Researchers at the National Institutes of Health (NIH) and their collaborators have discovered a new way in which RAS genes, which are commonly mutated in cancer, may drive tumor growth beyond their well-known role in signaling at the cell surface. Mutant RAS, they found, helps to kick off a series of events involving the transport of specific nuclear proteins that lead to uncontrolled tumor growth, according to a study published November 11, 2024, in Nature Cancer.

Gene fusions are vital biomarkers for tumor diagnosis and drug development, with precise detection becoming increasingly important. This review explores the links between gene fusions and common tumors, systematically evaluating detection technologies like fluorescence in situ hybridization (FISH), polymerase chain reaction (PCR), immunohistochemistry (IHC), electrochemiluminescence (ECL), and next-generation sequencing (NGS). FISH is the gold standard for DNA-level rearrangements, while PCR and NGS are widely used, with PCR confirming known fusions and NGS offering comprehensive genome-wide detection. Bioinformatic tools like STAR-Fusion, FusionCatcher, and Arriba are assessed for diagnostic accuracy. The review highlights how artificial intelligence (AI), particularly deep learning (DL) technologies like convolutional neural networks (CNNs) and recurrent neural networks (RNNs), is transforming gene fusion research by accurately detecting and annotating genes from genomic data, eliminating biases. Finally, we present an overview of advanced technologies for gene fusion analysis, emphasizing their potential to uncover unknown gene fusions.

In a study led by researchers at the NUS Yong Loo Lin School of Medicine, extracellular vesicles (EVs) loaded with customisable anti-cancer antisense oligonucleotides suppressed cancer growth.