Beyond Mutations: RNA Editing, Neoantigen Diversity, and the Next Frontier of Personalised Cancer

Beyond Mutations: How RNA Editing Could Transform Personalised Cancer Treatment. Cancer has long been understood as a disease of DNA mutations, permanent errors in our genetic code that drive tumour growth. Yet exciting new research reveals a hidden layer of complexity: RNA editing, a natural process that alters genetic messages after they have been copied from DNA, without changing the DNA itself. Here, Dr Ivo Fierro Monti at EMBL-EBI explores how a specific type of RNA editing, called A-to-I editing, acts as a dynamic "molecular switch" in cancer. Enzymes known as ADARs chemically tweak adenosine into inosine within RNA molecules, effectively rewriting the instructions used to build proteins. This can recode cancer-driving genes such as AZIN1 and NEIL1, sometimes accelerating tumour growth and other times suppressing it, highlighting the process's dual, context-dependent nature. Remarkably, RNA editing also generates neoantigens, novel protein fragments displayed on cancer cells that the immune system can recognise as foreign. These editing-derived signals expand the repertoire of targets for immunotherapy and personalised cancer vaccines, complementing traditional DNA mutation-based approaches. How RNA editing influences drug resistance and tumour heterogeneity, making it a valuable biomarker for predicting patient outcomes? Cutting-edge technologies, including programmable RNA editors and mRNA vaccines, are now being developed to harness or correct these edits therapeutically. Early clinical trials, such as the KEYNOTE-942 study combining personalised mRNA vaccines with immunotherapy in melanoma, show promising results. Integrating RNA editing profiles with multi-omics data and machine learning is already refining patient stratification and treatment selection. While challenges remain in delivery specificity and clinical translation, RNA editing, a versatile, reversible toolkit promises to advance precision oncology beyond the constraints of the static genome.