One of the most abundant non-canonical bases widely occurring on various RNA molecules is 5-methyluridine (m5U). Recent studies have revealed its influences on the development of breast cancer, systemic lupus erythematosus, and the regulation of stress responses. The accurate identification of m⁵U sites is crucial for understanding their biological functions. We propose RNADSN, the first transfer learning deep neural network that learns common features between tRNA m⁵U and mRNA m⁵U to enhance the prediction of mRNA m⁵U. Without seeing the experimentally detected mRNA m⁵U sites, RNADSN has already outperformed the state-of-the-art method, m5UPred. Using mRNA m⁵U classification as an additional layer of supervision, our model achieved another distinct improvement and presented an average area under the receiver operating characteristic curve (AUC) of 0.9422 and an average precision (AP) of 0.7855. The robust performance of RNADSN was also verified by cross-technical and cross-cellular validation. The interpretation of RNADSN also revealed the sequence motif of common features. Therefore, RNADSN should be a useful tool for studying m⁵U modification.

Ca2+/calmodulin-dependent protein kinase II γ (CAMKIIγ) has been identified as a potential target for treating cancer. Based on our previous study of berbamine (BBM) as a CAMKIIγ inhibitor, we have synthesized a new BBM derivative termed PA4. Compared with BBM, PA4 showed improved potency and specificity and was more cytotoxic against lymphoma and leukemia than against other types of cancer. In addition to indirectly targeting c-Myc protein stability, we demonstrated that its cytotoxic effects were also mediated via increased reactive oxygen species production in lymphoma cells. PA4 significantly impeded tumor growth in vivo in a xenograft T-cell lymphoma mouse model. Pharmacokinetics studies demonstrated quick absorption into plasma after oral administration, with a maximum concentration of 1680 ± 479 ng/mL at 5.33 ± 2.31 hours. The calculated oral absolute bioavailability was 34.1%. Toxicity assessment of PA4 showed that the therapeutic window used in our experiments was safe for future development. Given its efficacy, safety, and favorable pharmacokinetic profile, PA4 is a potential lead candidate for treating lymphoma.