Pancreatic ductal adenocarcinoma remains associated with a poor prognosis, even when diagnosed at an early stage. Consequently, it is imperative to carefully consider the available therapeutic options and tailor them based on clinically relevant biomarkers. In our comprehensive review, we specifically concentrated on the identification of novel predictive and prognostic markers that have the potential to be integrated into multiparametric scoring systems. These scoring systems aim to accurately predict the efficacy of neoadjuvant chemotherapy in surgically resectable pancreatic cancer cases. By identifying robust predictive markers, we can enhance our ability to select patients who are most likely to benefit from neoadjuvant chemotherapy. Furthermore, the identification of prognostic markers can provide valuable insights into the overall disease trajectory and inform treatment decisions. The development of multiparametric scoring systems that incorporate these markers holds great promise for optimizing the selection of patients for neoadjuvant chemotherapy, leading to improved outcomes in resectable pancreatic neoplasia. Continued research efforts are needed to validate and refine these markers and scoring systems, ultimately advancing the field of personalized medicine in pancreatic adenocarcinoma management.

Background: The aim of the present study was to dissect the clinical outcome of GB patients through the integration of molecular, immunophenotypic and MR imaging features. Methods: We enrolled 57 histologically proven and molecularly tested GB patients (5.3% IDH-1 mutant). Two-Dimensional Free ROI on the Biggest Enhancing Tumoral Diameter (TDFRBETD) acquired by MRI sequences were used to perform a manual evaluation of multiple quantitative variables, among which we selected: SD Fluid Attenuated Inversion Recovery (FLAIR), SD and mean Apparent Diffusion Coefficient (ADC). Characterization of the Tumor Immune Microenvironment (TIME) involved the immunohistochemical analysis of PD-L1, and number and distribution of CD3+, CD4+, CD8+ Tumor Infiltrating Lymphocytes (TILs) and CD163+ Tumor Associated Macrophages (TAMs), focusing on immune-vascular localization. Genetic, MR imaging and TIME descriptors were correlated with overall survival (OS). Results: MGMT methylation was associated with a significantly prolonged OS (median OS = 20 months), while no impact of p53 and EGFR status was apparent. GB cases with high mean ADC at MRI, indicative of low cellularity and soft consistency, exhibited increased OS (median OS = 24 months). PD-L1 and the overall number of TILs and CD163+TAMs had a marginal impact on patient outcome. Conversely, the density of vascular-associated (V) CD4+ lymphocytes emerged as the most significant prognostic factor (median OS = 23 months in V-CD4high vs. 13 months in V-CD4low, p = 0.015). High V-CD4+TILs also characterized TIME of MGMTmeth GB, while p53mut appeared to condition a desert immune background. When individual genetic (MGMTunmeth), MR imaging (mean ADClow) and TIME (V-CD4+TILslow) negative predictors were combined, median OS was 21 months (95% CI, 0–47.37) in patients displaying 0- 1 risk factor and 13 months (95% CI 7.22–19.22) in the presence of 2–3 risk factors (p = 0.010, HR = 3.39, 95% CI 1.26–9.09). Conclusion: Interlacing MRI–immune–genetic features may provide highly significant risk-stratification models in GB patients.