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      Elevated mRNA Levels of AURKA, CDC20 and TPX2 are associated with poor prognosis of smoking related lung adenocarcinoma using bioinformatics analysis

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          Abstract

          Background and aim: Adenocarcinoma is a very common pathological subtype for lung cancer. We aimed to identify the gene signature associated with the prognosis of smoking related lung adenocarcinoma using bioinformatics analysis.

          Methods: A total of five gene expression profiles (GSE31210, GSE32863, GSE40791, GSE43458 and GSE75037) have been identified from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using GEO2R software and functional and pathway enrichment analysis. Furthermore, the overall survival (OS) and recurrence-free survival (RFS) have been validated using an independent cohort from the Cancer Genome Atlas (TCGA) database.

          Results: We identified a total of 58 DEGs which mainly enriched in ECM-receptor interaction, platelet activation and PPAR signaling pathway. Then according to the enrichment analysis results, we selected three genes ( AURKA, CDC20 and TPX2) for their roles in regulating tumor cell cycle and cell division. The results showed that the hazard ratio (HR) of the mRNA expression of AURKA for OS was 1.588 with (1.127-2.237) 95% confidence interval (CI) (P=0.009). The mRNA levels of CDC20 (HR 1.530, 95% CI 1.086-2.115, P=0.016) and TPX2 (HR 1.777, 95%CI 1.262-2.503, P=0.001) were also significantly associated with the OS. Expression of these three genes were not associated with RFS, suggesting that there might be many factors affect RFS.

          Conclusion: The mRNA signature of AURKA, CDC20 and TPX2 were potential biomarkers for predicting poor prognosis of smoking related lung adenocarcinoma.

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          Most cited references27

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          Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas.

          Activation of the EGFR, KRAS, and ALK oncogenes defines 3 different pathways of molecular pathogenesis in lung adenocarcinoma. However, many tumors lack activation of any pathway (triple-negative lung adenocarcinomas) posing a challenge for prognosis and treatment. Here, we report an extensive genome-wide expression profiling of 226 primary human stage I-II lung adenocarcinomas that elucidates molecular characteristics of tumors that harbor ALK mutations or that lack EGFR, KRAS, and ALK mutations, that is, triple-negative adenocarcinomas. One hundred and seventy-four genes were selected as being upregulated specifically in 79 lung adenocarcinomas without EGFR and KRAS mutations. Unsupervised clustering using a 174-gene signature, including ALK itself, classified these 2 groups of tumors into ALK-positive cases and 2 distinct groups of triple-negative cases (groups A and B). Notably, group A triple-negative cases had a worse prognosis for relapse and death, compared with cases with EGFR, KRAS, or ALK mutations or group B triple-negative cases. In ALK-positive tumors, 30 genes, including ALK and GRIN2A, were commonly overexpressed, whereas in group A triple-negative cases, 9 genes were commonly overexpressed, including a candidate diagnostic/therapeutic target DEPDC1, that were determined to be critical for predicting a worse prognosis. Our findings are important because they provide a molecular basis of ALK-positive lung adenocarcinomas and triple-negative lung adenocarcinomas and further stratify more or less aggressive subgroups of triple-negative lung ADC, possibly helping identify patients who may gain the most benefit from adjuvant chemotherapy after surgical resection. ©2011 AACR.
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            GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics

            Since its first release in 2007, GeneCodis has become a valuable tool to functionally interpret results from experimental techniques in genomics. This web-based application integrates different sources of information to finding groups of genes with similar biological meaning. This process, known as enrichment analysis, is essential in the interpretation of high-throughput experiments. The frequent feedbacks and the natural evolution of genomics and bioinformatics have allowed the growth of the tool and the development of this third release. In this version, a special effort has been made to remove noisy and redundant output from the enrichment results with the inclusion of a recently reported algorithm that summarizes significantly enriched terms and generates functionally coherent modules of genes and terms. A new comparative analysis has been added to allow the differential analysis of gene sets. To expand the scope of the application, new sources of biological information have been included, such as genetic diseases, drugs–genes interactions and Pubmed information among others. Finally, the graphic section has been renewed with the inclusion of new interactive graphics and filtering options. The application is freely available at http://genecodis.cnb.csic.es.
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              The Aurora Kinases in Cell Cycle and Leukemia

              The Aurora kinases, which include Aurora A (AURKA), Aurora B (AURKB) and Aurora C (AURKC), are serine/threonine kinases required for the control of mitosis (AURKA and AURKB) and meiosis (AURKC). Since their discovery nearly twenty years ago, Aurora kinases have been studied extensively in cell and cancer biology 1 . Several early studies found that Aurora kinases are amplified and overexpressed at the transcript and protein level in various malignancies, including several types of leukemia. These discoveries and others provided a rationale for the development of small molecule inhibitors of Aurora kinases as leukemia therapies. The first generation of Aurora kinase inhibitors did not fare well in clinical trials, owing to poor efficacy and high toxicity. However, the creation of second generation, highly selective Aurora kinase inhibitors has increased the enthusiasm for targeting these proteins in leukemia. This review will describe the functions of each Aurora kinase, summarize their involvement in leukemia and discuss inhibitor development and efficacy in leukemia clinical trials.
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                Author and article information

                Journal
                Int J Med Sci
                Int J Med Sci
                ijms
                International Journal of Medical Sciences
                Ivyspring International Publisher (Sydney )
                1449-1907
                2018
                5 November 2018
                : 15
                : 14
                : 1676-1685
                Affiliations
                Department of Respiratory Medicine, Qilu Hospital of Shandong University, Jinan 250012, China
                Author notes
                ✉ Corresponding author: Yi-Qing Qu, Department of Respiratory Medicine, Qilu Hospital of Shandong University, Wenhuaxi Road 107#, Jinan 250012, China. E-mail: quyiqing@ 123456sdu.edu.cn ; Tel: +86 531 8216 9335

                Competing Interests: The authors have declared that no competing interest exists.

                Article
                ijmsv15p1676
                10.7150/ijms.28728
                6299412
                c74446d5-2846-4e45-a6c4-4163c44fc958
                © Ivyspring International Publisher

                This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license ( https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.

                History
                : 24 July 2018
                : 11 October 2018
                Categories
                Research Paper

                Medicine
                lung adenocarcinoma,differentially expressed genes,gene ontology,kaplan-meier analysis,biomarkers

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