Pier Paolo Di Fiore
The molecular heterogeneity of breast cancer (BC) translates into different disease courses and therapeutic outcomes and poses important challenges for patient management. Strategies to achieve patient stratification for prognostic judgment and therapy assignment have traditionally relied on the combined evaluation of clinical and pathological parameters, and more recently on molecular signatures. Together, these tools have led to the largely accepted molecular classification of BC into Luminal A, Luminal B, HER2+ and Basal-like/Triple-negative subtypes, which presently informs patient management1. Nevertheless, important unmet clinical needs remain in the management of BC patients, among which: The prediction of tumor recurrence and chemotherapy response, especially in Luminal BCs, which remain at persistent risk of recurrence for at least 15-20 years2. The scarcity of targetable alterations in Triple-negative BCs (TNBCs), which consequently lack effective targeted therapies. This technoshot aims at combining a PET-radiomics approach with transcriptomics analysis to exploit metabolic alterations in BC to meet the above clinical needs.
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