Interactions of miR-323/miR-326/miR-329 and miR-130a/miR-155/miR-210 as prognostic indicators for clinical outcome of glioblastoma patients

Journal of Translational Medicine

Ying Peng⁴  Yang Tan¹  Yimin Feng¹  Dan Hu²  Sheng Lin³  Shuwei Qiu¹ 

[1] Department of Internal Medicine, College of Medicine, East Tennessee State University, Johnson City, 37604, TN, USA;Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, 430060, China;Laboratory of Medical Genetics, Key Laboratory of Birth Defects Surveillance and Intervention of Guangdong Province, Shenzhen Research Institute of Population and Family Planning, Shenzhen, 518040, China;Department of Neurology, The Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China

关键词: Interaction;    Progression-free survival;    Overall survival;    Prognostic marker;    microRNA;    Glioblastoma multiforme;   

Others  :  828227
DOI  :  10.1186/1479-5876-11-10

 received in 2012-11-03, accepted in 2013-01-07,  发布年份 2013

【 摘 要 】

Background

Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor with poor clinical outcome. Identification and development of new markers could be beneficial for the diagnosis and prognosis of GBM patients. Deregulation of microRNAs (miRNAs or miRs) is involved in GBM. Therefore, we attempted to identify and develop specific miRNAs as prognostic and predictive markers for GBM patient survival.

Methods

Expression profiles of miRNAs and genes and the corresponding clinical information of 480 GBM samples from The Cancer Genome Atlas (TCGA) dataset were downloaded and interested miRNAs were identified. Patients’ overall survival (OS) and progression-free survival (PFS) associated with interested miRNAs and miRNA-interactions were performed by Kaplan-Meier survival analysis. The impacts of miRNA expressions and miRNA-interactions on survival were evaluated by Cox proportional hazard regression model. Biological processes and network of putative and validated targets of miRNAs were analyzed by bioinformatics.

Results

In this study, 6 interested miRNAs were identified. Survival analysis showed that high levels of miR-326/miR-130a and low levels of miR-323/miR-329/miR-155/miR-210 were significantly associated with long OS of GBM patients, and also showed that high miR-326/miR-130a and low miR-155/miR-210 were related with extended PFS. Moreover, miRNA-323 and miRNA-329 were found to be increased in patients with no-recurrence or long time to progression (TTP). More notably, our analysis revealed miRNA-interactions were more specific and accurate to discriminate and predict OS and PFS. This interaction stratified OS and PFS related with different miRNA levels more detailed, and could obtain longer span of mean survival in comparison to that of one single miRNA. Moreover, miR-326, miR-130a, miR-155, miR-210 and 4 miRNA-interactions were confirmed for the first time as independent predictors for survival by Cox regression model together with clinicopathological factors: Age, Gender and Recurrence. Plus, the availability and rationality of the miRNA-interaction as predictors for survival were further supported by analysis of network, biological processes, KEGG pathway and correlation analysis with gene markers.

Conclusions

Our results demonstrates that miR-326, miR-130a, miR-155, miR-210 and the 4 miRNA-interactions could serve as prognostic and predictive markers for survival of GBM patients, suggesting a potential application in improvement of prognostic tools and treatments.

【 授权许可】

   
2013 Qiu et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Porter KR, McCarthy BJ, Freels S, Kim Y, Davis FG: Prevalence estimates for primary brain tumors in the United States by age, gender, behavior, and histology. Neuro Oncol 2010, 12:520-527.
• [2]Verhaak RG, Hoadley KA, Purdom E, Wang V, Qi Y, Wilkerson MD, Miller CR, Ding L, Golub T, Mesirov JP, et al.: Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 2010, 17:98-110.
• [3]Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, Berman BP, Pan F, Pelloski CE, Sulman EP, Bhat KP, et al.: Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 2010, 17:510-522.
• [4]Inui M, Martello G, Piccolo S: MicroRNA control of signal transduction. Nat Rev Mol Cell Biol 2010, 11:252-263.
• [5]Bader AG, Brown D, Winkler M: The promise of microRNA replacement therapy. Cancer Res 2010, 70:7027-7030.
• [6]Zhi F, Chen X, Wang S, Xia X, Shi Y, Guan W, Shao N, Qu H, Yang C, Zhang Y, et al.: The use of hsa-miR-21, hsa-miR-181b and hsa-miR-106a as prognostic indicators of astrocytoma. Eur J Cancer 2010, 46:1640-1649.
• [7]Delfino KR, Serao NV, Southey BR, Rodriguez-Zas SL: Therapy-, gender- and race-specific microRNA markers, target genes and networks related to glioblastoma recurrence and survival. Cancer Genomics Proteomics 2011, 8:173-183.
• [8]Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA, et al.: MicroRNA expression profiles classify human cancers. Nature 2005, 435:834-838.
• [9]TCGA: Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008, 455:1061-1068.
• [10]Gabriely G, Yi M, Narayan RS, Niers JM, Wurdinger T, Imitola J, Ligon KL, Kesari S, Esau C, Stephens RM, et al.: Human glioma growth is controlled by microRNA-10b. Cancer Res 2011, 71:3563-3572.
• [11]Consortium TGO: Gene ontology: tool for the unification of biology. Nat Genet 2000, 25:25-29.
• [12]Kanehisa M, Goto S: KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000, 28:27-30.
• [13]Friedman RC, Farh KK, Burge CB, Bartel DP: Most mammalian mRNAs are conserved targets of microRNAs. Genome Res 2009, 19:92-105.
• [14]da Huang W, Sherman BT, Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009, 4:44-57.
• [15]Martin A, Ochagavia ME, Rabasa LC, Miranda J, Fernandez-de-Cossio J, Bringas R: BisoGenet: a new tool for gene network building, visualization and analysis. BMC Bioinformatics 2010, 11:91. BioMed Central Full Text
• [16]Vlachos IS, Kostoulas N, Vergoulis T, Georgakilas G, Reczko M, Maragkakis M, Paraskevopoulou MD, Prionidis K, Dalamagas T, Hatzigeorgiou AG: DIANA miRPath v. 2.0: investigating the combinatorial effect of microRNAs in pathways. Nucleic Acids Res 2012, 40:W498-504.
• [17]Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T: miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res 2009, 37:D105-110.
• [18]Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, Pfeffer S, Rice A, Kamphorst AO, Landthaler M, et al.: A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 2007, 129:1401-1414.
• [19]Silber J, Lim DA, Petritsch C, Persson AI, Maunakea AK, Yu M, Vandenberg SR, Ginzinger DG, James CD, Costello JF, et al.: miR-124 and miR-137 inhibit proliferation of glioblastoma multiforme cells and induce differentiation of brain tumor stem cells. BMC Med 2008, 6:14. BioMed Central Full Text
• [20]Huse JT, Brennan C, Hambardzumyan D, Wee B, Pena J, Rouhanifard SH, Sohn-Lee C, le Sage C, Agami R, Tuschl T, Holland EC: The PTEN-regulating microRNA miR-26a is amplified in high-grade glioma and facilitates gliomagenesis in vivo. Genes Dev 2009, 23:1327-1337.
• [21]Malzkorn B, Wolter M, Liesenberg F, Grzendowski M, Stuhler K, Meyer HE, Reifenberger G: Identification and functional characterization of microRNAs involved in the malignant progression of gliomas. Brain Pathol 2009, 20:539-550.
• [22]Zhou X, Ren Y, Moore L, Mei M, You Y, Xu P, Wang B, Wang G, Jia Z, Pu P, et al.: Downregulation of miR-21 inhibits EGFR pathway and suppresses the growth of human glioblastoma cells independent of PTEN status. Lab Invest 2010, 90:144-155.
• [23]Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ, Angenendt P, Mankoo P, Carter H, Siu IM, Gallia GL, et al.: An integrated genomic analysis of human glioblastoma multiforme. Science 2008, 321:1807-1812.
• [24]Camara-Quintana JQ, Nitta RT, Li G: Pathology: commonly monitored glioblastoma markers: EFGR, EGFRvIII, PTEN, and MGMT. Neurosurg Clin N Am 2012, 23:237-246.
• [25]Bady P, Sciuscio D, Diserens AC, Bloch J, van den Bent MJ, Marosi C, Dietrich PY, Weller M, Mariani L, Heppner FL, et al.: MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status. Acta Neuropathol 2012.
• [26]von Deimling A, Korshunov A, Hartmann C: The next generation of glioma biomarkers: MGMT methylation, BRAF fusions and IDH1 mutations. Brain Pathol 2011, 21:74-87.
• [27]Motomura K, Natsume A, Watanabe R, Ito I, Kato Y, Momota H, Nishikawa R, Mishima K, Nakasu Y, Abe T, et al.: Immunohistochemical analysis-based proteomic subclassification of newly diagnosed glioblastomas. Cancer Sci 2012.
• [28]Zinn PO, Sathyan P, Mahajan B, Bruyere J, Hegi M, Majumder S, Colen RR: A Novel Volume-Age-KPS (VAK) Glioblastoma Classification Identifies a Prognostic Cognate microRNA-Gene Signature. PLoS One 2012, 7:e41522.
• [29]Kong YW, Ferland-McCollough D, Jackson TJ, Bushell M: microRNAs in cancer management. Lancet Oncol 2012, 13:e249-258.
• [30]Osman A: MicroRNAs in health and disease–basic science and clinical applications. Clin Lab 2012, 58:393-402.
• [31]Corsini LR, Bronte G, Terrasi M, Amodeo V, Fanale D, Fiorentino E, Cicero G, Bazan V, Russo A: The role of microRNAs in cancer: diagnostic and prognostic biomarkers and targets of therapies. Expert Opin Ther Targets 2012, 16(Suppl 2):S103-109.
• [32]Lakomy R, Sana J, Hankeova S, Fadrus P, Kren L, Lzicarova E, Svoboda M, Dolezelova H, Smrcka M, Vyzula R, et al.: MiR-195, miR-196b, miR-181c, miR-21 expression levels and O-6-methylguanine-DNA methyltransferase methylation status are associated with clinical outcome in glioblastoma patients. Cancer Sci 2011, 102:2186-2190.
• [33]Srinivasan S, Patric IR, Somasundaram K: A ten-microRNA expression signature predicts survival in glioblastoma. PLoS One 2011, 6:e17438.
• [34]Kefas B, Comeau L, Floyd DH, Seleverstov O, Godlewski J, Schmittgen T, Jiang J, diPierro CG, Li Y, Chiocca EA, et al.: The neuronal microRNA miR-326 acts in a feedback loop with notch and has therapeutic potential against brain tumors. J Neurosci 2009, 29:15161-15168.
• [35]Poltronieri P, D'Urso PI, Mezzolla V, D'Urso OF: Potential of anti-cancer therapy based on anti-miR-155 oligonucleotides in glioma and brain tumours. Chem Biol Drug Des 2012.
• [36]Brennecke J, Stark A, Russell RB, Cohen SM: Principles of microRNA-target recognition. PLoS Biol 2005, 3:e85.
• [37]Monticone M, Daga A, Candiani S, Romeo F, Mirisola V, Viaggi S, Melloni I, Pedemonte S, Zona G, Giaretti W, et al.: Identification of a novel set of genes reflecting different in vivo invasive patterns of human GBM cells. BMC Cancer 2012, 12:358. BioMed Central Full Text
• [38]Xu N, Shen C, Luo Y, Xia L, Xue F, Xia Q, Zhang J: Upregulated miR-130a increases drug resistance by regulating RUNX3 and Wnt signaling in cisplatin-treated HCC cell. Biochem Biophys Res Commun 2012, 425:468-472.
• [39]Acunzo M, Visone R, Romano G, Veronese A, Lovat F, Palmieri D, Bottoni A, Garofalo M, Gasparini P, Condorelli G, et al.: miR-130a targets MET and induces TRAIL-sensitivity in NSCLC by downregulating miR-221 and 222. Oncogene 2012, 31:634-642.
• [40]Ebert MS, Sharp PA: Roles for microRNAs in conferring robustness to biological processes. Cell 2012, 149:515-524.