renal Carcinoma, Head and Neck Squamous Cell Carcinoma, Cutaneous Melanoma, Sarcoma, Lung Squamous Cell Carcinoma, Uterine Corpus Endometrial Carcinoma) .Germline DNA is obtained from blood and Normal control samples for proteomics varied by organ site. All cancer samples were derived from primary and untreated tumor.

  Study phs001287

• Prenatal lead exposure is associated with decreased cord blood DNA methylation of the glycoprotein VI gene involved in platelet activation and thrombus formation

  Early-life lead exposure impairs neurodevelopment and later exposure affects the cardiovascular system. Lead has been associated with reduced global 5-methylcytosine DNA methylation, suggesting that lead toxicity acts through epigenetic mechanisms. The objective of this study is to clarify how early life lead exposure alters DNA methylation of specific genes, using an epigenomic approach. We measured lead concentrations in urine (gestational week, GW, 8) and erythrocytes (GW 14), using ICP-MS, for 127 pregnant mothers recruited in the MINIMat food and supplementation cohort in rural Bangladesh. Cord blood DNA methylation was analyzed with the Infinium HumanMethylation450K BeadChip and top sites were validated by methylation-sensitive high-resolution melt curve analysis. Maternal urinary lead concentrations (divided into quartiles) showed significant (after adjustment for FDR) inverse associations with methylation at nine CpGs. Three of these sites were in the 5’ end, including the promoter, of glycoprotein IV (GP6); cg18355337 (q=0.029, β=-0.30), cg25818583 (q=0.041, β=-0.18) and cg23796967 (q=0.047, β=-0.17). The methylation in another CpG site in GP6 was close to significant (cg05374025, q=0.057, β=-0.23). The erythrocyte lead concentrations (divided into quartiles) were also inversely associated with CpG methylation in GP6, although this was not statistically significant after FDR-adjustments. Eight CpG sites in GP6 constituted a differentially methylated region in relation to urinary lead (p=0.005, q=0.48) and erythrocyte lead (p=0.007, q=0.46). In conclusion, we found that moderate prenatal lead exposure appear to epigenetically affect GP6, a key component of platelet aggregation and thrombus formation, suggesting a novel link between early lead exposure and cardiovascular disease later in life.

  Study EGAS00001001575

• Combining a Universal Telomerase Based Cancer Vaccine with Ipilimumab in Patients with Metastatic Melanoma - Five-year Follow up of a Phase I/IIa Trial

  Background Ipilimumab improves survival for patients with metastatic malignant melanoma. Combining a therapeutic cancer vaccine with ipilimumab may increase efficacy by providing enhanced anti-tumor immune responses. UV1 consists of three synthetic long peptides from human telomerase reverse transcriptase (hTERT). These peptides comprise epitopes recognized by T cells from cancer patients experiencing long-term survival following treatment with a first-generation hTERT vaccine, and generate long-lasting immune responses in cancer patients when used as monotherapy. The objective of this trial was to investigate the safety and efficacy of combining UV1 with ipilimumab in metastatic melanoma. Patients and methods In this phase I/IIa, single center trial [NCT02275416], patients with metastatic melanoma received repeated UV1 vaccinations, with GM-CSF as an adjuvant, in combination with ipilimumab. Patients were evaluated for safety, efficacy and immune response. Immune responses against vaccine peptides were monitored in peripheral blood by measuring antigen-specific proliferation and IFN-γ production. Results Twelve patients were recruited. Adverse events were mainly diarrhea, injection site reaction, pruritus, rash, nausea and fatigue. Ten patients showed a Th1 immune response to UV1 peptides, occurring early and after few vaccinations. Three patients obtained a partial response and one patient a complete response. Overall survival was 50% at 5 years. Conclusion Treatment was well tolerated. The rapid expansion of UV1-specific Th1 cells in the majority of patients indicates synergy between UV1 vaccine and CTLA-4 blockade. This may have translated into clinical benefit, encouraging the combination of UV1 vaccination with standard of care treatment regimes containing ipilimumab/CTLA-4 blocking antibodies.

  Study EGAS00001005253

• Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

  While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

  Study EGAS00001002499

• Jackson Heart Study (JHS) Cohort

  The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents, aged 35-84, during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (see study history) include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurements, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to update information, confirm vital statistics, document interim medical events, hospitalizations and functional status, and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. Note: Regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP, the coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000286 JHS Cohort. phs000402 ESP Heart GO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARephs001069 MI Gen JHS phs001098 T2D GENES Exome Seq phs001356 Exome Chip phs002256 Cardiometabolic Renal Proteomics phs002369 Metabolomics Insulin Resistance

  Study phs000286

• Kids First: Whole Genome Sequencing in Structural Defects of the Neural Tube

  Myelomeningocele (aka meningomyelocele, MM) is the most severe form of spina bifida, a neural tube defect (NTD) in humans and the most common CNS birth defect. MM is considered a genetically complex disease, and occurs in 3.72/10,000 live US birth, and is partly preventable with prenatal folate, but the genetic basis and the mechanisms by which folate work to reduce disease incidence remain obscure. MM is associated nearly uniformly with prenatal hydrocephalus and the Arnold-Chiari malformation, as well as paraplegia and lifelong neuromotor disability. The genes for several rare syndromic forms of NTDs are known, but the causes for the majority with sporadic MM remain unknown. Despite the importance of MM, most previous research has been limited to targeted sequencing and association studies of folate metabolism genes, or very small-scale exome sequencing. We hypothesize that de novo mutations (DNMs) produce likely gene disrupting (LGD) events that contribution to MM risk. Using conservative estimates of between 50-100 recurrently mutated discoverable genes contributing to risk, and our preliminary data demonstrating an excess of LGD DNMs in MM compared with control individuals, we estimate that with a cohort size of 1000 trios, we should uncover between 5-20 new recurrently mutated genes underlying MM, with minimal false-discovery. With this in mind, we formed the Spina Bifida Sequencing Consortium, and established a platform for data and sample sharing. Preliminary analysis of our first batch of 100 trios analyzed by WGS from GMKF suggests a wealth of important gene mutations. We have embarked on a new recruitment effort of an additional cohort of 400 new simplex MM trios, in collaboration with the US Spina Bifida Association, consented trios to allow for data sharing, and have performed detailed sample quality control. We also have preliminary data that use of dried bloodspot DNA from trios performs comparably to whole blood DNA, so will be happy to swap saliva for bloodspot recruitment at NIH's preference. This cohort is now half-way assembled, with the remaining cohort to be ascertained in the next 6 months. We have established a workflow for de novo SNP/INDEL/SV detection from WGS and have ample computer storage and nodes to see the project to completion. We also plan to continue recruitment into the future with the goal of 2000 trios in the next 5 years. We propose a detailed bioinformatics workflow to identify gene mutations within a statistical framework, considering detailed scRNA expression profiling from developing mammalian neural tube, and have developed a robust functional validation workflow using Xenopus and mouse gene targeting. Our project has the potential to uncover a host of causes for this most common of the CNS birth defects, paving the way for future breakthroughs in detection, treatment, and prevention.

  Study phs002591

• Population Genetic Testing and SERPINA1 Sequencing Identifies Unidentified Alpha-1 Antitrypsin Deficiency Alleles and Gene-Environment Interaction with Hepatitis C Infection

  Design and aims: Data were available through an institutional effort to combine de-identified electronic health records (EHR) data with genomic information from a DNA biobank. The design of this work was a retrospective cohort study in which we investigated the rates of liver transplantation and hepatitis C infection as it relates to genotype risk for alpha-1 antitrypsin deficiency (AATD). We used regression analysis to look for relationships between these risks and outcomes. This led to further investigation of environmental exposures and phenotypes as it related to the underlying genotypic risk. Population information: The cohort consisted of 72,027 individuals of European ancestry for whom genotype and EHR data were available. Molecular technologies employed: Genome-wide genotyping was previously performed using the Illumina Infinium Expanded Multi-Ethnic Genotyping Array plus custom content (referred to as the Vanderbilt University Medical Center BioVU MEGAEX). Individuals' AATD-related alleles were inferred from the genotyping data. Principal findings of the study: Liver transplantation was associated with presence of the Z AATD allele and with hepatitis C infection. There was a significant interaction between AATD genotype groups and hepatitis C infection as it related to liver transplantation. Data available through dbGaP: Inferred AATD genotype status, sex, age, length of EHR in years, presence/absence of AATD clinical diagnosis, liver transplant status, and hepatitis C infection status.

  Study phs003297

• eMERGE Geisinger eGenomic Medicine (GeM) - MyCode Project Controls

  A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patient agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. For the initial eMERGE Geisinger eGenomic Medicine (GeM) genotyping project, a subset of 1,232 unique samples were genotyped using Illumina HumanOmniExpress-12 v1.0 arrays, and used as population controls for other Geisinger Clinic case cohorts, including abdominal aortic aneurysm and gastric bypass surgery cases. These samples were selected from a larger subset of approximately 6,000 MyCode DNA samples using a partial matching algorithm that included age, sex, and body mass index as variables.

  Study phs000381

• Heterogeneity in Lysosomal Storage Disorders

  Gaucher disease (GD) is an inherited lysosomal storage disorder caused by biallelic pathogenic variants in GBA1, which encodes glucocerebrosidase. Additionally, GBA1 variants are a well-established genetic risk factor for Parkinson's disease (PD), leading some PD research centers to incorporate GBA1 screening to identify patients who may benefit from targeted therapeutics. However, detecting GBA1 variants remains challenging due to the gene's high sequence homology with its pseudogene, which can give rise to complex recombinant alleles. This study evaluates the performance of Gauchian, a recently developed software tool for identifying GBA1 variants from whole genome sequencing (WGS) data. The assessment was conducted in a cohort of 90 individuals with GD and five GBA1 heterozygotes, all previously characterized through Sanger sequencing. While Gauchian successfully identified the most common genotypes, it demonstrated limitations in detecting rare or de novo variants due to its restricted internal database and heavy reliance on intergenic structural variants. These limitations led to misclassified homozygosity, incomplete genotyping, and undetected recombination events, ultimately reducing the tool's utility for comprehensive variant screening and precluding its application in diagnostic settings. The study dataset includes WGS from the 90 individuals used in the Gauchian pipeline. This data will be available through dbGaP to facilitate further research on GBA1 variant detection, genotype-phenotype correlations in GD and PD, and the development of improved bioinformatics tools for complex variant identification.

  Study phs003459

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• Double mutant DNMT3A AML: a unique subtype

  Mutation of DNMT3A, encoding a de novo methyltransferase essential for cytosine methylation, is a common early event in clonal hematopoiesis (CH) and adult acute myeloid leukemia (AML). Spontaneous deamination of methylated cytosines damages DNA, which is repaired by the base excision repair (BER) enzymes MBD4 and TDG. Congenital MBD4-deficiency has been linked to early-onset CH and AML, and is marked by exceedingly high levels of DNA damage and mutation of DNMT3A. Strikingly, wildtype (WT) DNMT3A binds TDG, thereby potentiating its repair activity. Since TDG is the only remaining BER enzyme in MBD4-deficient AML patients capable of repairing methylation damage, we investigated whether mutant DNMT3A negatively affects the repair function of TDG. We found that, whereas WT DNMT3A stimulates TDG function, mutant DNMT3A impairs TDG-mediated repair of DNA damage in vitro. In light of this finding and to extrapolate our observations to the broader AML patient population, we investigate here the genetic profiles and survival outcomes of AML patients with single (SM) versus double mutant (DM) DNMT3A. DM DNMT3A AML patients show a characteristic driver mutation landscape and reduced overall survival when compared to SM DNMT3A AML patients. Importantly, whole-genome sequencing showed a trend for increased DNA damage in primary DM DNMT3A AML samples, especially when DNMT3A mutations are located at the DNMT3A-TDG interaction interface.

  Study EGAS00001007966

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Cross-site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms of CIMAC-CIDC Network

  The Cancer Immune Monitoring and Analysis Centers (CIMACs) and the Cancer Immunologic Data Commons (CIDC)  has engaged in efforts to harmonize Whole-exome (WES) and RNA-sequencing (RNA-seq) data from three different experimental platforms (MD Anderson, NCI MoCha lab, and Broad Institute) and are using a series of developed pipelines to process the early trial samples. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the CIMACs-CIDC conducted a systematic harmonization study. DNA and RNA were centrally extracted from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) non-small cell lung carcinoma (NSCLC) tumors and distributed to three centers for WES and RNA-seq profiling

  Study phs002295

• Test dataset: Sequence and variant data from public 1000 Genomes Project

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 2508 samples from the 1000 Genomes Project (https://www.nature.com/articles/nature15393). Samples' (e.g. NA18534) data can be accessed through the IGSR portal (e.g. https://www.internationalgenome.org/data-portal/sample/NA18534) or their corresponding folder at the 1000 Genomes' FTP site (e.g. http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/data/CHB/NA18534/exome_alignment/). There are several different types of data this dataset encompasses: Variant Calling Format (VCF, or its binary counterparts BCF) files, both joint (e.g. ALL_chr22_20130502_2504Individuals.vcf.gz) and split (HG01775.chrY.vcf.gz); exome sequencing CRAM files (e.g. NA18534.GRCh38DH.exome.cram); whole genome sequencing CRAM/BAM files (e.g. NA19239.cram). Additionally, there are multiple files that were sliced to create shorter files, which allows for a quick download, formated as "{FILE-INFO}__{NUMBER-OF-READS}r__{CHR}.{START-COORDINATE}-{END-COORDINATE}.{FILETYPE}" (e.g. "HG01500.GRCh38DH__90r__3.10000-10500__4.10000-10500.cram"). These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client).

  Dataset EGAD00001003338

• TSO500 STJAN33, BRAF mutated CUP

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

  Dataset EGAD50000000689

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

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

  Dataset EGAD00001008108

• Phenotype Risk Scores Identify Patients with Unrecognized Mendelian Disease Patterns

  This study was designed to assess the phenotypic effects of rare variants. Rare variants are difficult to study in a high-throughput manner because most cohorts are underpowered to detect associations. In order to gain power to test rare variants, we use Phenotype Risk Scores (PheRS) based on features of Mendelian diseases. PheRS is calculated using claims data from an EHR that is mapped to clinical features from OMIM's clinical descriptions of Mendelian disease. We calculated PheRS for 1,204 Mendelians diseases in a cohort of 21,701 individuals genotyped on the HumanExome BeadChip. We then tested for association between these diseases and rare variants in causal genes. A phenotype risk score is calculated as the weighted sum of features for a given disease. The features are defined as a set of phecodes (consolidated ICD codes) associated with a particular Mendelian disease as described in OMIM. The weights for each phecode are calculated as the log inverse prevalence of the phecode in our cohort. For an individual, their score equals the sum of the weights for each phecode that is present in their medical record. Our study was based on a cohort of individuals with genotype data linked to de-identified electronic health records (EHR) from Vanderbilt's BioVU resource. We hope that this method will help generate phenotype-genotype correlation data on rare variants which in turn may inform rare variant interpretations use for diagnostics.

  Study phs001516

• Cancer-associated fibroblasts promote drug resistance in ALK-driven lung adenocarcinoma cells by upregulating lipid biosynthesis

  Targeted therapy interventions using tyrosine kinase inhibitors (TKIs) provide encouraging treatment responses in ALK-rearranged lung adenocarcinomas, yet resistances occur almost inevitably. Apart from tumor cell-intrinsic resistance mechanisms, accumulating evidence supports a role of cancer-associated fibroblasts (CAFs) in affecting the therapeutic vulnerability of lung cancer cells. Here, we aimed to investigate underlying molecular networks shaping the therapeutic susceptibility of ALK-driven lung adenocarcinoma cells via tumor microenvironmental cues using three-dimensional (3D) spheroid co-culture settings. We show that CAFs promote therapy resistance of lung tumor cells against ALK inhibition by reducing apoptotic cell death and increasing cell proliferation. Using single-cell RNA-sequencing analysis, we show that genes involved in lipogenesis constitute the major transcriptional difference between TKI-treated homo- and heterotypic lung tumor spheroids. CAF-conditioned medium and CAF-secreted factors HGF and NRG1 were both able to promote resistance of 3D-cultured ALK-rearranged lung tumor cells via AKT signaling, which was accompanied by enhanced de novo lipogenesis and supression of lipid peroxidation. Notably, simultaneous targeting of ALK and SREBP-1 was able to overcome the established CAF-driven lipid metabolic-supportive niche of TKI-resistant lung tumor spheroids. Our findings highlight a crucial role of CAFs in mediating ALK-TKI resistance via lipid metabolic reprogramming and suggest new ways to overcome resistance towards molecular directed drugs by targeting vulnerabilities downstream of oncogenic signaling.

  Study EGAS50000000135

• Enhanced Adjuvanticity of a Personal Neoantigen Vaccine Generates Potent Neoantigen-Specific Immunity

  Personalized neoantigen-targeting vaccines can induce durable and diverse T cell responses and have been associated with improved outcomes. To augment immunogenicity, we tested a synthetic long peptide vaccine formulated with the adjuvants Montanide and poly-ICLC in 10 patients with melanoma. The vaccines, co-administered locally with ipilimumab and systemically with nivolumab, generated de novo ex vivo T cell responses against the majority of immunizing neoepitopes in all 9 fully vaccinated patients, and ex vivo CD8+ T cell responses in 6 of 9. Hundreds of circulating and intratumoral T cell receptor (TCR) clonotypes emerged following vaccination that were distinct from those arising after PD-1 inhibition. By linking vaccine-specificity and cellular phenotype of TCRs in post-treatment tumors at single cell resolution, we demonstrate remodeling of the intratumoral T cell repertoire following vaccination. These observations demonstrate the impact of multi-pronged immune adjuvanticity on the T cell repertoire in the context of neoantigen-targeting vaccines. We are submitting WES data from whole blood samples and tumor FFPE samples, and RNA-seq data from tumor FFPE samples. We are also submitting RNA-seq data from purified tumor samples. scRNA-seq data will also be submitted for skin samples (pre and post neoantigen vaccine dose #3), and tumor samples before starting treatment, before starting neoantigen vaccine Dose #1, and before neoantigen vaccine dose #4. Bulk TCR-seq data will be submitted for blood samples.

  Study phs003919

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• Small variants in mtDNA Canary Islands - WES Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005678

• Small variants in mtDNA Canary Islands - WGS Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005679

• Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005677

• Integrative genome profiling in AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Dataset EGAD00001001873

• National Institute on Aging (NIA) Late-Onset Alzheimer's Disease Genetics Initiative: The Multiplex Family Study

  Multiplex Family StudyThe purpose of the NIA Genetics Initiative: Multiplex Family Study is to identify families with multiple members diagnosed with late-onset Alzheimer's Disease. Families will be characterized clinically and blood samples will be collected to establish cell lines. If a blood sample is not available, autopsy samples will be collected for DNA extraction and storage. Our goal is to recruit 1,000 families over the course of the study. Clinical and demographic data from these families will be collected at the local site and coded data, without identifiers, will be sent and included in a national database of families with Alzheimer's Disease. This database, along with the biological samples, will be housed at the National Cell Repository for Alzheimer's Disease (NCRAD) at Indiana University. The Center or provider and the Cell Repository must sign a Material Transfer Agreement for shipment of biological samples and phenotypic data to NCRAD. The biological samples and data from these families will be available to qualified researchers, who must sign a Material Transfer Agreement before receiving DNA and data. An oversight committee known as the Cell Bank Advisory Committee (CBAC) will review and monitor the process of family identification and enrollment, data collection, the establishment of cell lines and access to samples. LOAD CIDR ProjectThe first 362 families of the Multiplex Family Study (including 2,105 family members) were included in a 6K SNP genome-wide scan at the NIH-supported, Center for Inherited Disease Research (CIDR). An additional 297 unrelated, healthy controls were also genotyped at CIDR. The average age of onset of AD in the genotyped sample is 74 years and 62% of the sample is women. While primarily Caucasian, 3% are African-American, and 3% are of Hispanic ancestry. 72% of the families had at least 2 affected siblings, whereas 21% had 3 or more sampled affected individuals and 7% had 4 or more genotyped, affected family members.

  Study phs000160

• Autism Sequencing Consortium (ASC)

  The ARRA Autism Sequencing Collaboration was created in 2010 bringing together expert large-scale sequencing center (at the Baylor College of Medicine, PI Richard Gibbs and the Board Institute of MIT and Harvard, PI Mark J. Daly) and a collaborative network of research labs focused on the genetics of autism (brought together by the Autism Genome Project and the Autism Consortium). These groups worked together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes. The Autism Sequencing Consortium (ASC) was founded by Joseph D. Buxbaum and colleagues as an international group of scientists who share autism spectrum disorder (ASD) samples and genetic data. The PIs are Drs. Joseph D. Buxbaum (Icahn School of Medicine at Mount Sinai), Mark J. Daly (Broad Institute of MIT and Harvard), Bernie Devlin (University of Pittsburgh School of Medicine), Kathryn Roeder (Carnegie Mellon University, Matthew State and Stephan Sanders (University of California, San Francisco). The rationale for the ASC is described in Buxbaum et al. 2012, and this paper should be cited when referencing the data set. All shared data and analysis is hosted at a single site, which enables joint analysis of large-scale data from many groups. The ASC was first supported by a cooperative agreement grant to four lead sites funded by the National Institute of Mental Health (U01MH100233, U01MH100209, U01MH100229, U01MH100239), with additional support from the National Human Genome Research Institute. The NIMH recently renewed their support with a second grant (U01MH111661, U01MH111660, U01MH111658 and U01MH111662) to expand the project from 29,000 genomes to more than 50,000 exomes over the next 5 years. NHGRI provides ongoing sequencing support for the ASD through the Broad Center for Common Disease Genomics (UM1HG008895, Mark Daly, PI).

  Study phs000298

• Human Dorsal Root Ganglion RNA Landscape Profiling for Neuropathic and Chronic Pain

  Bulk and spatial RNA sequencing were performed on human Dorsal Root Ganglia (DRGs), peripheral sensory nerves and nodose ganglia and relative gene abundances were calculated. Various analyses were performed: Human DRG gene expression profiles were contrasted with a panel of gene expression profiles of relevant tissues in human and mouse (integrating, among other sources, datasets from ENCODE and GTex) in order to identify. DRG-enriched gene expression, co-expression modules of DRG-expressed genes, and key transcriptional regulators in humans. Contrasting the human and mouse DRG transcriptomes to identify DRG-enriched gene expression patterns that were conserved between human and mouse, identifying putative cell types of expression of these genes, and potential known drugs that might target the corresponding gene products. Characterization of non-coding RNA profile of human and mouse DRGs. Characterization of DRG-enriched alternative splicing and alternative transcription start site usage based transcript variants in humans and mouse, and the overlap between these two species. Contrasting of human DRG and GTex human tibial nerve samples to identify putative axonally transported mRNAs in sensory neurons. Human DRG and peripheral nerves transcriptomes from donors suffering from neuropathic and/or chronic pain were contrasted with controls to identify. Differentially expressed genes, pathways and regulators path play a potential role in neuronal plasticity, electrophysiological activity, immune signaling and response. Predictive models (Random Forests) were built to jointly predict the sex and pain state of samples based on information contained solely in autosomal gene expression profile. Gene co-expression modules were identified and gene set enrichment analysis performed.to identify sample - pathway associations, and to broadly characterize plasticity in human DRG cell types. Spatial transcriptomics was performed on human DRGs and nodose ganglia to obtain near single-neuron resolution. We identified distinct clusters of human DRG sensory neurons. We characterized the expression of different gene families (e.g., GPCRs, sodium channels, potassium channels, etc.). We investigated differences between male and female neurons.

  Study phs001158

• Environmental Arsenic and Diabetes Mellitus (Chihuahua Cohort)

  The Chihuahua Cohort was established as part of a larger NIEHS-funded project that used laboratory models (tissue culture and mice) and human subjects to examine the association between exposure to arsenic and diabetes, including identification of mechanisms underlying this association. All procedures involving human subjects were approved by institutional review boards at the University of North Carolina at Chapel Hill and Cinvestav-IPN (Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico City, Mexico). All participants provided signed informed consent. A total of 1,160 adults (≥ 18 years old) with a minimum 5-year uninterrupted residency in the Chihuahua study area were recruited between 2008 and 2012. Samples of drinking water were obtained from the participants' households. Data on residency, occupation, drinking-water sources and use, smoking, alcohol consumption, and medical history were recorded by a study questionnaire. Spot urine and fasting venous blood were collected during medical examination that included an oral glucose tolerance test (OGTT) with blood drawn 2 hr after a 75-g glucose dose. Plasma from both fasting and 2-hr blood samples was collected. Body mass index (BMI) of each participant was calculated from body weight and height. BMI cutoffs of ≥ 25.0, ≥ 30, and < 18.5 kg/m2 were used to define overweight, obese, and underweight individuals, respectively. Participants' waist circumference was also measured. Blood pressure was assessed using a manual sphygmomanometer. Three measurements were taken at intervals of at least 1 min, with a 5-min rest before obtaining the first reading; the mean of the last two measurements was used. The concentrations of arsenic in drinking water and arsenic species in urine were measured by hydride generation-atomic absorption spectrometry. The limit of detection for As in water as well as for As species in urine was 0.01 µg As/L. Creatinine concentration in urine was determined using an established colorimetric assay. DNA was isolated from blood for genotyping analysis.The following measures were taken: glucose concentration in fasting blood (FBG) and in blood collected 2 hours into OGTT (2HBG); concentrations of triglycerides, HDL and total cholesterol (TC) in fasting plasma; and LDL was calculated using the Friedewald equation. Diabetes was classified by FPG ≥ 126 mg/dL, 2HPG ≥ 200 mg/dL, or self-reported diabetes diagnosis or medication use (WHO/International Diabetes Federation 2006). Prediabetes was defined as the absence of diabetes with FPG ≥ 110 mg/ dL or 2HPG ≥ 140 mg/dL. Elevated fasting levels of each lipid were defined as plasma TG ≥ 150 mg/dL, TC ≥ 200 mg/dL, and LDL ≥ 130 mg/dL. Fasting HDL < 40 mg/dL in men and < 50 mg/dL in women were designated as low. Hypertension was defined by systolic blood pressure (SBP) > 140 mm Hg, diastolic blood pressure (DBP) > 90 mmHg, or self-reported use of anti-hypertensive medication. Genotyping analysis, which will be available in version 2 of this study, was carried out in a subset of ~600 subjects with focus on enzymes involved in the metabolism of arsenic, including AS3MT, GSTs.All data collected during the medical exams or generated by the above-described chemical and biochemical analysis of water, urine and blood/plasma, as well as results of the genotyping analysis are included in dbGaP. Data generated by metabolomics and epigenetic analyses in small subsets of the Chihuahua cohort are not included, but are available in published articles.

  Study phs002139

• A Phase II Neoadjuvant Study of Palbociclib in Combination with Letrozole and Trastuzumab as Neoadjuvant Treatment of Stage II-III ER+ HER2+ Breast Cancer (PALTAN)

  Women with early stage ER+/HER2+ breast cancer (BC) are less likely to achieve pathological complete response (pCR) after chemotherapy with standard of care dual HER2 blockade than patients with ER-/HER2+ BC. Additionally, the toxicity burden of standard systemic therapy is high. Thus, this single arm phase 2 clinical trial investigated a novel de-escalation regimen with trastuzumab, letrozole, and palbociclib in those with early stage ER+/HER2+ BC. The aim was to determine if this treatment regimen will achieve similar pCR rates as conventional treatment and spare women the toxicity burden of regular treatments. The primary endpoint was pCR after 16 weeks of treatment with trastuzumab, letrozole, and palbociclib. Patients with newly diagnosed ER+ HER2+ invasive BC with clinical stages II and III were eligible for this protocol. Research biopsies were performed during the treatment course for whole exome and RNA sequencing, PAM50 molecular subtyping, and Ki67 assessment using immunohistochemistry for complete cell cycle arrest (CCCA: Ki67 ≤2.7%). Results showed a pCR of 7.7% and a rate of residual cancer burden at 0 or I of 38.5%. CCCA was observed in 85% at Cycle 1 day 15 post palbociclib, trastuzumab, and letrozole treatment (C1D15), compared to 27% at surgery after palbociclib was discontinued. PAM50 subtyping identified 31.2% HER2-E, 43.8% Luminal B, 25% Luminal A. 161 genes were differentially expressed comparing C1D15 to baseline. Whole exome and RNA sequencing data will be available through dbGaP.

  Study phs003147

• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided updates on the study.

  Study phs001931

• Transposable Elements in FTLD-TDP and ALS-TDP

  Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease involving the rapid and progressive loss of motor neurons. While a number of inherited mutations have been identified as causing ALS, the vast majority of cases are sporadic with no family history of disease. This has led to the model that ALS may be a complex syndrome with an unknown number of causal molecular pathways. However, nearly all ALS patient tissues display aggregates of the RNA binding protein TDP-43 (TARDBP/TAR DNA-binding protein), and mutations in the gene encoding this protein are known to cause ALS. We show that one of the normal functions of TDP-43 is to bind and regulate retrotransposons, repetitive sequences in the genome that are normally silent, due in part to the function of TDP-43. Furthermore, we demonstrate that many ALS patients with TDP-43 pathology also display de-silencing of retrotransposon RNAs, consistent with a loss of normal TDP-43 function. Those ALS patients that exhibit high levels of retrotransposon expression form a distinct subset of ALS subjects that also show other correlated alterations to the transcriptome. Using unsupervised machine learning algorithms, we identified three distinct molecular subtypes from the whole genomes and transcriptomes of a large cohort of 148 ALS patient samples. The retrotransposon re-activated subset formed 20% of ALS samples; two additional groups displayed signatures of oxidative stress (61%), and glial dysfunction (19%), respectively. Together these results demonstrate that retrotransposon re-activation is common in a subset of ALS patients with TDP-43 pathology.

  Study phs001889

• Count Me In (CMI): The Metastatic Breast Cancer (MBC) Project (CMI-MBCproject)

  Count Me In - The Metastatic Breast Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Breast Cancer Research The Metastatic Breast Cancer Project is a research study that directly engages patients with metastatic breast cancer via social media and advocacy groups and empowers them to accelerate cancer research by sharing their samples and clinical information. Our goal is to create a publicly available dataset of genomic, molecular, clinical, and patient-reported data to enable research. Patients in the US or Canada may register online. Registered patients are sent an online consent form that asks for permission to obtain and analyze their medical records, tumor tissue, saliva, and blood samples. Once enrolled, patients are sent a saliva kit and asked to mail back a saliva sample, which is used to extract germline DNA. Study staff contact participants' medical providers and obtain medical records and a portion of their stored tumor biopsies. Patients may be asked to mail in a blood sample, which is used to extract cell free DNA (cfDNA). Whole exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. Clinically annotated genomic data are used to study specific patient cohorts (including outliers) and to identify mechanisms of response and resistance to therapies. All de-identified data, including genomic, clinical, and patient-reported data, are shared via public databases on a pre-publication and recurring basis as it is generated. The latest data release in cBioPortal is available here. Study updates are shared with participants regularly.

  Study phs001709

• Durable clinical impacts and mechanisms of action and resistance in histone K27 methylation-targeting epigenetic therapy

  Epigenomes allow the rectification of disordered cancer gene expressions, thereby providing new targets for pharmacological interventions in cancer therapy. The clinical utility of targeting histone H3 lysine tri-methylation (H3K27me3) as an epigenetic hallmark has been demonstrated. However, in actual therapeutic settings, the mechanism by which H3K27me3-targeting therapies exert their effects and the response of tumor cells remain unclear. Here we show the potency and mechanisms of action and resistance of a newly developed EZH1/2 dual inhibitor, valemetostat, in the clinical trials of patients with adult T-cell leukemia/lymphoma (ATL). Valemetostat administration reduced the tumor size and demonstrated durable clinical benefits. Integrative single-cell analyses of patients before and after the administration of valemetostat showed that valemetostat abolishes the highly condensed chromatin structure formed by the plastic H3K27me3 and neutralizes multiple gene loci, such as tumor suppressor genes. Nevertheless, subsequent long-term treatment encounters the emergence of resistant clones with reconstructed aggregate chromatin that closely resemble the pre-dose state. The acquired mutations at the EZH2???compound interface result in the propagation of the clones with re-increased H3K27me3. In patients free of this mutation, TET2 mutation or elevated DNMT3A expression causes similar chromatin recondensation through de novo DNA methylation at the H3K27me3-associated regions. We identified subpopulations with distinct metabolic and gene translation characteristics implicated in primary susceptibility until the acquisition of the heritable (epi)mutations. Targeting chromatin homeostasis might provide opportunities for further sustained epigenetic cancer therapies.

  Study JGAS000553

• Prediction and quantification of splice events from RNA-seq data

  Analysis of splice variants from short read RNA-seq data remains a challenging problem. Here we present a novel method for the genome-guided prediction and quantification of splice events from RNA-seq data, which enables the analysis of unannotated and complex splice events. Splice junctions and exons are predicted from reads mapped to a reference genome and are assembled into a genome-wide splice graph. Splice events are identified recursively from the graph and are quantified locally based on reads extending across the start or end of each splice variant. We assess prediction accuracy based on simulated and real RNA-seq data, and illustrate how different read aligners (GSNAP, HISAT2, STAR, TopHat2) affect prediction results. We validate our approach for quantification based on simulated data, and compare local estimates of relative splice variant usage with those from other methods (MISO, Cufflinks) based on simulated and real RNA-seq data. In a proof-of-concept study of splice variants in 16 normal human tissues (Illumina Body Map 2.0) we identify 249 internal exons that belong to known genes but are not related to annotated exons. Using independent RNA samples from 14 matched normal human tissues, we validate 9/9 of these exons by RT-PCR and 216/249 by paired-end RNA-seq (2 x 250 bp). These results indicate that de novo prediction of splice variants remains beneficial even in well-studied systems. An implementation of our method is freely available as an R/Bioconductor package SGSeq.

  Study EGAS00001001026

• The University of Hong Kong Intestinal Metaplasia Organoids Study

  Background: Gastric intestinal metaplasia (IM) is a pre-cancerous stage spanning a morphological spectrum that is poorly represented by human cell line models. Objective: We aim to establish and characterize human IM cell models to better understand IM progression along the cancer spectrum. Design: A large human gastric IM organoid (IMO) cohort (n=28), their clonal derivatives and normal gastric organoids (n=42) for comparison were established. Comprehensive multi-omics profiling and functional characterization were performed. Results: Single-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation. Their lineage trajectories connected different cycling and quiescent stem and progenitors, highlighting differences in gastric to IM transition and the potential origin of IM from STMN1 cycling isthmus stem cells. Hybrid IMOs showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates, and reactivation of a fetal gene program. Cell populations in gastric IM and cancer tissues were highly similar to those derived from IMOs and exhibited a fetal signature. Genomically, IMOs showed elevated mutation burden, frequent chromosome 20 gain, and epigenetic de-regulation of many intestinal and gastric genes. Functionally, IMOs were FGF10 independent and showed downregulated FGFR2. Several IMOs exhibited a cell-matrix adhesion independent (CMi) subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, potentially representing the earliest neoplastic precursor of IM-induced gastric cancer. Conclusions: Overall, our IM organoid biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.

  Study EGAS00001007899