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      Spatial Genome Organization and Its Emerging Role as a Potential Diagnosis Tool

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          Abstract

          In eukaryotic cells the genome is highly spatially organized. Functional relevance of higher order genome organization is implied by the fact that specific genes, and even whole chromosomes, alter spatial position in concert with functional changes within the nucleus, for example with modifications to chromatin or transcription. The exact molecular pathways that regulate spatial genome organization and the full implication to the cell of such an organization remain to be determined. However, there is a growing realization that the spatial organization of the genome can be used as a marker of disease. While global genome organization patterns remain largely conserved in disease, some genes and chromosomes occupy distinct nuclear positions in diseased cells compared to their normal counterparts, with the patterns of reorganization differing between diseases. Importantly, mapping the spatial positioning patterns of specific genomic loci can distinguish cancerous tissue from benign with high accuracy. Genome positioning is an attractive novel biomarker since additional quantitative biomarkers are urgently required in many cancer types. Current diagnostic techniques are often subjective and generally lack the ability to identify aggressive cancer from indolent, which can lead to over- or under-treatment of patients. Proof-of-principle for the use of genome positioning as a diagnostic tool has been provided based on small scale retrospective studies. Future large-scale studies are required to assess the feasibility of bringing spatial genome organization-based diagnostics to the clinical setting and to determine if the positioning patterns of specific loci can be useful biomarkers for cancer prognosis. Since spatial reorganization of the genome has been identified in multiple human diseases, it is likely that spatial genome positioning patterns as a diagnostic biomarker may be applied to many diseases.

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          Most cited references146

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          Overdiagnosis in cancer.

          This article summarizes the phenomenon of cancer overdiagnosis-the diagnosis of a "cancer" that would otherwise not go on to cause symptoms or death. We describe the two prerequisites for cancer overdiagnosis to occur: the existence of a silent disease reservoir and activities leading to its detection (particularly cancer screening). We estimated the magnitude of overdiagnosis from randomized trials: about 25% of mammographically detected breast cancers, 50% of chest x-ray and/or sputum-detected lung cancers, and 60% of prostate-specific antigen-detected prostate cancers. We also review data from observational studies and population-based cancer statistics suggesting overdiagnosis in computed tomography-detected lung cancer, neuroblastoma, thyroid cancer, melanoma, and kidney cancer. To address the problem, patients must be adequately informed of the nature and the magnitude of the trade-off involved with early cancer detection. Equally important, researchers need to work to develop better estimates of the magnitude of overdiagnosis and develop clinical strategies to help minimize it.
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            Breast cancer intrinsic subtype classification, clinical use and future trends.

            Breast cancer is composed of multiple subtypes with distinct morphologies and clinical implications. The advent of microarrays has led to a new paradigm in deciphering breast cancer heterogeneity, based on which the intrinsic subtyping system using prognostic multigene classifiers was developed. Subtypes identified using different gene panels, though overlap to a great extent, do not completely converge, and the avail of new information and perspectives has led to the emergence of novel subtypes, which complicate our understanding towards breast tumor heterogeneity. This review explores and summarizes the existing intrinsic subtypes, patient clinical features and management, commercial signature panels, as well as various information used for tumor classification. Two trends are pointed out in the end on breast cancer subtyping, i.e., either diverging to more refined groups or converging to the major subtypes. This review improves our understandings towards breast cancer intrinsic classification, current status on clinical application, and future trends.
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              Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12 155 patients

              The Ki-67 antigen is used to evaluate the proliferative activity of breast cancer (BC); however, Ki-67's role as a prognostic marker in BC is still undefined. In order to better define the prognostic value of Ki-67/MIB-1, we performed a meta-analysis of studies that evaluated the impact of Ki-67/MIB-1 on disease-free survival (DFS) and/or on overall survival (OS) in early BC. Sixty-eight studies were identified and 46 studies including 12 155 patients were evaluable for our meta-analysis; 38 studies were evaluable for the aggregation of results for DFS, and 35 studies for OS. Patients were considered to present positive tumours for the expression of Ki-67/MIB-1 according to the cut-off points defined by the authors. Ki-67/MIB-1 positivity is associated with higher probability of relapse in all patients (HR=1.93 (95% confidence interval (CI): 1.74–2.14); P<0.001), in node-negative patients (HR=2.31 (95% CI: 1.83–2.92); P<0.001) and in node-positive patients (HR=1.59 (95% CI: 1.35–1.87); P<0.001). Furthermore, Ki-67/MIB-1 positivity is associated with worse survival in all patients (HR=1.95 (95% CI: 1.70–2.24; P<0.001)), node-negative patients (HR=2.54 (95% CI: 1.65–3.91); P<0.001) and node-positive patients (HR=2.33 (95% CI: 1.83–2.95); P<0.001). Our meta-analysis suggests that Ki-67/MIB-1 positivity confers a higher risk of relapse and a worse survival in patients with early BC.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                26 July 2016
                2016
                : 7
                : 134
                Affiliations
                Cell Biology of Genomes Group, National Cancer Institute, National Institutes of Health Bethesda, MD, USA
                Author notes

                Edited by: Joanna Mary Bridger, Brunel University London, UK

                Reviewed by: Justin Martin O’Sullivan, University of Auckland, New Zealand; Zong Wei, Salk Institute for Biological Studies, USA

                *Correspondence: Karen J. Meaburn, meaburnk@ 123456mail.nih.gov

                This article was submitted to Epigenomics and Epigenetics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2016.00134
                4961005
                27507988
                5d6a1abc-e7aa-4905-97d2-cc0d720cd66d
                Copyright © 2016 Meaburn.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 March 2016
                : 13 July 2016
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 206, Pages: 18, Words: 0
                Funding
                Funded by: U.S. Department of Defense 10.13039/100000005
                Award ID: W81XWH-12-1-0224
                Award ID: W81XWH-15-1-0322
                Categories
                Genetics
                Review

                Genetics
                genome organization,nuclear architecture,spatial positioning,gene positioning,disease,cancer,diagnosis

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