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      Overexpression of the E2F target gene CENPI promotes chromosome instability and predicts poor prognosis in estrogen receptor-positive breast cancer

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          Abstract

          During cell division, chromosome segregation is facilitated by the mitotic checkpoint, or spindle assembly checkpoint (SAC), which ensures correct kinetochore-microtubule attachments and prevents premature sister-chromatid separation. It is well established that misexpression of SAC components on the outer kinetochores promotes chromosome instability (CIN) and tumorigenesis. Here, we study the expression of CENP-I, a key component of the HIKM complex at the inner kinetochores, in breast cancer, including ductal, lobular, medullary and male breast carcinomas. CENPI mRNA and protein levels are significantly elevated in estrogen receptor-positive (ER+) but not in estrogen receptor-negative (ER-) breast carcinoma. Well-established prognostic tests indicate that CENPI overexpression constitutes a powerful independent marker for poor patient prognosis and survival in ER+ breast cancer. We further demonstrate that CENPI is an E2F target gene. Consistently, it is overexpressed in RB1-deficient breast cancers. However, CENP-I overexpression is not purely due to cell cycle-associated expression. In ER+ breast cancer cells, CENP-I overexpression promotes CIN, especially chromosome gains. In addition, in ER+ breast carcinomas the degree of CENPI overexpression is proportional to the level of aneuploidy and CENPI overexpression is one of the strongest markers for CIN identified to date. Our results indicate that overexpression of the inner kinetochore protein CENP-I promotes CIN and forecasts poor prognosis for ER+ breast cancer patients. These observations provide novel mechanistic insights and have important implications for breast cancer diagnostics and potentially therapeutic targeting.

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          Most cited references42

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            The spindle-assembly checkpoint in space and time.

            In eukaryotes, the spindle-assembly checkpoint (SAC) is a ubiquitous safety device that ensures the fidelity of chromosome segregation in mitosis. The SAC prevents chromosome mis-segregation and aneuploidy, and its dysfunction is implicated in tumorigenesis. Recent molecular analyses have begun to shed light on the complex interaction of the checkpoint proteins with kinetochores--structures that mediate the binding of spindle microtubules to chromosomes in mitosis. These studies are finally starting to reveal the mechanisms of checkpoint activation and silencing during mitotic progression.
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              Stromal gene expression predicts clinical outcome in breast cancer.

              Although it is increasingly evident that cancer is influenced by signals emanating from tumor stroma, little is known regarding how changes in stromal gene expression affect epithelial tumor progression. We used laser capture microdissection to compare gene expression profiles of tumor stroma from 53 primary breast tumors and derived signatures strongly associated with clinical outcome. We present a new stroma-derived prognostic predictor (SDPP) that stratifies disease outcome independently of standard clinical prognostic factors and published expression-based predictors. The SDPP predicts outcome in several published whole tumor-derived expression data sets, identifies poor-outcome individuals from multiple clinical subtypes, including lymph node-negative tumors, and shows increased accuracy with respect to previously published predictors, especially for HER2-positive tumors. Prognostic power increases substantially when the predictor is combined with existing outcome predictors. Genes represented in the SDPP reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses, highlighting the importance of stromal biology in tumor progression.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                22 September 2017
                10 July 2017
                : 8
                : 37
                : 62167-62182
                Affiliations
                1 University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute, Brisbane, QLD, Australia
                2 Institute of Health and Biomedical Innovation, Queensland University of Technology, Translational Research Institute, Brisbane, QLD, Australia
                Author notes
                Correspondence to: Pascal H.G. Duijf, p.duijf@ 123456uq.edu.au
                Article
                19131
                10.18632/oncotarget.19131
                5617495
                28977935
                d732bdd0-4399-481c-afd9-0a949059ee1b
                Copyright: © 2017 Thangavelu et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 August 2016
                : 3 June 2017
                Categories
                Research Paper

                Oncology & Radiotherapy
                breast cancer,prognosis,chromosome instability,aneuploidy,cenpi
                Oncology & Radiotherapy
                breast cancer, prognosis, chromosome instability, aneuploidy, cenpi

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