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Resolving the complexity of the cancer transcriptome through 3’ UTRs
Date
2017-06-30
Author
Erson Bensan, Ayşe Elif
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Advancements in sequencing and transcriptome analysis methods contributed to a better understanding of the complexity of cancer. These findings are paving the way toward the development of improved diagnostics, prognostic predictions, and targeted treatment options. In an effort to have a more comprehensive understanding of cancer, we focus on the 3’ UTRs (untranslated regions) of genes as we came to appreciate the value of the noncoding regions of our genomes, partly due to microRNAs. The 3’UTRs have long been known to have important roles in maintaining the stability, localization, and half-life of mRNAs but a detailed mechanistic explanation as to how these properties are regulated or the consequences of deregulation are just beginning to be appreciated. Our group is interested in the regulation and consequences of 3’UTR length changes in mRNA isoforms in breast cancers. 3’UTR length is controlled mainly by the position of the polyadenylation (poly(A)) signal. Interestingly, majority of human genes harbor multiple poly(A) signals on their 3’ UTRs that can be differentially selected on the basis of the physiologic state of cells, resulting in alternative mRNA isoforms. Hence, deregulation of alternative polyadenylation (APA) has increasing interest in cancer research, because APA generates mRNA isoforms with potentially different protein functions. In this talk, our groups efforts to identify and characterize novel cancer related genes will be discussed based on our combinatorial approach to reveal APA events. Overall, detection of deregulated APA-generated isoforms in cancer may implicate some proto-oncogene activation cases of unknown causes and may help the discovery of novel cases; thus, contributing to a better understanding of molecular mechanisms of cancer.
URI
https://hdl.handle.net/11511/86518
Conference Name
HIBIT 2017
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Department of Biology, Conference / Seminar
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A. E. Erson Bensan, “Resolving the complexity of the cancer transcriptome through 3’ UTRs,” presented at the HIBIT 2017, 2017, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/86518.