Identification of core miRNA based on small RNA-seq and RNA-seq for colorectal cancer by bioinformatics

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• 作者：Youwei Kou ; Lei Qiao ; Qiang Wang
• 关键词：RNA ; seq ; MicroRNAs ; Molecular mechanism
• 刊名：Tumor Biology
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：36
• 期：4
• 页码：2249-2255
• 全文大小：540 KB
• 参考文献：1.Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61(2):69-0.View Article PubMed
  2.Botteri E, Iodice S, Bagnardi V, Raimondi S, Lowenfels AB, Maisonneuve P. Smoking and colorectal cancer: a meta-analysis. JAMA. 2008;300(23):2765-8.View Article PubMed
  3.Chan DS, Lau R, Aune D, Vieira R, Greenwood DC, Kampman E, et al. Red and processed meat and colorectal cancer incidence: meta-analysis of prospective studies. PLoS One. 2011;6(6):6.
  4.Kontou N, Psaltopoulou T, Soupos N, Polychronopoulos E, Xinopoulos D, Linos A, et al. Alcohol consumption and colorectal cancer in a Mediterranean population: a case-control study. Dis Colon Rectum. 2012;55(6):703-0.View Article PubMed
  5.Bardou M, Barkun AN, Martel M. Obesity and colorectal cancer. Gut. 2013;62(6):933-7.View Article PubMed
  6.Atkin WS, Edwards R, Kralj-Hans I, Wooldrage K, Hart AR, Northover JM, et al. Once-only flexible sigmoidoscopy screening in prevention of colorectal cancer: a multicentre randomised controlled trial. Lancet. 2010;375(9726):1624-3.View Article PubMed
  7.Rutter CM, Johnson E, Miglioretti DL, Mandelson MT, Inadomi J, Buist DS. Adverse events after screening and follow-up colonoscopy. Cancer Causes Control. 2012;23(2):289-6.View Article PubMed Central PubMed
  8.Chan SK, Griffith OL, Tai IT, Jones SJ. Meta-analysis of colorectal cancer gene expression profiling studies identifies consistently reported candidate biomarkers. Cancer Epidemiol Biomarkers Prev. 2008;17(3):543-2.View Article PubMed
  9.Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281-7.View Article PubMed
  10.Esquela-Kerscher A, Slack FJ. Oncomirs—microRNAs with a role in cancer. Nat Rev Cancer. 2006;6(4):259-9.View Article PubMed
  11.Zhang GJ, Li Y, Zhou H, Xiao HX, Zhou T. miR20a is an independent prognostic factor in colorectal cancer and is involved in cell metastasis. Mol Med Rep. 2014;10(1):283-1.PubMed
  12.Valeri N, Braconi C, Gasparini P, Hart J, Grivennikov S, Lovat F, et al. microRNA-135b promotes cancer progression acting as a downstream effector of oncogenic pathways in colon cancer. Lancet. 2013;381:S17.View Article
  13.Asangani IA, Rasheed SA, Nikolova DA, Leupold JH, Colburn NH, Post S, et al. MicroRNA-21 (miR-21) post-transcriptionally downregulates tumor suppressor Pdcd4 and stimulates invasion, intravasation and metastasis in colorectal cancer. Oncogene. 2008;27(15):2128-6.View Article PubMed
  14.Ng EK, Chong WW, Jin H, Lam EK, Shin VY, Yu J, et al. Differential expression of microRNAs in plasma of patients with colorectal cancer: a potential marker for colorectal cancer screening. Gut. 2009;58(10):1375-1.View Article PubMed
  15.Rohr C, Kerick M, Fischer A, Kuhn A, Kashofer K, Timmermann B et al. High-throughput miRNA and mRNA sequencing of paired colorectal normal, tumor and metastasis tissues and bioinformatic modeling of miRNA-1 therapeutic applications. PLoS One. 2013;8(7)
  16.Burge SW, Daub J, Eberhardt R, Tate J, Barquist L, Nawrocki EP et al. Rfam 11.0: 10 years of RNA families. Nucleic Acids Res. 2013;41(database issue):3
  17.Kozomara A, Griffiths-Jones S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res. 2011;39(Database issue):30
  18.Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3):2009-0.View Article
  19.Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105-1.View Article PubMed Central PubMed
  20.Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28(5):511-.View Article PubMed Central PubMed
  21.Schee K, Lorenz S, Worren MM, Gunther CC, Holden M, Hovig E et al. Deep sequencing the microRNA transcriptome in colorectal cancer. PLoS One. 2013;8(6)
  22.Zhao M, Sun J, Zhao Z. TSGene: a web resource for tumor suppressor genes. Nucleic Acids Res. 2013;41(Database issue):12
  23.Chen JS, Hung WS, Chan HH, Tsai SJ, Sun HS. In silico identification of oncogenic potential of FYN-related kinase in hepatocellular carcinoma. Bioinformatics. 2013;29(4):420-.View Article PubMed
  24.Migliore C, Martin V, Leoni VP, Restivo A, Atzori L, Petrelli A, et al. MiR-1 downregulation cooperates with MACC1 in promoting MET overexpression in human colon cancer. Clin Cancer Res. 2012;18(3):737-7.View Article PubMed
  25.Reid JF, Sokolova V, Zoni E, Lampis A, Pizzamiglio S, Bertan C, et al. miRNA profiling in colorectal cancer highlights miR-1 involvement in MET-dependent proliferation. Mol Cancer Res. 2012;10(4):504-5.View Article PubMed
  26.Suzuki H, Takatsuka S, Akashi H, Yamamoto E, Nojima M, Maruyama R, et al. Genome-w
• 作者单位：Youwei Kou (1)
  Lei Qiao (2)
  Qiang Wang (1)
  
  1. Department of Gastrointestinal and Nutriology Surgery, Shengjing Hospital of China Medical University, Sanhao Street No. 36, Shenyang, 110004, People’s Republic of China
  2. Department of Colorectal Surgery and Oncology, Shengjing Hospital of China Medical University, Sanhao Street No. 36, Shenyang, 110004, People’s Republic of China
  
• 刊物主题：Cancer Research;
• 出版者：Springer Netherlands
• ISSN：1423-0380

文摘

We aimed to identify the potential microRNA (miRNA) targets for colorectal cancer (CRC). Small RNA-seq and RNA-seq data of GSE46622 were downloaded from Gene Expression Omnibus (GEO) database, including samples of tumor tissue, metastasis tissue, and normal tissue from eight CRC patients. Data comparison of small RNA-seq and RNA-seq was performed through Bowtie and TopHat softwares, respectively. Then the expressed values of each sample were calculated by Cufflinks and Cuffdiff based on fragments per kilobase of exon per millionfragments mapped (FPKM) methods. The differentially expressed miRNAs and core miRNAs were identified by paired t-test. Besides, miRNA target genes were integrated through miRanda, MirTarget2, PicTar, PITI, TargetScan, and miRecords databases, followed by functional analysis of specific miRNA. The average comparison rate of sequence reads in miRNA, noncoding RNA, and other areas of the genome is 49.75, 2.90, and 47.35?%, respectively. A total of 49 miRNAs was differentially expressed. Compared with normal controls, 3 miRNAs were upregulated and 13 miRNAs were downregulated in tumor samples as well as 48 miRNAs were upregulated and 20 miRNAs were downregulated in the metastasis samples. Among them, 18 metastasis-specific expressed miRNAs, 2 tumor-specific expressed miRNAs, and 11 normal expressed miRNA were found. miRNA-1, miRNA-338-5p, miRNA-326, and miR-490-5p were selected as important miRNAs. Besides, miRNA-338-5p target gene RAB6B, FAP, and CTGF were identified as oncogenes. The miRNAs, such as miRNA-1, miRNA-338-5p, and miRNA-326 may be used as potential targets for CRC diagnosis and treatment.