OTS-167

Cancer stem cells (CSCs) are a subpopulation of cancer cells within tumors that exhibit stem-like properties and represent a potentially effective therapeutic target toward long-term remission by means of differentiation induction. By leveraging an artificial intelligence approach solely based on transcriptomics data, this study scored a large library of small molecules based on their predicted ability to induce differentiation in stem-like cells. In particular, a deep neural network model was trained using publicly available single-cell RNA-Seq data obtained from untreated human-induced pluripotent stem cells at various differentiation stages and subsequently utilized to screen drug-induced gene expression profiles from the Library of Integrated Network-based Cellular Signatures (LINCS) database. The challenge of adapting such different data domains was tackled by devising an adversarial learning approach that was able to effectively identify and remove domain-specific bias during the training phase. Experimental validation in MDA-MB-231 and MCF7 cells demonstrated the efficacy of five out of six tested molecules among those scored highest by the model. In particular, the efficacy of triptolide, OTS-167, quinacrine, granisetron and A-443654 offer a potential avenue for targeted therapies against breast CSCs.

The balance between T helper 1 (Th1) and T helper 2 (Th2) has a critical function in determining intratumoral immune response and anti-PD-1 immunotherapy. The level of maternal embryonic leucine zipper kinase (MELK) is reported to correlate with infiltration of immune cells in cancers, but the underlying molecular mechanism is not clarified. In the present study, we aimed to elucidate the potential function of MELK in cervical cancer. We found that MELK was upregulated and played an oncogenic role in cervical cancer. MELK overexpression shifted Th1/Th2 balance toward Th2 predisposition in mouse cervical tumors in vivo and naive T cells from human PBMCs in vitro, whereas MELK knockdown exhibited opposite effects. MELK overexpression activated NF-κB signaling and promoted IL-6 secretion by cervical cancer cells. Depletion of IL-6 by neutralization antibodies abrogated the influence of MELK on Th1/Th2 balance. In addition, MELK modulated the antitumor activity of cytotoxic CD8⁺ T cells in cervical tumors, but depletion of Th2 cells by IL-4 neutralization abrogated this effect. Finally, MELK overexpression conferred tolerance to PD-1 blockade in cervical tumors, whereas targeting MELK by OTSSP167 significantly enhanced PD-1 blockade efficiency. Our data elucidated a novel role of MELK in regulating Th1/Th2 balance and anti-PD-1 immunotherapy in cervical cancer.