Digital twins as simulations of individual cancer pathophysiology through extensive tumor profiling: A guide to successful disease management.

e23303 Background: Advances in tumor-specific therapies guided by molecular genetic profiling are increasingly being integrated into clinical oncology. This study examines the significance of pathophysiology in tumors towards achieving treatment success, focusing not only on mutations but also on comprehensive tumorigenic characteristics. Methods: We conducted an analysis on 44 metastatic cancer patients who had previously undergone extensive therapies. The median progression-free survival after prior therapies (PFS1) was 18 weeks. Molecular profiling was performed, encompassing genetic alterations, gene expression, and pathway analysis. These were categorized into distinct tumor biological signatures, aligning with key oncogenic mechanisms such as proliferation, angiogenesis, immune evasion, among others. Clinical endpoints included progression-free survival following profiling-guided therapy (PFS2), the ratio of PFS2 to PFS1, and overall survival outcomes opposed to data of deceased patients. The treatment modalities assessed included chemotherapy, targeted and combination therapies. Results: The median PFS2 for all patients was 30 weeks (range: 5–217 weeks), with a median PFS2/PFS1 ratio of 1.38 (0.92–11.3). Patients with PFS2 longer than 24 weeks constituted 64% of the cohort (n = 28). Among those who survived the 5-years observation period, 15 out of 44 patients had a median PFS2 of 72 weeks and a PFS2/PFS1 ratio of 2.45 (0.4–10.14), being significantly better than that of deceased patients (median PFS2: 24 weeks, p = 4.611 × e × 10 -5 ratio of 1,25 (0,29-11,33): p = 0.033). Significantly more targetable and non-targetable oncogenes were present in the survival group (p = 0.005), and functional effects were more frequently associated with kinases (p = 0.007). The most involved oncogenic pathways include cell cycle regulation, proliferation, metabolism, microenvironment, and immune evasion. These pathways are significantly more often represented in the survival group, but not more frequently targeted. Patients who passed away were twice as likely to have received chemotherapy in the absence of detectable targetable alterations, whereas those who survived were three times more likely to have undergone targeted therapy based on individual tumor characteristics. Conclusions: Comprehensive tumor profiling revealed distinct molecular genetic signatures across patient cohorts, enabling personalized therapeutic strategies. Targeting key pathways, particularly those related to the cell cycle, angiogenesis, and immune evasion, correlates with improved clinical outcomes. These findings underscore the potential of tumor profiling to refine therapeutic decision-making, optimize resource allocation, and improve survival in oncology.