The latest medical research on Pancreatic Cancer

This study aimed to evaluate the efficacy of radiomics signatures derived from polyenergetic images (PEIs) and virtual monoenergetic images (VMIs) obtained through dual-layer spectral detector CT (DLCT). Moreover, it sought to develop a clinical-radiomics nomogram based on DLCT for predicting cancer stage (early stage: stage I-II, advanced stage: stage III-IV) in pancreatic ductal adenocarcinoma (PDAC).

A total of 173 patients histopathologically diagnosed with PDAC and who underwent contrast-enhanced DLCT were enrolled in this study. Among them, 49 were in the early stage, and 124 were in the advanced stage. Patients were randomly categorized into training (n = 122) and test (n = 51) cohorts at a 7:3 ratio. Radiomics features were extracted from PEIs and 40-keV VMIs were reconstructed at both arterial and portal venous phases. Radiomics signatures were constructed based on both PEIs and 40-keV VMIs. A radiomics nomogram was developed by integrating the 40-keV VMI-based radiomics signature with selected clinical predictors. The performance of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves analysis (DCA).

The PEI-based radiomics signature demonstrated satisfactory diagnostic efficacy, with the areas under the ROC curves (AUCs) of 0.92 in both the training and test cohorts. The optimal radiomics signature was based on 40-keV VMIs, with AUCs of 0.96 and 0.94 in the training and test cohorts. The nomogram, which integrated a 40-keV VMI-based radiomics signature with two clinical parameters (tumour diameter and normalized iodine density at the portal venous phase), demonstrated promising calibration and discrimination in both the training and test cohorts (0.97 and 0.91, respectively). DCA indicated that the clinical-radiomics nomogram provided the most significant clinical benefit.

The radiomics signature derived from 40-keV VMI and the clinical-radiomics nomogram based on DLCT both exhibited exceptional performance in distinguishing early from advanced stages in PDAC, aiding clinical decision-making for patients with this condition.

Low targeting efficacy and high toxicity continue to be challenges in Oncology. A promising strategy is the glycosylation of chemotherapeutic agents to improve their pharmacodynamics and anti-tumoral activity. Herein, we provide evidence of a novel approach using diglycosidases from fungi of the Hypocreales order to obtain novel rutinose-conjugates therapeutic agents with enhanced anti-tumoral capacity.

Screening for diglycosidase activity in twenty-eight strains of the genetically related genera Acremonium and Sarocladium identified 6-O-α-rhamnosyl-β-glucosidase (αRβG) of Sarocladium strictum DMic 093557 as candidate enzyme for our studies. Biochemically characterization shows that αRβG has the ability to transglycosylate bulky OH-acceptors, including bioactive compounds. Interestingly, rutinoside-derivatives of phloroglucinol (PR) resorcinol (RR) and 4-methylumbelliferone (4MUR) displayed higher growth inhibitory activity on pancreatic cancer cells than the respective aglycones without significant affecting normal pancreatic epithelial cells. PR exhibited the highest efficacy with an IC50 of 0.89 mM, followed by RR with an IC50 of 1.67 mM, and 4MUR with an IC50 of 2.4 mM, whereas the respective aglycones displayed higher IC50 values: 4.69 mM for phloroglucinol, 5.90 mM for resorcinol, and 4.8 mM for 4-methylumbelliferone. Further, glycoconjugates significantly sensitized pancreatic cancer cells to the standard of care chemotherapy agent gemcitabine.

αRβG from S. strictum transglycosylate-based approach to synthesize rutinosides represents a suitable option to enhance the anti-proliferative effect of bioactive compounds. This finding opens up new possibilities for developing more effective therapies for pancreatic cancer and other solid malignancies.