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Grant Details

Grant Number: 5R21CA175553-02 Interpret this number
Primary Investigator: Christensen, Brock
Organization: Dartmouth College
Project Title: Microrna Related Genetic Variation in Bladder Cancer Recurrence and Survival
Fiscal Year: 2014


DESCRIPTION (provided by applicant): MicroRNA related genetic variation and bladder cancer recurrence and survival Over 500,000 individuals in the U.S. are living with a diagnosis of bladder cancer, a disease where over half of cases will recur. With a high likelihood of recurrence, the clinical management of bladder cancer includes routine screening of patients with invasive cystoscopy, resulting in significant patient morbidity. Further, in part because invasive cystoscopy is repeated over the course of disease, bladder cancer is the most expensive cancer to treat per capita, accounting for nearly 3.7 billion U.S. dollars (2001 dollars) in annual expenditures. Currently there is a lack of clinically used determinants that can inform on the risk of recurrence and survival. Here, we propose to systematically investigate a novel class of genetic variation - microRNA-related genetic variation (miR-SNPs) - for new determinants of bladder cancer recurrence and survival. MiR-SNPs include variation in miRNA target sites on mRNA transcripts, SNPs in miRNA genes, and SNPs in genes that participate in miRNA biogenesis and processing. While GWAS approaches have had some success, miR- SNPs have not been well represented on GWAS panels, and there is a very limited understanding of miRNA- related natural genetic variation. Almost exclusively non-coding, miR-SNPs clearly have critical regulatory capacity and the rapidly emerging literature has begun to demonstrate associations between candidate miR- SNPs and both risk and prognosis of human cancers, though there is a gap in the study of bladder cancers. Recent and continued advances in miRNA target site prediction allows a more comprehensive cataloging and characterization of miR-SNPs that can be used for hypothesis testing in population studies. The primary aim of this work is to use proven epidemiologic resources to identify miR-SNPs associated with recurrence and survival of bladder cancer. Our group has completed a geographically defined, population-based epidemiologic study of bladder cancer that includes a comprehensive assessment of patient recurrences and survival. To our knowledge this is the only study of its kind in the U.S., and one of the few worldwide from which inferences of the general population can be made regarding the determinant of bladder cancer prognosis. Our approach will extend well beyond candidate miR-SNP approaches by genotyping over 18,000 miR-SNPs. We propose to identify a new class of genetic markers of bladder cancer recurrence and survival that will contribute to the development of clinical decision-making tools to stratify patients into follow-up groups based on their likelihood of recurrence. In this way we aim to maximize the impact and translational potential of our identified markers, reduce patient morbidity and mortality, and decrease the cost burden of routine cystoscopy by shifting the current paradigm of bladder cancer management.


Topological Feature Extraction and Visualization of Whole Slide Images using Graph Neural Networks.
Authors: Levy J. , Haudenschild C. , Barwick C. , Christensen B. , Vaickus L. .
Source: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2021; 26, p. 285-296.
PMID: 33691025
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