Accurate identification of primary site in tumors of unknown origin (TUO) using DNA methylation.

Tumors of unknown origin (TUO) generally result in poor patient survival and are clinically difficult to address. Identification of the site of origin in TUO patients is paramount to their improved treatment and survival but is difficult to obtain with current methods. Here, we develop a random forest machine learning TUO methylation classifier using a large number of primary and metastatic tumor samples.

Discovery and design of molecular glue enhancers of CDK12-DDB1 interactions for targeted degradation of cyclin K.

The CDK12 inhibitor SR-4835 promotes the proteasomal degradation of cyclin K, contingent on the presence of CDK12 and the CUL4-RBX1-DDB1 E3 ligase complex. The inhibitor displays molecular glue activity, which correlates with its enhanced ability to inhibit cell growth. This effect is achieved by facilitating the formation of a ternary complex that requires the small molecule SR-4835, CDK12, and the adaptor protein DDB1, leading to the subsequent ubiquitination and degradation of cyclin K.

Structure-independent machine-learning predictions of the CDK12 interactome.

Cyclin-dependent kinase 12 (CDK12) is a critical regulatory protein involved in transcription and DNA repair processes. Dysregulation of CDK12 has been implicated in various diseases, including cancer. Understanding the CDK12 interactome is pivotal for elucidating its functional roles and potential therapeutic targets.