Project Summary/Abstract
Alternative polyadenylation (APA) is a major mechanism of posttranscriptional regulation that generates
distinct 3′ untranslated regions (3′UTR) on RNA transcripts from most human genes. Mechanistically, APA is
mainly regulated in trans through APA regulators and in cis by single-nucleotide variants (SNVs) enriched in
3′UTRs and downstream gene regions. Several reported examples indicate that APA can regulate the activity
of oncogenes and tumor suppressor genes. However, the upstream regulatory mechanism and downstream
function of APA in the cancer progression within clinical cohorts, particularly in prostate cancer, remains largely
uncharacterized. Prostate cancer presentation is frequently stratified into groups: highly treatable androgen-
dependent prostate cancer (ADPC), followed by the lethal castration-resistant prostate adenocarcinoma
(CRPC), and ultimately progressing to the most aggressive form, neuroendocrine prostate cancer (NEPC).
While significant efforts have been made to characterize gene expression changes during prostate cancer
progression, a link between APA and prostate cancer progression has not previously been established. Our
preliminary studies found that 3′UTR lengths are significantly shortened in CRPC patients compared with
ADPC patients and are significantly lengthened in NEPC patients compared with CRPC patients. We further
found that APA factor-regulated genes with altered 3′UTRs can function as novel oncogenes for CRPC or
NEPC. Importantly, manipulating 3′UTR lengths of selected novel oncogenes by our developed 3′UTR
CRISPR-dCas13 Engineering System (3′UTRCES) generates distinct molecular outcomes, leading to
decreased prostate cancer growth in vitro and in vivo. We thus hypothesize that APA drives prostate cancer
progression and can potentially be reversed in a clinically meaningful manner. In Aim 1, we will identify APA
target genes during prostate cancer progression to castration resistance through multi-omics analyses in
prostate clinical samples and cell models. In Aim 2, we will develop a computational model, namely
MARS3'aQTL, to infer upstream APA regulators. In Aim 3, we will characterize the molecular regulations,
biological functions, and clinical relevance of inferred APA regulators and will use 3′UTRCES to precisely
interfere with APA of novel oncogenes. Our proposed studies' successful completion will establish APA as an
important targetable posttranscriptional regulatory mechanism, contributing to a more complete understanding
of prostate cancer progression.