91
Views
1
CrossRef citations to date
0
Altmetric
Article

Identification of Key mRNAs and Pathways in Colorectal Cancer

, , , , , , , , & show all
Pages 1040-1046 | Received 11 Feb 2020, Accepted 06 Jun 2020, Published online: 25 Jun 2020

References

  • Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30. doi:10.3322/caac.21387
  • Falzone L, Salomone S, Libra M. Evolution of cancer pharmacological treatments at the turn of the third millennium. Front Pharmacol. 2018;9:1300. doi:10.3389/fphar.2018.01300
  • Markowitz SD, Bertagnolli MM. Molecular origins of cancer: molecular basis of colorectal cancer. N Engl J Med. 2009;361(25):2449–2460. doi:10.1056/NEJMra0804588
  • Ballard-Barbash R, Friedenreich CM, Courneya KS, Siddiqi SM, McTiernan A, Alfano CM. Physical activity, biomarkers, and disease outcomes in cancer survivors: a systematic review. J Natl Cancer Inst. 2012;104(11):815–840. doi:10.1093/jnci/djs207
  • Xu P, Zhu Y, Sun B, Xiao Z. Colorectal cancer characterization and therapeutic target prediction based on microRNA expression profile. Sci Rep. 2016;6:20616. doi:10.1038/srep20616
  • Ågesen TH, Berg M, Clancy T, Thiis-Evensen E, Cekaite L, Lind GE, Nesland JM, Bakka A, Mala T, Hauss HJ, et al. CLC and IFNAR1 are differentially expressed and a global immunity score is distinct between early- and late-onset colorectal cancer. Genes Immun. 2011;12(8):653–662. doi:10.1038/gene.2011.43
  • Lech G, Słotwiński R, Słodkowski M, Krasnodębski IW. Colorectal cancer tumour markers and biomarkers: recent therapeutic advances. World J Gastroenterol. 2016;22(5):1745–1755. doi:10.3748/wjg.v22.i5.1745
  • Gröne J, Lenze D, Jurinovic V, Hummel M, Seidel H, Leder G, Beckmann G, Sommer A, Grützmann R, Pilarsky C, et al. Molecular profiles and clinical outcome of stage UICC II colon cancer patients. Int J Colorect Dis. 2011;26(7):847–858. doi:10.1007/s00384-011-1176-x
  • Marisa L, de Reyniès A, Duval A, Selves J, Gaub MP, Vescovo L, Etienne-Grimaldi M-C, Schiappa R, Guenot D, Ayadi M, et al. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med. 2013;10(5):e1001453. doi:10.1371/journal.pmed.1001453
  • Deyati A, Bagewadi S, Senger P, Hofmann-Apitius M, Novac N. Systems approach for the selection of micro-RNAs as therapeutic biomarkers of anti-EGFR monoclonal antibody treatment in colorectal cancer. Sci Rep. 2015;5:8013doi:10.1038/srep08013
  • Sun Z, Liu J, Chen C, Zhou Q, Yang S, Wang G, Song J, Li Z, Zhang Z, Xu J, et al. The biological effect and clinical application of long noncoding RNAs in colorectal cancer. Cell Physiol Biochem. 2018;46(2):431–441. doi:10.1159/000488610
  • Snipstad K, Fenton CG, Kjaeve J, Cui G, Anderssen E, Paulssen RH. New specific molecular targets for radio-chemotherapy of rectal cancer. Mol Oncol. 2010;4(1):52–64. doi:10.1016/j.molonc.2009.11.002
  • Bachmayr-Heyda A, Reiner AT, Auer K, Sukhbaatar N, Aust S, Bachleitner-Hofmann T, Mesteri I, Grunt TW, Zeillinger R, Pils D, et al. Correlation of circular RNA abundance with proliferation-exemplified with colorectal and ovarian cancer, idiopathic lung fibrosis, and normal human tissues. Sci Rep. 2015;5:8057. doi:10.1038/srep08057
  • Cheng X, Hu M, Chen C, Hou D. Computational analysis of mRNA expression profiles identifies a novel triple-biomarker model as prognostic predictor of stage II and III colorectal adenocarcinoma patients. Cancer Manag Res. 2018;10:2945–2952. doi:10.2147/CMAR.S170502
  • Goossens-Beumer IJ, Derr RS, Buermans HPJ, Goeman JJ, Böhringer S, Morreau H, Nitsche U, Janssen K-P, van de Velde CJH, Kuppen PJK, et al. MicroRNA classifier and nomogram for metastasis prediction in colon cancer. Cancer Epidemiol Biomark Prev. 2015;24(1):187–197. doi:10.1158/1055-9965.EPI-14-0544-T
  • Ogata-Kawata H, Izumiya M, Kurioka D, Honma Y, Yamada Y, Furuta K, Gunji T, Ohta H, Okamoto H, Sonoda H, et al. Circulating exosomal microRNAs as biomarkers of colon cancer. PLoS One. 2014;9(4):e92921. doi:10.1371/journal.pone.0092921
  • Sun Y, Shen S, Tang H, Xiang J, Peng Y, Tang A, Li N, Zhou W, Wang Z, Zhang D, et al. miR-429 identified by dynamic transcriptome analysis is a new candidate biomarker for colorectal cancer prognosis. OMICS. 2014;18(1):54–64. doi:10.1089/omi.2012.0132
  • Guo S, Zhang J, Wang B, Zhang B, Wang X, Huang L, Liu H, Jia B. A 5-serum miRNA panel for the early detection of colorectal cancer. Onco Targets Ther. 2018;11:2603–2614. doi:10.2147/OTT.S153535
  • Falzone L, Scola L, Zanghì A, Biondi A, Di Cataldo A, Libra M, Candido S. Integrated analysis of colorectal cancer microRNA datasets: identification of microRNAs associated with tumor development. Aging (Albany NY)). 2018;10(5):1000–1014. doi:10.18632/aging.101444
  • Falzone L, Candido S, Salemi R, Basile MS, Scalisi A, McCubrey JA, Torino F, Signorelli SS, Montella M, Libra M, et al. Computational identification of microRNAs associated to both epithelial to mesenchymal transition and NGAL/MMP-9 pathways in bladder cancer. Oncotarget. 2016;7(45):72758–72766. doi:10.18632/oncotarget.11805
  • Hafsi S, Candido S, Maestro R, Falzone L, Soua Z, Bonavida B, Spandidos DA, Libra M. Correlation between the overexpression of Yin Yang 1 and the expression levels of miRNAs in Burkitt's lymphoma: a computational study. Oncol Lett. 2016;11(2):1021–1025. doi:10.3892/ol.2015.4031
  • Zhang T, Guo J, Gu J, Wang Z, Wang G, Li H, Wang J. Identifying the key genes and microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro experiments. Oncol Rep. 2019;41(1):279–291. doi:10.3892/or.2018.6840
  • Liang B, Li C, Zhao J. Identification of key pathways and genes in colorectal cancer using bioinformatics analysis. Med Oncol. 2016;33(10):111. doi:10.1007/s12032-016-0829-6
  • Koduru SV, Tiwari AK, Hazard SW, Mahajan M, Ravnic DJ. Exploration of small RNA-seq data for small non-coding RNAs in human colorectal cancer. J Genom. 2017;5:16–31. doi:10.7150/jgen.18856
  • Falzone L, Romano GL, Salemi R, Bucolo C, Tomasello B, Lupo G, Anfuso CD, Spandidos DA, Libra M, Candido S, et al. Prognostic significance of deregulated microRNAs in uveal melanomas. Mol Med Rep. 2019;19(4):2599–2610. doi:10.3892/mmr.2019.9949
  • Su Y, Zhang M, Zhang L, Chen S, Zhang D, Zhang X. Construction of an miRNA-mRNA regulatory network in colorectal cancer with bioinformatics methods. Anticancer Drugs. 2019;30(6):588–595. doi:10.1097/CAD.0000000000000745
  • Li R, Grimm SA, Mav D, Gu H, Djukovic D, Shah R, Merrick BA, Raftery D, Wade PA. Transcriptome and DNA methylome analysis in a mouse model of diet-induced obesity predicts increased risk of colorectal cancer. Cell Rep. 2018;22(3):624–637. doi:10.1016/j.celrep.2017.12.071
  • Zhou X-G, Huang X-L, Liang S-Y, Tang S-M, Wu S-K, Huang T-T, Mo Z-N, Wang Q-Y. Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis. Onco Targets Ther. 2018;11:2815–2830. doi:10.2147/OTT.S163891
  • Tsukamoto S, Ishikawa T, Iida S, Ishiguro M, Mogushi K, Mizushima H, Uetake H, Tanaka H, Sugihara K. Clinical significance of osteoprotegerin expression in human colorectal cancer. Clin Cancer Res. 2011;17(8):2444–2450. doi:10.1158/1078-0432.CCR-10-2884
  • Law CW, Alhamdoosh M, Su S, Smyth GK, Ritchie ME. RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR. F1000Res. 2016;5:1408. doi:10.12688/f1000research.9005.2
  • Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47. doi:10.1093/nar/gkv007
  • Diboun I, Wernisch L, Orengo CA, Koltzenburg M. Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC Genomics. 2006;7(1):252. doi:10.1186/1471-2164-7-252
  • Cao C, Wang W, Ma C, Jiang P. Computational analysis identifies invasion-associated genes in pituitary adenomas. Mol Med Rep. 2015;12(2):1977–1982. doi:10.3892/mmr.2015.3564
  • Luo W, Brouwer C. Pathview: an R/Bioconductor package for pathway-based data integration and visualization. Bioinformatics. 2013;29(14):1830–1831. doi:10.1093/bioinformatics/btt285
  • Del Carratore F, Jankevics A, Eisinga R, Heskes T, Hong F, Breitling R. RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets. Bioinformatics. 2017;33(17):2774–2775. doi:10.1093/bioinformatics/btx292
  • Moosavi A, Motevalizadeh Ardekani A. Role of epigenetics in biology and human diseases. Iran Biomed J. 2016;20(5):246–258. doi:10.22045/ibj.2016.01
  • Perez R, Wu N, Klipfel AA, Beart RW Jr. A better cell cycle target for gene therapy of colorectal cancer: cyclin G. J Gastrointest Surg. 2003;7(7):884–889. doi:10.1007/s11605-003-0034-8
  • Tominaga O, Nita ME, Nagawa H, Fujii S, Tsuruo T, Muto T. Expressions of cell cycle regulators in human colorectal cancer cell lines. Jpn J Cancer Res. 1997;88(9):855–860. doi:10.1111/j.1349-7006.1997.tb00461.x

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.