American Association for Cancer Research
00085472can191094-sup-220188_2_supp_5725865_pwl3m3.pdf (69.1 kB)

Table S1 from Quantification and Localization of Protein–RNA Interactions in Patient-Derived Archival Tumor Tissue

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journal contribution
posted on 2023-03-31, 02:42 authored by Emmeline L. Blanchard, Danae Argyropoulou, Chiara Zurla, Sushma M. Bhosle, Daryll Vanover, Philip J. Santangelo

PNA Oligonucleotide Sequences



National Science Foundation

National Science Foundation Graduate Research



Abnormal post-transcriptional regulation induced by alterations of mRNA–protein interactions is critical during tumorigenesis and cancer progression and is a hallmark of cancer cells. A more thorough understanding is needed to develop treatments and foresee outcomes. Cellular and mouse tumor models are insufficient for vigorous investigation as they lack consistency and translatability to humans. Moreover, to date, studies in human tumor tissue are predominately limited to expression analysis of proteins and mRNA, which do not necessarily provide information about the frequency of mRNA–protein interactions. Here, we demonstrate novel optimization of a method that is based on FISH and proximity ligation techniques to quantify mRNA interactions with RNA-binding proteins relevant for tumorigenesis and cancer progression in archival patient-derived tumor tissue. This method was validated for multiple mRNA-protein pairs in several cellular models and in multiple types of archival human tumor samples. Furthermore, this approach allowed high-throughput analysis of mRNA–protein interactions across a wide range of tumor types and stages through tumor microarrays. This method is quantitative, specific, and sensitive for detecting interactions and their localization at both the individual cell and whole-tissue scales with single interaction sensitivity. This work presents an important tool in investigating post-transcriptional regulation in cancer on a high-throughput scale, with great potential for translatability into any applications where mRNA–protein interactions are of interest. This work presents an approach to sensitively, specifically, and quantitatively detect and localize native mRNA and protein interactions for analysis of abnormal post-transcriptional regulation in patient-derived archival tumor samples.

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