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dbGaP phs001223 Analysis of AR Gene Rearrangements in Prostate Cancer - pht005799.v1.p1

- 16-05-23 - 5 Formulieren, 1 Itemgroep, 3 Data-elementen, 1 Taal
Itemgroep: pht005799
Principal Investigator: Scott M. Dehm, PhD, Masonic Cancer Center, University of Minnesota, Minneapolis, MN, Departments of Laboratory Medicine and Pathology and Urology, University of Minnesota, Minneapolis, MN, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001223 Molecularly-targeted therapies for advanced prostate cancer include castration modalities that suppress ligand-dependent transcriptional activity of the androgen receptor (AR). However, persistent AR signaling undermines therapeutic efficacy and promotes progression to lethal castration-resistant prostate cancer (CRPC), even when patients are treated with potent second-generation AR-targeted therapies abiraterone and enzalutamide. Here we define diverse AR genomic structural rearrangements (AR-GSRs) as a class of molecular alterations occurring in one third of CRPC-stage tumors. AR-GSRs occur in the context of copy-neutral and amplified AR and display heterogeneity in breakpoint location, rearrangement class, and sub-clonal enrichment in tumors within and between patients. Despite this heterogeneity, one common outcome in tumors with high sub-clonal enrichment of AR-GSRs is outlier expression of diverse AR variant species lacking the ligand binding domain and possessing ligand-independent transcriptional activity. Collectively, these findings reveal AR-GSRs as important drivers of persistent AR signaling in CRPC.

Eligibility

1 Itemgroep 1 Data-element

pht005800.v1.p1

1 Itemgroep 3 Data-elementen

pht005801.v1.p1

1 Itemgroep 5 Data-elementen

pht005802.v1.p1

1 Itemgroep 6 Data-elementen

dbGaP phs000673 University of Michigan Clinical Sequencing Exploratory Research (CSER) - Eligibility

- 25-01-23 - 5 Formulieren, 1 Itemgroep, 16 Data-elementen, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Arul Chinnaiyan, MD PhD, Michigan Center for Translational Pathology, University of Michigan, MI, USA MeSH: Neoplasms,Breast Neoplasms,Sarcoma,Prostatic Neoplasms,Aromatase Inhibitors,Hematologic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000673 Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing & Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics & Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

pht003661.v4.p1

1 Itemgroep 5 Data-elementen

pht003662.v4.p1

1 Itemgroep 4 Data-elementen

pht003663.v4.p1

1 Itemgroep 9 Data-elementen

pht003660.v4.p1

1 Itemgroep 5 Data-elementen

dbGaP phs000717 Genomics of Circulating Tumor Cells - pht003808.v1.p1

- 13-12-22 - 4 Formulieren, 1 Itemgroep, 2 Data-elementen, 1 Taal
Itemgroep: pht003808
Principal Investigator: Christopher Love, Massachusetts Institute of Technology, Cambridge, MA, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000717 Comprehensive analyses of cancer genomes in clinical settings promise to inform prognoses and guide the deployment of precise cancer treatments. A major barrier, however, is the inaccessibility of adequate metastatic tissue for accurate genomic analysis in prostate and other cancers. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming multiple technical hurdles. Here, we report an integrated process to isolate, qualify, and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of over 99.995% of the territory accessible in bulk exome sequencing is possible in CTCs. We validated our sequencing process in two prostate cancer patients including one for whom we compared CTC-derived mutations to mutations found in a lymph node metastasis and nine cores of the primary tumor. 51 of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early trunk mutations and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

pht003809.v1.p1

1 Itemgroep 3 Data-elementen

pht003810.v1.p1

1 Itemgroep 2 Data-elementen

pht003811.v1.p1

1 Itemgroep 3 Data-elementen

dbGaP phs000597 DNA Methylation Analysis of Prostate Cancer - Eligibility

- 13-12-22 - 5 Formulieren, 1 Itemgroep, 1 Data-element, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Dr. Arul M. Chinnaiyan, MD,PhD, University of Michigan, Ann Arbor, MI, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000597 Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

pht003199.v1.p1

1 Itemgroep 5 Data-elementen

pht003200.v1.p1

1 Itemgroep 3 Data-elementen

pht003201.v1.p1

1 Itemgroep 5 Data-elementen

pht003202.v1.p1

1 Itemgroep 10 Data-elementen

dbGaP phs000447 Prostate Cancer Genome Sequencing Project - Eligibility

- 13-12-22 - 5 Formulieren, 1 Itemgroep, 1 Data-element, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Levi Garraway, M.D. Ph.D, Dana Farber Cancer Institute, Boston, MA USA; Broad Institute, Cambridge, MA USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000447 Prostate cancer is a prevalent cause of cancer morbidity and mortality in men. In order to characterize the full range of somatic mutations in protein-coding genes that may drive the growth of prostate cancer, we sequenced the exonic regions of genomic and tumor DNA from over 100 patients with high-risk primary prostate cancer. Using hybrid capture and paired end DNA sequencing, we identified mutations in several novel putative prostate cancer genes. We interrogated copy number changes across tumor genomes using high-density SNP arrays, and identified a molecular subtype of cancer characterized by mutation of the ubiquitin ligase subunit SPOP and copy number loss at specific genomic loci.

pht002580.v1.p1

1 Itemgroep 5 Data-elementen

pht002581.v1.p1

1 Itemgroep 7 Data-elementen

pht002582.v1.p1

1 Itemgroep 11 Data-elementen

pht002579.v1.p1

1 Itemgroep 4 Data-elementen

dbGaP phs000554 Mutational Landscape of Lethal Castrate Resistant Prostate Cancer - pht003197.v1.p1

- 13-12-22 - 5 Formulieren, 1 Itemgroep, 2 Data-elementen, 1 Taal
Itemgroep: pht003197
Principal Investigator: Arul M. Chinnaiyan, MD, PhD, University of Michigan, MI, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000554 Exome sequencing of matched pairs of tumor / normal genomic DNA was performed from high risk localized prostate cancer or lethal, metastatic, castrate resistant prostate cancer (CRPC). Exome libraries were prepared using Illumina Paired_End Genome DNA Sample Prep Kit and captured using Agilent SureSelect Capture Library or Roche EZ Exome capture library. Sequencing was performed on Illumina GAII and HiSeq 2000 platforms in paired end mde, with 80 base pair reads from the final library fragments. Copy number alterations and somatic mutations were identified.

pht003198.v1.p1

1 Itemgroep 13 Data-elementen

pht003196.v1.p1

1 Itemgroep 6 Data-elementen

pht003194.v1.p1

1 Itemgroep 4 Data-elementen

pht003195.v1.p1

1 Itemgroep 5 Data-elementen

dbGaP phs000559 PAGE: Epidemiologic Architecture for Genes Linked to Environment (EAGLE) - BioVU Cancer Project - Eligibility

- 12-12-22 - 5 Formulieren, 1 Itemgroep, 20 Data-elementen, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Dana Crawford, PhD, Vanderbilt University, Nashville, TN, USA MeSH: Neoplasms,Breast Neoplasms,Colorectal Neoplasms,Endometrial Neoplasms,Lung Neoplasms,Lymphoma, Non-Hodgkin,Ovarian Neoplasms,Melanoma,Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000559 As part of Population Architecture using Genomics and Epidemiology PAGE study (Phase I), the Epidemiologic Architecture using Genomics and Epidemiology (EAGLE I) project accessed both epidemiologic- and clinic-based collections. The epidemiologic-based collection of EAGLE I included the National Health and Nutritional Examination Surveys (NHANES), ascertained between 1991-1994 (NHANES III), 1999-2002, and 2007-2008. NHANES is a population-based cross-sectional survey now conducted every year in the United States to assess the health status of Americans at the time of ascertainment and to assess trends over the years of survey. Genetic NHANES consists of 19,613 DNA samples linked to thousands of variables including demographics, health and lifestyle variables, physical examination variables, laboratory variables, and exposures. NHANES is diverse with almost one-half of the samples (46.4%) coming from self-reported Mexican Americans and non-Hispanic blacks. In contrast to NHANES, BioVU is a clinic-based collection of 150,000 DNA samples from Vanderbilt University Medical Center linked to de-identified electronic medical records (EMRs). Approximately 12% of BioVU's overall DNA sample collection is from African American, Hispanic, and Asian patients. The overall goals of PAGE I and EAGLE I were broad and several-fold:- Replicate genome-wide association study (GWAS)- identified variants in European Americans; - Identify population-specific and trans-population genotype-phenotype associations; - Identify genetic and environmental modifiers of these associations. NHANES is an excellent resource for the study of quantitative traits associated with common human diseases. However, given that the age range of NHANES spans childhood to late adulthood and not all diseases are surveyed, NHANES is less useful for the study of adult-onset diseases such as major cancers. Therefore, under American Recovery and Reinvestment Act (ARRA) funding, EAGLE as part of PAGE I defined eight major cancers sites for genetic analysis in BioVU, Vanderbilt's biorepository linked to de-identified EMRs. The eight major cancers defined for this study included melanoma, breast, ovarian, prostate, colorectal, lung, endometrial, and Non-Hodgkin's lymphoma (NHL). Cancer cases were defined using a combination of ICD-9 codes and tumor registry entries. Controls include BioVU participants without cancer and encompassing the age and gender distributions of cancer cases. Targeted genotyping of GWAS-identified variants for these diseases (124 SNPs) and ancestry informative markers (128 AIMs) was performed by the Center for Human Genetics Research Vanderbilt DNA Resources Core. After quality control, a total of 116 cancer-associated SNPs and 122 AIMs were available for downstream analyses.

pht003614.v1.p1

1 Itemgroep 2 Data-elementen

pht003615.v1.p1

1 Itemgroep 3 Data-elementen

pht003616.v1.p1

1 Itemgroep 58 Data-elementen

pht003617.v1.p1

1 Itemgroep 5 Data-elementen

dbGaP phs000602 Identification of Targetable FGFR Gene Fusions in Diverse Cancers - Eligibility

- 11-11-22 - 4 Formulieren, 1 Itemgroep, 19 Data-elementen, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Arul M. Chinnaiyan, MD, PhD, University of Michigan, MI, USA MeSH: Neoplasms,Cholangiocarcinoma,Breast Neoplasms,Prostatic Neoplasms,Urinary Bladder Neoplasms,Mouth Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000602 In this study, patients with advanced cancer across all histologies were enrolled in our IRB approved clinical sequencing program, called MI-ONCOSEQ, to go through an integrative sequencing which includes whole exome sequencing of the tumor and matched normal, and transcriptome sequencing. Four index cases were identified which harbor gene rearrangements of FGFR2 including two cholangiocarcinoma cases, a metastatic breast cancer case, and a metastatic prostate cancer case. After extending our assessment of FGFR rearrangements across multiple tumor cohorts, including TCGA, we identified FGFR gene fusions with intact kinase domains of FGFR1, FGFR2, or FGFR3 in cholangiocarcinoma, breast cancer, prostate cancer, lung squamous cell cancer, bladder cancer, thyroid cancer, oral cancer, glioblastoma, and head and neck squamous cell cancer. All FGFR fusion partners tested exhibit oligomerization capability, suggesting a shared mode of kinase activation. Overexpression of FGFR fusion proteins in vitro induced cell proliferation, and bladder cancer cell lines that harbors FGFR3 fusion proteins exhibited enhanced susceptibility to pharmacologic inhibition in vitro and in vivo. Due to the combinatorial possibilities of FGFR family fusion to a variety of oligomerization partners, clinical sequencing efforts which incorporate transcriptome analysis for gene fusions are poised to identify rare, targetable FGFR fusions across diverse cancer types.

pht003221.v1.p1

1 Itemgroep 5 Data-elementen

pht003222.v1.p1

1 Itemgroep 6 Data-elementen

pht003220.v1.p1

1 Itemgroep 5 Data-elementen

dbGaP phs000311 FusionSeq: Finding Fusions with Paired-End RNA-Seq - pht002127.v1.p1

- 12-10-22 - 5 Formulieren, 1 Itemgroep, 5 Data-elementen, 1 Taal
Itemgroep: pht002127
Principal Investigator: Mark A. Rubin, MD, Weill Cornell Medical College, New York, NY, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000311 We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts such as misalignments or random pairing of transcript fragments and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including 8 cancers with and without known rearrangements.

pht002128.v1.p1

1 Itemgroep 4 Data-elementen

pht002129.v1.p1

1 Itemgroep 8 Data-elementen

pht002130.v1.p1

1 Itemgroep 10 Data-elementen

Eligibility

1 Itemgroep 1 Data-element

dbGaP phs000306 A Multiethnic GWAS of Prostate Cancer - pht002081.v1.p1

- 12-10-22 - 8 Formulieren, 1 Itemgroep, 20 Data-elementen, 1 Taal
Itemgroep: pht002081
Principal Investigator: Christopher Haiman, ScD, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000306 Multiple GWA studies of prostate cancer conducted in European White populations are ongoing. These studies will continue to have a dramatic impact on our understanding of the contribution of common genetic variation on inter-individual susceptibility to this common cancer. Important questions that will remain unanswered, however, are whether all common risk alleles for prostate cancer will be revealed in studies limited to populations of European ancestry. A comprehensive examination of common genetic variation in men of Japanese, Latino, and African ancestry will be required to understand population differences in disease risk and to reveal the full spectrum of causal alleles that exist in these populations. Further, genetic and environmental diversity is likely to contribute to ethnic heterogeneity of genetic effects. Elucidating gene x gene and gene x environment interactions is also likely to provide knowledge that may be critical for understanding the contribution of genetic susceptibility to racial/ethnic disparities in prostate cancer incidence and for translating the findings from GWA studies into interventions. In this study we plan to undertake a genome-wide association study (GWAS) of prostate cancer in the Multiethnic Cohort (MEC) Study. We propose the following hypotheses: (a) that inherited DNA variation influences risk of prostate cancer; (b) that many of the causal alleles will be outside known "candidate genes" requiring an agnostic, comprehensive search; and (c) that performing this search in a multi-ethnic cohort is more powerful than a study limited to a single population to reveal the full range of causal alleles relevant to the U.S. population. The version 1 release of this dataset will include genotype data for the Japanese and Latino populations in the study. The version 2 release will include data for the African ancestry population along with the Japanese and Latino subjects. The version 3 release will include fully-cleaned genotype data for all three populations. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prostate cancer through large-scale genome-wide association studies of a well-characterized multi-ethnic cohort. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center and at the University of Southern California. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington. As an add-on to this GWAS we performed a targeted re-sequencing of all known prostate cancer risk loci in the samples from the MEC. Sequencing was performed in Dr. Reich's lab at Harvard Medical School.

pht001908.v2.p1

1 Itemgroep 4 Data-elementen

pht001911.v1.p1

1 Itemgroep 20 Data-elementen

pht001909.v1.p1

1 Itemgroep 5 Data-elementen

pht001910.v3.p1

1 Itemgroep 5 Data-elementen

Eligibility

1 Itemgroep 2 Data-elementen

pht002082.v1.p1

1 Itemgroep 9 Data-elementen

dbGaP phs000310 Discovery of Non-ETS Gene Fusions using RNA Sequencing - Eligibility

- 12-10-22 - 5 Formulieren, 1 Itemgroep, 1 Data-element, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Mark A. Rubin, Weill Cornell Medical College, New York, NY, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000310 Half of prostate cancers harbor gene fusions between *TMPRSS2* and members of the *ETS* transcription factor family. To date little is known about the presence of non-ETS fusion events in prostate cancer. We employed next-generation transcriptome sequencing (RNA-Seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes *ETV1* and *ERG*, and five involving non-ETS genes such as *CDKN1A* (p21), *CD9* and *IKBKB* (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene *RSRC2*. The novel gene fusions are found to be of low frequency but interestingly, the non-ETS fusions were all present in prostate cancer harboring the *TMPRSS2-ERG* gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement prone phenotype.

pht002095.v1.p1

1 Itemgroep 5 Data-elementen

pht002096.v1.p1

1 Itemgroep 4 Data-elementen

pht002097.v1.p1

1 Itemgroep 11 Data-elementen

pht002131.v1.p1

1 Itemgroep 10 Data-elementen

dbGaP phs000350 FHCRC - Whole-Exome Sequencing of Hereditary Prostate Cancer Families - pht002201.v1.p1

- 12-10-22 - 6 Formulieren, 1 Itemgroep, 6 Data-elementen, 1 Taal
Itemgroep: pht002201
Principal Investigator: Janet L. Stanford, PhD, Fred Hutchinson Cancer Research Center, Seattle, WA, USA MeSH: Prostatic Neoplasms https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000350 The specific aim of this study is to identify hereditary prostate cancer (HPC) susceptibility genes using a novel study design, whereby whole-exome sequencing will be undertaken on multiple affected relatives from 19 HPC families, in which ≥ 3 affected relatives were diagnosed with clinically aggressive and/or early onset prostate cancer (PC). While whole-exome sequencing of unrelated affected individuals would result in hundreds of candidate disease variants, this family-based, aggressive/early onset phenotype approach will provide an enriched genetic background for discovery and significantly reduce the number of candidate mutations that will require follow-up. Findings from this pilot study will immediately be followed-up to confirm whether candidate mutations found in each family segregate with disease in the remaining unscreened relatives. As part of this pilot study, we aim to:- Perform whole-exome sequencing on 80 affected and 11 unaffected relatives from 19 HPC families that have multiple men diagnosed with an aggressive and/or early onset disease phenotype using the Illumina HiSeq platform; and, - Analyze sequencing data using BWA, SAMtools and SeattleSeq to prioritize candidate HPC mutations that segregate with aggressive and/or early onset disease in affected relatives.

pht002202.v1.p1

1 Itemgroep 4 Data-elementen

pht002203.v1.p1

1 Itemgroep 6 Data-elementen

pht002199.v1.p1

1 Itemgroep 5 Data-elementen

pht002200.v1.p1

1 Itemgroep 5 Data-elementen

Eligibility

1 Itemgroep 1 Data-element

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