Artificial intelligence (AI) has contributed substantially to the resolution of a variety of
biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI …

Historically, the primary focus of cancer research has been molecular and clinical studies of
a few essential pathways and genes. Recent years have seen the rapid accumulation of …

The role of B cells in anti-tumour immunity is still debated and, accordingly,
immunotherapies have focused on targeting T and natural killer cells to inhibit tumour …

Multitargeting compounds comprising activity on more than a single biological target have
gained remarkable relevance in drug discovery owing to the complexity of multifactorial …

The promise of highly personalized oncology care using artificial intelligence (AI)
technologies has been forecasted since the emergence of the field. Cumulative advances …

Combination of anti-cancer drugs is broadly seen as way to overcome the often-limited
efficacy of single agents. The design and testing of combinations are however very …

Cancer dependency maps have accelerated the discovery of tumor vulnerabilities that can
be exploited as drug targets when translatable to patients. The Cancer Genome Atlas …

Activating mutations in GNAQ/GNA11, encoding Gαq G proteins, are initiating oncogenic
events in uveal melanoma (UM). However, there are no effective therapies for UM. Using an …

Precision oncology has made significant advances, mainly by targeting actionable mutations
in cancer driver genes. Aiming to expand treatment opportunities, recent studies have begun …

Identification of targeted therapies for TNBC is an urgent medical need. Using a drug
combination screen reliant on synthetic lethal interactions, we identified clinically relevant …