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Activity Number:
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535
- Contributed Poster Presentations: Section on Statistics in Genomics and Genetics
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2018 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Genomics and Genetics
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Abstract #330937
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Title:
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Integration of Simultaneous Group Effects in MiRNA and Targeted Gene Sets in Ovarian Cancer
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Author(s):
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Wenjun He* and Ravikumar Muthuswamy and Daniel Gaile and Kevin Eng
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Companies:
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Dept. Biostatistics, Univ. at Buffalo and Center for Immunotherapy, Roswell Park Comprehensive Cancer Center and Dept. of Biostatistics, University at Buffalo and Roswell Park Comprehensive Cancer Center
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Keywords:
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Ovarian Cancer;
microRNA;
mRNA;
targeted gene sets;
integration
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Abstract:
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Ovarian cancer is the most lethal of malignant gynecological tumors. Its lethality is partially due to the poor diagnosis at the early stage. There is a strong need for reliable prognostic and predictive markers for early diagnosis to help effective personalized treatment. MicroRNAs (miRNA) are noncoding RNAs that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Both changes in miRNA expression and miRNA/mRNA dysregulation are associated with ovarian cancer. In this study, using ovarian cancer patient matched miRNA/mRNA expression data from The Cancer Genome Atlas (TCGA), we developed an approch composed of correlation methods, regression methods, and causal inference methods to identify direct mRNA targets of miRNA. The simultaneous group effects are determined individually for each miRNA, and by enrichment tests and global test for target gene sets. Novel miR/mRNA pairwise-dependent interplay and associated pathways were identified. The results were validated by the thirdparty data and simulated data.
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Authors who are presenting talks have a * after their name.
