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Open accessJournal ArticleDOI: 10.1016/J.STEM.2021.02.005

Development, maturation, and maintenance of human prostate inferred from somatic mutations

02 Mar 2021-Cell Stem Cell (Elsevier)-Vol. 28, Iss: 7
Abstract: Clonal dynamics and mutation burden in healthy human prostate epithelium are relevant to prostate cancer. We sequenced whole genomes from 409 microdissections of normal prostate epithelium across 8 donors, using phylogenetic reconstruction with spatial mapping in a 59-year-old man's prostate to reconstruct tissue dynamics across the lifespan. Somatic mutations accumulate steadily at ∼16 mutations/year/clone, with higher rates in peripheral than peri-urethral regions. The 24-30 independent glandular subunits are established as rudimentary ductal structures during fetal development by 5-10 embryonic cells each. Puberty induces formation of further side and terminal branches by local stem cells disseminated throughout the rudimentary ducts during development. During adult tissue maintenance, clonal expansions have limited geographic scope and minimal migration. Driver mutations are rare in aging prostate epithelium, but the one driver we did observe generated a sizable intraepithelial clonal expansion. Leveraging unbiased clock-like mutations, we define prostate stem cell dynamics through fetal development, puberty, and aging.

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Topics: Prostate cancer (52%), Stem cell (51%), Mutation (51%)

7 results found

Journal ArticleDOI: 10.1016/J.SEMCANCER.2021.06.016
Weiping Li1, Michael M. Shen1Institutions (1)
Abstract: Although prostate adenocarcinoma lacks distinguishable histopathological subtypes, prostate cancer displays significant inter- and intratumor heterogeneity at the molecular level and with respect to disease prognosis and treatment response. In principle, understanding the basis for prostate cancer heterogeneity can help distinguish aggressive from indolent disease, and help overcome castration-resistance in advanced prostate cancer. In this review, we will discuss recent advances in understanding the cell types of origin, putative cancer stem cells, and tumor plasticity in prostate cancer, focusing on insights from studies of genetically engineered mouse models (GEMMs). We will also outline future directions for investigating tumor heterogeneity using mouse models of prostate cancer.

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3 Citations

Open accessJournal ArticleDOI: 10.1016/J.TIG.2021.06.012
Sigurgeir Olafsson1, Carl A. Anderson1Institutions (1)
01 Oct 2021-Trends in Genetics
Abstract: Somatic evolution of cells within the body is well known to lead to cancers. However, spread of somatic mutations within a tissue over time may also contribute to the pathogenesis of non-neoplastic diseases. Recent years have seen the publication of many studies aiming to characterize somatic evolution in healthy tissues. A logical next step is to extend such work to diseased conditions. As our understanding of the interplay between somatic mutations and non-neoplastic disease grows, opportunities for the joint study of germline and somatic variants will present themselves. Here, we present our thoughts on the utility of somatic mutations for understanding both the causes and consequences of common complex disease and the challenges that remain for the joint study of the soma and germline.

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Topics: Somatic evolution in cancer (55%), Somatic cell (53%), Germline (51%)

1 Citations

Journal ArticleDOI: 10.1016/J.CANLET.2021.10.035
Laura Crowley1, Michael M. Shen1Institutions (1)
28 Jan 2022-Cancer Letters
Abstract: The recent advent of single-cell RNA-sequencing technology has provided new fundamental insights into the heterogeneity of the prostate epithelium. Several independent studies have described extensive heterogeneity of the luminal epithelial compartment, including a major division between a novel population of luminal cells located in the proximal region of the prostate ducts versus luminal cells located more distally. Proximal luminal cells as well as novel periurethral cells display increased progenitor potential in organoid culture and tissue reconstitution assays, but not in lineage-tracing analyses during prostate homeostasis, suggesting context-dependent plasticity of these populations. Here we describe and synthesize recent findings regarding the epithelial cell populations in the mouse prostate, draw comparisons to the human prostate, and address the relevance of these findings to prostate diseases and cancer.

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Topics: Prostate (53%), Population (51%)

Open accessPosted ContentDOI: 10.21203/RS.3.RS-745238/V1
Joakim Lundeberg1, Andrew Erickson2, Emelie Berglund1, Mengxiao He1  +30 moreInstitutions (9)
30 Jul 2021-bioRxiv
Abstract: Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

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Topics: Copy-number variation (50%)

Journal ArticleDOI: 10.1038/S41585-021-00524-7
Amin Ali1, Alexander Du Feu1, Pedro Oliveira, Ananya Choudhury1  +2 moreInstitutions (1)
Abstract: Localized prostate cancer shows great clinical, genetic and environmental heterogeneity; however, prostate cancer treatment is currently guided solely by clinical staging, serum PSA levels and histology. Increasingly, the roles of differential genomics, multifocality and spatial distribution in tumorigenesis are being considered to further personalize treatment. The human prostate is divided into three zones based on its histological features: the peripheral zone (PZ), the transition zone (TZ) and the central zone (CZ). Each zone has variable prostate cancer incidence, prognosis and outcomes, with TZ prostate tumours having better clinical outcomes than PZ and CZ tumours. Molecular and cell biological studies can improve understanding of the unique molecular, genomic and zonal cell type features that underlie the differences in tumour progression and aggression between the zones. The unique biology of each zonal tumour type could help to guide individualized treatment and patient risk stratification. The prostate is divided into the peripheral, transition and central zones, which have different prostate cancer incidences and prognoses. Differences between the zones suggest their potential roles in tumour aggressiveness, but treatment of prostate cancer remains zonal agnostic. Improved understanding of the zones and their roles in tumorigenesis could improve prostate cancer management.

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Topics: Prostate cancer (60%), Cancer (55%), Prostate (54%)


62 results found

Open accessJournal Article
01 Jan 2014-MSOR connections
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.

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Topics: R Programming Language (78%)

229,202 Citations

Open accessJournal ArticleDOI: 10.18637/JSS.V067.I01
Abstract: Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer.

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37,650 Citations

Open accessJournal ArticleDOI: 10.1093/BIOINFORMATICS/BTP352
Heng Li1, Bob Handsaker2, Alec Wysoker2, T. J. Fennell2  +5 moreInstitutions (4)
01 Aug 2009-Bioinformatics
Abstract: Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: Contact: [email protected]

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Topics: Variant Call Format (62%), Stockholm format (61%), FASTQ format (56%) ... read more

35,747 Citations

Open accessPosted ContentDOI: 10.6084/M9.FIGSHARE.963153.V1
16 Mar 2013-arXiv: Genomics
Abstract: Summary: BWA-MEM is a new alignment algorithm for aligning sequence reads or long query sequences against a large reference genome such as human. It automatically chooses between local and end-to-end alignments, supports paired-end reads and performs chimeric alignment. The algorithm is robust to sequencing errors and applicable to a wide range of sequence lengths from 70bp to a few megabases. For mapping 100bp sequences, BWA-MEM shows better performance than several state-of-art read aligners to date. Availability and implementation: BWA-MEM is implemented as a component of BWA, which is available at this http URL. Contact:

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Topics: Sequence assembly (59%), Reference genome (52%)

6,090 Citations

Open accessJournal ArticleDOI: 10.1016/J.CELL.2015.10.025
Adam Abeshouse1, Jaeil Ahn1, Rehan Akbani1, Adrian Ally1  +308 moreInstitutions (1)
05 Nov 2015-Cell
Abstract: There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, and FLI1) or mutations (SPOP, FOXA1, and IDH1). Epigenetic profiles showed substantial heterogeneity, including an IDH1 mutant subset with a methylator phenotype. Androgen receptor (AR) activity varied widely and in a subtype-specific manner, with SPOP and FOXA1 mutant tumors having the highest levels of AR-induced transcripts. 25% of the prostate cancers had a presumed actionable lesion in the PI3K or MAPK signaling pathways, and DNA repair genes were inactivated in 19%. Our analysis reveals molecular heterogeneity among primary prostate cancers, as well as potentially actionable molecular defects.

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Topics: SPOP (62%), Prostate cancer (57%), Fusion gene (51%) ... read more

1,633 Citations

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