Protein Kinases and Signal Transduction Pathways in Regulating Tumor Growth

Dear Colleagues,

Since their first description in the early 50s, protein kinases (PKs) have emerged amongst the most dominant but also most versatile means of regulating cellular processes. From the evolutionary older serine threonine kinases and dual-specificity kinases to the “later” tyrosine kinases, phosphorylation events can control the association behavior of their targets, alter catalytic activities or protein stability, control structural transitions and protein localization, and perform many other critical functions. The over 500 catalytically active kinases have for some time been complemented by a subset of pseudokinases with regulatory functions. Yet, with the emergence of more and better therapeutic inhibitors, more cases are emerging in which the same protein kinase may have cancer-relevant regulatory catalytic and non-catalytic contributions, thereby making them prime targets for targeted degradation approaches.

The rate at which kinase inhibitors are produced using both screening and structure-guided design methods is remarkable, especially considering that the highly conserved nature of the kinase fold had initially raised doubts about the suitability of PKs as drug targets. The pendulum between the exploitation of more diverse, but less defined inactive states (or even distant allosteric states) versus high-affinity binding to less diverse, but more rigid active states has swung in both directions over the years. Yet, true diversity in targeting has long remained a challenge. Although the toolsets for the screening or development of kinase inhibitors have dramatically increased, as has our understanding of the molecular mechanisms of PK drug resistance, the preferred practice has long been to improve already existing PK inhibitors that target clinically validated targets, or those with emerging resistance needs.

Beyond the classic model of mutated binary on/off switches or pathological up/downregulation, our molecular understanding of how PKs operate in complex cellular settings has not kept pace with the screening and initial validation of new PK targets. Many of the related observations receive more attention in areas such as basic biochemistry, neurobiology, or immunology than the cancer field. For example, the on/off status of PKs has been described as the perturbation of a bistable state of rapid constitutive phosphorylation and dephosphorylation. This is not only exquisitely sensitive to any perturbance of the associated phosphatases, but also to the cellular redox state, thereby establishing multiple cancer-relevant modes of crosstalk. Another example is shifts in the membrane glycolipid complement or overall membrane lipid composition. These events directly alter the signaling behavior of membrane-associated protein kinases. Significant shifts in these membrane lipid or glycolipid species occur in cancer and in ways that are qualitatively different for cancer subtypes or states. In this setting, the interface with cancer research faces severe technological hurdles. Similarly, while many PKs have explicit lipid targeting domains, lipid kinases directly interface with PKs at many points, with PIP3/AKT signaling receiving most of the attention. Yet, we know much less about the broader signaling by lipid kinases and the distinct functions of their associated substrates themselves, let alone how their activity in turn is controlled by protein kinases. Bioinformatic approaches, such as machine learning algorithms, are increasingly applied to large proteomic or kinome datasets to better classify or even predict systemic responses to pathological alterations or therapeutic perturbations. Such efforts are likely to benefit greatly from a more comprehensive understanding of how PKs are embedded into cellular signaling and adaptation. In particular, we should assess the more complex layers of crosstalk that are currently understudied.

Dr. Ralf Landgraf
Guest Editor

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• protein kinases
• protein kinase inhibitors
• protein phosphatases
• inositol kinases
• signal integration
• kinase–lipid interaction