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Grant Details

Grant Number: 5R21CA182659-02 Interpret this number
Primary Investigator: Andrew, Angeline
Organization: Dartmouth College
Project Title: Microrna Dysregulation and Bladder Cancer Prognosis
Fiscal Year: 2015


DESCRIPTION (provided by applicant): MicroRNA dysregulation and bladder cancer prognosis. Bladder cancer is the fourth most common malignancy in U.S. men. More than half of non-muscle invasive urothelial cell carcinoma patients experience recurrent disease. Among the most clinically challenging cases are those with histologies that denote poor differentiation or carcinoma in situ features (high grade Ta, T1, or Tis). Some of these patients have frequently recurring tumors that are refractory to treatment, but it is difficult to predict which patients hae this phenotype. The objective of this proposal is to identify prognostic markers of this rapidly recurrent phenotype in the primary tumor tissue. MicroRNAs (miRNAs) are stable, non-protein coding RNA molecules that are frequently dysregulated during tumorigenesis. No previous miRNA studies in urothelial carcinoma have focused on comprehensively identifying prognostic miRNAs within the clinically challenging, non-muscle invasive tumor types. We have assembled a unique population-based tissue bank of bladder tumors with extensive, long-term recurrence, progression, and survival data from a large epidemiologic cohort encompassing n=1062 non-muscle invasive urothelial cell carcinoma patients. We first plan to identify the miRNAs associated with rapid recurrence by comprehensively assessing primary tumor tissue specimens for miRNA expression levels using small RNA sequence count analysis (RNA-Seq). We will integrate our results with information from the literature to prioritize the prognostic miRNAs. We will technically confirm the priority miRNA expression levels by reverse-transcription and quantitative real-time PCR (qRT-PCR), and will evaluate the miRNA distribution in urothelial carcinoma cells versus other cell-types using in situ hybridization. Finally, we will evaluate the prognostic value of the prioritized miRNA in relation to recurrence, progression and survival using our large population-based case cohort. Successful identification of a prognostic dysregulated miRNA will help tailor management of clinically challenging bladder cancer cases by enabling early detection of rapidly recurrent and refractory phenotypes. The dysregulated miRNAs that we identify are also potentially viable therapeutic targets and could lead to the future development of novel anti-miR or miRNA-replacement therapies for this malignancy.


Identification of Let-7f-5p as a novel biomarker of recurrence in non-muscle invasive bladder cancer.
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PMID: 32623385
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MicroRNA Dysregulation and Non-Muscle-Invasive Bladder Cancer Prognosis.
Authors: Andrew A.S. , Karagas M.R. , Schroeck F.R. , Marsit C.J. , Schned A.R. , Pettus J.R. , Armstrong D.A. , Seigne J.D. .
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EPub date: 2019-01-30.
PMID: 30700445
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Hyper-Methylated Loci Persisting from Sessile Serrated Polyps to Serrated Cancers.
Authors: Andrew A.S. , Baron J.A. , Butterly L.F. , Suriawinata A.A. , Tsongalis G.J. , Robinson C.M. , Amos C.I. .
Source: International journal of molecular sciences, 2017-03-02; 18(3), .
EPub date: 2017-03-02.
PMID: 28257124
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Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies.
Authors: Cheng S. , Andrew A.S. , Andrews P.C. , Moore J.H. .
Source: BioData mining, 2016; 9, p. 40.
EPub date: 2016-12-12.
PMID: 27999618
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Detecting gene-gene interactions using a permutation-based random forest method.
Authors: Li J. , Malley J.D. , Andrew A.S. , Karagas M.R. , Moore J.H. .
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EPub date: 2016-04-06.
PMID: 27053949
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Expression of tumor suppressive microRNA-34a is associated with a reduced risk of bladder cancer recurrence.
Authors: Andrew A.S. , Marsit C.J. , Schned A.R. , Seigne J.D. , Kelsey K.T. , Moore J.H. , Perreard L. , Karagas M.R. , Sempere L.F. .
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EPub date: 2015-02-25.
PMID: 25556547
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Genetic polymorphisms modify bladder cancer recurrence and survival in a USA population-based prognostic study.
Authors: Andrew A.S. , Gui J. , Hu T. , Wyszynski A. , Marsit C.J. , Kelsey K.T. , Schned A.R. , Tanyos S.A. , Pendleton E.M. , Ekstrom R.M. , et al. .
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PMID: 24666523
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Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks.
Authors: Hu T. , Andrew A.S. , Karagas M.R. , Moore J.H. .
Source: BioData mining, 2015; 8, p. 43.
EPub date: 2015-12-21.
PMID: 26697115
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A screening-testing approach for detecting gene-environment interactions using sequential penalized and unpenalized multiple logistic regression.
Authors: Frost H.R. , Andrew A.S. , Karagas M.R. , Moore J.H. .
Source: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2015; , p. 183-94.
PMID: 25592580
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Clinicopathological correlates of Gli1 expression in a population-based cohort of patients with newly diagnosed bladder cancer.
Authors: Sverrisson E.F. , Zens M.S. , Fei D.L. , Andrews A. , Schned A. , Robbins D. , Kelsey K.T. , Li H. , DiRenzo J. , Karagas M.R. , et al. .
Source: Urologic oncology, 2014 Jul; 32(5), p. 539-45.
EPub date: 2014-05-22.
PMID: 24856810
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Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility.
Authors: Hu T. , Pan Q. , Andrew A.S. , Langer J.M. , Cole M.D. , Tomlinson C.R. , Karagas M.R. , Moore J.H. .
Source: BioData mining, 2014-04-11; 7(1), p. 5.
EPub date: 2014-04-11.
PMID: 24725556
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A system-level pathway-phenotype association analysis using synthetic feature random forest.
Authors: Pan Q. , Hu T. , Malley J.D. , Andrew A.S. , Karagas M.R. , Moore J.H. .
Source: Genetic epidemiology, 2014 Apr; 38(3), p. 209-19.
EPub date: 2014-02-17.
PMID: 24535726
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Body mass and smoking are modifiable risk factors for recurrent bladder cancer.
Authors: Wyszynski A. , Tanyos S.A. , Rees J.R. , Marsit C.J. , Kelsey K.T. , Schned A.R. , Pendleton E.M. , Celaya M.O. , Zens M.S. , Karagas M.R. , et al. .
Source: Cancer, 2014-02-01; 120(3), p. 408-14.
EPub date: 2013-10-10.
PMID: 24122218
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