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• DNA Double Strand Breaks in KMT2A-Rearranged AML patients

  DNA breakage at specific rearrangement-participating genes, which are more sensitive to a range of environmental and chemotherapeutic agents than other regions of the human genome, contributes to the generation of leukemia-causing rearrangements, and can be used as a predictor of susceptibility to cancer caused by gene rearrangements. As a direct proof-of-principle regarding the feasibility of employing fragile site breakage to identify and monitor high-risk populations to allow personalized treatments, genome-wide DNA break mapping/sequencing was used to determine whether preferential DNA breaks are generated at the major breakpoint regions of KMT2A in AML remission patients with previously diagnosed KMT2A rearrangement. We are submitting break mapping data from three patients with KMT2A rearrangements and three non-fusion patients, with and without etoposide treatments.

  Study phs002804

• 10x genomics single cell RNA-seq and ATAC-seq from 10 pre-menopausal patients fimbriae and ampullary part of the fallopian tube

  The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.

  Study EGAS50000000628

• 3.5KJPNv2, an allele frequency panel of 3,552 Japanese individuals

  In the Tohoku Medical Megabank Project, we have conducted whole-genome sequencing of nearly 4,000 individuals from a Japanese population, and constructed an allele frequency panel of 3,552 individuals (3.5KJPNv2) after removing genetically related individuals. The 3.5KJPNv2 was constructed by using a standard pipeline including the 1KGP and gnomAD algorithms to reduce technical biases and to allow comparisons to other populations. The 3.5KJPNv2 includes variants in chromosome X and mitochondrial genome as well as autosome. The submitter has changed the access level of this study from controlled-access [Type I] to un-restricted access since 11th, January, 2019. The un-restricted access data ?hum0015.v3.3.5kjpnv2.v1? are available at the NBDC site: https://humandbs.biosciencedbc.jp/en/hum0015-v3. This study does not contain any controlled-access dataset.

  Study JGAS000159

• The NCAA-DoD Concussion Assessment, Research, and Education (CARE) Consortium

  Study Description: Established in 2014, the U.S. Department of Defense (DoD) and the National Collegiate Athletic Association (NCAA) funded the Concussion Assessment, Research and Education (CARE) Consortium to inform science, clinical care and public policy related to concussion and repetitive head impact exposure (HIE) in U.S. Military Service Academy (MSA) cadets and collegiate student-athletes. The primary aims of the initial study were to: (1) establish a multisite research consortium to characterize the effects of concussion and repetitive head impact exposure on brain health, (2) characterize the clinical sequelae and natural history of concussion, (3) characterize the effect of concussion and repetitive head impacts on brain structure and brain function. The 30 member institutions of the CARE Consortium (26 civilian universities/colleges and 4 military service academies) agreed to invite all varsity athletes to undergo multimodal clinical assessments at preseason baseline, and at 5 additional timepoints after concussion diagnosis. At the service academies, non-varsity athlete cadets/midshipmen were also studied. Assessment Categories At Each Time Point Baseline: • Demographics • Personal and Family History • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms ACUTE POST-INJURY FOLLOW-UP (CARE 1.0) (24 hrs; 48hrs; Asymptomatic; Unrestricted Return to Play (RTP); 6 mos) • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms CUMULATIVE & PERSISTENT EFFECTS. (CARE 2.0) In-Person Exit Visit; Post-grad Online • Demographics • Personal and Family History • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms • PROs • MROs (at academies only) LONG-TERM EFFECTS (CARE/SALTOS Integrated (CSI))Annual Online Assessment (at MSAs only); In-Person Research Visits • Demographics • Symptoms • Psychological health • PROs • MROs (at academies only)A subset of athletes at 6 of the CARE institutions underwent additional assessments including multimodal MRI, proteomic and genomic biomarker characterization, and head impact quantification (helmet-based sensors). Assessment time points for the ARC/pARC Neurocognitive and Behavioral Testing was done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), Unrestricted Return to Play, 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career.Blood biomarker collection was done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career. Multi-modal MRI studies were done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career. However, please note that only athletes from one study performance site completed a multi-modal MRI study at baseline.

  Study phs002175

• 86 paired-end MiSeq 16S rRNA sequencing samples

  We compared bacterial communities in breast milk from teen (≤19 yr, n = 26) vs. adult (>19 yr, n = 56) mothers, normal weight (BMI 18.5-24.9, n = 63) vs. overweight (BMI ≥ 25, n = 19) mothers, primiparous (parity = 1, n = 41) vs. multiparous (parity > 1, n = 44), early (5-46d postpartum, n = 39) vs. established lactation (4-6 mo postpartum, n = 45), breastfeeding (EBF: PBF, n = 72) vs. mixed feeding (n = 11) and mothers with (Na/K ratio < 0.6, n = 75) and without SCM (Na/K ration ≥ 0.6, n = 10).

  Dataset EGAD00001004160

• National Sleep Research Resource (NSRR): Cleveland Family Study (CFS)

  The Cleveland Family Study (CFS) is a family-based study of sleep apnea, consisting of 2,284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study began in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. National Institutes of Health (NIH) renewals provided expansion of the original cohort, including increased minority recruitment, and longitudinal follow-up, with the last exam occurring in February 2006. The CFS was designed to provide fundamental epidemiological data on risk factors for sleep disordered breathing (SDB). The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first-degree relatives, spouses and available second-degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first-degree relatives. Each exam, occurring at approximately 4-year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. Currently, data of 710 individuals are available for use through BioData Catalyst (with genotype data available through dbGaP).The National Sleep Research Resource (NSRR) is a NIH-supported sleep data repository that offers free access to large collections of de-identified physiological signals and related clinical data from a large range of cohort studies, clinical trials and other data sources from children and adults, including healthy individuals from the community and individuals with known sleep or other health disorders. The goals of NSRR are to facilitate rigorous research that requires access to large or more diverse data sets, including raw physiological signals, to promote a better understanding of risk factors for sleep and circadian disorders and/or the impact of sleep disturbances on health-related outcomes. Data from over 15 data sources and more than 40,000 individual sleep studies, many linked to dozens if not hundreds of clinical data elements, are available (as of Feb. 2022). Query tools are available to identify variables of interest, and their meta-data and provenance.

  Study phs002715

• Genes for Non-Syndromic Congenital Heart Disease

  Congenital heart defects (CHDs) are the most common serious birth defect and a leading cause of infant mortality. Affected individuals who survive infancy require substantial medical care and experience lifelong morbidity and early mortality. Despite their prevalence and impact upon public health, the etiology of CHDs is poorly understood. Our long-term goal is to better define the genetic basis of CHDs and using this information, develop preventive measures and provide precise medical management based on genotype. As CHDs are a heterogeneous group of conditions, we have focused our studies on cases with conotruncal heart defects (CTDs) that comprise at least 36% of all CHDs and are a prominent feature of the 22q11.2 deletion syndrome (22q11DS). We have conducted both SNP- and CNV-based genome-wide association studies as part of our previous and current P01 (HD070454). Our current analyses of genes and gene-sets provide new insights regarding the contribution of common and rare inherited genetic variants to CTDs. Specifically, based on the results from our studies as well as recently published findings, we hypothesize that: (1) CTDs are influenced by the full range of genetic variability (rare to common; de novo and inherited) in relevant gene-sets; (2) the number of disease-related variants within these gene-sets varies directly with CTD severity; and (3) gene-sets associated with CTDs in nonsyndromic individuals are also associated with CTDs in individuals with the 22q11DS. To augment our existing cohorts and thus substantially improve the statistical power of our proposed analyses, application was made to complete array genotyping of a set of patients with CTDs and in particular, those with mild disease represented by isolated aortic arch anomalies. The new cases with CTD and some with an isolated aortic arch anomaly were ascertained at the Children's Hospital of Philadelphia (CHOP) while some of the cases with isolated aortic arch anomalies were ascertained by the Pediatric Cardiac Genomics Consortium (PCGC). A small group of cases with left-sided obstructive lesions from CHOP were included to combine with our existing datasets to serve as a comparison to those with CTD. The additional genotype data will augment the statistical power of the proposed common variant analyses. We anticipate that this work will reduce the gaps in our understanding of CTDs by identifying an explicit set of genes associated with CTD-risk by way of common variants. This work will also help define the genetic architecture for the full clinical spectrum of these common birth defects.

  Study phs002059

• High density copy number analysis and whole exome sequencing of unselected chronic lymphocytic leukemia cases and of paired chronic lymphocytic leukemia and Richter Syndrome cases

  Analysis of the chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational activation The pathogenesis of chronic lymphocytic leukemia (CLL), the most common leukemia in adults, is still largely unknown since the full spectrum of genetic lesions that are present in the CLL genome, and therefore the number and identity of dysregulated cellular pathways, have not been identified. By combining next-generation sequencing and copy number analysis, we show here that the typical CLL coding genome contains less than 20 clonally represented gene alterations/case, including predominantly non-silent mutations and fewer copy number aberrations. These analyses led to the discovery of several genes not previously known to be altered in CLL. While most of these genes were affected at low frequency in an expanded CLL screening cohort, mutational activation of NOTCH1, observed in 8.3% of CLL at diagnosis, was detected at significantly higher frequency during disease progression toward Richter transformation (31.0%) as well as in chemorefractory CLL (20.8%). Consistent with the association of NOTCH1 mutations with clinically aggressive forms of the disease, NOTCH1 activation at CLL diagnosis emerged as an independent predictor of poor survival. These results provide initial data on the complexity of the CLL coding genome and identify a dysregulated pathway of diagnostic and therapeutic relevance. Genetic Lesions associated with Chronic Lymphocytic Leukemia transformation to Richter Syndrome Richter syndrome (RS) derives from the rare transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, most commonly of the diffuse large B cell type (DLBCL). The molecular pathogenesis of RS is only partially understood. By combining whole-exome sequencing and copy-number analysis of 9 CLL-RS pairs and of an extended panel of 43 RS cases, we show that this aggressive disease typically arises from the predominant CLL clone by acquiring an average of ~20 genetic lesions/case. RS lesions are heterogeneous in terms of load and spectrum among patients, and include those involved in CLL progression and chemorefractoriness (TP53 disruption and NOTCH1 activation) as well as some not previously implicated in CLL or RS pathogenesis. In particular, disruption of the CDKN2A/B cell cycle regulator locus is associated with ~30% of RS cases. Finally, we report that the genomic landscape of RS is significantly different from that of de novo DLBCL, suggesting that they represent distinct disease entities. These results provide insights into RS pathogenesis, and identify dysregulated pathways of potential diagnostic and therapeutic relevance.

  Study phs000364

• Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Dynamic approaches that integrate population-based research and molecular biology are needed to explain the mechanisms underlying pediatric rhabdomyosarcoma (RMS) and to determine novel prevention strategies. RMS, the most common soft-tissue sarcoma in children and adolescents, has one of the poorest 5-year survival rates among all pediatric cancers (less than 65%). One of the strongest risk factors for RMS is having a cancer predisposition syndrome. The syndromes that are most commonly seen among those with RMS are Li-Fraumeni, neurofibromatosis type 1, Costello, Noonan, and DICER1. Based on smaller clinic-based studies, only about 7% of RMS cases are thought to be associated with the genes responsible for these syndromes. However, there have been no population-based assessments to support this estimate. Even in the most recent large-scale evaluations of germline mutations in predisposition genes among children with cancer, very few RMS cases were included (43 cases). Furthermore, no distinctions were made between the major histologic subtypes of RMS: embryonal (eRMS) and alveolar (aRMS), which display differences in terms of age distribution, incidence, and cytogenetics. For instance, nearly 80% of alveolar cases are driven by a chromosomal translocation between either PAX3 or PAX7 and FOXO1, whereas these fusions are not seen in embryonal cases. In fact, RMS research is shifting from categorization based on histology to fusion status (eRMS is overwhelmingly fusion-negative). Another limitation in previous studies has been the inability to evaluate the frequency of de novo germline mutations (DNMs) in cancer predisposition genes due to the absence of any well-characterized cohorts of RMS case-parent trios. Therefore, a major gap in our understanding of the role of cancer predisposition in pediatric RMS that limit translational impact is there have been no population-based assessments to determine the true impact of these mutations on pediatric RMS, which limits clinical sequencing guidelines and surveillance protocols in these children.Overall Project Strategy: The objective of this project is to advance our understanding of the relationship between cancer predisposition genes and pediatric RMS. Our central hypotheses are: 1) mutations in cancer predisposition genes are more common than expected in children with RMS; and 2) children with fusion-negative tumors have a higher burden of germline mutations than those with fusion-positive tumors. The framework for this study relies on >600 well annotated samples collected from newly diagnosed RMS patients and stored in the Children’s Oncology Group (COG) Biopathology Center.

  Study phs002304

• The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program 'CASCADE'

  Background: Understanding the cancer genome is seen as a key step in improving outcomes for cancer patients. Genomic assays are emerging as a possible avenue to personalised medicine in breast cancer. The majority of work in this area has targeted primary tumours however, and very few studies have performed comprehensive profiling of advanced disease. Evolution of the cancer genome during the natural history of breast cancer is largely unknown, as is the profile of disease at death. We sought to study in detail these aspects of advanced breast cancers that have resulted in lethal disease. Methods and Findings: Three patients with ER-positive, HER2-negative breast cancer and one patient with triple negative breast cancer underwent rapid autopsy as part of an institutional prospective community-based rapid autopsy program. Cases represented a range of management problems in breast cancer, including late relapse after early stage disease; de novo metastatic disease; discordant disease response and disease refractory to treatment. Between 5 and 12 metastatic sites were collected at autopsy together with available primary tumours and longitudinal metastatic biopsies taken during life. Samples underwent paired tumour-normal whole exome sequencing and single nucleotide polymorphism arrays. Subclonal architectures were inferred by jointly analysing all samples from each patient. Mutations were validated using high depth amplicon sequencing.Between cases, there were significant differences in mutational burden, driver mutations, mutational processes and copy number variation. Within each case, we found dramatic heterogeneity in subclonal structure from primary to metastatic disease and between metastatic sites, such that no single lesion captured the breadth of disease. Metastatic cross seeding was found in each case and treatment drove subclonal diversification. Subclones displayed parallel evolution of treatment resistance in some cases, and apparent augmentation of key oncogenic drivers as an alternative resistance mechanism. We also observed the key role of mutational processes in subclonal evolution.Limitations of this study include the potential for bias introduced by joint analysis of formalin fixed archival specimens with fresh specimens, and the difficulties in resolving subclones with whole exome sequencing. Other alterations that could define subclones such as structural variants or epigenetic modifications were not assessed. Conclusions: This study highlights the variety of mechanisms that shape the genome of metastatic breast cancer, and the value of studying advanced disease in detail. Treatment drives significant genomic heterogeneity in breast cancers which has implications for disease monitoring and treatment selection in the personalised medicine paradigm.

  Study EGAS00001002153