RNA-protein interactions are integral to the regulation of gene expression. RNAs have diverse functions and the protein interactomes of individual RNAs vary temporally, spatially, and with physiological context. These factors make the global acquisition of individual RNA-protein interactomes an essential endeavor. Although techniques have been reported for discovery of the protein interactomes of specific RNAs they are largely laborious, costly, and accomplished singly in individual experiments. We developed HyPR-MS for the discovery and analysis of the protein interactomes of multiple RNAs in a single experiment while also reducing design time and improving efficiencies. Presented here is the application of HyPR-MS to simultaneously and selectively isolate the interactomes of lncRNAs MALAT1, NEAT1, and NORAD. Our analysis features the proteins that potentially contribute to both known and previously undiscovered roles of each lncRNA. This platform provides a powerful new multiplexing tool for the efficient and cost-effective elucidation of specific RNA-protein interactomes.
Proteins bind mRNA through their entire life cycle from transcription to degradation. We analyzed c-Myc mRNA protein interactors in vivo using the HyPR-MS method to capture the crosslinked mRNA by hybridization and then analyzed the bound proteins using mass spectrometry proteomics. Using HyPR-MS, 229 c-Myc mRNA-binding proteins were identified, confirming previously proposed interactors, suggesting new interactors, and providing information related to the roles and pathways known to involve c-Myc. We performed structural and functional analysis of these proteins and validated our findings with a combination of RIP-qPCR experiments, in vitro results released in past studies, publicly available RIP-and eCLIP-seq data, and results from software tools for predicting RNA-protein interactions.
INTRODUCTION: The molecular mechanisms underlying aggressive versus indolent disease are not fully understood. Recent research has implicated a class of molecules known as long noncoding RNAs (lncRNAs) in tumorigenesis and progression of cancer. Our objective was to discover lncRNAs that differentiate aggressive and indolent prostate cancers. METHODS: We analyzed paired tumor and normal tissues from six aggressive Gleason score (GS) 8-10 and six indolent GS 6 prostate cancers. Extracted RNA was split for poly(A)+ and ribosomal RNA depletion library preparations, followed byRNA sequencing (RNA-Seq) using an Illumina HiSeq 2000. We developed an RNA-Seq data analysis pipeline to discover and quantify these molecules. Candidate lncRNAs were validated using RT-qPCR on 87 tumor tissue samples: 28 (GS 6), 28 (GS 3+4), 6 (GS 4+3), and 25 (GS 8-10). Statistical correlations between lncRNAs and clinicopathologic variables were tested using ANOVA. RESULTS: The 43 differentially expressed (DE) lncRNAs between aggressive and indolent prostate cancers included 12 annotated and 31 novel lncRNAs. The top six DE lncRNAs were selected based on large, consistent fold-changes in the RNA-Seq results. Three of these candidates passed RT-qPCR validation, including AC009014.3 (P < .001 in tumor tissue) and a newly discovered X-linked lncRNA named XPLAID (P = .049 in tumor tissue and P = .048 in normal tissue). XPLAID and AC009014.3 show promise as prognostic biomarkers. CONCLUSIONS: We discovered several dozen lncRNAs that distinguish aggressive and indolent prostate cancers, of which four were validated using RT-qPCR. The investigation into their biology is ongoing.
Prostate cancer (PC) patients and providers have tremendous uncertainty as they decide on intervention with adjuvant or salvage radiation therapy (ART, SRT) after radical prostatectomy (RP). We prospectively evaluated the impact of Decipher test, a genomic classifier which predicts metastasis post-RP, on providers' decision-making for ART and SRT.METHODS: 150 men considering ART and 115 men considering SRT from 19 sites across the US were enrolled. Participating providers submitted a management recommendation prior to processing the Decipher test and again after receiving test results. We then followed patients for 12 months to assess actual treatment received and patient reported decisional conflict scale (DCS) and a validated survey on PC-related anxiety.RESULTS: Pre-Decipher, observation was recommended for 89% of adjuvant men and 58% of salvage men. Post-Decipher, 17% of treatment recommendations changed in the adjuvant arm and 30% of recommendations changed in the salvage arm. Among adjuvant men, 78% maintained their recommended management 12 months after Decipher; 76% of salvage men maintained their recommended treatment after Decipher. Among 21 adjuvant men who intensified their treatment (observation to ART or ART to ART plus androgen deprivation therapy), 5 (24%) experienced biochemical recurrence with detectable PSA. In adjuvant men, PC-specific anxiety decreased differently among Decipher risk categories (p-value ¼ 0.045), most notably among Decipher high risk men ( 9. 07 [7.87, 5.61 [5.35,5.88] 12 months post-Decipher). In salvage men, PC-specific anxiety decreased differently among those whose treatment were concordant (10.28 [8.1, 7.18 [6.82,7.54] 12 months post-Decipher) and those whose treatment were intensified (p-val-ue¼0.01), and decreased differently among low-risk and high-risk Decipher patients (p¼0.04).CONCLUSIONS: Use of the Decipher test changed treatment decisions that was consistent with the eventual treatment received in three-fourths of adjuvant and salvage men after RP. Several men that pursued ART experienced PSA progression. PC-specific anxiety decreased in both adjuvant and salvage men.
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