Nature Cancer, Published online: 13 March 2026; doi:10.1038/s43018-026-01137-yRNA N6-methyladenosine (m6A) is the most abundant internal RNA modification, yet its functional landscape in cancer remains poorly defined. A study now introduces a METTL3-based RNA base-editing screen that maps functional m6A sites and reveals m6A-dependent translational activation of the tumor suppressor CHD9 in prostate cancer and beyond.

Nature Cancer, Published online: 13 March 2026; doi:10.1038/s43018-025-01111-0We developed and clinically implemented the genomic prostate cancer risk prediction model P-CARE that identifies men at a high or low risk of prostate cancer. P-CARE enabled the design and initiation of a precision screening trial across the national healthcare system in which it was developed.

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-025-01109-8Whether support from artificial intelligence (AI) models improves breast screening is a topic of research in national cancer screening programmes and clinical oncology. Three studies now show that AI tools can assist radiologists with evaluating mammograms, substantially reducing workloads and possibly improving screening performance.

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-026-01127-0Kelly et al. assessed an artificial intelligence system for breast cancer screening in retrospective datasets, followed by prospective feasibility evaluation, and report its accuracy, fairness and clinical implementation in multiple workflow settings.

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-026-01128-zWarren et al. used data from a retrospective cohort of 50,000 women attending breast screening. Arbitration between human and AI decisions was performed in a reader study following normal arbitration workflow. After arbitration, replacing the second human reader with AI in a double-read breast screening workflow was noninferior to two human readers.

Nature Cancer, Published online: 10 March 2026; doi:10.1038/s43018-026-01126-1De Vries et al. performed prospective evaluation of AI for breast cancer screening leveraged in many different workflow settings and report several clinical and operational gains depending on the type of AI integration.

Nature Cancer, Published online: 05 March 2026; doi:10.1038/s43018-026-01135-0Dong and colleagues report that blockade of T cell-expressed cytotoxic and regulatory T cell molecule results in selective mitigation of immune-related toxicities without affecting antitumor efficacy of immune checkpoint inhibitors.