Grant Details
Grant Number: |
1R03CA167695-01A1 Interpret this number |
Primary Investigator: |
Zhao, Zhongming |
Organization: |
Vanderbilt University |
Project Title: |
Investigating Micrornas and Their Regulatory Networks in Glioblastoma |
Fiscal Year: |
2013 |
Abstract
DESCRIPTION (provided by applicant): Glioblastoma multiforme (GBM) is the most common and lethal brain tumor in humans. It is highly resistant to radiation and chemotherapy. Understanding its molecular mechanisms is critical in order to develop more effective treatments. Recent studies revealed that microRNAs (miRNAs) play critical roles in the pathogenesis of GBM. To date, more than 100 dysregulated miRNAs have been found in GBM from various miRNA expression studies, which provide us with astonishing insights into the patterns of miRNA expression in GBM. However, the results reported so far have been inconsistent, presenting a great challenge in deciphering the underlying miRNA regulatory mechanisms in GBM. Therefore, a systematic examination of previous miRNA data is immediately needed and executable. In this project, we will develop innovative strategies to identify functionally important miRNAs significantly associated with GBM in the context of miRNA regulatory networks. The project will start by prioritizing miRNAs through integrating results from multiple studies using a mixed effects model, then build GBM-specific regulatory networks comprised of weighted molecules, i.e. GBM miRNAs, GBM genes and human transcription factors (TFs), and finally perform dense module search (DMS) of the regulatory networks to detect functionally critical miRNAs in GBM regulatory networks. We propose three specific aims. (1) To develop a novel, statistical integrative framework for the meta-analysis of miRNA expression data from multiple studies using a mixed effects model. Compared to traditional pooled analysis, we will integrate all possible effect sizes of each miRNA into a mixed
effects model and calculate a P-value as its overall effect size to GBM. (2) To develop a novel computational pipeline to construct GBM-specific miRNA- mediated regulatory networks consisting of GBM miRNAs, GBM genes, and TFs. (3) To develop a novel dense module search (DMS) algorithm for identifying functionally important miRNAs in GBM. In this DMS algorithm, a module is defined as a set of FFLs, each of which includes miRNA, gene(s), and TF, and their regulatory relationships. This project constitutes a pioneering effort to establish an integrative and comprehensive modeling framework, as well as practical computational methods for detecting functionally important miRNAs in complex diseases and demonstrates it in GBM. Successful completion of this project will greatly enhance our understanding of the regulatory systems in GBM, which will likely lead to the development of effective prevention, diagnosis, and treatment strategies.
Publications
The Potential Roles Of Long Noncoding Rnas (lncrna) In Glioblastoma Development
Authors: Liu S.
, Mitra R.
, Zhao M.M.
, Fan W.
, Eischen C.M.
, Yin F.
, Zhao Z.
.
Source: Molecular Cancer Therapeutics, 2016 Dec; 15(12), p. 2977-2986.
PMID: 27784795
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Microrna-31 Initiates Lung Tumorigenesis And Promotes Mutant Kras-driven Lung Cancer
Authors: Edmonds M.D.
, Boyd K.L.
, Moyo T.
, Mitra R.
, Duszynski R.
, Arrate M.P.
, Chen X.
, Zhao Z.
, Blackwell T.S.
, Andl T.
, et al.
.
Source: The Journal Of Clinical Investigation, 2016 Jan; 126(1), p. 349-64.
PMID: 26657862
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A Cross-cancer Differential Co-expression Network Reveals Microrna-regulated Oncogenic Functional Modules
Authors: Lin C.C.
, Mitra R.
, Cheng F.
, Zhao Z.
.
Source: Molecular Biosystems, 2015 Dec; 11(12), p. 3244-52.
PMID: 26448606
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Microrna Regulation In Cancer: One Arm Or Two Arms?
Authors: Mitra R.
, Sun J.
, Zhao Z.
.
Source: International Journal Of Cancer, 2015-09-15 00:00:00.0; 137(6), p. 1516-8.
PMID: 25758934
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Concordant Dysregulation Of Mir-5p And Mir-3p Arms Of The Same Precursor Microrna May Be A Mechanism In Inducing Cell Proliferation And Tumorigenesis: A Lung Cancer Study
Authors: Mitra R.
, Lin C.C.
, Eischen C.M.
, Bandyopadhyay S.
, Zhao Z.
.
Source: Rna (new York, N.y.), 2015 Jun; 21(6), p. 1055-65.
PMID: 25852169
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Clinically Relevant Genes And Regulatory Pathways Associated With Nrasq61 Mutations In Melanoma Through An Integrative Genomics Approach
Authors: Jiang W.
, Jia P.
, Hutchinson K.E.
, Johnson D.B.
, Sosman J.A.
, Zhao Z.
.
Source: Oncotarget, 2015-02-10 00:00:00.0; 6(4), p. 2496-508.
PMID: 25537510
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Snowball: Resampling Combined With Distance-based Regression To Discover Transcriptional Consequences Of A Driver Mutation
Authors: Xu Y.
, Guo X.
, Sun J.
, Zhao Z.
.
Source: Bioinformatics (oxford, England), 2015-01-01 00:00:00.0; 31(1), p. 84-93.
PMID: 25192743
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Mbstar: Multiple Instance Learning For Predicting Specific Functional Binding Sites In Microrna Targets
Authors: Bandyopadhyay S.
, Ghosh D.
, Mitra R.
, Zhao Z.
.
Source: Scientific Reports, 2015; 5, p. 8004.
PMID: 25614300
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Regulation Rewiring Analysis Reveals Mutual Regulation Between Stat1 And Mir-155-5p In Tumor Immunosurveillance In Seven Major Cancers
Authors: Lin C.C.
, Jiang W.
, Mitra R.
, Cheng F.
, Yu H.
, Zhao Z.
.
Source: Scientific Reports, 2015; 5, p. 12063.
PMID: 26156524
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Algorithms For Network-based Identification Of Differential Regulators From Transcriptome Data: A Systematic Evaluation
Authors: Yu H.
, Mitra R.
, Yang J.
, Li Y.
, Zhao Z.
.
Source: Science China. Life Sciences, 2014 Nov; 57(11), p. 1090-102.
PMID: 25326829
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Reproducible Combinatorial Regulatory Networks Elucidate Novel Oncogenic Micrornas In Non-small Cell Lung Cancer
Authors: Mitra R.
, Edmonds M.D.
, Sun J.
, Zhao M.
, Yu H.
, Eischen C.M.
, Zhao Z.
.
Source: Rna (new York, N.y.), 2014 Sep; 20(9), p. 1356-68.
PMID: 25024357
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Studying Tumorigenesis Through Network Evolution And Somatic Mutational Perturbations In The Cancer Interactome
Authors: Cheng F.
, Jia P.
, Wang Q.
, Lin C.C.
, Li W.H.
, Zhao Z.
.
Source: Molecular Biology And Evolution, 2014 Aug; 31(8), p. 2156-69.
PMID: 24881052
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A Meta-analysis Of Somatic Mutations From Next Generation Sequencing Of 241 Melanomas: A Road Map For The Study Of Genes With Potential Clinical Relevance
Authors: Xia J.
, Jia P.
, Hutchinson K.E.
, Dahlman K.B.
, Johnson D.
, Sosman J.
, Pao W.
, Zhao Z.
.
Source: Molecular Cancer Therapeutics, 2014 Jul; 13(7), p. 1918-28.
PMID: 24755198
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Quantitative Network Mapping Of The Human Kinome Interactome Reveals New Clues For Rational Kinase Inhibitor Discovery And Individualized Cancer Therapy
Authors: Cheng F.
, Jia P.
, Wang Q.
, Zhao Z.
.
Source: Oncotarget, 2014-06-15 00:00:00.0; 5(11), p. 3697-710.
PMID: 25003367
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Network.assisted Analysis To Prioritize Gwas Results: Principles, Methods And Perspectives
Authors: Jia P.
, Zhao Z.
.
Source: Human Genetics, 2014 Feb; 133(2), p. 125-38.
PMID: 24122152
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Varwalker: Personalized Mutation Network Analysis Of Putative Cancer Genes From Next-generation Sequencing Data
Authors: Jia P.
, Zhao Z.
.
Source: Plos Computational Biology, 2014 Feb; 10(2), p. e1003460.
PMID: 24516372
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A Tri-component Conservation Strategy Reveals Highly Confident Microrna-mrna Interactions And Evolution Of Microrna Regulatory Networks
Authors: Lin C.C.
, Mitra R.
, Zhao Z.
.
Source: Plos One, 2014; 9(7), p. e103142.
PMID: 25054916
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Synergetic Regulatory Networks Mediated By Oncogene-driven Micrornas And Transcription Factors In Serous Ovarian Cancer
Authors: Zhao M.
, Sun J.
, Zhao Z.
.
Source: Molecular Biosystems, 2013 Dec; 9(12), p. 3187-98.
PMID: 24129674
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Cnvannotator: A Comprehensive Annotation Server For Copy Number Variation In The Human Genome
Authors: Zhao M.
, Zhao Z.
.
Source: Plos One, 2013; 8(11), p. e80170.
PMID: 24244640
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Dcgl V2.0: An R Package For Unveiling Differential Regulation From Differential Co-expression
Authors: Yang J.
, Yu H.
, Liu B.H.
, Zhao Z.
, Liu L.
, Ma L.X.
, Li Y.X.
, Li Y.Y.
.
Source: Plos One, 2013; 8(11), p. e79729.
PMID: 24278165
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Dynamic Protein Interaction Modules In Human Hepatocellular Carcinoma Progression
Authors: Yu H.
, Lin C.C.
, Li Y.Y.
, Zhao Z.
.
Source: Bmc Systems Biology, 2013; 7 Suppl 5, p. S2.
PMID: 24564909
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