Multimodal AI biomarkers: from biology to patient stratification
Artificial intelligence is enabling a new class of biomarkers by integrating histology, molecular data, imaging, and clinical records to generate scalable, biologically grounded insights for precision oncology.
AI-driven multimodal strategy improves risk stratification in early breast cancer
Integrating digital pathology with genomic and clinical data may enhance prediction of late recurrence and refine selection for adjuvant treatment intensification in HR-positive, HER2-negative disease
Sustained quality-of-life benefits reported with first-line antibody-drug conjugate in triple negative breast cancer
Patient-reported outcomes show that datopotamab deruxtecan also improved patient functioning and symptom control compared to chemotherapy
How to sequence antibody–drug conjugates in metastatic breast cancer? Target switching alone may not be the answer
The first prospective phase II trials evaluating TOPO1 ADC after prior TOPO1 ADC therapy confirm the emergence of cross-resistance
The role of ctDNA surveillance is still uncertain in early breast cancer
Data from two novel studies further support the feasibility of this approach, although its clinical utility has yet to be determined
Towards a chemotherapy-free future in breast cancer?
Recent studies support treatment optimisation for improving patients’ quality of life, but its implementation in clinical practice remains limited
Chemotherapy-free adjuvant treatment preserves quality of life in HER2-positive early breast cancer
A pathological complete response-guided approach enables treatment optimisation in a selected population with HER2-positive breast cancer in the PHERGain-2 study
SERD therapy demonstrates robust anti-proliferative activity in young patients with ER-positive/HER2-negative early breast cancer
Encouraging results with giredestrant support the future use of SERD-based endocrine strategies in this setting
Customised app shows promise for monitoring prostate cancer patients in real-time
A pilot study reports high levels of acceptance and compliance despite an older patient population
Why AI-powered trial matching alone will not fix oncology trial recruitment
AI-powered trial matching helps identify relevant trials faster, but recruitment often fails beyond the algorithm. Limited cross-site trial discovery, outdated recruitment information and fragmented referral pathways continue to prevent potentially eligible patients from participating in relevant trials.