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An ESMO roadmap addresses how the new challenges in oncology can be transformed into opportunities for the benefits of oncology professionals and patients with cancer

Leveraging artificial intelligence and digital pathology, oncology is entering a transformative stage where advanced image analysis and AI-driven biomarkers enable personalised cancer treatment decisions.

Pathology is going digital. More than 50 AIs cleared for diagnostic use are now available. This article summarises the status quo and gives an outlook of upcoming emerging technologies.

The innovative approach was successfully tested on NY-ESO-1 and promises to bypass some current challenges in the identification of T cell receptors for therapeutic use

In a phase III trial, lower doses of adjuvant radiotherapy plus docetaxel were associated with reduced toxicity and need for percutaneous endoscopic gastrostomy, with an impact on quality of life 

Data from two studies suggest a good rationale for targeting T-cell dysfunction with precision immunotherapy to intercept pre-cancerous lesions 

Presented studies explore different approaches to predict cancer cachexia and inform on the intra-tumour heterogeneity to personalise treatment

An initiative fosters inclusive research by improving patient access and participation in cancer research 

Real world experience suggests that the integration of digital tools into cancer care may close current gaps in patient outcomes reporting

In a study, a machine learning approach outperformed cancer-specific models and revealed universal biomarkers to guide end-of-life care decisions