High-throughput tools to track the fate of prematurely terminated transcripts in cancer cells

About This Grant

Post-transcriptional gene regulation plays a critical but understudied role in cancer development. The genetic basis of cancer has been extensively characterized; yet, alterations in RNA processing mechanisms, such as alternative polyadenylation (APA) events, can also drive oncogenesis independent of DNA mutations. In chronic lymphocytic leukemia, APA inactivates tumor suppressor genes by generating intronically terminated transcripts that produce truncated proteins lacking tumor-suppressive domains. Similar APA-driven oncogenic mechanisms have been observed in glioblastoma and lung adenocarcinoma. APA events in 3’ UTRs are prevalent in many cancer types, leading to changes in stability, localization, and translation of these transcripts, with widespread ramifications including increased cell proliferation, angiogenesis, and metastasis. Despite the recognition that APA events play a significant role in cancer, technological limitations have hampered our ability to track the dynamic fate and functional impact of alternatively processed transcripts across the cell in different cancer types. Current methods that identify APA events cannot simultaneously monitor the nuclear export, translation efficiency, or degradation patterns of APA transcripts to understand their movement and fate in the cell. A better understanding of the dynamics of APA transcripts, and how they differ in cancer cells versus healthy cells, will help us to define critical regulatory nodes for these transcripts, and uncover cellular processes that promote the usage of oncogenic APA transcripts across different cancer types. To quantify RNA flow rates across subcellular compartments, from synthesis to export, translation, and degradation, we developed subcellular TimeLapse-seq (TL-seq). While this technology establishes a foundation for investigating RNA dynamics, it has not yet been engineered to track the fate of transcripts that are alternatively polyadenylated (APA transcripts). Here, we propose to integrate subcellular TL-seq with 3'-end sequencing to create powerful new tools for comprehensively studying the flow and fate of alternatively polyadenylated transcripts in cancer cells. Aim 1: To map the fate of APA transcripts, we will develop 3prime-TLseq, a novel method that combines subcellular TimeLapse-seq with 3'-end sequencing to quantify APA transcript dynamics. To demonstrate the utility of our approach, we will apply the developed protocol to investigate how JTE-607 – a small molecule that interferes with cleavage and polyadenylation machinery and shows promising activity against various cancer types– affects the dynamics of APA transcripts. Aim 2: To determine whether and how well APA transcripts are translated, we will develop 3primeTL-polysome profiling, which combines TimeLapse-seq and 3'-end sequencing with polysome profiling to quantitatively measure both the rate of RNA loading onto polysomes and the half-life of associated RNAs. By overcoming the limitations of current methods, which can identify global APA events but cannot track their dynamic flow and fate through subcellular compartments, we will enable researchers to study previously inaccessible aspects of RNA regulation in cancer, and potentially identify novel therapeutic vulnerabilities.