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• Single-cell RNA-sequencing of a multi-region pleural mesothelioma case

  Single-cell RNA-seq (Smart-Seq2) from 3 distant biopsies (costal, mediastinal, diaphragmatic) of a pleural mesothelioma case.

  Dataset EGAD00001015519

• WGS and RNA-Seq data from a GBM patient PT-AK7565

  WGS and RNA-Seq data from a GBM patient PT-AK7565

  Dataset EGAD00001004224

• WGS and RNA-Seq data from a GBM patient PT-GR2309

  WGS and RNA-Seq data from a GBM patient PT-GR2309

  Dataset EGAD00001004241

• Genome and transcriptome sequence data from a ewing sarcoma tumor patient

  Genome and transcriptome sequence data from a ewing sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015286

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015299

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015298

• WGS and RNA-Seq data from a GBM patient PT-GB9483

  WGS and RNA-Seq data from a GBM patient PT-GB9483

  Dataset EGAD00001004238

• TFL unique case study

  Whole exome sequencing of a normal sample, primary tumor sample, and relapse tumor sample of a transformed non-Hodgkins follicular lymphoma patient with extraordinary response to treatment.

  Dataset EGAD00001002707

• WGS and RNA-Seq data from a GBM patient PT-HN6692

  WGS and RNA-Seq data from a GBM patient PT-HN6692

  Dataset EGAD00001004242

• Bulk exome sequencing of primary GBM - SF 10360

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10360

  Dataset EGAD00001002274

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015305

• Genome and transcriptome sequence data from a metastatic osteosarcoma tumor patient

  Genome and transcriptome sequence data from a metastatic osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015306

• WGS and RNA-Seq data from a GBM patient PT-BK0248

  WGS and RNA-Seq data from a GBM patient PT-BK0248

  Dataset EGAD00001004228

• WGS and RNA-Seq data from a GBM patient PT-LS4891

  WGS and RNA-Seq data from a GBM patient PT-LS4891

  Dataset EGAD00001004252

• WGS and RNA-Seq data from a GBM patient PT-AB0029

  WGS and RNA-Seq data from a GBM patient PT-AB0029

  Dataset EGAD00001004221

• WGS and RNA-Seq data from a GBM patient PT-LR9369

  WGS and RNA-Seq data from a GBM patient PT-LR9369

  Dataset EGAD00001004251

• WGS and RNA-Seq data from a GBM patient PT-JP2405

  WGS and RNA-Seq data from a GBM patient PT-JP2405

  Dataset EGAD00001004247

• WGS and RNA-Seq data from a GBM patient PT-JB1730

  WGS and RNA-Seq data from a GBM patient PT-JB1730

  Dataset EGAD00001004245

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015283

• Genome and transcriptome sequence data from a relapsed osteosarcoma tumor patient

  Genome and transcriptome sequence data from a relapsed osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015311

• Genome and transcriptome sequence data from a synovial sarcoma tumor patient

  Genome and transcriptome sequence data from a synovial sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015313

• Genome and transcriptome sequence data from a ewing sarcoma tumor patient

  Genome and transcriptome sequence data from a ewing sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015315

• Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar tumor patient

  Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015318

• Genome and transcriptome sequence data from a anaplastic astrocytoma tumor patient

  Genome and transcriptome sequence data from a anaplastic astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015319

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015324

• WGS and RNA-Seq data from a GBM patient PT-RL7940

  WGS and RNA-Seq data from a GBM patient PT-RL7940

  Dataset EGAD00001004258

• Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015329

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015330

• Genome and transcriptome sequence data from a pIlomyxoid astrocytoma tumor patient

  Genome and transcriptome sequence data from a pIlomyxoid astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015333

• Genome and transcriptome sequence data from a wilms tumor tumor patient

  Genome and transcriptome sequence data from a wilms tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015334

• Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar tumor patient

  Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015335

• Genome and transcriptome sequence data from a infantile fibrosarcoma tumor patient

  Genome and transcriptome sequence data from a infantile fibrosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015263

• Genome and transcriptome sequence data from a CNS sarcoma tumor patient

  Genome and transcriptome sequence data from a CNS sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015268

• Genome and transcriptome sequence data from a ocular melanoma tumor patient

  Genome and transcriptome sequence data from a ocular Melanoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015269

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015279

• Parkinson's Disease Cognitive Genetics Consortium (PDCGC) Stage I, NeuroX Dataset

  Cognitive impairment is a common and disabling problem in Parkinson's disease (PD). Identification of genetic variants that influence the presence or severity of cognitive deficits in PD might provide a clearer understanding of the pathophysiology underlying this important nonmotor feature. We are presently undertaking a large-scale, two-stage study designed to identify genetic risk factors for cognitive impairment in PD. The study population is divided into a discovery (Stage I) and a validation (Stage II) sample of patients enrolled in the PD Cognitive Genetics Consortium (PDCGC). Each patient has undergone a detailed neurological evaluation and cognitive testing. Clinical and genetic data for the project are stored and managed at the Coordinating Center at the University of Washington and VA Puget Sound Health Care System in Seattle. Stage I of the project is now complete; 1,219 PD patients were genotyped for 249,336 variants using the NeuroX array. Participants underwent assessments of learning and memory (Hopkins Verbal Learning Test-Revised [HVLT-R]), working memory/executive function (Letter-Number Sequencing and Trail Making Test [TMT] A and B), language processing (semantic and phonemic verbal fluency), visuospatial abilities (Benton Judgment of Line Orientation [JoLO]), and global cognitive function (Montreal Cognitive Assessment). We excluded individuals who were of non-European ancestry, failed genotyping, were missing data for one or more covariates, were related to another participant in the cohort, or failed to complete at least half of the cognitive tests. After these quality control measures were implemented, 1,105 participants remained and were included in all subsequent analyses. For common variants we used linear regression to test for association between genotype and cognitive performance with adjustment for important covariates. Rare variants were analyzed using the optimal unified sequence kernel association test. The significance threshold was defined as a false discovery rate corrected P-value (PFDR) of 0.05. Eighteen common variants in 13 genomic regions exceeded the significance threshold for one of the cognitive tests. These included GBA rs2230288 (E326K; PFDR = 2.7 x 10-4) for JoLO, PARP4 rs9318600 (PFDR = 0.006) and rs9581094 (PFDR = 0.006) for HVLT-R total recall, and MTCL1 rs34877994 (PFDR = 0.01) for TMT B-A. Analysis of rare variants did not yield any significant gene regions. We have conducted the first large-scale PD cognitive genetics analysis and nominated several new putative susceptibility genes for cognitive impairment in PD. These results will require replication in independent PD cohorts, and efforts to validate the findings in PDCGC Stage II are in progress.

  Study phs001664

• Starr County Health Studies' Genetics of Diabetes Study

  An initial observation in the 1970s that Starr County, Texas, had the highest diabetes-specific mortality of any of the 254 Texas counties led to the establishment of a field office in Rio Grande City, Texas (the county seat of Starr County) and the initiation of a series of studies to understand the epidemiology and genetics of type 2 diabetes, its complications and related conditions in this predominantly (97%) Mexican American population. The field office opened in February 1981 and has operated continuously since then. During this time, three systematic surveys of the population have been conducted as well as family and longitudinal studies. Culturally sensitive diabetes education programs have been developed and implemented and also a weight loss intervention. In total, more than 23,000 Mexican American individuals have been examined with more than 200,000 aliquots of biological specimens stored. Collectively, these studies are known as the Starr County Health Studies. The present Genetics of Diabetes Study has the goal of identifying loci/alleles that underlie susceptibility to type 2 diabetes in this high risk population using genome wide markers and association testing. The study makes use of two primary resources that have been developed in order to identify 1,000 type 2 diabetes cases and 1,000 disease free controls. In the first instance we have identified a subset of unrelated cases from the total cases that we have identified. Where multiply affected sibships were available, the youngest onset case with detailed phenotyping (including assessment of diabetic retinopathy) was selected. Controls came from a recent survey to establish a representative sample of the Starr County population. Blocks were randomly selected, households on selected blocks enumerated and one individual randomly selected from each household for a detailed examination. The examination included an oral glucose tolerance test. Those included as controls are those with no prior diagnosis of diabetes and a negative oral glucose tolerance test. This collection of cases and controls provides the opportunity to identify susceptibility loci for type 2 diabetes and its complications, specifically diabetic retinopathy and albuminuria. The data set also allows the examination of impaired fasting glucose and impaired glucose tolerance. The samples are split between those born in the United States and those born in Mexico and this gives a natural contrast for examining genotype and environmental interactions. It is anticipated that the understanding that will come will lead to strategies for delaying and preventing the onset of diabetes and its complications.

  Study phs000143

• The Lung Genomics Research Consortium (LGRC)

  Chronic lung diseases represent a broad spectrum of chronic fibrosing/inflammatory lung conditions that are for the most part poorly responsive to treatment and often fatal. COPD/emphysema is the fourth leading cause of death in the United States and the incidence and rate of death from pulmonary fibrosis is increasing each year. Although progress has been made in interpretation of the clinical, radiological, and pathological features of chronic lung disorders, and progress in determining the pathobiology continues, the causes, biologic mechanisms, and therapeutic options remain obscure. Moreover, predicting individuals or populations at risk for developing any of these complex diseases, at present, is not possible. To address this challenge, we plan to create a genetic, molecular, and quantitative clinical phenotyping data warehouse with bioinformatic tools that will empower investigators to make fundamental discoveries in disease pathogenesis, refine diagnostic criteria, and lead to real gains in personalized medicine. The composite genetic, genomic, and epigenetic signature combined with quantitative clinical phenotypes has the potential to characterize the dynamic biological state of a complex disease and complement existing diagnostic approaches that are reliant on traditional clinical measures of disease. In the proposed project, we plan to extend the scope and impact of the NHLBI Lung Tissue Research Consortium (LTRC) biorepository by creating the Lung Genomics Research Consortium (LGRC), a comprehensive genetic, molecular, and quantitative clinical phenotyping warehouse. Our overall hypothesis is that a genetic, molecular, and quantitative clinical phenotyping warehouse combined with a rich clinical database will enable the lung research community to make fundamental discoveries in disease pathogenesis, refine diagnostic criteria, and lead to real gains in personalized medicine. We plan to pursue this hypothesis through the following aims. Specific Aim 1: Establish a genetic, genomic, and epigenetic molecular library to complement the existing clinical database in the LTRC. Specific Aim 2: Develop a quantitative clinical phenotyping platform using existing LTRC data, as well as an enhanced data set including novel quantitative CT and histology imaging analyses. Specific Aim 3: Establish a publicly-accessible database that would integrate the genetic, molecular, and quantitative phenotyping data with the existing clinical data in the LTRC and provide query and data exploration tools that are easily accessible to the lung research community. These discoveries will enable clinicians to Identify individuals at risk of developing chronic lung diseases; Diagnose these conditions earlier; Identify novel mechanisms that cause these diseases; Reclassify disease entities into categories more representative of molecular and cellular pathogenic mechanisms regardless of traditional disease categories; develop personalized approaches to treatment.

  Study phs000624

• Assessing Neural Mechanisms of Injury in Inborn Errors of Urea Metabolism Using Structural MRI, Functional MRI, and Magnetic Resonance Spectroscopy

  Urea cycle disorders represent a group of rare inborn errors of metabolism that lead to accumulation of ammonia, a toxic product of protein metabolism. Individuals with urea cycle disorders cannot metabolize the ammonia that accumulates due to enzyme deficiency. The symptoms of these disorders may present at birth, childhood or adulthood (milder deficiencies). There are currently eight enzyme deficiencies that constitute the range of inborn errors of ureagenesis. This project will focus on the most common enzyme disorder of the urea cycle, ornithine transcarbamylase deficiency, inherited as an X-linked trait. This project will study cognitive and motor dysfunction in patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non -invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies will range from ages 18-60 years and will be compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

  Study phs001108

• Randomized Evaluation of Sedation Titration for Respiratory Failure (RESTORE-BioLINCC)

  Data Access NOTE Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The primary aim of the RESTORE clinical trial was to determine whether critically ill children managed with a nurse-implemented, goal-directed sedation protocol would experience fewer days of mechanical ventilation than participants receiving usual care. Background Ensuring the safety and comfort of critically ill infants and children supported by mechanical ventilation is integral to the practice of pediatric critical care. Although sedation therapy benefits young participants who cannot understand the imperative nature of invasive life-sustaining therapies, sedative use is also associated with untoward adverse effects. Specifically, opioids and benzodiazepines commonly used for pediatric sedation may impair bedside neurological assessment, depress spontaneous ventilation, and prolong mechanical ventilation. Over time, drug tolerance develops, which may precipitate iatrogenic withdrawal syndrome when sedation therapy is no longer necessary.Numerous studies in adult critical care support a minimal yet effective approach to sedation management. Sedation goals for mechanically ventilated adults have shifted from an unresponsive state to a calm, easily aroused, readily evaluated participant. Studies in adult participants evaluating targeted sedation, daily interruption and/or titration of sedation, pairing of spontaneous awakening with breathing, and no sedation have reported improved clinical outcomes, including decreased length of mechanical ventilation when compared with usual care. In contrast, few data inform sedation practices in pediatric critical care, and international studies describe significant practice variation. Given unique biobehavioral differences, knowledge generated in adult critical care may not translate to the care of critically ill children. The RESTORE study was conducted to test the effect of a nurse-implemented, goal-directed sedation protocol on clinical outcomes in pediatric participants with acute respiratory failure. Participants There was a total of 2,449 participants (mean age: 4.7 years; range: 2 weeks to 17 years). Design The RESTORE study was a cluster randomized clinical trial conducted in 31 US PICUs. Intervention PICUs (17 sites; 1,225 participants) used a protocol that included targeted sedation, arousal assessments, extubation readiness testing, sedation adjustment every 8 hours, and sedation weaning. Control PICUs (14 sites; 1,224 participants) managed sedation per usual care. The primary outcome variable was duration of mechanical ventilation. Conclusions Among children undergoing mechanical ventilation for acute respiratory failure, the use of a sedation protocol compared with usual care did not reduce the duration of mechanical ventilation. Exploratory analyses of secondary outcomes suggest a complex relationship among wakefulness, pain, and agitation (JAMA 2015; 313(4):379-89).

  Study phs003783

• The EGA Helpdesk team: 2025 in review and what we are building next

  Behind every dataset submitted, every access request processed, and every technical question answered, there is a team working quietly to keep things moving: the Helpdesk (HD). With the onset of 2026, this feels like the right moment to look back on what 2025 has been like for the HD team: the challenges we faced, how we adapted, and where we're heading next. Why the Helpdesk matters to EGA The EGA Helpdesk is more than a support channel. It plays a key role in maintaining trust in the EGA ecosystem. By supporting data submitters, researchers, Data Access Committees (DACs), and institutional partners, the HD helps ensure that data can flow securely, efficiently, and reliably. When issues arise, the Helpdesk is often the first place where their impact is felt and addressed. In that sense, the HD sits at the intersection of technology, policy, and people. One Helpdesk, two locations, one shared mission The EGA Helpdesk is a joint, distributed team working closely across two locations: CRG (Barcelona, Spain) and EMBL-EBI (Cambridge, UK). Although we are based in different institutions, we operate as a single Helpdesk, with shared workflows, priorities, and responsibility towards users. At CRG, the HD team is formed by: Andrea Max Àlex and me At EMBL-EBI, we work closely with: Silvia Coline Aravind What defines us as a team is simple: we work user-first, even under pressure. In a highly technical environment, clarity, empathy, and consistency matter just as much as tools and processes. A close collaboration across sites is essential to making that happen. What does the EGA Helpdesk do? The HD supports users across the full lifecycle of data in EGA. This includes: Data submissions, uploads, and encryption workflows. Data access requests and permissions. Questions around policies, consent, and data usage. Technical and system-related issues. Coordination between users, internal teams, and external partners. 2025: growth, change, and recalibration 2025 was a year of growth, but not always a predictable one. Early in the year, several technical and system-related challenges required us to adjust our original plans. Priorities shifted, timelines changed, and some improvements had to be rethought. For the HD team, this is often the hardest part of the job: we see delays through the eyes of users and understand the real impact they can have on ongoing research. One of the key lessons from 2025 was that stability is not only a technical challenge, but also an organisational one. Teamwork proved to be essential: anticipating peak periods, sharing context early, and coordinating closely across teams made a tangible difference. When things became complex, working together across roles and locations was what allowed us to keep moving forward. In 2025, the Helpdesk received 5.313 tickets and resolved 5.511 requests, reflecting both increased adoption of EGA and the team’s ability to absorb higher demand. At the same time, demand continued to grow. Compared to 2024, ticket creation increased by over 6%, while resolution capacity grew by more than 11%. The team not only kept up with incoming requests but also resolved part of the accumulated backlog, finishing the year having solved more tickets than were created. The real challenge of 2025 was not overall performance, but how the workload was concentrated during peak months. Seasonality and demand spikes placed pressure on the system, even while overall efficiency remained strong. On a team level, 2025 was also a year of transition. I joined the HD leadership role in January 2025, stepping into a period of change and rapid learning. Later in the year, in October, we said goodbye to Raül, and in January 2026, we welcomed Àlex, strengthening the team for the next phase. What users needed most in 2025 While requests vary widely, some themes stood out throughout the year: Support with data submissions and uploads Data access requests and permissions Technical and system-related issues As EGA matures, day-to-day operations have become more complex. Many long-running tickets are not delayed due to a lack of follow-up, but because they depend on external approvals, cross-institutional coordination, or multi-step processes. Understanding these patterns helps us focus not just on resolving tickets, but on improving how work flows through the system. Looking ahead to 2026 With a reinforced team and clearer insights from 2025, our focus for 2026 shifts from throughput to flow. Key priorities include: Strengthening our web content and documentation Reducing structural backlog Improving cross-team and cross-system coordination Anticipating peak demand earlier and planning capacity accordingly Challenges will continue to arise in 2026, as they always do. However, 2025 reinforced something important: a stable, empathetic, and well-aligned Helpdesk team is essential to supporting EGA's mission at scale. Supporting users well means supporting research, and that remains at the core of what we do.

  Blog ega-helpdesk-team-2025-in-review-and-upcoming-improvements

• Efficacy of two different FGFR-inhibitors in a patient with extrahepatic cholangiocarcinoma harboring an FGFR2 mutation

  Cholangiocarcinomas (CCAs) is a type of cancer with few effective systemic therapies. Elucidation of the molecular landscape of the disease from genomic studies based on next generation sequencing (NGS) has contributed to the introduction of new targeted therapies. One of these treatments consists of a class of small molecules that target members of the FGFR family of receptor tyrosine kinases. These drugs are effective and have been approved for cholangiocarcinomas with fusions or rearrangements of FGFR genes. In contrast, the role of these inhibitors in cholangiocarcinomas with mutations in FGFR genes is less well defined. We report here a patient with a cholangiocarcinoma bearing a FGFR2 p.Ser252Trp mutation. The patient was treated with two different FGFR inhibitors, as the first caused ocular toxicity. She obtained clinical benefit from both. This case illustrates the efficacy of FGFR inhibitors on cholangiocarcinoma with specific point mutations. This is the first case to report the clinical benefit of these drugs in FGFR2 p.Ser252Trp mutation. Clinical benefit can be sustained, as seen in our patient. Our case also shows that FGFR inhibitors-induced adverse effects, such as ocular toxicities, may not recur after re-challenge with an alternative drug of the same class.

  Dataset EGAD50000000021

• Selenium Chemoprevention: Benefits and Harms

  Selenium is a trace element that may have anti-carcinogenetic effect, but heterogenous treatment effects have been observed. This genome-wide association study investigates if genetic variation modifies the effect of selenium chemoprevention in the Selenium and Celecoxib Trial, a randomized, double-blind, placebo-controlled trial conducted at the University of Arizona Cancer Center. The objective of the clinical trial was to determine whether daily intake of 200 µg/d of selenium as a supplement could reduce the risk for developing metachronous colorectal adenomas. The study participants were recruited between 2001 and 2011. Genome-wide association study was performed for 1,323 study participants who provided blood sample at the time of study entry.

  Study phs002283

• Single Cell Genome Variation Induced by Mutational Processes in Cancer - HGSOC Trios Study

  Mutational signatures derived from whole genome sequencing have potential prognostic significance. Identification of high grade serous ovarian cancer patients with deficiency in homologous recombination repair pathways could identify a subset of patients that would benefit from homologous recombination deficiency-specific treatments independent of identification of a pathological BRCA1/2 gene mutation. Clinical protocols rely on a pathologist's assessment of formalin-fixed paraffin-embedded (FFPE) tissues, and thus FFPE tissue samples are readily available. However, the bulk of mutational signature analyses have been performed on fresh frozen tissues. In this study, we aimed to assess the reliability of whole genome sequencing, variant calling, and mutational signature analysis from FFPE tissue samples.

  Study phs003036

• Preclinical Modeling of Leiomyosarcoma Identifies Susceptibility to Transcriptional CDK Inhibitors through Antagonism of E2F-Driven Oncogenic Gene Expression

  Leiomyosarcoma (LMS) is a smooth muscle-derived mesenchymal cancer commonly found to have recurrent loss of tumor suppressor genes and a poorly defined oncogenic program. Empiric cytotoxic chemotherapy is the standard systemic treatment for LMS, and while more targeted and effective therapies are urgently needed, insights into therapeutic vulnerabilities in LMS have been limited by available preclinical models. We generated a panel of LMS patient-derived xenograft (PDX) models and evaluated fidelity to their tumors of origin using RNA sequencing and ultra-low passage whole-genome sequencing (ULP-WGS). Data available at dbGaP include RNA sequencing and ULP-WGS of primary tumors and early and late passages of PDX. 

  Study phs002587

• Molecular Genetics of Heroin Dependence in China

  Our principal goal was to determine the chromosomal locations of genetic variations associated with increased vulnerability to heroin dependence. This goal was attained by identifying specific DNA markers that are genetically linked to heroin dependence. We collected blood and diagnostic information (using a structured diagnostic interview) from 1230 people (sib-pairs) having DSM-IV defined heroin dependence as well as from their parents and other affected and unaffected siblings, when possible. Genotype and clinical data was archived using database software. We conducted a multipoint linkage analysis using the guidelines of Lander and Kruglyak to assert statistical significance, and followed up on regions of interest with a dense set of markers to evaluate candidate genes.

  Study phs001213

• Multiethnic Cohort Adiposity Phenotype Study (MEC-APS)

  A total of 1,861 healthy men and postmenopausal women aged 60-77 years with body mass indexes (BMIs) of 17.1-46.2 kg/m2 were enrolled into the study. Stratified sampling was conducted based on sex, race/ethnicity, and six BMI categories (18.5-21.9, 22-24.9, 25-26.9, 27-29.9, 30-34.9, and 35-40 kg/m2) to balance the sample size across the wide range of BMI and optimize adjustment for total adiposity in populations with different BMI distributions. Study participants underwent body composition assessment, in person interview, blood collection, and completed a self-administered questionnaire. A genome-wide association study of obesity phenotypes was conducted among five racial/ethnic groups of the Multiethnic Cohort Study.

  Study phs001689

• Paired Acute Myeloid Leukemia (AML) Epigenetics Study on Epialleles and Clonality

  We describe methclone, a novel method to identify epigenetic loci that harbor large changes in the clonality of their epialleles (epigenetic alleles). Methclone efficiently analyzes genome-wide DNA methylation sequencing data. We quantify the changes using a composition entropy difference calculation and also introduce a new measure of global clonality shift, loci with epiallele shift per million loci covered, which enables comparisons between different samples to gauge overall epiallelic dynamics. Finally, we demonstrate the utility of methclone in capturing functional epiallele shifts in leukemia patients from diagnosis to relapse. Methclone is open-source and freely available at https://code.google.com/p/methclone. Reprinted with permission from BMC Publishing (Genome Biology).

  Study phs000793

• Mega-GWAS ALS I

  Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder clinically characterized by rapidly progressive paralysis and death due to respiratory failure, typically within two to three years of symptom onset. The number of ALS cases across the globe will increase to nearly 400,000 in 2040, predominantly due to aging of the population. Unraveling the genetics underlying ALS provides insights into the cellular mechanism leading to motor neuron death and provides targets for therapeutic intervention. We performed a genome-wide association study involving a meta-analysis of 20,806 ALS cases and 59,804 controls. The current study release makes available genotype data of the 15,480 subjects assayed in the Laboratory of Neurogenetics for this effort.

  Study phs000101

• Whole Exome Sequencing Analysis of Carfilzomib-Related Cardiotoxicity in Multiple Myeloma Patients

  This study investigated the contribution of germline genetic variants in protein-coding genes in carfilzomib-related cardiovascular adverse events among patients with multiple myeloma using whole-exome sequencing (WES) analysis. We analyzed 247 patients with multiple myeloma who had been treated with carfilzomib at the Moffitt Cancer Center. We identified a missense mutation in the TMSB10/TRABD2A locus that appeared to be associated with a higher risk for cardiovascular adverse events in these patients. In this submission, we will provide all the genotype data along with the phenotype data of whether or not a patient developed cardiovascular adverse events after carfilzomib treatment and all the covariates used in this analysis.

  Study phs003308