What is it about?
Cancer, obesity, and diabetes are often treated as separate diseases, yet they share common biological mechanisms. In this review, we show how Protein Kinase D (PKD) isoforms act as central signalling hubs connecting these conditions. We break down the distinct roles of PKD1, PKD2, and PKD3, highlighting how they regulate processes such as tumour growth, metabolism, immune evasion, and cell migration. In particular, PKD2 emerges as a key integrator of metabolic stress and oncogenic signalling, linking hypoxia, inflammation, and metabolic dysfunction to cancer progression.
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Why is it important?
Obesity and diabetes significantly increase cancer risk, but the molecular links between these diseases are still not fully understood. This work identifies PKD isoforms as a unifying mechanism underlying this connection. Importantly, it shows that PKD isoforms have distinct and sometimes opposing roles, meaning that non-selective targeting could lead to unintended effects. By highlighting PKD2 as a central signalling node, this review provides a clearer direction for developing more precise, isoform-specific therapeutic strategies in cancer patients with metabolic disorders.
Perspectives
This work shifts the focus from studying cancer and metabolic diseases in isolation to understanding their shared signalling networks. Targeting PKD isoforms, particularly PKD2, could enable therapies that address both tumour progression and underlying metabolic dysfunction. Future research should focus on developing isoform-selective inhibitors and exploring how patient-specific metabolic states influence PKD signalling. More broadly, this review supports a move toward integrated therapeutic strategies that consider cancer within the context of systemic metabolic health where PKD may be the missing link between cancer and metabolic disease.
Ahmed Shemy
Associatie KU Leuven
Read the Original
This page is a summary of: Protein kinase D: Integrating cancer and metabolic disorders, Molecular Aspects of Medicine, April 2026, Elsevier,
DOI: 10.1016/j.mam.2026.101446.
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