Defense: Creating Transcriptomic Signatures for Interpretation of Cancer Variants and Characterization of Immune Cells

Alexis Thornton
Biomolecular Engineering & Bioinformatics PhD Candidate
Virtual Event
Angela Brooks

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Description: A molecular signature is a distinct molecular pattern that is specific to a particular phenotype. While gene expression and alternative splicing are both key regulatory mechanisms, only gene expression signatures are commonly used to investigate cell biology. In my thesis, I use gene expression signatures for variant interpretation and then present methods for integrated creation and use of gene expression and splicing signatures. 

In the first chapter, I present the expression-based Variant Impact Phenotyping (eVIP2) approach. Many cancer-associated mutations remain uninvestigated because experimental validation of their effect on gene function is costly, time-consuming, and requires prior knowledge of a gene's function. Here, I present eVIP2, which uses gene expression data to characterize a gene variant's function, requiring no prior knowledge of the wild-type gene's function. With eVIP2, we can predict if a mutation causes a gain, loss, or change in function, or if it is neutral. We determined that two recurrent frameshift mutations in RNF43 have different effects on gene function, where one mutation causes multiple cancer pathways to be activated. 

Next, I present sigil, a tool for the parallel creation of representative gene expression and splicing signatures. Microarray-based immunological gene expression signatures are widely used for gene set enrichment analysis and to better understand human diseases. However, despite evidence of splicing differences across cell lineages, there is no equivalent resource for alternative splicing. Here, we use sigil to create RNA-seq-based gene expression and splicing signatures that are compatible with enrichment analysis. We identify prevalent alternative promoter usage and enrichment for cell-type specific junctions associated with differential inclusion of protein modifications. Together, my thesis work demonstrates the utility of signature-based approaches.