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      TRIP13 impairs mitotic checkpoint surveillance and is associated with poor prognosis in multiple myeloma

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          Abstract

          AAA-ATPase TRIP13 is one of the chromosome instability gene recently established in multiple myeloma (MM), the second most common and incurable hematological malignancy. However, the specific function of TRIP13 in MM is largely unknown. Using sequential gene expression profiling, we demonstrated that high TRIP13 expression levels were positively correlated with progression, disease relapse, and poor prognosis in MM patients. Overexpressing human TRIP13 in myeloma cells prompted cell growth and drug resistance, and overexpressing murine TRIP13, which shares 93% sequence identity with human TRIP13, led to colony formation of NIH/3T3 fibroblasts in vitro and tumor formation in vivo. Meanwhile, the knockdown of TRIP13 inhibited myeloma cell growth, induced cell apoptosis, and reduced tumor burden in xenograft MM mice. Mechanistically, we observed that the overexpression of TRIP13 abrogated the spindle checkpoint and induced proteasome-mediated degradation of MAD2 primarily through the Akt pathway. Thus, our results demonstrate that TRIP13 may serve as a biomarker for MM disease development and prognosis, making it a potential target for future therapies.

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          Most cited references29

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          Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression.

          Many studies have used DNA microarrays to identify the gene expression signatures of human cancer, yet the critical features of these often unmanageably large signatures remain elusive. To address this, we developed a statistical method, comparative metaprofiling, which identifies and assesses the intersection of multiple gene expression signatures from a diverse collection of microarray data sets. We collected and analyzed 40 published cancer microarray data sets, comprising 38 million gene expression measurements from >3,700 cancer samples. From this, we characterized a common transcriptional profile that is universally activated in most cancer types relative to the normal tissues from which they arose, likely reflecting essential transcriptional features of neoplastic transformation. In addition, we characterized a transcriptional profile that is commonly activated in various types of undifferentiated cancer, suggesting common molecular mechanisms by which cancer cells progress and avoid differentiation. Finally, we validated these transcriptional profiles on independent data sets.
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            A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1.

            To molecularly define high-risk disease, we performed microarray analysis on tumor cells from 532 newly diagnosed patients with multiple myeloma (MM) treated on 2 separate protocols. Using log-rank tests of expression quartiles, 70 genes, 30% mapping to chromosome 1 (P < .001), were linked to early disease-related death. Importantly, most up-regulated genes mapped to chromosome 1q, and down-regulated genes mapped to chromosome 1p. The ratio of mean expression levels of up-regulated to down-regulated genes defined a high-risk score present in 13% of patients with shorter durations of complete remission, event-free survival, and overall survival (training set: hazard ratio [HR], 5.16; P < .001; test cohort: HR, 4.75; P < .001). The high-risk score also was an independent predictor of outcome endpoints in multivariate analysis (P < .001) that included the International Staging System and high-risk translocations. In a comparison of paired baseline and relapse samples, the high-risk score frequency rose to 76% at relapse and predicted short postrelapse survival (P < .05). Multivariate discriminant analysis revealed that a 17-gene subset could predict outcome as well as the 70-gene model. Our data suggest that altered transcriptional regulation of genes mapping to chromosome 1 may contribute to disease progression, and that expression profiling can be used to identify high-risk disease and guide therapeutic interventions.
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              NEK2 induces drug resistance mainly through activation of efflux drug pumps and is associated with poor prognosis in myeloma and other cancers.

              Using sequential gene expression profiling (GEP) samples, we defined a major functional group related to drug resistance that contains chromosomal instability (CIN) genes. One CIN gene in particular, NEK2, was highly correlated with drug resistance, rapid relapse, and poor outcome in multiple cancers. Overexpressing NEK2 in cancer cells resulted in enhanced CIN, cell proliferation and drug resistance, while targeting NEK2 by NEK2 shRNA overcame cancer cell drug resistance and induced apoptosis in vitro and in a xenograft myeloma mouse model. High expression of NEK2 induced drug resistance mainly through activation of the efflux pumps. Thus, NEK2 represents a strong predictor for drug resistance and poor prognosis in cancer and could be an important target for cancer therapy. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                18 April 2017
                1 February 2017
                : 8
                : 16
                : 26718-26731
                Affiliations
                1 Department of Hematology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China
                2 Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China
                3 Shanghai Chenshan Plant Science Research Center, Chienes Academy of Sciences, Shanghai 201602, China
                4 Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA
                5 CAS Key Laboratory of Receptor Research, Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
                Author notes
                Correspondence to: Jumei Shi, shijumei@ 123456tongji.edu.cn
                Article
                14957
                10.18632/oncotarget.14957
                5432292
                28157697
                0b86df4c-208d-4021-87ad-a59cdd8bf600
                Copyright: © 2017 Tao et al.

                This article is distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 16 April 2016
                : 10 January 2017
                Categories
                Research Paper

                Oncology & Radiotherapy
                trip13,multiple myeloma,prognosis,drug resistance,mad2
                Oncology & Radiotherapy
                trip13, multiple myeloma, prognosis, drug resistance, mad2

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