Abstract
To explore the universal law of the abnormal gene expression and the structural variation of genes related to lung adenocarcinoma, the gene expression profile of GSE37765 were downloaded from Gene Expression Omnibus database. The differentially expressed genes (DEGs) were analyzed with t-test and NOISeq tool, and the core DEGs were screened out by combining with another RNA-seq data containing totally 77 pairs of samples in 77 patients with lung adenocarcinoma. Moreover, the functional annotation of the core DEGs was performed by using the Database for Annotation Visualization and Integrated Discovery following selection of oncogene and tumor suppressor by combining with tumor suppressor genes and Cancer Genes database, and motif-finding of core DEGs was performed with motif-finding algorithm Seqpos. We also used Tophat-fusion tool to further explore the fusion genes. In total, 850 downregulated DEGs and 206 upregulated DEGs were screened out in lung adenocarcinoma tissues. Next, we selected 543 core DEGs, including 401 downregulated and 142 upregulated genes, and vasculature development (P=1.89E−06) was significantly enriched among downregulated core genes, as well as mitosis (P=6.26E−04) enriched among upregulated core genes. On the basis of the cellular localization analysis of core genes, wnt-1-induced secreted protein 1 (WISP1) and receptor (G protein-coupled) activity modifying protein 1 (RAMP1) identified mainly located in extracellular region and extracellular space. We also screened one oncogene, v-myb avian myeloblastosis viral oncogene homolog-like 2 (MYBL2). Moreover, transcription factor GATA2 was mined by motif-finding analysis. Finally, four fusion genes belonged to the human leukocyte antigen (HLA) family. WISP1, RAMP1, MYBL2 and GATA2 could be potential targets of treatment for lung adenocarcinoma and the fusion of HLA family genes might have important roles in lung adenocarcinoma.
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Yang, ZH., Zheng, R., Gao, Y. et al. Abnormal gene expression and gene fusion in lung adenocarcinoma with high-throughput RNA sequencing. Cancer Gene Ther 21, 74–82 (2014). https://doi.org/10.1038/cgt.2013.86
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DOI: https://doi.org/10.1038/cgt.2013.86