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Whole genome sequencing was conducted on 10 tumor/germline paired samples along with 20 additional unpaired tumor samples from patients with Waldesntrom's macroglobulinemia. Tumor lymphoplasmacytic lymphoma cells were obtained from CD19+ selected bone marrow mononuclear cells. Germline tissue was obtained from CD19 depleted peripheral blood mononuclear cells. High molecular weight DNA was then submitted for whole genome sequencing with Complete Genomics and aligned to HG19/NCBI human reference build 37.
Analysis of the chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational activation The pathogenesis of chronic lymphocytic leukemia (CLL), the most common leukemia in adults, is still largely unknown since the full spectrum of genetic lesions that are present in the CLL genome, and therefore the number and identity of dysregulated cellular pathways, have not been identified. By combining next-generation sequencing and copy number analysis, we show here that the typical CLL coding genome contains less than 20 clonally represented gene alterations/case, including predominantly non-silent mutations and fewer copy number aberrations. These analyses led to the discovery of several genes not previously known to be altered in CLL. While most of these genes were affected at low frequency in an expanded CLL screening cohort, mutational activation of NOTCH1, observed in 8.3% of CLL at diagnosis, was detected at significantly higher frequency during disease progression toward Richter transformation (31.0%) as well as in chemorefractory CLL (20.8%). Consistent with the association of NOTCH1 mutations with clinically aggressive forms of the disease, NOTCH1 activation at CLL diagnosis emerged as an independent predictor of poor survival. These results provide initial data on the complexity of the CLL coding genome and identify a dysregulated pathway of diagnostic and therapeutic relevance. Genetic Lesions associated with Chronic Lymphocytic Leukemia transformation to Richter Syndrome Richter syndrome (RS) derives from the rare transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, most commonly of the diffuse large B cell type (DLBCL). The molecular pathogenesis of RS is only partially understood. By combining whole-exome sequencing and copy-number analysis of 9 CLL-RS pairs and of an extended panel of 43 RS cases, we show that this aggressive disease typically arises from the predominant CLL clone by acquiring an average of ~20 genetic lesions/case. RS lesions are heterogeneous in terms of load and spectrum among patients, and include those involved in CLL progression and chemorefractoriness (TP53 disruption and NOTCH1 activation) as well as some not previously implicated in CLL or RS pathogenesis. In particular, disruption of the CDKN2A/B cell cycle regulator locus is associated with ~30% of RS cases. Finally, we report that the genomic landscape of RS is significantly different from that of de novo DLBCL, suggesting that they represent distinct disease entities. These results provide insights into RS pathogenesis, and identify dysregulated pathways of potential diagnostic and therapeutic relevance.
Pilocytic astrocytoma (PA), the most common childhood brain tumor, is a low-grade glioma with a single driver BRAF rearrangement. Here, we perform scRNAseq in six PAs using methods that enabled detection of the rearrangement. When compared to higher-grade gliomas, a strikingly higher proportion of the PA cancer cells exhibit a differentiated, astrocyte-like phenotype. A smaller proportion of cells exhibit a progenitor-like phenotype with evidence of proliferation. These express a mitogen-activated protein kinase (MAPK) program that was absent from higher-grade gliomas. Immune cells, especially microglia, comprise 40% of all cells in the PAs and account for differences in bulk expression profiles between tumor locations and subtypes. These data indicate that MAPK signaling is restricted to relatively undifferentiated cancer cells in PA, with implications for investigational therapies directed at this pathway. Note that 931 out of 1234 samples in the Sequence Read Archive (SRA) passed QC and have transcript count data available from the Broad Institute Single Cell Portal. The transcript count data can be found at https://singlecell.broadinstitute.org/single_cell/study/SCP271/pilocytic-astrocytoma-single-cell-rna-seq#study-download
Chronic lymphocytic leukemia (CLL) is a subtype of B-cell lymphoproliferative disorders (LPD), and is the most common form of adult leukemia in Caucasians in the United States. Small lymphocytic lymphoma (SLL) is also a B-cell LPD and is typically considered to be the same disease as CLL, based on pathology. We consider CLL and SLL as the same disease entity, and hereafter refer to both simply as "CLL". Using genealogical databases and cancer records, the familial clustering for CLL is one of the strongest for all cancer sites, strongly implicating germline genetic risk. We ascertained CLL cases and controls for a genomewide association study (GWAS) that was undertaken as part of the International Lymphoma Epidemiology (InterLymph) consortium GWAS. Some CLL cases are also part of extended high-risk CLLpedigrees.
Metastatic melanoma patients who develop melanoma-associated vitiligo, an autoimmune cutaneous side effect after receiving immunotherapy, have better overall survival than those who do not develop vitiligo. The objective of this study is to determine the tumor-specific memory T cell responses in the skin, tumor and blood of melanoma patients with vitiligo. Matched melanoma tumor, distant vitiligo-affected skin, and blood were collected and sorted for T cells to perform paralleled single-cell RNA sequencing (scRNA-seq) and single-cell TCR sequencing (scTCR-seq) on the day of tissue collection. The transcriptional analysis identified three resident memory T (TRM) cell subsets which were shared between tumors and vitiligo-affected skin. scRNA-seq identified CD8+ T-cell clonotypes in tumors that co-existed as TRM in skin and as effector memory T (TEM) cells in blood. This study revealed that long-term melanoma survivors maintained memory T cell responses as broadly-distributed TRM and TEM compartments. 
Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer by incidence worldwide(1). Various chemical carcinogens (tobacco, alcohol and betel nut), human papillomavirus (HPV) infection, and genetic predisposition contribute to the etiology of HNSCC, and to the complex genetic alterations in tumor subsets that differ in prognosis and response to therapies (2). Recently, a comprehensive landscape of genomic and transcriptomic alterations in HNSCC tumors has emerged from The Cancer Genome Atlas (TCGA) Network (3). TCGA revealed novel and previously recognized gene and chromosomal region copy number alterations (CNAs), mutations, and expression clusters, and defined their frequency, co-occurrence, and relationship to common and rare subtypes of HPV(-) and (+) tumors that vary in prognosis. To identify cell line models for determining the functional role and therapeutic importance of these alterations, we are performing whole exome and RNA sequencing and bioinformatic analysis of an expanded panel of 15 HPV(-) and 11 HPV(+) HNSCC cell lines and primary oral keratinocytes. We find that the recurrent genomic alterations in cell lines are remarkably consistent with those found in more aggressive tumors, from which cell lines have traditionally been most readily adapted to culture (4). Genome-wide correlation of CN (copy number) with expression identified a suite of potential drivers or modifier genes that differ by HPV status, and are of potential biologic and therapeutic relevance. Further, our findings elucidate and validate genomic alterations underpinning numerous discoveries made with these widely-used and recently derived HNSCC lines, and provide a roadmap for their potential use as models for future studies of tumor subtypes with worse prognosis. References Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87-108. Van Waes C, Musbahi O. Genomics and advances towards precision medicine for head and neck squamous cell carcinoma. Laryngoscope Investig Otolaryngol. 2017;2(5):310-9. Cancer Genome Atlas N. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 2015;517(7536):576-82. White JS, Weissfeld JL, Ragin CC, Rossie KM, Martin CL, Shuster M, et al. The influence of clinical and demographic risk factors on the establishment of head and neck squamous cell carcinoma cell lines. Oral Oncol. 2007;43(7):701-12.
This study is designed to help us understand the biological factors that contribute to the development of Cutaneous T Cell Lymphoma (CTCL) through the use of single-cell -omics technologies. The data that will be available include single-cell RNAseq and paired single-cell TCRseq data from the primary lesions of CTCL patients.The number of consented subjects listed here is artificially inflated by one to account for the pooling of all subjects.
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.
Ocular melanocytosis is the most important predisposing condition for the eye cancer uveal melanoma (UM). Here we used whole-exome and deep targeted sequencing to identify for the first time a clonal Gq pathway mutation in ocular melanocytosis, which gave rise to UM. Additionally, we elucidated the order in which canonical genetic aberrations were acquired during tumor evolution. These findings provide a mechanistic explanation for the well-known clinical association of ocular melanocytosis with UM, and they provide new insights into UM tumor evolution. Reprinted from: Durante MA, Field MG, Sanchez MI, Covington KR, Decatur CL, Dubovy SR, Harbour JW. Genomic evolution of uveal melanoma arising in ocular melanocytosis, with permission from Cold Spring Harbor Molecular Case Studies.
The overall goal of our research is to elucidate the pathogenesis of exfoliation syndrome and the associated glaucoma, making it possible to implement effective screening and prevention strategies and to develop novel therapies. Cases genotyped for this project are from the Nurses Health Study (NHS), the Health Professionals Follow-up Study (HPFS), the Women's Genome Health Study (WGHS), the Massachusetts Eye and Ear Infirmary (MEEI), Mayo Clinic, the University of Iowa, the University of Miami and Duke University Medical Center. Exfoliation syndrome (XFS) is a common condition that is a major risk factor for high-tension open-angle glaucoma, pre-mature cataract formation, and increased risk of complications during cataract surgery. Previous studies suggest that exfoliation syndrome and the related glaucoma (XFG) are genetically complex, and one gene, LOXL1, has been identified as a major genetic risk factor. LOXL1 variants are found in up to 98% of affected patients; however, these same variants are also present in up to 80% of unaffected individuals, indicating that additional genetic and/or environmental factors are necessary for disease development. Samples genotyped for this study are a case set (1,096 samples) and 24 pedigrees (98 samples). Controls for association analyses are selected from the NEIGHBORHOOD study.
The study was conducted in Bulgaria as a collaboration between the Molecular Medicine Center (Medical University, Sofia), the Bulgarian Addictions Institute (Sofia), the Initiative for Health Foundation (Sofia) and Washington University School of Medicine (Saint Louis, MO, USA). This is a case-population control study. Participants (N=2,499 interviews; N=1,995 with GWAS data) in our study are primarily active heroin users (78%) aged 18 and over, with a median 8.9 years of daily heroin use (minimum of 12 months). Virtually all participants (99.1%) qualified for a lifetime DSM-IV diagnosis of dependence, symptom endorsement probabilities ranging from 77% to 99.3%; and 61% endorsing all symptoms. 85% were heroin injectors and 97% reported using (or having used) heroin daily. Anonymized, population-representative control samples (no phenotypic data, N = 1,062 with GWAS data) were drawn from the MMC repository. Unlike other studies, where samples are clinically ascertained (e.g., from ORT programs), our participants are primarily untreated. PTSD, major depression, suicidality, mania, alcohol, nicotine and substance dependence (separating heroin and opioids) were assessed using the MAGIC (Todd et al., 2003, PMID: 14627881), a broad semi-structured psychiatric assessment tool with good reliability and prospective stability. The onset of (any) illicit drug use in this sample is not particularly remarkable (age~16), but the age of onset of heroin use is much lower than in the USA: 25% by age 16; 50% by age 19, with no differences between ethnicities or gender. This is consistent with findings from other studies in Bulgaria. In contrast, in 2008, SAMHSA estimated an average age of 23.4 for new heroin initiates in the USA. Further, progression from first use to regular use appears to be more rapid, with the majority of participants reporting onset of dependence problems within one year of initiation. Another unique aspect of this study population are the comparatively low levels of polysubstance use (outside of nicotine and alcohol). This early-use, fast-transition and monosubstance heroin pattern stands in sharp contrast to what is reported in many studies in the Western World. In our study, 47% of Ethnic Bulgarians and 66% of Roma used only opioids, even years after the onset of drug use. 15.4% of Ethnic Bulgarians and 66.2% of Roma reported heroin as the very first illicit drug used. Lifetime, 12.5% of Ethnic Bulgarians and 52.8% of Roma report never having used another illicit drug other than heroin more than five times. While both Roma and Ethnic Bulgarians certainly experiment with other drugs, abuse/dependence rates for these drugs are low in Ethnic Bulgarians (from 8.4% for inhalants to 28% for stimulants) and in the Roma population (from 1.3% for hallucinogens to 11.2% for stimulants).
The main goals of the GICC Study were: 1) to identify novel genetic risk variants for glioma, as well as validate variants implicated by previous genome-wide association studies of glioma; and 2) to explore biologically relevant gene-gene and gene-environment interactions in glioma susceptibility. The GICC Study includes participants from the following centers: Brigham and Women's Hospital (Boston, Massachusetts), Case Western Reserve University (Cleveland, Ohio), Columbia University (New York, New York), the Danish Cancer Society Research Centre (Copenhagen, Denmark), Duke University (Durham, North Carolina), the University of Texas MD Anderson Cancer Center (Houston, Texas), Memorial Sloan Kettering Cancer Center (New York, New York), the Mayo Clinic (Rochester, Minnesota), NorthShore HealthSystem (Chicago, Illinois), Umea University (Umea, Sweden), the University of California, San Francisco (San Francisco, California), the University of Southern California (Los Angeles, California), and the Institute of Cancer Research (London, United Kingdom).
This study was the first-known effort to complete the complete genome sequencing of primary colorectal adenocarcinomas and the matched germline genome. Nine colorectal adenocarcinomas selected on the basis of having chromosomal instability were subjected to 'shotgun' Illumina sequencing with 101-bp paired end reads to an approximate goal of 30x coverage of tumor and of normal. From these sequences, we used various computational techniques to identify somatic point mutations, insertion/deletions and structural rearrangements in these tumors. From these data, we identified new insights into the rates of background mutations in these cancers, new spectrums of structural alterations including the identification of a novel in-frame fusion gene.
This is a comprehensive genomic analysis of a rare set of secondary histiocytic/dendritic sarcomas from the consult service of the Hematopathology section of the Laboratory of Pathology, NCI, NIH.
Uveal melanoma (UM) is the most common primary cancer of the eye and frequently leads to metastatic death. Metastatic risk can be stratified into low, intermediate and high based on the presence of mutually exclusive mutations in EIF1AX, SF3B1 and BAP1, respectively. The purpose of this study was to comprehensively profile the genetic aberrations in a set of primary uveal melanomas using whole exome sequencing, as well as DNA methylation profiling of selected samples, to improve understanding of its pathogenesis.
Immune checkpoint therapies, including monoclonal antibodies to programmed cell death-1 (PD-1) and cytotoxic % lymphocyte associated protein-4 (CTLA-4), yield durable clinical responses across many tumor types, including metastatic melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). However, predictors of response to these therapies in RCC are still unknown. Genomic characterization of large clinical cohorts of patients treated with anti-CTLA-4 and anti-PD-1 agents in melanoma and NSCLC have suggested that high mutational burden, high neoantigen burden, and high expression of certain genes in pre-treatment tumors may be associated with patient response to these therapies. In this study, we sought to investigate genomic predictors of response to anti-PD1 therapy in metastatic RCC in two independent clinical cohorts using whole exome and whole transcriptome sequencing.
The purpose of this study was to obtain tissue specimens derived from patients with melanoma to generate research tools to advance our understanding of the genetics, pathogenesis, and therapeutics of melanoma. Briefly, tissue was obtained from metastatic lesions and used to generate clonal primary cell lines from melanoma cells and fibroblasts from the tumor microenvironment. RNA was extracted from low passage cell lines using Trizol reagent. cDNA libraries were prepared using the TruSeq mRNA sample preparation kit, v2 (Illumina) and sequenced on the HiSeq 2000 platform (Illumina). The submitted files are bam files that contain both unaligned and aligned reads (human genome, build hg19).
Ewing Sarcoma (EwS) is rare but the second most common cancer in children, adolescents and young adults. Recent studies suggest germline variation in or around GGAA microsatellites may interact with fusion oncoprotein binding causing changes in binding affinity and potentially impacting enhancer activity on nearby target genes. This study aims to better understand germline variation around EwS susceptibility regions by performing long-range haplotype sequencing of these regions using PacBio sequencing. Our analysis focused on characterizing variation in GGAA microsatellite length as well as germline variants in or around the microsatellite and their association with EwS risk.
T cells were sorted from metastatic tumors (colon, rectal, breast, anal, melanoma primary histologies) following tumor dissociation and single-cell sequencing was performed (RNAseq and TCRseq). For samples from tumors that had been previously studied, cells were analyzed comparing known neoantigen-reactive TCR-expressing cells to other T cells. For samples without previously identified neoantigen reactivity, TCRs were predicted on the basis of T cell transcriptomic states. To determine candidate neoantigen screening, exome and RNA sequencing were performed on fragments of matched tumors from which T cells were sequenced
Recently developed methods that utilize partitioning of long genomic DNA fragments, and barcoding of shorter fragments derived from them, have succeeded in retaining long-range information in short sequencing reads. These so-called read cloud approaches represent a powerful, accurate, and cost-effective alternative to single-molecule long-read sequencing. We developed software, GROC-SVs, that takes advantage of read clouds for structural variant detection and assembly. We apply the method to two 10x Genomics data sets, one chromothriptic sarcoma with several spatially separated samples, and one breast cancer cell line, all Illumina-sequenced to high coverage. Comparison to short-fragment data from the same samples, and validation by mate-pair data from a subset of the sarcoma samples, demonstrate substantial improvement in specificity of breakpoint detection compared to short-fragment sequencing, at comparable sensitivity, and vice versa. The embedded long-range information also facilitates sequence assembly of a large fraction of the breakpoints; importantly, consecutive breakpoints that are closer than the average length of the input DNA molecules can be assembled together and their order and arrangement reconstructed, with some events exhibiting remarkable complexity. These features facilitated an analysis of the structural evolution of the sarcoma. In the chromothripsis, rearrangements occurred before copy number amplifications, and using the phylogenetic tree built from point mutation data, we show that single nucleotide variants and structural variants are not correlated. We predict significant future advances in structural variant science using 10x data analyzed with GROC-SVs and other read cloud-specific methods.
The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in childhood cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Although the survival of children with relapsed osteosarcoma is very poor, little is known about the etiology of treatment failure in this disease. The purpose of this project is to perform whole genome sequencing on serial samples from patients with osteosarcoma obtained before treatment, after treatment, and at relapse/metastasis in order to identify the mutations and pathways that are drivers of drug resistance. If successful, our results may help identify patients at high risk for treatment failure and may yield new treatments for children who cannot currently be cured.
The Ewing sarcoma family of tumors (EFT) is a group of malignant small round blue cell tumors that arise in bone or soft tissue. Ewing sarcoma (ES) is the second most common type of primary bone tumor to affect children and adolescents and accounts for 2.9% of all childhood cancers. This data set reports whole-genome sequencing of 6 primary Ewing's Sarcoma samples and matching germline samples.
Through clinical trials focused on molecularly guided therapy in pediatric cancers (NCT01355679, NCT01802567, NCT02162732), the Beat Childhood Cancer Consortium performed paired tumor/normal whole exome sequencing and/or tumor mRNA sequencing for 202 pediatric or adolescent young adult patients with rare, relapsed and refractory cancers (including neuroblastoma, Ewing sarcoma, osteosarcoma, rhabdomyosarcoma, ependymoma, glioma, and other rare solid tumors). A subset of these patients had multiple biopsies sequenced, including longitudinal profiling.
Despite the growing incidence of hepatocellular carcinoma (HCC) due to increased hepatitis C virus infection and non-alcoholic steatohepatitis in Western populations, the genetic determinants of this cancer have yet to be established. A minority (15-20%) of HCC occurs in livers without cirrhosis or other chronic disease. Because the liver is functionally preserved in these patients and surgical resection of the tumor may be performed safely, and because of the scarcity of livers available for transplantation, non-cirrhotic patients undergo surgical resection for HCC treatment. These resected tumors present investigatory opportunities in two ways: First, they provide tumor specimen which have not been treated with chemotherapy and embolization. Second, the absence of cirrhosis may provide an unconfounded background from which to investigate the genetic tumorigenesis of HCC. In livers with cirrhosis, genetic instability is prevalent as assessed by assays for microsatellite instability, loss of heterozygosity and aberrant DNA methylation. In contrast, in livers without cirrhosis, the non-tumor tissue surrounding HCC have been found to have fewer genetic aberrations. It has been postulated that the pathologic process of cirrhosis may result in the accumulation of many "passenger"; as well as "driver" mutations, and that the examination of the HCC cancer genome may be facilitated in non-cirrhotic livers because of the absence of an accumulated background noise of mutations.
This study contains sequence data from 15 patients with stage IV melanoma, including the whole genome sequence of 15 metastatic tumors and corresponding normal blood samples from 13 cases, and targeted capture sequence of four synchronous metastatic samples from two additional cases. These data provide a comprehensive survey of the clonal architecture and associated driver mutations in metastatic melanoma.
