CK1 protein kinases form a family of serine/threonine kinases which are highly conserved through different species and ubiquitously expressed. CK1 family members can phosphorylate numerous substrates thereby regulating different biological processes including membrane trafficking, cell cycle regulation, circadian rhythm, apoptosis, and signal transduction. Deregulation of CK1 activity and/or expression contributes to the development of neurological diseases and cancer. Therefore, CK1 became an interesting target for drug development and it is relevant to further understand the mechanisms of its regulation. In the present study, Cyclin-dependent kinase 2/Cyclin E (CDK2/E) and Cyclin-dependent kinase 5/p35 (CDK5/p35) were identified as cellular kinases able to modulate CK1δ activity through site-specific phosphorylation of its C-terminal domain. Furthermore, pre-incubation of CK1δ with CDK2/E or CDK5/p35 reduces CK1δ activity in vitro, indicating a functional impact of the interaction between CK1δ and CDK/cyclin complexes. Interestingly, inhibition of Cyclin-dependent kinases by Dinaciclib increases CK1δ activity in pancreatic cancer cells. In summary, these results suggest that CK1δ activity can be modulated by the interplay between CK1δ and CDK2/E or CDK5/p35. These findings extend our knowledge about CK1δ regulation and may be of use for future development of CK1-related therapeutic strategies in the treatment of neurological diseases or cancer.
Germline variants such as BRCA1/2 play an important role in tumorigenesis and clinical outcomes of cancer patients. However, only a small fraction (i.e., 5–10%) of inherited variants has been associated with clinical outcomes (e.g., BRCA1/2, APC, TP53, PTEN and so on). The challenge remains in using these inherited germline variants to predict clinical outcomes of cancer patient population. In an attempt to solve this issue, we applied our recently developed algorithm, eTumorMetastasis, which constructs predictive models, on exome sequencing data to ER+ breast (n = 755) cancer patients. Gene signatures derived from the genes containing functionally germline variants significantly distinguished recurred and non-recurred patients in two ER+ breast cancer independent cohorts (n = 200 and 295, P = 1.4 × 10−3). Furthermore, we compared our results with the widely known Oncotype DX test (i.e., Oncotype DX breast cancer recurrence score) and outperformed prediction for both high- and low-risk groups. Finally, we found that recurred patients possessed a higher rate of germline variants. In addition, the inherited germline variants from these gene signatures were predominately enriched in T cell function, antigen presentation, and cytokine interactions, likely impairing the adaptive and innate immune response thus favoring a pro-tumorigenic environment. Hence, germline genomic information could be used for developing non-invasive genomic tests for predicting patients’ outcomes in breast cancer.
Cellular signal transduction components are usually regulated not only on transcriptional or translational level, but also by posttranslational modifications. Among these, reversible phosphorylation represents the most abundant modification. In general, phosphorylation events are essential for regulating the activity of central signal transduction proteins, also including kinases itself. Members of the CK1 family can be found as central signal transduction proteins in numerous cellular pathways. Due to its wide variety of cellular functions the activity of CK1 family members has to be tightly regulated. We previously reported that PKA and Chk1 are able to phosphorylate CK1δ within its C-terminal regulatory domain, consequently resulting in altered CK1 kinase activity. In the present study, we show by several methods that protein kinase C α (PKCα) as well is able to phosphorylate CK1δ at its C-terminally located residues S328, T329, and S370. Furthermore, we analyze the functional consequences of PKCα-mediated phosphorylation on CK1δ kinase activity. Mutation of S328, T329, or S370 to alanine dramatically alters the kinetic parameters of CK1δ. By using the PKCα-specific inhibitor Go-6983 in a selected cell culture model, we finally show that the in vitro detected regulatory connection between PKCα and CK1δ is also relevant in the cellular context. Taken together, these data contribute to a deeper understanding of cellular signal transduction networks thereby helping to form a basis for the development of future therapeutic concepts.
Continual reduction in sequencing cost is expanding the accessibility of genome sequencing data for routine clinical applications. However, the lack of methods to construct machine learning-based predictive models using these datasets has become a crucial bottleneck for the application of sequencing technology in clinics. Here, we develop a new algorithm, eTumorMetastasis, which transforms tumor functional mutations into network-based profiles and identifies network operational gene (NOG) signatures. NOG signatures model the tipping point at which a tumor cell shifts from a state that doesn’t favor recurrence to one that does. We show that NOG signatures derived from genomic mutations of tumor founding clones (i.e., the ‘most recent common ancestor’ of the cells within a tumor) significantly distinguish the recurred and non-recurred breast tumors as well as outperform the most popular genomic test (i.e., Oncotype DX). These results imply that mutations of the tumor founding clones are associated with tumor recurrence and can be used to predict clinical outcomes. As such, predictive tools could be used in clinics to guide treatment routes. Finally, the concepts underlying the eTumorMetastasis pave the way for the application of genome sequencing in predictions for other complex genetic diseases. eTumorMetastasis pseudocode and related data used in this study are available at https://github.com/WangEdwinLab/eTumorMetastasis.
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