Targeting lipid biosynthesis in cancer

Epithelial cancers, such as non-small cell lung cancer and pancreatic ductal adenocarcinoma, represent the leading causes of death in the Western world. They are characterised by primary and acquired resistance to most drugs used for cancer therapy, clearly indicating the need for novel treatments.

Despite the significant heterogeneity of these tumours, certain biochemical features are common to most of them, including signalling molecules and biochemical pathways. The scope of the EU-funded CANCERALIA (Development of novel diagnostic and therapeutic approaches to improve patient outcome in lung and pancreatic tumours) project was to improve survival of patients with lung and pancreatic cancer by studying the contribution of certain pathways to cancer risk. The generated knowledge should in the long run lead to the development of novel therapeutic strategies.

Most studies so far have focused on pathways required for protein synthesis or cell growth. CANCERALIA researchers focused on pathways implicated in membrane lipid biosynthesis given their vitality for cell maintenance. For example, the Kennedy pathway is crucial for the biosynthesis of membrane lipids and choline kinase is a central enzyme for tumour growth. Small molecule inhibitors of choline kinase have already reached clinical evaluation as an anti-cancer strategy.

The consortium performed lipidomics analysis in primary samples and xenograft tumours, and assigned particular profiles to cancer subtypes. They also identified predictors of response to inhibitors of choline kinase. Project activities additionally unveiled novel mechanisms underlying the observed resistance to choline kinase inhibitors, and identified the molecular pathways involved. As a solution to this major hurdle of cancer treatment, they proposed new targets for future drug development.

Overall, the activities of the CANCERALIA initiative demonstrated the capacity to translate cellular and molecular knowledge into better tools for patient management. The generated deliverables will lead to better strategies for patient stratification, help identify risk and apply novel therapies on a personalised basis.