Loss-of-function phenotype of a PKCθT219A knockin mouse strain

Cancer-associated mutations in protein kinase C theta are loss-of-function

The Ca2+-independent, but diacylglycerol-regulated, novel protein kinase C (PKC) theta (θ) is highly expressed in hematopoietic cells where it participates in immune signaling and platelet function. Mounting evidence suggests that PKCθ may be involved in cancer, particularly blood cancers, breast cancer, and gastrointestinal stromal tumors, yet how to target this kinase (as an oncogene or as a tumor suppressor) has not been established. Here, we examine the effect of four cancer-associated mutations, R145H/C in the autoinhibitory pseudosubstrate, E161K in the regulatory C1A domain, and R635W in the regulatory C-terminal tail, on the cellular activity and stability of PKCθ. Live-cell imaging studies using the genetically-encoded fluorescence resonance energy transfer-based reporter for PKC activity, C kinase activity reporter 2 (CKAR2), revealed that the pseudosubstrate and C1A domain mutations impaired autoinhibition to increase basal signaling. This impaired autoinhibition resulted in decreased stability of the protein, consistent with the well-characterized behavior of Ca2+-regulated PKC isozymes wherein mutations that impair autoinhibition are paradoxically loss-of-function because the mutant protein is degraded. In marked contrast, the C-terminal tail mutation resulted in enhanced autoinhibition and enhanced stability. Thus, the examined mutations were loss-of-function by different mechanisms: mutations that impaired autoinhibition promoted the degradation of PKC, and those that enhanced autoinhibition stabilized an inactive PKC. Supporting a general loss-of-function of PKCθ in cancer, bioinformatics analysis revealed that protein levels of PKCθ are reduced in diverse cancers, including lung, renal, head and neck, and pancreatic. Our results reveal that PKCθ function is lost in cancer.

Darovasertib, a novel treatment for metastatic uveal melanoma

The FDA granted orphan drug designation to darovasertib, a first-in-class oral, small molecular inhibitor of protein kinase C (PKC), for the treatment of uveal melanoma, on 2 May 2022. Primary uveal melanoma has a high risk of progressing to metastatic uveal melanoma, with a poor prognosis. The activation of the PKC and mitogen-activated protein kinase pathways play an essential role in the pathogenesis of uveal melanoma, and mutations in the G protein subunit alpha q (GNAQ), and G protein subunit alpha11 (GNA11) genes are considered early events in the development of uveal melanoma. Compared to other PKC inhibitors, such as sotrastaurin and enzastaurin, darovasertib is significantly more potent in inhibiting conventional (α, β) and novel (δ, ϵ, η, θ) PKC proteins and has a better tolerability and safety profile. Current Phase I/II clinical trials indicated that darovasertib, combined with the Mitogen-activated protein kinase/Extracellular (MEK) inhibitors, binimetinib or crizotinib, produced a synergistic effect of uveal melanoma. In this article, we summarize the development of drugs for treating uveal melanomas and discuss problems associated with current treatments. We also discuss the mechanism of action, pharmacokinetic profile, adverse effects, and clinical trial for darovasertib, and future research directions for treating uveal melanoma.

CORAL: Monte Carlo based global QSAR modelling of Bruton tyrosine kinase inhibitors using hybrid descriptors

Global QSAR modelling was performed to predict the pIC₅₀ values of 233 diverse heterocyclic compounds as BTK inhibitors with the Monte Carlo algorithm of CORAL software using the DCW hybrid descriptors extracted from SMILES notations of molecules. The dataset of 233 BTK inhibitors was randomly split into training, invisible training, calibration and validation sets. The index of ideality of correlation was also applied to build and judge the predictability of the QSAR models. Eight global QSAR models based on the hybrid optimal descriptor using two target functions, i.e. TF₁ (W_IIC = 0) and TF₂ (W_IIC = 0.2) have been constructed. The statistical parameters of QSAR models computed by TF₂ are more reliable and robust and were used to predict the pIC₅₀ values. The model constructed for split 4 via TF₂ is regarded as the best model and the numerical values of r²_Train, r²_Valid, Q²_Train and Q²_Valid are equal to 0.7981, 0.7429, 0.7898 and 0.6784, respectively. By internal and external validation techniques, the predictability and reliability of the designed models have been assessed. The structural attributes responsible for the increase and decrease of pIC₅₀ of BTK inhibitors were also identified.

Equivocal, explicit and emergent actions of PKC isoforms in cancer

The maturing mutational landscape of cancer genomes, the development and application of clinical interventions and evolving insights into tumour-associated functions reveal unexpected features of the protein kinase C (PKC) family of serine/threonine protein kinases. These advances include recent work showing gain or loss-of-function mutations relating to driver or bystander roles, how conformational constraints and plasticity impact this class of proteins and how emergent cancer-associated properties may offer opportunities for intervention. The profound impact of the tumour microenvironment, reflected in the efficacy of immune checkpoint interventions, further prompts to incorporate PKC family actions and interventions in this ecosystem, informed by insights into the control of stromal and immune cell functions. Drugging PKC isoforms has offered much promise, but when and how is not obvious.