The aim of our project is to decipher the genomic of advanced hepatocellular carcinoma using whole exome sequencing. To this purpose, we aim to compare genetic landscape of advanced hepatocellular carcinoma with early tumor in order to understand the mechanisms of tumor progression. This work will also help to identify new therapeutic targets potentially useful to treat patients at advanced stage. This study contain whole exome sequencing aligned reads for 41 tumor with matched normal samples
Broadly, the objectives of the study are to characterize genetic variation in any gene or genomic region in South African populations, in the first place HIV. The purpose is to apply this knowledge to establish assays and gene signatures to test in disease-association studies, and to study underlying mechanisms of disease causation/severity.
We performed RNA sequencing to screen for alternative splicing alterations in patients with ALS to identify those linked to ALS pathology.
We aim to identify epigenomic features dysregulated in hematological malignancies through epigenetic analyses of hematological malignant cells. We also perform RNA sequencing to profile tumor cell-specific transcriptomes and target gene sequencing to profile somatic gene mutations in tumor cells. Regarding identified epigenomic abnormalities, we perform further analysis to determine whether they could be good candidates to translate into therapy development. To this end, we will modulate the activity of targets by using their activators and inhibitors in vitro and establish xenograft mouse models of hematological malignancies and manipulate their activity in vivo. Through these studies, we aim to develop new therapeutic agents or modalities that lead to improved patients��� prognosis.
This study examines B cell transcriptomic profiles in Juvenile Idiopathic Arthritis (JIA) patients to investigate molecular mechanisms underlying disease heterogeneity. CD19+ B cells were isolated from peripheral blood samples and subjected to RNA sequencing to characterise gene expression patterns. The dataset includes patients with documented uveitis status to enable investigation of B cell contributions to the common JIA comorbidity.
We aim to use whole-genome medical sequencing (WGMS) to discover causative molecular lesions for a set of rare, severe phenotypes hypothesized to be caused by either somatic mutations, germline de nova heterozygous mutations, germline inherited recessive, or germline inherited dominant mutations in currently unknown or uncharacterized genes. The goal of this research is threefold: to identify causative sequence variants for disorders whose molecular etiology was previously unknown, to apply this insight to both the rare disorders under study and more common phenotypes, and to enhance the study of mutation on a genome-wide level.
In order to evaluate the effects of TFEB, a master regulator of autophagy and lysosomal biogenesis, CRISPR-Cas9 TFEB knock out cell lines were generated and reconstituted with wild-type TFEB (TFEB-WT), a vector control (TFEB-KO) or TFEB engineered to remain localized to the cytosol (TFEB-cyto) or to the nucleus (TFEB-nuc). RNA sequencing was performed on engineered cell lines at steady-state or following exogenous stimulation with autophagy inducer (Torin1 or Salmonella bacterial infection). Comparative analyses were performed to identify TFEB-dependent transcriptional response to subcellular localization at steady-state or to exogenous stimuli.
To assess how Notch inhibition impacts chromatin accessibility and how chromatin changes relate to HNF4A and CEBPA activities, we performed Assay-for-Transposase-Accessible-Chromatin (ATAC) sequencing of LIV78 tumors, 72 hours after treatment with NOTCH2 blocking or control antibodies. Our TF activity and chromatin analyses thus lead to a model in which Notch inhibition leads to increased expression of CEBPA, thus enabling CEBPA to partner with HNF4A to jointly drive transcriptional programs and the underlying chromatin rearrangements that promote differentiation of progenitor-like tumor cells to a mature hepatocyte fate incompatible with tumor growth and maintenance.
Our aim is to identify genes involved in resistance to anti-cancer therapies. In order to do this we have taken advantage of a lentiviral vector (LV)-based insertional mutagen to mutagenize cancer cell lines. LV-transduced cell lines were then treated with anti-cancer therapies and the emergence of resistant clones scored. DNA from pools of resistant clones was collected, subjected to custom capture by baits designed against the LV sequence, and then sequenced to identify the LV-genomic junction. We hope that the identification of recurrently targeted genes in resistant cell population will allow us to identify genes that mediate drug resistance.
Original description of the study: From ELLIPSE (linked to the PRACTICAL consortium), we contributed ~78,000 SNPs to the OncoArray. A large fraction of the content was derived from the GWAS meta-analyses in European ancestry populations (overall and aggressive disease; ~27K SNPs). We also selected just over 10,000 SNPs from the meta-analyses in the non-European populations, with a majority of these SNPs coming from the analysis of overall prostate cancer in African ancestry populations as well as from the multiethnic meta-analysis. A substantial fraction of SNPs (~28,000) were also selected for fine-mapping of 53 loci not included in the common fine-mapping regions (tagging at r2>0.9 across ±500kb regions). We also selected a few thousand SNPs related with PSA levels and/or disease survival as well as SNPs from candidate lists provided by study collaborators, as well as from meta-analyses of exome SNP chip data from the Multiethnic Cohort and UK studies. The Contributing Studies: Aarhus: Hospital-based, Retrospective, Observational. Source of cases: Patients treated for prostate adenocarcinoma at Department of Urology, Aarhus University Hospital, Skejby (Aarhus, Denmark). Source of controls: Age-matched males treated for myocardial infarction or undergoing coronary angioplasty, but with no prostate cancer diagnosis based on information retrieved from the Danish Cancer Register and the Danish Cause of Death Register. AHS: Nested case-control study within prospective cohort. Source of cases: linkage to cancer registries in study states. Source of controls: matched controls from cohort ATBC: Prospective, nested case-control. Source of cases: Finnish male smokers aged 50-69 years at baseline. Source of controls: Finnish male smokers aged 50-69 years at baseline BioVu: Cases identified in a biobank linked to electronic health records. Source of cases: A total of 214 cases were identified in the VUMC de-identified electronic health records database (the Synthetic Derivative) and shipped to USC for genotyping in April 2014. The following criteria were used to identify cases: Age 18 or greater; male; African Americans (Black) only. Note that African ancestry is not self-identified, it is administratively or third-party assigned (which has been shown to be highly correlated with genetic ancestry for African Americans in BioVU; see references). Source of controls: Controls were identified in the de-identified electronic health record. Unfortunately, they were not age matched to the cases, and therefore cannot be used for this study. Canary PASS: Prospective, Multi-site, Observational Active Surveillance Study. Source of cases: clinic based from Beth Israel Deaconness Medical Center, Eastern Virginia Medical School, University of California at San Francisco, University of Texas Health Sciences Center San Antonio, University of Washington, VA Puget Sound. Source of controls: N/A CCI: Case series, Hospital-based. Source of cases: Cases identified through clinics at the Cross Cancer Institute. Source of controls: N/A CerePP French Prostate Cancer Case-Control Study (ProGene): Case-Control, Prospective, Observational, Hospital-based. Source of cases: Patients, treated in French departments of Urology, who had histologically confirmed prostate cancer. Source of controls: Controls were recruited as participating in a systematic health screening program and found unaffected (normal digital rectal examination and total PSA < 4 ng/ml, or negative biopsy if PSA > 4 ng/ml). COH: hospital-based cases and controls from outside. Source of cases: Consented prostate cancer cases at City of Hope. Source of controls: Consented unaffected males that were part of other studies where they consented to have their DNA used for other research studies. COSM: Population-based cohort. Source of cases: General population. Source of controls: General population CPCS1: Case-control - Denmark. Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPCS2: Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPDR: Retrospective cohort. Source of cases: Walter Reed National Military Medical Center. Source of controls: Walter Reed National Military Medical Center ACS_CPS-II: Nested case-control derived from a prospective cohort study. Source of cases: Identified through self-report on follow-up questionnaires and verified through medical records or cancer registries, identified through cancer registries or the National Death Index (with prostate cancer as the primary cause of death). Source of controls: Cohort participants who were cancer-free at the time of diagnosis of the matched case, also matched on age (±6 mo) and date of biospecimen donation (±6 mo). EPIC: Case-control - Germany, Greece, Italy, Netherlands, Spain, Sweden, UK. Source of cases: Identified through record linkage with population-based cancer registries in Italy, the Netherlands, Spain, Sweden and UK. In Germany and Greece, follow-up is active and achieved through checks of insurance records and cancer and pathology registries as well as via self-reported questionnaires; self-reported incident cancers are verified through medical records. Source of controls: Cohort participants without a diagnosis of cancer EPICAP: Case-control, Population-based, ages less than 75 years at diagnosis, Hérault, France. Source of cases: Prostate cancer cases in all public hospitals and private urology clinics of département of Hérault in France. Cases validation by the Hérault Cancer Registry. Source of controls: Population-based controls, frequency age matched (5-year groups). Quotas by socio-economic status (SES) in order to obtain a distribution by SES among controls identical to the SES distribution among general population men, conditionally to age. ERSPC: Population-based randomized trial. Source of cases: Men with PrCa from screening arm ERSPC Rotterdam. Source of controls: Men without PrCa from screening arm ERSPC Rotterdam ESTHER: Case-control, Prospective, Observational, Population-based. Source of cases: Prostate cancer cases in all hospitals in the state of Saarland, from 2001-2003. Source of controls: Random sample of participants from routine health check-up in Saarland, in 2000-2002 FHCRC: Population-based, case-control, ages 35-74 years at diagnosis, King County, WA, USA. Source of cases: Identified through the Seattle-Puget Sound SEER cancer registry. Source of controls: Randomly selected, age-frequency matched residents from the same county as cases Gene-PARE: Hospital-based. Source of cases: Patients that received radiotherapy for treatment of prostate cancer. Source of controls: n/a Hamburg-Zagreb: Hospital-based, Prospective. Source of cases: Prostate cancer cases seen at the Department of Oncology, University Hospital Center Zagreb, Croatia. Source of controls: Population-based (Croatia), healthy men, older than 50, with no medical record of cancer, and no family history of cancer (1st & 2nd degree relatives) HPFS: Nested case-control. Source of cases: Participants of the HPFS cohort. Source of controls: Participants of the HPFS cohort IMPACT: Observational. Source of cases: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has been diagnosed with prostate cancer during the study. Source of controls: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has not been diagnosed with prostate cancer during the study. IPO-Porto: Hospital-based. Source of cases: Early onset and/or familial prostate cancer. Source of controls: Blood donors Karuprostate: Case-control, Retrospective, Population-based. Source of cases: From FWI (Guadeloupe): 237 consecutive incident patients with histologically confirmed prostate cancer attending public and private urology clinics; From Democratic Republic of Congo: 148 consecutive incident patients with histologically confirmed prostate cancer attending the University Clinic of Kinshasa. Source of controls: From FWI (Guadeloupe): 277 controls recruited from men participating in a free systematic health screening program open to the general population; From Democratic Republic of Congo: 134 controls recruited from subjects attending the University Clinic of Kinshasa KULEUVEN: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases recruited at the University Hospital Leuven. Source of controls: Healthy males with no history of prostate cancer recruited at the University Hospitals, Leuven. LAAPC: Subjects were participants in a population-based case-control study of aggressive prostate cancer conducted in Los Angeles County. Cases were identified through the Los Angeles County Cancer Surveillance Program rapid case ascertainment system. Eligible cases included African American, Hispanic, and non-Hispanic White men diagnosed with a first primary prostate cancer between January 1, 1999 and December 31, 2003. Eligible cases also had (a) prostatectomy with documented tumor extension outside the prostate, (b) metastatic prostate cancer in sites other than prostate, (c) needle biopsy of the prostate with Gleason grade ≥8, or (d) needle biopsy with Gleason grade 7 and tumor in more than two thirds of the biopsy cores. Eligible controls were men never diagnosed with prostate cancer, living in the same neighborhood as a case, and were frequency matched to cases on age (± 5 y) and race/ethnicity. Controls were identified by a neighborhood walk algorithm, which proceeds through an obligatory sequence of adjacent houses or residential units beginning at a specific residence that has a specific geographic relationship to the residence where the case lived at diagnosis. Malaysia: Case-control. Source of cases: Patients attended the outpatient urology or uro-onco clinic at University Malaya Medical Center. Source of controls: Population-based, age matched (5-year groups), ascertained through electoral register, Subang Jaya, Selangor, Malaysia MCC-Spain: Case-control. Source of cases: Identified through the urology departments of the participating hospitals. Source of controls: Population-based, frequency age and region matched, ascertained through the rosters of the primary health care centers MCCS: Nested case-control, Melbourne, Victoria. Source of cases: Identified by linkage to the Victorian Cancer Registry. Source of controls: Cohort participants without a diagnosis of cancer MD Anderson: Participants in this study were identified from epidemiological prostate cancer studies conducted at the University of Texas MD Anderson Cancer Center in the Houston Metropolitan area. Cases were accrued in the Houston Medical Center and were not restricted with respect to Gleason score, stage or PSA. Controls were identified via random-digit-dialing or among hospital visitors and they were frequency matched to cases on age and race. Lifestyle, demographic, and family history data were collected using a standardized questionnaire. MDACC_AS: A prospective cohort study. Source of cases: Men with clinically organ-confined prostate cancer meeting eligibility criteria for a prospective cohort study of active surveillance at MD Anderson Cancer Center. Source of controls: N/A MEC: The Multiethnic Cohort (MEC) is comprised of over 215,000 men and women recruited from Hawaii and the Los Angeles area between 1993 and 1996. Between 1995 and 2006, over 65,000 blood samples were collected from participants for genetic analyses. To identify incident cancer cases, the MEC was cross-linked with the population-based Surveillance, Epidemiology and End Results (SEER) registries in California and Hawaii, and unaffected cohort participants with blood samples were selected as controls MIAMI (WFPCS): Prostate cancer cases and controls were recruited from the Departments of Urology and Internal Medicine of the Wake Forest University School of Medicine using sequential patient populations as described previously (PMID:15342424). All study subjects received a detailed description of the study protocol and signed their informed consent, as approved by the medical center's Institutional Review Board. The general eligibility criteria were (i) able to comprehend informed consent and (ii) without previously diagnosed cancer. The exclusion criteria were (i) clinical diagnosis of autoimmune diseases; (ii) chronic inflammatory conditions; and (iii) infections within the past 6 weeks. Blood samples were collected from all subjects. MOFFITT: Hospital-based. Source of cases: clinic based from Moffitt Cancer Center. Source of controls: Moffitt Cancer Center affiliated Lifetime cancer screening center NMHS: Case-control, clinic based, Nashville TN. Source of cases: All urology clinics in Nashville, TN. Source of controls: Men without prostate cancer at prostate biopsy. PCaP: The North Carolina-Louisiana Prostate Cancer Project (PCaP) is a multidisciplinary population-based case-only study designed to address racial differences in prostate cancer through a comprehensive evaluation of social, individual and tumor level influences on prostate cancer aggressiveness. PCaP enrolled approximately equal numbers of African Americans and Caucasian Americans with newly-diagnosed prostate cancer from North Carolina (42 counties) and Louisiana (30 parishes) identified through state tumor registries. African American PCaP subjects with DNA, who agreed to future use of specimens for research, participated in OncoArray analysis. PCMUS: Case-control - Sofia, Bulgaria. Source of cases: Patients of Clinic of Urology, Alexandrovska University Hospital, Sofia, Bulgaria, PrCa histopathologically confirmed. Source of controls: 72 patients with verified BPH and PSA<3,5; 78 healthy controls from the MMC Biobank, no history of PrCa PHS: Nested case-control. Source of cases: Participants of the PHS1 trial/cohort. Source of controls: Participants of the PHS1 trial/cohort PLCO: Nested case-control. Source of cases: Men with a confirmed diagnosis of prostate cancer from the PLCO Cancer Screening Trial. Source of controls: Controls were men enrolled in the PLCO Cancer Screening Trial without a diagnosis of cancer at the time of case ascertainment. Poland: Case-control. Source of cases: men with unselected prostate cancer, diagnosed in north-western Poland at the University Hospital in Szczecin. Source of controls: cancer-free men from the same population, taken from the healthy adult patients of family doctors in the Szczecin region PROCAP: Population-based, Retrospective, Observational. Source of cases: Cases were ascertained from the National Prostate Cancer Register of Sweden Follow-Up Study, a retrospective nationwide cohort study of patients with localized prostate cancer. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PROGReSS: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases from the Hospital Clínico Universitario de Santiago de Compostela, Galicia, Spain. Source of controls: Cancer-free men from the same population ProMPT: A study to collect samples and data from subjects with and without prostate cancer. Retrospective, Experimental. Source of cases: Subjects attending outpatient clinics in hospitals. Source of controls: Subjects attending outpatient clinics in hospitals ProtecT: Trial of treatment. Samples taken from subjects invited for PSA testing from the community at nine centers across United Kingdom. Source of cases: Subjects who have a proven diagnosis of prostate cancer following testing. Source of controls: Identified through invitation of subjects in the community. PROtEuS: Case-control, population-based. Source of cases: All new histologically-confirmed cases, aged less or equal to 75 years, diagnosed between 2005 and 2009, actively ascertained across Montreal French hospitals. Source of controls: Randomly selected from the Provincial electoral list of French-speaking men between 2005 and 2009, from the same area of residence as cases and frequency-matched on age. QLD: Case-control. Source of cases: A longitudinal cohort study (Prostate Cancer Supportive Care and Patient Outcomes Project: ProsCan) conducted in Queensland, through which men newly diagnosed with prostate cancer from 26 private practices and 10 public hospitals were directly referred to ProsCan at the time of diagnosis by their treating clinician (age range 43-88 years). All cases had histopathologically confirmed prostate cancer, following presentation with an abnormal serum PSA and/or lower urinary tract symptoms. Source of controls: Controls comprised healthy male blood donors with no personal history of prostate cancer, recruited through (i) the Australian Red Cross Blood Services in Brisbane (age range 19-76 years) and (ii) the Australian Electoral Commission (AEC) (age and post-code/ area matched to ProsCan, age range 54-90 years). RAPPER: Multi-centre, hospital based blood sample collection study in patients enrolled in clinical trials with prospective collection of radiotherapy toxicity data. Source of cases: Prostate cancer patients enrolled in radiotherapy trials: CHHiP, RT01, Dose Escalation, RADICALS, Pelvic IMRT, PIVOTAL. Source of controls: N/A SABOR: Prostate Cancer Screening Cohort. Source of cases: Men >45 yrs of age participating in annual PSA screening. Source of controls: Males participating in annual PSA prostate cancer risk evaluations (funded by NCI biomarkers discovery and validation grant), recruited through University of Texas Health Science Center at San Antonio and affiliated sites or through study advertisements, enrolment open to the community SCCS: Case-control in cohort, Southeastern USA. Prospective, Observational, Population-based. Source of cases: SCCS entry population. Source of controls: SCCS entry population SCPCS: Population-based, Retrospective, Observational. Source of cases: South Carolina Central Cancer Registry. Source of controls: Health Care Financing Administration beneficiary file SEARCH: Case-control - East Anglia, UK. Source of cases: Men < 70 years of age registered with prostate cancer at the population-based cancer registry, Eastern Cancer Registration and Information Centre, East Anglia, UK. Source of controls: Men attending general practice in East Anglia with no known prostate cancer diagnosis, frequency matched to cases by age and geographic region SNP_Prostate_Ghent: Hospital-based, Retrospective, Observational. Source of cases: Men treated with IMRT as primary or postoperative treatment for prostate cancer at the Ghent University Hospital between 2000 and 2010. Source of controls: Employees of the University hospital and members of social activity clubs, without a history of any cancer. SPAG: Hospital-based, Retrospective, Observational. Source of cases: Guernsey. Source of controls: Guernsey STHM2: Population-based, Retrospective, Observational. Source of cases: Cases were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PCPT: Case-control from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial SELECT: Case-cohort from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial TAMPERE: Case-control - Finland, Retrospective, Observational, Population-based. Source of cases: Identified through linkage to the Finnish Cancer Registry and patient records; and the Finnish arm of the ERSPC study. Source of controls: Cohort participants without a diagnosis of cancer UGANDA: Uganda Prostate Cancer Study: Uganda is a case-control study of prostate cancer in Kampala Uganda that was initiated in 2011. Men with prostate cancer were enrolled from the Urology unit at Mulago Hospital and men without prostate cancer (i.e. controls) were enrolled from other clinics (i.e. surgery) at the hospital. UKGPCS: ICR, UK. Source of cases: Cases identified through clinics at the Royal Marsden hospital and nationwide NCRN hospitals. Source of controls: Ken Muir's control- 2000 ULM: Case-control - Germany. Source of cases: familial cases (n=162): identified through questionnaires for family history by collaborating urologists all over Germany; sporadic cases (n=308): prostatectomy series performed in the Clinic of Urology Ulm between 2012 and 2014. Source of controls: age-matched controls (n=188): age-matched men without prostate cancer and negative family history collected in hospitals of Ulm WUGS/WUPCS: Cases Series, USA. Source of cases: Identified through clinics at Washington University in St. Louis. Source of controls: Men diagnosed and managed with prostate cancer in University based clinic. Acknowledgement Statements: Aarhus: This study was supported by the Danish Strategic Research Council (now Innovation Fund Denmark) and the Danish Cancer Society. The Danish Cancer Biobank (DCB) is acknowledged for biological material. AHS: This work was supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01CP010119). ATBC: This research was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004, HHSN261201000006C, and HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services. BioVu: The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding and by the National Center for Research Resources, Grant UL1 RR024975-01 (which is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06). Canary PASS: PASS was supported by Canary Foundation and the National Cancer Institute's Early Detection Research Network (U01 CA086402) CCI: This work was awarded by Prostate Cancer Canada and is proudly funded by the Movember Foundation - Grant # D2013-36.The CCI group would like to thank David Murray, Razmik Mirzayans, and April Scott for their contribution to this work. CerePP French Prostate Cancer Case-Control Study (ProGene): None reported COH: SLN is partially supported by the Morris and Horowitz Families Endowed Professorship COSM: The Swedish Research Council, the Swedish Cancer Foundation CPCS1 & CPCS2: Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, DenmarkCPCS1 would like to thank the participants and staff of the Copenhagen General Population Study for their important contributions. CPDR: Uniformed Services University for the Health Sciences HU0001-10-2-0002 (PI: David G. McLeod, MD) CPS-II: The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study II cohort. CPS-II thanks the participants and Study Management Group for their invaluable contributions to this research. We would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. EPIC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by the Danish Cancer Society (Denmark); the Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation, Greek Ministry of Health; Greek Ministry of Education (Greece); the Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); the Statistics Netherlands (The Netherlands); the Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, Spanish Ministry of Health ISCIII RETIC (RD06/0020), Red de Centros RCESP, C03/09 (Spain); the Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skåne and Västerbotten, Fundacion Federico SA (Sweden); the Cancer Research UK, Medical Research Council (United Kingdom). EPICAP: The EPICAP study was supported by grants from Ligue Nationale Contre le Cancer, Ligue départementale du Val de Marne; Fondation de France; Agence Nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES). The EPICAP study group would like to thank all urologists, Antoinette Anger and Hasina Randrianasolo (study monitors), Anne-Laure Astolfi, Coline Bernard, Oriane Noyer, Marie-Hélène De Campo, Sandrine Margaroline, Louise N'Diaye, and Sabine Perrier-Bonnet (Clinical Research nurses). ERSPC: This study was supported by the DutchCancerSociety (KWF94-869,98-1657,2002-277,2006-3518, 2010-4800), The Netherlands Organisation for Health Research and Development (ZonMW-002822820, 22000106, 50-50110-98-311, 62300035), The Dutch Cancer Research Foundation (SWOP), and an unconditional grant from Beckman-Coulter-HybritechInc. ESTHER: The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. The ESTHER group would like to thank Hartwig Ziegler, Sonja Wolf, Volker Hermann, Heiko Müller, Karina Dieffenbach, Katja Butterbach for valuable contributions to the study. FHCRC: The FHCRC studies were supported by grants R01-CA056678, R01-CA082664, and R01-CA092579 from the US National Cancer Institute, National Institutes of Health, with additional support from the Fred Hutchinson Cancer Research Center. FHCRC would like to thank all the men who participated in these studies. Gene-PARE: The Gene-PARE study was supported by grants 1R01CA134444 from the U.S. National Institutes of Health, PC074201 and W81XWH-15-1-0680 from the Prostate Cancer Research Program of the Department of Defense and RSGT-05-200-01-CCE from the American Cancer Society. Hamburg-Zagreb: None reported HPFS: The Health Professionals Follow-up Study was supported by grants UM1CA167552, CA133891, CA141298, and P01CA055075. HPFS are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. IMPACT: The IMPACT study was funded by The Ronald and Rita McAulay Foundation, CR-UK Project grant (C5047/A1232), Cancer Australia, AICR Netherlands A10-0227, Cancer Australia and Cancer Council Tasmania, NIHR, EU Framework 6, Cancer Councils of Victoria and South Australia, and Philanthropic donation to Northshore University Health System. We acknowledge support from the National Institute for Health Research (NIHR) to the Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden Foundation NHS Trust. IMPACT acknowledges the IMPACT study steering committee, collaborating centres, and participants. IPO-Porto: The IPO-Porto study was funded by Fundaçäo para a Ciência e a Tecnologia (FCT; UID/DTP/00776/2013 and PTDC/DTP-PIC/1308/2014) and by IPO-Porto Research Center (CI-IPOP-16-2012 and CI-IPOP-24-2015). MC and MPS are research fellows from Liga Portuguesa Contra o Cancro, Núcleo Regional do Norte. SM is a research fellow from FCT (SFRH/BD/71397/2010). IPO-Porto would like to express our gratitude to all patients and families who have participated in this study. Karuprostate: The Karuprostate study was supported by the the Frech National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la ProstateKarusprostate thanks Séverine Ferdinand. KULEUVEN: F.C. and S.J. are holders of grants from FWO Vlaanderen (G.0684.12N and G.0830.13N), the Belgian federal government (National Cancer Plan KPC_29_023), and a Concerted Research Action of the KU Leuven (GOA/15/017). TVDB is holder of a doctoral fellowship of the FWO. LAAPC: This study was funded by grant R01CA84979 (to S.A. Ingles) from the National Cancer Institute, National Institutes of Health. Malaysia: The study was funded by the University Malaya High Impact Research Grant (HIR/MOHE/MED/35). Malaysia thanks all associates in the Urology Unit, University of Malaya, Cancer Research Initiatives Foundation (CARIF) and the Malaysian Men's Health Initiative (MMHI). MCCS: MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553, and 504711, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MCC-Spain: The study was partially funded by the Accion Transversal del Cancer, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI09/00773-Cantabria, PI11/01889-FEDER, PI12/00265, PI12/01270, and PI12/00715), by the Fundación Marqués de Valdecilla (API 10/09), by the Spanish Association Against Cancer (AECC) Scientific Foundation and by the Catalan Government DURSI grant 2009SGR1489. Samples: Biological samples were stored at the Parc de Salut MAR Biobank (MARBiobanc; Barcelona) which is supported by Instituto de Salud Carlos III FEDER (RD09/0076/00036). Also sample collection was supported by the Xarxa de Bancs de Tumors de Catalunya sponsored by Pla Director d'Oncologia de Catalunya (XBTC). MCC-Spain acknowledges the contribution from Esther Gracia-Lavedan in preparing the data. We thank all the subjects who participated in the study and all MCC-Spain collaborators. MD Anderson: Prostate Cancer Case-Control Studies at MD Anderson (MDA) supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388. MDACC_AS: None reported MEC: Funding provided by NIH grant U19CA148537 and grant U01CA164973. MIAMI (WFPCS): ACS MOFFITT: The Moffitt group was supported by the US National Cancer Institute (R01CA128813, PI: J.Y. Park). NMHS: Funding for the Nashville Men's Health Study (NMHS) was provided by the National Institutes of Health Grant numbers: RO1CA121060. PCaP only data: The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. For HCaP-NC follow-up data: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. For studies using both PCaP and HCaP-NC follow-up data please use: The North Carolina - Louisiana Prostate Cancer Project (PCaP) and the Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study are carried out as collaborative studies supported by the Department of Defense contract DAMD 17-03-2-0052 and the American Cancer Society award RSGT-08-008-01-CPHPS, respectively. For any PCaP data, please include: The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. For studies using PCaP DNA/genotyping data, please include: We would like to acknowledge the UNC BioSpecimen Facility and LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). For studies using PCaP tissue, please include: We would like to acknowledge the RPCI Department of Urology Tissue Microarray and Immunoanalysis Core for our tissue processing, storage and sample disbursement. For studies using HCaP-NC follow-up data, please use: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. The authors thank the staff, advisory committees and research subjects participating in the HCaP-NC study for their important contributions. For studies that use both PCaP and HCaP-NC, please use: The authors thank the staff, advisory committees and research subjects participating in the PCaP and HCaP-NC studies for their important contributions. PCMUS: The PCMUS study was supported by the Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2-2009; DFNI-B01/28/2012) with additional support from the Science Fund of Medical University - Sofia (contract 51/2009; 8I/2009; 28/2010). PHS: The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490, and HL34595. PHS members are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. PLCO: This PLCO study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHPLCO thanks Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention at the National Cancer Institute, the screening center investigators and staff of the PLCO Cancer Screening Trial for their contributions to the PLCO Cancer Screening Trial. We thank Mr. Thomas Riley, Mr. Craig Williams, Mr. Matthew Moore, and Ms. Shannon Merkle at Information Management Services, Inc., for their management of the data and Ms. Barbara O'Brien and staff at Westat, Inc. for their contributions to the PLCO Cancer Screening Trial. We also thank the PLCO study participants for their contributions to making this study possible. Poland: None reported PROCAP: PROCAP was supported by the Swedish Cancer Foundation (08-708, 09-0677). PROCAP thanks and acknowledges all of the participants in the PROCAP study. We thank Carin Cavalli-Björkman and Ami Rönnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skilful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. We acknowledge The NPCR steering group: Pär Stattin (chair), Anders Widmark, Stefan Karlsson, Magnus Törnblom, Jan Adolfsson, Anna Bill-Axelson, Ove Andrén, David Robinson, Bill Pettersson, Jonas Hugosson, Jan-Erik Damber, Ola Bratt, Göran Ahlgren, Lars Egevad, and Roy Ehrnström. PROGReSS: The PROGReSS study is founded by grants from the Spanish Ministry of Health (INT15/00070; INT16/00154; FIS PI10/00164, FIS PI13/02030; FIS PI16/00046); the Spanish Ministry of Economy and Competitiveness (PTA2014-10228-I), and Fondo Europeo de Desarrollo Regional (FEDER 2007-2013). ProMPT: Founded by CRUK, NIHR, MRC, Cambride Biomedical Research Centre ProtecT: Founded by NIHR. ProtecT and ProMPT would like to acknowledge the support of The University of Cambridge, Cancer Research UK. Cancer Research UK grants (C8197/A10123) and (C8197/A10865) supported the genotyping team. We would also like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge, UK. We would also like to acknowledge the support of the National Cancer Research Prostate Cancer: Mechanisms of Progression and Treatment (PROMPT) collaborative (grant code G0500966/75466) which has funded tissue and urine collections in Cambridge. We are grateful to staff at the Welcome Trust Clinical Research Facility, Addenbrooke's Clinical Research Centre, Cambridge, UK for their help in conducting the ProtecT study. We also acknowledge the support of the NIHR Cambridge Biomedical Research Centre, the DOH HTA (ProtecT grant), and the NCRI/MRC (ProMPT grant) for help with the bio-repository. The UK Department of Health funded the ProtecT study through the NIHR Health Technology Assessment Programme (projects 96/20/06, 96/20/99). The ProtecT trial and its linked ProMPT and CAP (Comparison Arm for ProtecT) studies are supported by Department of Health, England; Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466, and The NCRI, UK. The epidemiological data for ProtecT were generated though funding from the Southwest National Health Service Research and Development. DNA extraction in ProtecT was supported by USA Dept of Defense award W81XWH-04-1-0280, Yorkshire Cancer Research and Cancer Research UK. The authors would like to acknowledge the contribution of all members of the ProtecT study research group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health of England. The bio-repository from ProtecT is supported by the NCRI (ProMPT) Prostate Cancer Collaborative and the Cambridge BMRC grant from NIHR. We thank the National Institute for Health Research, Hutchison Whampoa Limited, the Human Research Tissue Bank (Addenbrooke's Hospital), and Cancer Research UK. PROtEuS: PROtEuS was supported financially through grants from the Canadian Cancer Society (13149, 19500, 19864, 19865) and the Cancer Research Society, in partnership with the Ministère de l'enseignement supérieur, de la recherche, de la science et de la technologie du Québec, and the Fonds de la recherche du Québec - Santé.PROtEuS would like to thank its collaborators and research personnel, and the urologists involved in subjects recruitment. We also wish to acknowledge the special contribution made by Ann Hsing and Anand Chokkalingam to the conception of the genetic component of PROtEuS. QLD: The QLD research is supported by The National Health and Medical Research Council (NHMRC) Australia Project Grants (390130, 1009458) and NHMRC Career Development Fellowship and Cancer Australia PdCCRS funding to J Batra. The QLD team would like to acknowledge and sincerely thank the urologists, pathologists, data managers and patient participants who have generously and altruistically supported the QLD cohort. RAPPER: RAPPER is funded by Cancer Research UK (C1094/A11728; C1094/A18504) and Experimental Cancer Medicine Centre funding (C1467/A7286). The RAPPER group thank Rebecca Elliott for project management. SABOR: The SABOR research is supported by NIH/NCI Early Detection Research Network, grant U01 CA0866402-12. Also supported by the Cancer Center Support Grant to the Cancer Therapy and Research Center from the National Cancer Institute (US) P30 CA054174. SCCS: SCCS is funded by NIH grant R01 CA092447, and SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SCPCS: SCPCS is funded by CDC grant S1135-19/19, and SCPCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). SEARCH: SEARCH is funded by a program grant from Cancer Research UK (C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. SNP_Prostate_Ghent: The study was supported by the National Cancer Plan, financed by the Federal Office of Health and Social Affairs, Belgium. SPAG: Wessex Medical ResearchHope for Guernsey, MUG, HSSD, MSG, Roger Allsopp STHM2: STHM2 was supported by grants from The Strategic Research Programme on Cancer (StratCan), Karolinska Institutet; the Linné Centre for Breast and Prostate Cancer (CRISP, number 70867901), Karolinska Institutet; The Swedish Research Council (number K2010-70X-20430-04-3) and The Swedish Cancer Society (numbers 11-0287 and 11-0624); Stiftelsen Johanna Hagstrand och Sigfrid Linnérs minne; Swedish Council for Working Life and Social Research (FAS), number 2012-0073STHM2 acknowledges the Karolinska University Laboratory, Aleris Medilab, Unilabs and the Regional Prostate Cancer Registry for performing analyses and help to retrieve data. Carin Cavalli-Björkman and Britt-Marie Hune for their enthusiastic work as research nurses. Astrid Björklund for skilful data management. We wish to thank the BBMRI.se biobank facility at Karolinska Institutet for biobank services. PCPT & SELECT are funded by Public Health Service grants U10CA37429 and 5UM1CA182883 from the National Cancer Institute. SWOG and SELECT thank the site investigators and staff and, most importantly, the participants who donated their time to this trial. TAMPERE: The Tampere (Finland) study was supported by the Academy of Finland (251074), The Finnish Cancer Organisations, Sigrid Juselius Foundation, and the Competitive Research Funding of the Tampere University Hospital (X51003). The PSA screening samples were collected by the Finnish part of ERSPC (European Study of Screening for Prostate Cancer). TAMPERE would like to thank Riina Liikanen, Liisa Maeaettaenen and Kirsi Talala for their work on samples and databases. UGANDA: None reported UKGPCS: UKGPCS would also like to thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. UKGPCS should also like to acknowledge the NCRN nurses, data managers, and consultants for their work in the UKGPCS study. UKGPCS would like to thank all urologists and other persons involved in the planning, coordination, and data collection of the study. ULM: The Ulm group received funds from the German Cancer Aid (Deutsche Krebshilfe). WUGS/WUPCS: WUGS would like to thank the following for funding support: The Anthony DeNovi Fund, the Donald C. McGraw Foundation, and the St. Louis Men's Group Against Cancer.
The study "Genomic Characteristics of Myeloproliferative Neoplasms in Patients Exposed to Ionizing Radiation following the Chernobyl Nuclear Accident" was designed as case-control study. We studied genomic characteristics of chronic Philadelphia chromosome-negative myeloproliferative neoplasm (MPNs) in Ukrainian patients who were previously exposed to Ionizing Radiation (IR) due to Chernobyl accident in comparison to unexposed MPN patients and controls (previously exposed to IR due to Chernobyl accident and unexposed people who were not diagnosed with any oncological condition at the moment of DNA sampling).
The neoantigen presentation score (NEOPS) study was designed to better understand molecular determinants of response to immunotherapies, including pembrolizumab and nivolumab in stage III or IV melanoma patients. From this work, we developed a composite approach to predicting neoantigens (NEOPS), which takes into account additional escape mechanisms, including HLA LOH (human leukocyte antigen loss of heterozygosity) and the impact of deleterious mutations to the antigen presentation machinery (APM), yielding an improved prediction of response to immunotherapy compared to TMB (tumor mutational burden) or neoantigen burden alone.
Two patient-derived xenograft model of myxoid liposarcoma one sensitive and one resistant to trabectedin. The aim of the study was to study the resistance to the drug.
SAFER-COVID provides a set of self-management tools to consumers to track symptoms, test results, vaccine record, and environmental factors, such as exposure to others. Consumers may choose to integrate data from wearables and electronic health records (EHR) for self management. These data are used to enable multiple use cases such as return-to-work, activity risk assessment and self-management within SAFER-COVID.DOI: https://rapids.ll.mit.edu/10.57895/cmt5-gh78
The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality-of-life for people with Down syndrome. The INCLUDE Project Data Coordinating Center and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions.
Organoids were established from both tumor and matched wildtype tissue from patients diagnosed with head and neck squamous cell carcinoma (HNSCC). In order to confirm tumor status and identify oncogenic driver mutations, DNA derived of these organoids was sequenced. After validation of tumor identity, organoids were exposed to a range of (targeted) chemotherapeutics and radiotherapy. Differential responses to therapeutics were subsequently correlated to underlying genetic alterations to see if DNA mutation status could be predictive for responses to therapy.
Understanding the evolutionary pathways to metastasis and resistance to immune checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here we present the most comprehensive intra-patient metastatic melanoma dataset assembled to date as part of the PEACE research autopsy programme, including exome, panel-sequenced, RNA-seq, and single-cell whole-genome sequencing samples from 14 ICI-treated patients. The main goals of the project are to decipher the evolutionary dynamics of melanoma metastases and to elucidate mechnisms of resistance to therapies.
In addition to Exome-sequencing, we used RNA-sequencing to also characterize resistance to lirafugratinib with whole exome sequencing in patients with FGFR2-driven cancers, treated in the phase 1/2 ReFocus trial (NCT04526106) and enrolled in the UNLOCK program at Gustave Roussy
This study aims to use RNAseq to identify differentially expressed transcripts in human melanoma cells that over-express the cell surface protein, LRRN4CL, relative to empty-vector control cells, to provide mechanistic insight into how LRRN4CL over-expression confers enhanced pulmonary metastatic colonisation abilities.
The goal is to study and specify the response to treatment against Plasmodium falciparum malaria in subjects with sickle cell disease in order to propose to the National Malaria Control Program of Côte d'Ivoire effective prevention and treatment strategies for this population at risk.
Analysis of mutational signatures caused by exposure to known mutagens in human induced pluripotent stem (iPS) cells. A reference human iPS cell-line will be exposed to 100 chemicals known or proposed to be mutagenic. Following exposure to mutagen, cells will undergo a period of recovery before sub clones are generated and sequenced. The progenitor "parental" IPS cell-line will be used to generate reference sequence data, in order to determine the mutational signatures acquired as a result of exposure to different mutagens.
In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.
Systematic next generation sequencing efforts are beginning to define the genomic landscape across a range of primary tumours, but we know very little of the mutational evolution that contributes to disease progression.We therefore propose to obtain a comprehensive description of genomic, transcriptomic and epigenomic changes in a cohort of matched primary and metastatic colorectal cancers, and additionally to explore the extent to which those mutations identified as recurrent in the metastatic setting are able to subvert normal biological processes using both genetically engineered mouse models and established cancer cell lines. This study will enable us to define to what extent primary tumour profiling can capture the biological processes operative in matched metastases as well as the significance of intratumoural heterogeneity.
In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers will work together with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to Avastin® combination therapy. Diagnostic tests using these biomarkers will also be developed to provide clinicians with the means to predict patient treatment responses in the future.
Colorectal cancer (CRC) is the third most common cancer world-wide with 1.2 million patients diagnosed yearly. In late stage CRC, the most commonly used targeted therapies are monoclonal antibodies cetuximab and panitumumab, which inactivate EGFR. Recent studies have identified alterations in KRAS and other genes as likely mechanisms of primary and secondary resistance to anti-EGFR antibody therapy. Despite these efforts, additional mechanisms of resistance to EGFR blockade are thought to be present in CRC and little is known about determinants of sensitivity to this therapy. To examine the effect of somatic genetic changes in CRC on response to anti-EGFR antibody therapy, we performed complete exome sequence and copy number analyses of 129 patient-derived tumorgrafts and targeted genomic analyses of 55 patient tumors, all of which were KRAS wild-type. We analyzed the response of tumors to anti-EGFR antibody blockade in tumorgraft models or in clinical settings. In addition to previously identified genes, we detected mutations in ERBB2, EGFR, FGFR1, PDGFRA, and MAP2K1 as potential mechanisms of primary resistance to this therapy. Novel alterations in the ectodomain of EGFR were identified in patients with acquired resistance to EGFR blockade. Amplifications and sequence changes in the tyrosine kinase receptor adaptor gene IRS2 were identified in tumors with increased sensitivity to anti-EGFR therapy. Therapeutic resistance to EGFR blockade could be overcome in tumorgraft models through combinatorial therapies targeting actionable genes. These analyses provide a systematic approach to evaluate response to targeted therapies in human cancer, highlight new mechanisms of responsiveness to anti-EGFR therapies, and provide new avenues for intervention in the management of CRC.
This study aimed to investigate genetic factors related to appetite, eating in the absence of hunger and brain reward response to food cues in a convenience sample of pre-adolescent children taken through two studies (A and B). The study involved genome-wide genotyping using the Illumina Global Screening Array. The study found an obesity polygenic risk score related to parent-reported appetitive traits in children, The study also found that FTO was related to eating in the absence of hunger and brain reward response to food cues. Available data include genotypes, measured height and weight, appetitive traits, consumption, brain reward response to food cues, and sociodemographic variables.
With the DAC Portal, it is possible to streamline the process of managing access to sensitive data, ensuring that researchers have the necessary resources to advance scientific discovery while maintaining the highest standards of data protection and privacy. We know that, as a new tool, its first use can be complex. For this reason, in this article we will try to show all the elements of interest. Enjoy! Credentials: who needs to create a new user to access the DAC Portal and who doesn't? Only new users (since September the 12th) need to create an EGA account to access the DAC Portal. The EGA team went one step ahead by creating EGA accounts for former DAC members to login to the DAC Portal. These accounts are linked to the personal email used in the DAC structure: To check the linked email, DAC members can paste the DAC ID right after this link: https://metadata.ega-archive.org/dacs/ (e.g. https://metadata.ega-archive.org/dacs/EGAC00001002543) In case of password oblivion, it is possible to set a new one. All the process is channelled through the personal email. Some DAC members may be interested in updating the DAC email. This action can be done contacting our Helpdesk team. For the correct functioning of the DAC Portal, users must add the missing information of the DAC Profile. For a deeper dive, check out our documentation. The first step: knowing your workspace on the Portal Once logged in to the platform using the EGA User credentials, note the sections available: DACs and Policies. In the first one it is possible to check all user's registered DACs by default. It provides a comprehensive overview of each DAC, including its EGA accessions (EGAC), title, status, and the number of data access requests associated with each DAC. Whereas the Policies section is where users can manage and view all their registered policies, along with their associated EGA accessions, links, and titles. A drop-down menu is available with shortcuts to the most useful pages in the top right corner. It is possible to check DACs and policies, as well as creating new ones. In this menu, users can also contact the Helpdesk team using the “Need Help?” section to make inquiries about DACs and policies. Comprehending the DACs list & making the most of all the features Colours are crucial in the DAC's section as they will indicate the user role and the status in every committee, namely: Yellow: you are the administrator of the DAC and have full control to add other contacts, modify the content, and manage data access requests. Orange: you are a member of the DAC and have the authority to manage data access requests but cannot make any changes to the content. Blue: you have been invited to join the DAC and need to either accept or decline the invitation. Grey: the DAC is currently pending validation by the EGA Helpdesk team. Red: the DAC has been declined by the EGA Helpdesk team. Discover more information on how to view the message from Helpdesk containing the declination reason or how to validate or reject a DAC invitation by taking the tour of the DAC Portal. How to create, register and edit a DAC Creating a DAC is an easy process that only requires users to complete the necessary information. After that, the EGA Helpdesk team will review the proposal and validate the proposal. Once the DAC is validated it is possible for authorised users with admin role to edit it at any time, ensuring that all information and contacts associated with the committee is accurate and up to date. Membership management is controlled by searching for the EGA user looking for their username, email, or organisation. Please, note that for a person's details to appear in this search engine, they must have registered as a EGA user. Data Access Committee administrators manage two types of permissions that apply to contacts: Main contact and Role. Both can be modified at any time: Main contact refers to the primary person we firstly contact for any inquiry about the DAC (please, note that we can contact all DAC members, and this refers to the person we will contact first). Role defines the actions that can be taken by each contact. There are two possible status, admin and member, details of which can be found in the Take the Tour. Keep in mind that, to save the modifications, it is always necessary to click on “Update”. Moreover, it is also possible to delete any contact in a DAC whenever it is needed. The data request process: how to manage access requests The data request process is now channelled through the EGA website. Once a user sends a request access, the petition will go directly to the DAC Portal profile of the DAC members liked to the requested dataset. Whenever a request is received, a sand clock symbol will be displayed next to the DAC responsible for the dataset involved. By clicking on the DAC, it is possible to discover more information about requester(s). In this section, DAC Portal users will also be able to modify the display of the data access requests. It is possible to group requests by dataset accession or username, depending on the user preferences. Additionally, it is possible to isolate specific requests by user or dataset. To accept a request, users must slide the button to the right. Once the button turns green, it signifies that the request is accepted; the requester will be granted access to the requested dataset. To make lives easier, we have implemented a “Select all” button to easily accept or revoke multiple requests at once. To decline requests, it is necessary to slide the button to the left. A red button means the requester will not be granted access to the dataset. The DAC Portal will always ask to submit the reason why the data access was denied. Please, note that any decision, grant or denial, must be confirmed clicking the "Apply" button. This will update the status of the request and notify the requester accordingly. Taking control of the activity in the DAC Portal: checking the requests history The History button is a useful feature that allows users to access a list of all the requests that have been granted. This is especially useful for auditing purposes, as it enables to keep track of who has been granted access to the data and when. To facilitate control for those users with several requests we have included a filtering option. It allows to filter requests by user, mail, dataset, EGA ID, and date (these are combinable to boost the search). Don't forget about policies: creation, management, and update Similarly to the DACs section, in the Policies one users can manage and view all their registered policies. By clicking on any policy, it is possible to view its details as well as making any necessary updates or modifications. The sheets symbol and its adjacent number indicate the quantity of objects using a policy. By clicking in the location symbol users will go directly to the DAC page on the DAC Portal to see more information about that DAC. DAC Portal users can create new policies. The first step requires to link the policy to a registered DAC. After defining the title, users can either add a link to an external URL containing terms & conditions or write the policy content directly on the DAC Portal. Keep in mind that both options can be included. Data Use Ontology (DUO) codes can be added to new policies. These codes are used to specify the permitted and prohibited uses of the data. Please, note that some of them require a modifier to provide additional specificity. Find out more by checking out this specific content on the DAC Portal Tour. Policies can be modified at any given time by clicking on one registered policy, which will display the current information.
For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.
The aim of this study was to assess genomic copy number alterations in a panel of breast cancer cell lines. These data were used to identify common aberrations associated with breast cancer, and also to identify aberrations associated with response to therapeutic compounds.
KRAS mutant CRC is currently in clinical trial with a combination of a MEK and Akt inhibitor. These patients will likely develop resistance to this combination. We aim to identify the mechanisms of resistance via ENU mutagenesis, with a view to identifying additional therapeutics which have the ability to overcome this resistance.
In this project, we aim to identify genetic changes that predispose to epilepsy and those that predict the response to various anti-epileptic drugs. We sequenced whole genomes and whole exomes of epileptic individuals with different range of response to anti-epileptic drugs, and their relatives.
This study investigates the transcriptomic heterogeneity and evolutionary progression of intraductal papillary mucinous neoplasms (IPMNs) and their associated pancreatic ductal adenocarcinomas (PDAC). Multi-region tumour sampling was performed to characterise spatial variation in gene expression and to identify transcriptional changes associated with malignant transformation. The project aims to improve understanding of tumour evolution in pancreatic cancer and to identify molecular pathways involved in IPMN-to-PDAC progression.
This study relates to the overall project of constructing the phylogeny of foetal haematopoiesis. This is an additional project relating to pre-existing work in projects 2043, 2169, 2243 and 2244. This project is to perform WGS (to around 40X) of polyclonal LCM tissues from the 8pcw foetus that have previously undergone library prep and targeted sequencing only. This work is to address reviewers comments for the publication of this work.
Schizophrenia is a complex neuropsychiatric disorder characterized by marked genetic heterogeneity. Much of the genetic architecture of the disorder has yet to be explained, but de novo mutations appear to play an important role. We used exome sequencing of parent-offspring quads and trios to detect de novo mutations in persons with schizophrenia. Patients were more likely to harbor one or more damaging de novo mutations, as compared to their healthy siblings. The genes disrupted by damaging mutations in patients operated in processes important to early brain development.
In this study, we whole genome sequenced tumor/normal pairs from three pancreatic adenocarcinoma patients to separately characterize each patient with respect to somatic alterations. For 2 patients for whom tumor RNA was available, we also performed RNA sequencing to evaluate gene expression changes. While additional sequencing is needed to improve our understanding of the disease, the information acquired from this study contributes to our knowledge base on pancreatic cancer and helps to establish a foundation for identifying and developing more efficacious treatments for patients.
We applied high-fidelity duplex sequencing to 94 samples from 36 individuals exposed to diverse chemotherapies along with 32 controls. We found that in many of the sperm samples from men exposed to chemotherapy, the somatic mutation burden was elevated compared to controls as well as the expected burden based on trio studies. We then validated this finding using other tissues, and also found increased somatic mutation burden in the blood and liver of many subjects exposed to chemotherapy compared to unexposed controls.
Analysis of mutational signatures caused by DNA repair defects in human induced pluripotent stem (iPS) cells. A reference human iPS cell line will be used for genetic manipulation to introduce homozygous knockouts of 100 genes known to be involved in or connected to DNA repair or DNA editing. Following a defined period of growth after homozygous knockout of each gene, sub clones will be generated and sequenced. The progenitor “parental” IPS cell line will be used to generate reference sequence data, in order to determine the mutational signature acquired due to the gene knockout.
We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistanceThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistanceThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
The purpose of this study was to better understand behavioral and physiological functioning in relation to recent self-reported influenza and influenza-like-illness (ILI), including coronavirus disease (COVID-19). Over 65,000 Achievement members responded to a weekly one-click survey asking if they had experienced ILI within the previous 7-day period. If they responded no, they were given the option to complete a survey about their risk factors and behavior. If they responded yes, they were given the option to complete a survey asking about the specifics of the incident. Participants were also asked to sync their wearable activity trackers and health apps in order for researchers to better understand changes in behavioral and physiological outcomes related to self-reported ILI experiences.DOI: https://rapids.ll.mit.edu/10.57895/fkth-d352
Human pigmentation traits are of great interest to many research areas, from ancient DNA analysis to forensic science. We aimed to develop a gene-based predictive model for pigmentation phenotypes in a realistic target population for forensic case work from Northern Germany. Our aim was to determine whether better prediction accuracy can be achieved, or fewer genetic markers may suffice, than in previously studied, genetically more heterogeneous populations. We investigated the association between eye, hair and skin colour, and 12 candidate single nucleotide polymorphisms (SNPs) from six genes. Our study comprised two samples of 300 and 100 individuals from Northern Germany who were carefully characterized with regard to pigmentation phenotypes. The first sample was used to select trait-associated SNPs whereas the second sample served to estimate odds ratios (ORs) and to quantify the predictive capability of the respective SNP genotypes. SNP rs12913832 in HERC2 was found to be strongly associated with blue eye colour (OR=15.6, p<1.2•10-4) and to yield reasonable predictive power (90% sensitivity, 63% specificity). SNP associations with hair and skin colour were weaker and genotypes less predictive. A comparison to two recently published sets of markers to predict eye and hair colour revealed that the consideration of additional SNPs with weak to moderate effect increases the predictive power in Northern Germans for eye colour, but not for hair colour. In addition, fine phenotyping and differentiation of hair colour (light / dark and red tint / no red tint) were found to increase the number of significant genotype-phenotype associations.
We analyzed circulating RNA levels using small RNA sequencing, targeting RNA in the size range 17 to 47 nucleotides, in samples collected prior to endometrial cancer diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to diagnosis , and 316 matched controls, both from the Janus Serum Bank Cohort in Norway.
We would like to direct you to the service provider for the Finnish FEGA Node, which is CSC – IT Center for Science (https://research.csc.fi/-/fega). It's important to note that this is not a genuine DAC and does not serve as the data controller. To obtain access to data stored in FI-FEGA, it is essential to utilize the local access management system SD Apply. Please be aware that applications submitted through the EGA DAC portal will not be processed. For a seamless experience, we kindly request you to refer to the policy of your selected dataset and submit your access application through SD Apply (https://sd-apply.csc.fi/). Your cooperation is highly appreciated.
Enteropathy associated T cell lymphoma (EATL) is frequently preceded by a state of refractoriness to the gluten-free diet, called “refractory celiac disease” or RCD. We aim to study which mutations and copy number aberrations are already manifest in RCD and to identify differences between RCD patients that do, and do not, develop EATL. We have applied whole exome sequencing to detect mutations and copy number aberration predictive for progression from RCD to EATL.
The phase II clinical study CAIN457A2223 (NCT01537432) was designed to evaluate the proportion of patients achieving reversal of chronic plaque psoriasis at weeks 4 and 12 following multiple doses of secukinumab, administered subcutaneously, compared to placebo. 36 patients were enrolled in this study, with 24 being randomly assigned to the treatment arm and 12 to the placebo arm. Starting from week 13, all patients received multiple doses of secukinumab up to week 52 to study long term effects of secukinumab. The microarray gene expression data deposited in this dbGaP study are derived from the early (baseline to week 12) skin biopsies of this clinical trial.
We developed an artificial intelligence (AI)-model applied to histological images using CDH1 biallelic mutations, pathognomonic for breast invasive lobular carcinoma (ILC), as ground truth. We evaluated the performance of the AI-model to predict the presence of CDH1 biallelic mutations and to diagnose ILC. Subsequently, we investigated the molecular underpinning cases of predicted by the model to harbor a CDH1 biallelic mutations but lacking these alterations according to targeted sequencing. Among this analyses, we subjected to whole genome sequencing (WGS) one ILC case lacking CDH1 biallelic mutations by targeted sequencing and lacking CDH1 promoter methylation to determine the molecular basis of its lobular phenotype.
Analysis of mutational signatures caused by DNA repair defects in human induced pluripotent stem (iPS) cells. A reference human iPS cell line will be used for genetic manipulation to introduce homozygous knockouts of 100 genes known to be involved in or connected to DNA repair or DNA editing. Following a defined period of growth after homozygous knockout of each gene, sub clones will be generated and sequenced. The progenitor “parental” IPS cell line will be used to generate reference sequence data, in order to determine the mutational signature acquired due to the gene knockout. This is a pilot study to investigate the effects of oxygen conditions and growth period on mutations acquired
This study aims to elucidate the genetic determinants of susceptibility to aggressive prostate carcinoma. To this end, germ line whole exome sequence has been generated from patients with aggressive prostate cancer. Whole genome sequence for a representative subset of tumors from patients whose cancer was resistant to primary therapy is included as well. This deep genomic interrogation will allow the identification of rare, functionally disruptive variants that may play a role in disease progession and response to treatment.
This study aimed to investigate the genetic basis of severe idiopathic scoliosis (IS) using whole exome sequencing (WES) and SNP array methods. We intended to identify structural and point genetic variations contributing to the development of IS. By analyzing intraoperatively collected articular processes (AP) and blood (BL) samples from 70 unrelated individuals with IS, we sought to uncover pathogenic copy number variants (CNVs), regions of homozygosity (ROH), and single-nucleotide variants (SNVs) linked to the condition. EGAD00001015758
