International Journal of Molecular Sciences Article Long Non-Coding RNA Landscape in Prostate Cancer Molecular Subtypes: A Feature Selection Approach Simona De Summa 1,* , Antonio Palazzo 2 , Mariapia Caputo 1, Rosa Maria Iacobazzi 3 , Brunella Pilato 1, Letizia Porcelli 3, Stefania Tommasi 1 , Angelo Virgilio Paradiso 4,† and Amalia Azzariti 3,† 1 Molecular Diagnostics and Pharmacogenetics Unit, IRCCS IstitutoTumori Giovanni Paolo II, 70124 Bari, Italy;
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[email protected] (S.T.) 2 Laboratory of Nanotechnology, IRCCS IstitutoTumori Giovanni Paolo II, 70124 Bari, Italy;
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[email protected] (A.A.) 4 Scientific Directorate, IRCCS Istituto Tumori Giovanni Paolo II, 70124 Bari, Italy;
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[email protected] † Co-senior authors. Abstract: Prostate cancer is one of the most common malignancies in men. It is characterized by a high molecular genomic heterogeneity and, thus, molecular subtypes, that, to date, have not been used in clinical practice. In the present paper, we aimed to better stratify prostate cancer patients through the selection of robust long non-coding RNAs. To fulfill the purpose of the study, a bioinformatic approach focused on feature selection applied to a TCGA dataset was used. In such a way, LINC00668 and long non-coding(lnc)-SAYSD1-1, able to discriminate ERG/not-ERG subtypes, Citation: De Summa, S.; Palazzo, A.; were demonstrated to be positive prognostic biomarkers in ERG-positive patients.