Noncoding RNAs (ncRNAs) constitute the majority of the human transcribed genome. This largest class of RNA transcripts plays diverse roles in a multitude of cellular processes, and has been implicated in many pathological conditions, especially cancer. The different subclasses of ncRNAs include microRNAs, a class of short ncRNAs; and a variety of long ncRNAs (lncRNAs), such as lincRNAs, antisense RNAs, pseudogenes, and circular RNAs. Many studies have demonstrated the involvement of these ncRNAs in competitive regulatory interactions, known as competing endogenous RNA (ceRNA) networks, whereby lncRNAs can act as microRNA decoys to modulate gene expression. These interactions are often interconnected, thus aberrant expression of any network component could derail the complex regulatory circuitry, culminating in cancer development and progression. Recent integrative analyses have provided evidence that new computational platforms and experimental approaches can be harnessed together to distinguish key ceRNA interactions in specific cancers, which could facilitate the identification of robust biomarkers and therapeutic targets, and hence, more effective cancer therapies and better patient outcome and survival.

We present a high content multiwell plate cell-based assay approach to quantify protein interactions directly in cells using Förster resonance energy transfer (FRET) read out by automated fluorescence lifetime imaging (FLIM). Automated FLIM is implemented using wide-field time-gated detection, typically requiring only 10 s per field of view (FOV). Averaging over biological, thermal and shot noise with 100’s to 1000’s of FOV enables unbiased quantitative analysis with high statistical power. Plotting average donor lifetime vs. acceptor/donor intensity ratio clearly identifies protein interactions and fitting to double exponential donor decay models provides estimates of interacting population fractions that, with calibrated donor and acceptor fluorescence intensities, can yield dissociation constants. We demonstrate the application to identify binding partners of MST1 kinase and estimate interaction strength among the members of the RASSF protein family, which have important roles in apoptosis via the Hippo signalling pathway. KD values broadly agree with published biochemical measurements.

Non-coding RNAs play a vital role in diverse cellular processes. Pseudogenes, which are non-coding homologs of protein-coding genes, were once considered non-functional evolutional relics. However, recent studies have shown that pseudogene transcripts can regulate their parental transcripts by sequestering shared microRNAs (miRNAs), thus acting as competing endogenous RNAs (ceRNAs). In this study, we utilize an unbiased screen to identify the ferritin heavy chain 1 (FTH1) transcript and multiple FTH1 pseudogenes as targets of several oncogenic miRNAs in prostate cancer (PCa). We characterize the critical role of this FTH1 gene:pseudogene:miRNA network in regulating tumorigenesis in PCa, whereby oncogenic miRNAs downregulate the expression of FTH1 and its pseudogenes to drive oncogenesis. We further show that impairing miRNA binding and subsequent ceRNA crosstalk completely rescues the slow growth phenotype in vitro and in vivo. Our results also demonstrate the reciprocal regulation between the pseudogenes and intracellular iron levels, which are crucial for multiple physiological and pathophysiological processes. In summary, we describe an extensive gene:pseudogene network comprising multiple miRNAs and multiple pseudogenes derived from a single parental gene. The network could be regulated through multiple mechanisms to modulate iron storage in various signaling pathways, the deregulation of which results in PCa development and progression.