Abstract

Simple SummaryTo date, there has not been adequate research conducted on prostate cancer tumor stem cells, which play an important role in tumor recurrence, invasion, and drug resistance. In this study, we innovatively used a tumor stem cell-associated index (mRNAsi), calculated by a single-class logistic regression machine learning algorithm (OCRL), in combination with multiple databases to identify MBNL1-AS1 as a key lncRNA for prostate cancer stem cells and elucidated via in vivo and in vitro experiments. In addition, the experiments showed that the down-regulation of MBNL1-AS1 promotes the malignance of prostate cancer cell lines through the miR-221-3p/CDKN1B/C-myc axis by stimulating the stemness of tumor stem cells. This provides the basis for theoretical studies of prostate cancer and provides targets for precision therapy.AbstractThe recurrence, progression, and drug resistance of prostate cancer (PC) is closely related to the cancer stem cells (CSCs). Therefore, it is necessary to find the key regulators of prostate cancer stem cells (PCSCs). Here, we analyzed the results of a single-class logistic regression machine learning algorithm (OCLR) to identify the PCSC-associated lncRNA MBNL1-AS1. The effects of MBNL1-AS1 on the stemness of CSCs was assessed using qPCR, western blot and sphere-forming assays. The role of MBNL1-AS1 in mediating the proliferation and invasion of the PC cell lines was examined using Transwell, wounding-healing, CCK-8, EdU and animal assays. Dual-luciferase and ChIRP assays were used to examine the molecular mechanism of MBNL1-AS1 in PCSCs. MBNL1-AS1 was shown to be negatively correlated with stemness index (mRNAsi), and even prognosis, tumor progression, recurrence, and drug resistance in PC patients. The knockdown of MBNL1-AS1 significantly affected the stemness of the PC cells, and subsequently their invasive and proliferative abili