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Bester, Assaf

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Bester, Assaf

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Author's Publications: search.filters.isAuthorOfPublication.174e25fa-a68c-4a20-9e42-3b48ac78e7ff

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    Identification of competing endogenous RNAs of the tumor suppressor gene PTEN: A probabilistic approach
    (Nature Publishing Group UK, 2017) Zarringhalam, Kourosh; Tay, Yvonne; Kulkarni, Prajna; Bester, Assaf; Pandolfi, Pier Paolo; Kulkarni, Rahul V.
    Regulation by microRNAs (miRNAs) and modulation of miRNA activity are critical components of diverse cellular processes. Recent research has shown that miRNA-based regulation of the tumor suppressor gene PTEN can be modulated by the expression of other miRNA targets acting as competing endogenous RNAs (ceRNAs). However, the key sequence-based features enabling a transcript to act as an effective ceRNA are not well understood and a quantitative model associating statistical significance to such features is currently lacking. To identify and assess features characterizing target recognition by PTEN-regulating miRNAs, we analyze multiple datasets from PAR-CLIP experiments in conjunction with RNA-Seq data. We consider a set of miRNAs known to regulate PTEN and identify high-confidence binding sites for these miRNAs on the 3′ UTR of protein coding genes. Based on the number and spatial distribution of these binding sites, we calculate a set of probabilistic features that are used to make predictions for novel ceRNAs of PTEN. Using a series of experiments in human prostate cancer cell lines, we validate the highest ranking prediction (TNRC6B) as a ceRNA of PTEN. The approach developed can be applied to map ceRNA networks of critical cellular regulators and to develop novel insights into crosstalk between different pathways involved in cancer.