Differential correlation analysis of glioblastoma reveals immune ceRNA interactions predictive of patient survival

BackgroundRecent studies illuminated a novel role of microRNA (miRNA) in the competing endogenous RNA (ceRNA) interaction: two genes (ceRNAs) can achieve coexpression by competing for a pool of common targeting miRNAs. Individual biological investigations implied ceRNA interaction performs crucial oncogenic/tumor suppressive functions in glioblastoma multiforme (GBM). Yet, a systematic analysis has not been conducted to explore the functional landscape and prognostic significance of ceRNA interaction.ResultsIncorporating the knowledge that ceRNA interaction is highly condition-specific and modulated by the expressional abundance of miRNAs, we devised a ceRNA inference by differential correlation analysis to identify the miRNA-modulated ceRNA pairs. Analyzing sample-paired miRNA and gene expression profiles of GBM, our data showed that this alternative layer of gene interaction is essential in global information flow. Functional annotation analysis revealed its involvement in activated processes in brain, such as synaptic transmission, as well as critical tumor-associated functions. Notably, a systematic survival analysis suggested the strength of ceRNA-ceRNA interactions, rather than expressional abundance of individual ceRNAs, among three immune response genes (CCL22, IL2RB, and IRF4) is predictive of patient survival. The prognostic value was validated in two independent cohorts.ConclusionsThis work addresses the lack of a comprehensive exploration into the functional and prognostic relevance of ceRNA interaction in GBM. The proposed efficient and reliable method revealed its significance in GBM-related functions and prognosis. The highlighted roles of ceRNA interaction provide a basis for further biological and clinical investigations.

[1]  Josef Ammermüller,et al.  The Presynaptic Active Zone Protein Bassoon Is Essential for Photoreceptor Ribbon Synapse Formation in the Retina , 2003, Neuron.

[2]  Jin Ding,et al.  Exosome-Transmitted lncARSR Promotes Sunitinib Resistance in Renal Cancer by Acting as a Competing Endogenous RNA. , 2016, Cancer cell.

[3]  Yidong Chen,et al.  Modeling competing endogenous RNA regulatory networks in glioblastoma multiforme , 2013, 2013 IEEE International Conference on Bioinformatics and Biomedicine.

[4]  Pieter Wesseling,et al.  Prognostic significance and mechanism of Treg infiltration in human brain tumors , 2010, Journal of Neuroimmunology.

[5]  C. Burge,et al.  Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets , 2005, Cell.

[6]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[7]  S. Barik,et al.  MicroRNAs: Processing, Maturation, Target Recognition and Regulatory Functions. , 2011, Molecular and cellular pharmacology.

[8]  Sandra L. Schmid,et al.  Phosphorylation of the AP2 μ subunit by AAK1 mediates high affinity binding to membrane protein sorting signals , 2002, The Journal of cell biology.

[9]  Ryuzo Ueda,et al.  CCR4 as a novel molecular target for immunotherapy of cancer , 2006, Cancer science.

[10]  M. Lesniak,et al.  An increase in CD4+CD25+FOXP3+ regulatory T cells in tumor-infiltrating lymphocytes of human glioblastoma multiforme. , 2006, Neuro-oncology.

[11]  Beth Israel,et al.  Decision letter: Replication Study: A coding-independent function of gene and pseudogene mRNAs regulates tumour biology , 2010 .

[12]  Pieter Wesseling,et al.  Regulatory T cells and the PD-L1/PD-1 pathway mediate immune suppression in malignant human brain tumors. , 2009, Neuro-oncology.

[13]  Raymond M. Welsh,et al.  Graded Levels of IRF4 Regulate CD8+ T Cell Differentiation and Expansion, but Not Attrition, in Response to Acute Virus Infection , 2014, The Journal of Immunology.

[14]  Pier Paolo Pandolfi,et al.  ceRNA cross-talk in cancer: when ce-bling rivalries go awry. , 2013, Cancer discovery.

[15]  Tomohiro Yamaguchi,et al.  Interleukin-15 effectively potentiates the in vitro tumor-specific activity and proliferation of peripheral blood γδT cells isolated from glioblastoma patients , 1998, Cancer Immunology, Immunotherapy.

[16]  C. Melief,et al.  Cancer immunology. , 2011, Current opinion in immunology.

[17]  Sujit S. Prabhu,et al.  Preferential migration of regulatory T cells mediated by glioma-secreted chemokines can be blocked with chemotherapy , 2007, Cancer Immunology, Immunotherapy.

[18]  S. Gabriel,et al.  Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. , 2010, Cancer cell.

[19]  Harinder Singh,et al.  IRF-4,8 orchestrate the pre-B-to-B transition in lymphocyte development. , 2003, Genes & development.

[20]  Enzo Marinari,et al.  Probing the Limits to MicroRNA-Mediated Control of Gene Expression , 2016, PLoS Comput. Biol..

[21]  George Coukos,et al.  Cancer immunotherapy comes of age , 2011, Nature.

[22]  Tzu-Pin Lu,et al.  Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers , 2016, Scientific Reports.

[23]  Alessandro Laganà,et al.  MicroRNA-148a reduces tumorigenesis and increases TRAIL-induced apoptosis in NSCLC , 2015, Proceedings of the National Academy of Sciences.

[24]  Thomas D. Wu,et al.  Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. , 2006, Cancer cell.

[25]  B. Silva-Santos,et al.  γδ T cells in cancer , 2015, Nature Reviews Immunology.

[26]  Xuerui Yang,et al.  An Extensive MicroRNA-Mediated Network of RNA-RNA Interactions Regulates Established Oncogenic Pathways in Glioblastoma , 2011, Cell.

[27]  Qun Zhou,et al.  lincRNA-RoR and miR-145 Regulate Invasion in Triple-Negative Breast Cancer via Targeting ARF6 , 2014, Molecular Cancer Research.

[28]  Mariano J. Alvarez,et al.  Genome-wide Identification of Post-translational Modulators of Transcription Factor Activity in Human B-Cells , 2009, Nature Biotechnology.

[29]  J. Uhm.  An Integrated Genomic Analysis of Human Glioblastoma Multiforme , 2009 .

[30]  Yu-Chiao Chiu,et al.  Parameter optimization for constructing competing endogenous RNA regulatory network in glioblastoma multiforme and other cancers , 2015, BMC Genomics.

[31]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[32]  E. Chuang,et al.  A 3-microRNA scoring system for prognostication in de novo acute myeloid leukemia patients , 2014, Leukemia.

[33]  P. Pandolfi,et al.  In Vivo Identification of Tumor- Suppressive PTEN ceRNAs in an Oncogenic BRAF-Induced Mouse Model of Melanoma , 2011, Cell.

[34]  Charlotte Soneson,et al.  A glioma classification scheme based on coexpression modules of EGFR and PDGFRA , 2014, Proceedings of the National Academy of Sciences.

[35]  Ming Sun,et al.  Lnc RNA HOTAIR functions as a competing endogenous RNA to regulate HER2 expression by sponging miR-331-3p in gastric cancer , 2014, Molecular Cancer.

[36]  Phillip A Sharp,et al.  Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition. , 2014, Molecular cell.

[37]  M. Huber,et al.  IRF4 at the crossroads of effector T‐cell fate decision , 2014, European journal of immunology.

[38]  Gavin Brown,et al.  Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection , 2012, J. Mach. Learn. Res..

[39]  Chris Wiggins,et al.  ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context , 2004, BMC Bioinformatics.

[40]  Tanja Woyke,et al.  Gene expression profile of glioblastoma multiforme invasive phenotype points to new therapeutic targets. , 2005, Neoplasia.

[41]  Edwin R Chapman,et al.  Glycosylated SV2A and SV2B mediate the entry of botulinum neurotoxin E into neurons. , 2008, Molecular biology of the cell.

[42]  L. Staudt,et al.  IRF4: Immunity. Malignancy! Therapy? , 2009, Clinical Cancer Research.

[43]  Theodore J. Perkins,et al.  On cross-conditional and fluctuation correlations in competitive RNA networks , 2016, Bioinform..

[44]  Maurice G. Kendall,et al.  The advanced theory of statistics , 1945 .

[45]  Wen-Yuan Lee,et al.  Adjuvant immunotherapy with whole-cell lysate dendritic cells vaccine for glioblastoma multiforme: a phase II clinical trial. , 2012, World neurosurgery.

[46]  Olaf Wolkenhauer,et al.  Understanding microRNA-mediated gene regulatory networks through mathematical modelling , 2016, Nucleic acids research.

[47]  C. K. Hsiao,et al.  miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets , 2012, PloS one.

[48]  S. Horvath,et al.  Gene Expression Profiling of Gliomas Strongly Predicts Survival , 2004, Cancer Research.

[49]  D. Botstein,et al.  Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[50]  A. Parsa,et al.  Soluble factors secreted by glioblastoma cell lines facilitate recruitment, survival, and expansion of regulatory T cells: implications for immunotherapy. , 2012, Neuro-oncology.

[51]  Wei Li,et al.  CFIm25 links Alternative Polyadenylation to Glioblastoma Tumor Suppression , 2014, Nature.

[52]  John Macsharry,et al.  Gamma-secretase-independent role for cadherin-11 in neurotrophin receptor p75 (p75NTR) mediated glioblastoma cell migration , 2015, Molecular and Cellular Neuroscience.

[53]  T. Mak,et al.  Requirement for the Transcription Factor LSIRF/IRF4 for Mature B and T Lymphocyte Function , 1997, Science.

[54]  M. Dinger,et al.  Endogenous microRNA sponges: evidence and controversy , 2016, Nature Reviews Genetics.

[55]  J. Uhm.  Comprehensive genomic characterization defines human glioblastoma genes and core pathways , 2009 .

[56]  Maurice G. Kendall,et al.  The Advanced Theory of Statistics, Vol. 2: Inference and Relationship , 1979 .

[57]  Tzu-Pin Lu,et al.  Prognostic significance of NPM1 mutation-modulated microRNA−mRNA regulation in acute myeloid leukemia , 2016, Leukemia.

[58]  Mulin Jun Li,et al.  Exploring functional variation affecting ceRNA regulation in humans , 2015, bioRxiv.

[59]  L. Castellano,et al.  Emerging Roles of Competing Endogenous RNAs in Cancer: Insights from the Regulation of PTEN , 2013, Molecular and Cellular Biology.

[60]  Sol Efroni,et al.  MicroRNA-Gene Association As a Prognostic Biomarker in Cancer Exposes Disease Mechanisms , 2013, PLoS Comput. Biol..

[61]  Michael Q. Zhang,et al.  Model-guided quantitative analysis of microRNA-mediated regulation on competing endogenous RNAs using a synthetic gene circuit , 2015, Proceedings of the National Academy of Sciences.

[62]  David Warde-Farley,et al.  Dynamic modularity in protein interaction networks predicts breast cancer outcome , 2009, Nature Biotechnology.

[63]  R. Zecchina,et al.  Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments , 2013, Proceedings of the National Academy of Sciences.

[64]  D. Bartel.  MicroRNAs: Target Recognition and Regulatory Functions , 2009, Cell.

[65]  Pei Yang,et al.  MicroRNA profiling of Chinese primary glioblastoma reveals a temozolomide-chemoresistant subtype , 2015, Oncotarget.

[66]  Xia Li,et al.  Extensive ceRNA–ceRNA interaction networks mediated by miRNAs regulate development in multiple rhesus tissues , 2016, Nucleic acids research.

[67]  Leng Han,et al.  Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types , 2014, Nature Communications.

[68]  Ferdinando Di Cunto,et al.  Coding-Independent Regulation of the Tumor Suppressor PTEN by Competing Endogenous mRNAs , 2011, Cell.

[69]  Lin Song,et al.  Comparison of co-expression measures: mutual information, correlation, and model based indices , 2012, BMC Bioinformatics.

[70]  T. Ideker,et al.  Differential network biology , 2012, Molecular systems biology.

[71]  Wei Li,et al.  Dynamic analyses of alternative polyadenylation from RNA-seq reveal a 3′-UTR landscape across seven tumour types , 2014, Nature Communications.

[72]  Vikram Agarwal,et al.  Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance. , 2014, Molecular cell.