Abstract
Lupeol attracted lots of research attention because of its anticancer activity. This work presents the complete microRNA profile between lupeol treated HeLa cell lines and control group, and investigates the complete small RNA sequencing data analysis process, including microRNA annotation, novel microRNA prediction, dysregulated microRNA identification and microRNA target prediction. Based on single replicate data, we applied generalized fold change (GFOLD) algorithm to detect significant regulated microRNAs. Furthermore, we adopted GOmir to predict targets of some microRNAs which have received fully attention and perform ontology analysis. The experimental results indicate that the predicted microRNAs are highly correlated with carcinogenesis.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Redshaw, N., Wilkes, T., Whale, A., Cowen, S., Huggett, J., Foy, C.A.: A comparison of microRNA isolation and RT-qPCR technologies and their effects on quantification accuracy and repeatability. BioTechniques 54(3), 155–164 (2013)
Mattie, M.D., Benz, C.C., Bowers, J., Sensinger, K., Wong, L., Scott, G.K., Fedele, V., Ginzinger, D., Getts, R., Haqq, C.: Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies. Mol. Cancer 5, 24 (2006)
Griffiths-Jones, S.: miRBase: the microRNA sequence database. Methods Mol. Biol. 342, 129–138 (2006)
Davison, T.S., Johnson, C.D., Andruss, B.F.: Analyzing micro-RNA expression using microarrays. Methods Enzymol. 411, 14–34 (2006)
Cummins, J.M., He, Y., Leary, R.J., Pagliarini, R., Diaz, L.A.: The colorectal microRNAome. Proc. Natl. Acad. Sci. U. S. A. 103(10), 3687–3692 (2006)
Morin, R.D., O’Connor, M.D., Griffith, M., Kuchenbauer, F., Delaney, A.: Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells. Genome Res. 18(4), 610–621 (2008)
Hesse, J.E., Liu, L., Innes, C.L., Cui, Y., Palii, S.S., Paules, R.S.: Genome-Wide Small RNA Sequencing and Gene Expression Analysis Reveals a microRNA Profile of Cancer Susceptibility in ATM-Deficient Human Mammary Epithelial Cells. PLoS One 8(5), 1–9 (2013)
Li, Y., Zhang, Z., Liu, F., Vongsangnak, W., Jing, Q., Shen, B.R.: Performance comparison and evaluation of software tools for microRNA deep-sequencing data analysis. Nucleic Acids Research 40(10), 4298–4305 (2012)
Liu, D.C., Dai, C.H., Xu, D.C.: Cluster analysis of microRNAs microarray data and prediction of lupeol’s anti-cancer path. In: 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, pp. 440–445. IEEE Press, Atlanta (2011)
Saleem, M.: Lupeol, a novel anti-inflammatory and anti-cancer dietary triterpene. Cancer Lett. 285, 109–115 (2009)
Hackenberg, M., Sturm, M., Langenberger, D., Falcón-Pérez, J.M., Aransay, A.M.: miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res. 37(Web Server issue), W68–W76 (2009)
National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov
Feng, J., Meyer, C.A., Wang, Q., Liu, J.S., Shirley Liu, X., Zhang, Y.: GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data. Bioinformatics 28(21), 2782–2788 (2012)
Anders, S., Huber, W.: Differential expression analysis for sequence count data. Genome Biol. 11(10), R106 (2010)
Cai, Z., Eulenstein, O., Gibas, C.: Guest Editors Introduction to the Special Section on Bioinformatics Research and Applications. IEEE/ACM Transactions on Computational Biology and Bioinformatics 11(2), 1–2 (2014)
GOmir, http://www.bioacademy.gr/bioinformatics/projects/GOmir/
Tian, Q., Liang, L., Ding, J., Zha, R., Shi, H., Wang, Q., Huang, S., Guo, W., Ge, C., Chen, T., Li, J., He, X.: MicroRNA-550a acts as a pro-metastatic gene and directly targets cytoplasmic polyadenylation element-binding protein 4 in hepatocellular carcinoma. PLoS One 7(11), 1–9 (2012)
Ma, Y., Yu, S., Zhao, W., Lu, Z., Chen, J.: miR-27a regulates the growth, colony formation and migration of pancreatic cancer cells by targeting Sprouty2. Cancer Lett. 298, 150–158 (2010)
Zhu, H., Wu, H., Liu, X., Evans, B.R., Medina, D.J., Liu, C.G., Yang, J.M.: Role of MicroRNA miR-27a and miR-451 in the regulation of MDR1/P-glycoprotein expression in human cancer cells. Biochem. Pharmacol. 76, 582–588 (2008)
Li, Z., Hu, S., Wang, J., Cai, J., Xiao, L., Yu, L., Wang, Z.: MiR-27a modulates MDR1/P-glycoprotein expression by targeting HIPK2 in human ovarian cancer cells. Gynecol. Oncol. 119, 125–130 (2010)
Xiang, Y., Ma, N., Wang, D., Zhang, Y., Zhou, J., Wu, G., Zhao, R., Huang, H., Wang, X., Qiao, Y., Li, F., Han, D., Wang, L., Zhang, G., Gao, X.: MiR-152 and miR-185 co-contribute to ovarian cancer cells cisplatin sensitivity by targeting DNMT1 directly: a novel epigenetic therapy independent of decitabine. Oncogene, 1–9 (2013)
Weeraratne, S.D., Amani, V., Teider, N., Pierre-Francois, J., Winter, D.: Pleiotropic effects of miR-183~96~182 converge to regulate cell survival, proliferation and migration in medulloblastoma. Acta, Neuropathol. 123, 539–552 (2012)
Tang, H., Bian, Y., Tu, C., Wang, Z., Yu, Z., Liu, Q., Xu, G., Wu, M., Li, G.: The miR-183/96/182 cluster regulates oxidative apoptosis and sensitizes cells to chemotherapy in gliomas. Curr. Cancer Drug Targets 13(2), 221–231 (2013)
Guttilla, I.K., White, B.A.: Coordinate Regulation of FOXO1 by miR-27a, miR-96, and miR-182 in Breast Cancer Cells. J. Biol. Chem. 284, 23204–23216 (2009)
Li, J., Fu, H., Xu, C., Tie, Y., Xing, R., Zhu, J., Qin, Y., Sun, Z., Zheng, X.: miR-183 inhibits TGF-β1-induced apoptosis by downregulation of PDCD4 expression in human hepatocellular carcinoma cells. BMC Cancer 10, 354 (2010)
Chiang, C.H., Hou, M.F., Hung, W.C.: Up-regulation of miR-182 by β-catenin in breast cancer increases tumorigenicity and invasiveness by targeting the matrix metalloproteinase inhibitor RECK. Biochim. Biophys. Acta. 1830, 3067–3076 (2013)
Takata, A., Otsuka, M., Kojima, K., Yoshikawa, T., Kishikawa, T., Yoshida, H., Koike, K.: MicroRNA-22 and microRNA-140 suppress NF-κB activity by regulating the expression of NF-κB coactivators. Biochem. Biophys. Res. Commun. 411, 826–831 (2011)
Li, X.F., Yan, P.J., Shao, Z.M.: Downregulation of miR-193b contributes to enhance urokinase-type plasminogen activator (uPA) expression and tumor progression and invasion in human breast cancer. Oncogene 28, 3937–3948 (2009)
Chen, J., Zhang, X., Lentz, C., Abi-Daoud, M., Paré, G.C., Yang, X., Feilotter, H.E., Tron, V.A.: miR-193b Regulates Mcl-1 in Melanoma. Am. J. Pathol. 179(5), 2162–2168 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Lu, X., Dai, C., Hou, A., Cui, J., Cheng, D., Xu, D. (2014). Dysregulated microRNA Profile in HeLa Cell Lines Induced by Lupeol. In: Basu, M., Pan, Y., Wang, J. (eds) Bioinformatics Research and Applications. ISBRA 2014. Lecture Notes in Computer Science(), vol 8492. Springer, Cham. https://doi.org/10.1007/978-3-319-08171-7_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-08171-7_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08170-0
Online ISBN: 978-3-319-08171-7
eBook Packages: Computer ScienceComputer Science (R0)