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      Identification of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis

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          Abstract

          Small cell lung cancer (SCLC) is one of the highly malignant tumors and a serious threat to human health. The aim of the present study was to explore the underlying molecular mechanisms of SCLC. mRNA microarray datasets GSE6044 and GSE11969 were downloaded from Gene Expression Omnibus database, and the differentially expressed genes (DEGs) between normal lung and SCLC samples were screened using GEO2R tool. Functional and pathway enrichment analyses were performed for common DEGs using the DAVID database, and the protein-protein interaction (PPI) network of common DEGs was constructed by the STRING database and visualized with Cytoscape software. In addition, the hub genes in the network and module analysis of the PPI network were performed using CentiScaPe and plugin Molecular Complex Detection. Finally, the mRNA expression levels of hub genes were validated in the Oncomine database. A total of 150 common DEGs with absolute fold-change >0.5, including 66 significantly downregulated DEGs and 84 upregulated DEGs were obtained. The Gene Ontology term enrichment analysis suggested that common upregulated DEGs were primarily enriched in biological processes (BPs), including ‘cell cycle’, ‘cell cycle phase’, ‘M phase’, ‘cell cycle process’ and ‘DNA metabolic process’. The common downregulated genes were significantly enriched in BPs, including ‘response to wounding’, ‘positive regulation of immune system process’, ‘immune response’, ‘acute inflammatory response’ and ‘inflammatory response’. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified that the common downregulated DEGs were primarily enriched in the ‘complement and coagulation cascades’ signaling pathway; the common upregulated DEGs were mainly enriched in ‘cell cycle’, ‘DNA replication’, ‘oocyte meiosis’ and the ‘mismatch repair’ signaling pathways. From the PPI network, the top 10 hub genes in SCLC were selected, including topoisomerase IIα, proliferating cell nuclear antigen, replication factor C subunit 4, checkpoint kinase 1, thymidylate synthase, minichromosome maintenance protein (MCM) 2, cell division cycle (CDC) 20, cyclin dependent kinase inhibitor 3, MCM3 and CDC6, the mRNA levels of which are upregulated in Oncomine SCLC datasets with the exception of MCM2. Furthermore, the genes in the significant module were enriched in ‘cell cycle’, ‘DNA replication’ and ‘oocyte meiosis’ signaling pathways. Therefore, the present study can shed new light on the understanding of molecular mechanisms of SCLC and may provide molecular targets and diagnostic biomarkers for the treatment and early diagnosis of SCLC.

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          Most cited references55

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          Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses.

          We have generated a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, we analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct subclasses of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.
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            Altered macrophage differentiation and immune dysfunction in tumor development.

            Tumors require a constant influx of myelomonocytic cells to support the angiogenesis and stroma remodeling needed for their growth. This is mediated by tumor-derived factors, which cause sustained myelopoiesis and the accumulation and functional differentiation of myelomonocytic cells, most of which are macrophages, at the tumor site. An important side effect of the accumulation and functional differentiation of these cells is that they can induce lymphocyte dysfunction. A complete understanding of the complex interplay between neoplastic and myelomonocytic cells might offer novel targets for therapeutic intervention aimed at depriving tumor cells of important growth support and enhancing the antitumor immune response.
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              Diversity of gene expression in adenocarcinoma of the lung.

              The global gene expression profiles for 67 human lung tumors representing 56 patients were examined by using 24,000-element cDNA microarrays. Subdivision of the tumors based on gene expression patterns faithfully recapitulated morphological classification of the tumors into squamous, large cell, small cell, and adenocarcinoma. The gene expression patterns made possible the subclassification of adenocarcinoma into subgroups that correlated with the degree of tumor differentiation as well as patient survival. Gene expression analysis thus promises to extend and refine standard pathologic analysis.
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                Author and article information

                Journal
                Mol Med Rep
                Mol Med Rep
                Molecular Medicine Reports
                D.A. Spandidos
                1791-2997
                1791-3004
                August 2018
                29 May 2018
                29 May 2018
                : 18
                : 2
                : 1538-1550
                Affiliations
                [1 ]Department of Pathophysiology, Jinzhou Medical University, Jinzhou, Liaoning 121001, P.R. China
                [2 ]Biological Anthropology Institute, Jinzhou Medical University, Jinzhou, Liaoning 121001, P.R. China
                [3 ]Department of Anatomy, Jinzhou Medical University, Jinzhou, Liaoning 121001, P.R. China
                [4 ]Department of Ultrasonography, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning 121001, P.R. China
                Author notes
                Correspondence to: Professor Yuhong Li or Dr Jing Gao, Department of Ultrasonography, The First Affiliated Hospital of Jinzhou Medical University, 2, Section V Renmin Street, Jinzhou, Liaoning 121001, P.R. China, E-mail: yuhong_jiahui@ 123456163.com , E-mail: gaojinggg@ 123456163.com
                Article
                mmr-18-02-1538
                10.3892/mmr.2018.9095
                6072191
                29845250
                a1e2defb-ba06-40c2-9b00-f451f87c1402
                Copyright: © Wen et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 06 December 2017
                : 23 April 2018
                Categories
                Articles

                lung cancer,small cell lung cancer,differentially expressed genes,bioinformatics analysis,microarray

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