Fine-tuning the activation behaviors of ternary modular cabazitaxel prodrugs for efficient and on-target oral anti-cancer therapy.

The disulfide bond plays a crucial role in the design of anti-tumor prodrugs due to its exceptional tumor-specific redox responsiveness. However, premature breaking of disulfide bonds is triggered by small amounts of reducing substances (e.g., ascorbic acid, glutathione, uric acid and tea polyphenols) in the systemic circulation. This may lead to toxicity, particularly in oral prodrugs that require more frequent and high-dose treatments. Fine-tuning the activation kinetics of these prodrugs is a promising prospect for more efficient on-target cancer therapies. In this study, disulfide, steric disulfide, and ester bonds were used to bridge cabazitaxel (CTX) to an intestinal lymph vessel-directed triglyceride (TG) module. Then, synthetic prodrugs were efficiently incorporated into self-nanoemulsifying drug delivery system (corn oil and Maisine CC were used as the oil phase and Cremophor EL as the surfactant). All three prodrugs had excellent gastric stability and intestinal permeability. The oral bioavailability of the disulfide bond-based prodrugs (CTX-(C)S-(C)S-TG and CTX-S-S-TG) was 11.5- and 19.1-fold higher than that of the CTX solution, respectively, demonstrating good oral delivery efficiency. However, the excessive reduction sensitivity of the disulfide bond resulted in lower plasma stability and safety of CTX-S-S-TG than that of CTX-(C)S-(C)S-TG. Moreover, introducing steric hindrance into disulfide bonds could also modulate drug release and cytotoxicity, significantly improving the anti-tumor activity even compared to that of intravenous CTX solution at half dosage while minimizing off-target adverse effects. Our findings provide insights into the design and fine-tuning of different disulfide bond-based linkers, which may help identify oral prodrugs with more potent therapeutic efficacy and safety for cancer therapy.

Multiparametric MRI-based whole-liver radiomics for predicting early-stage liver fibrosis in rabbits.

OBJECTIVES: To develop and validate a whole-liver radiomic model using multiparametric MRI for predicting early-stage liver fibrosis (LF) in rabbits. METHODS: A total of 134 rabbits (early-stage LF, n = 91; advanced-stage LF, n = 43) who underwent liver magnetic resonance elastography (MRE), hepatobiliary phase, dynamic contrast enhanced (DCE), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging, and T2* scanning were enrolled and randomly allocated to either the training or validation cohort. Whole-liver radiomic features were extracted and selected to develop a radiomic model and generate quantitative Rad-scores. Then, multivariable logistic regression was utilized to determine the Rad-scores associated with early-stage LF, and effective features were integrated to establish a combined model. The predictive performance was assessed by the area under the curve (AUC). RESULTS: The MRE model achieved superior AUCs of 0.95 in the training cohort and 0.86 in the validation cohort, followed by the DCE-MRI model (0.93 and 0.82), while the IVIM model had lower AUC values of 0.91 and 0.82, respectively. The Rad-scores of MRE, DCE-MRI and IVIM were identified as independent predictors associated with early-stage LF. The combined model demonstrated AUC values of 0.96 and 0.88 for predicting early-stage LF in the training and validation cohorts, respectively. CONCLUSIONS: Our study highlights the remarkable performance of a multiparametric MRI-based radiomic model for the individualized diagnosis of early-stage LF. ADVANCES IN KNOWLEDGE: This is the first study to develop a combined model by integrating multiparametric radiomic features to improve the accuracy of LF staging.

Enhancing Oral Performance of Paclitaxel Lipid-Mimic Prodrug via Modulating Type of Fatty Acids.

Owing to the serious clinical side effects of intravenous Taxol, an oral chemotherapeutic strategy is expected to be promising for paclitaxel (PTX) delivery. However, its poor solubility and permeability, high first-pass metabolism, and gastrointestinal toxicity need to be overcome. A triglyceride (TG)-like prodrug strategy facilitates oral drug delivery by bypassing liver metabolism. However, the effect of fatty acids (FAs) in sn-1,3 on the oral absorption of prodrugs remains unclear. Herein, a series of TG-mimetic prodrugs of PTX is explored with different carbon chain lengths and degrees of unsaturation of FAs at the sn-1,3 position in an attempt to enhance oral antitumor effect and to guide the design of TG-like prodrugs. Interestingly, the different FA lengths exhibit great influence on in vitro intestinal digestion behavior, lymph transport efficiency, and up to fourfold differences in plasma pharmacokinetics. The prodrug with long-chain FAs shows a more effective antitumor effect, whereas the degree of unsaturation has a negligible impact. The findings illustrate how FAs structures affect the oral delivery efficiency of TG-like PTX prodrugs and thus provide a theoretical basis for their rational design.

Simultaneous liver steatosis, fibrosis and iron deposition quantification with mDixon quant based on radiomics analysis in a rabbit model.

PURPOSE: To evaluate the feasibility of simultaneous quantification of liver fibrosis, liver steatosis and abnormal iron deposition using mDixon Quant based on radiomics analysis, and to eliminate the interference among different histopathologic features. METHODS: One hundred and twenty rabbits that were administered CCl4 for 4-16 weeks and a cholesterol rich diet for the initial 4 weeks in the experimental group and 20 rabbits in the control group were examined using mDixon. Radiomics features of the whole liver were extracted from PDFF and R2* and radiomics models for discriminating steatosis: S0-S1 vs. S2-S4, fibrosis: F0-F2 vs. F3-F4 and iron deposition: normal vs. abnormal were constructed respectively and evaluated using receiver operating characteristic (ROC) curves with the histopathological results as reference standard. Combined corrected models merging the radscore and the other two histopathologic features were evaluated using multiple logistic regression analyses and compared with radiomics models. RESULTS: The area under the ROC curve (AUC) of the radiomics model with PDFF features was 0.886 and 0.843 in the training and the test set, respectively, for the diagnosis of liver steatosis grade S0-1 and S2-S4. The radiomics model based on R2* features were 0.815 and 0.801 for distinguishing F0-F2 and F3-F4 and 0.831 and 0.738 for discriminating abnormal iron deposition in the training and test set, respectively. The corrected model for liver steatosis and fibrosis (0.944 and 0.912 in the test set) outperformed the radiomics models by eliminating the interference of histopathologic features(P < 0.05), but had comparable diagnostic performance for abnormal iron deposition(P > 0.05). CONCLUSIONS: It is feasible for mDixon to simultaneously quantify whole liver steatosis, fibrosis and iron deposition based on radiomics analysis. It is valuable to minimize the interference of different pathological features for the assessment of liver steatosis and fibrosis.

Comparing and combining MRE, T1ρ, SWI, IVIM, and DCE-MRI for the staging of liver fibrosis in rabbits: Assessment of a predictive model based on multiparametric MRI.

PURPOSE: To establish and validate an optimal predictive model based on multiparametric MRI for staging liver fibrosis (LF) in rabbits with magnetic resonance elastography (MRE), spin-lattice relaxation time in the rotating frame (T1ρ imaging), SWI, intravoxel incoherent motion (IVIM), and DCE-MRI. METHODS: The LF group included 120 rabbits induced by subcutaneous injections of carbon tetrachloride (CCl4 ); 30 normal rabbits served as the control group. Multiparametric MRI was performed, including MRE, T1ρ, SWI, IVIM, and DCE-MRI. The quantitative parameters were analyzed in two groups, with histopathological results serving as the reference standard. The diagnostic performance of multiparametric MRI and the predictive model established by multivariable logistic regression analysis were evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: In total, 32, 67, and 51 rabbits were histologically diagnosed as no fibrosis (stage F0), early-stage LF (F1-F2), and advanced-stage LF (F3-F4), respectively. The LF stages presented a strong correlation with liver stiffness (LS) on MRE (r = 0.90), signal-intensity ratio (SIR) on SWI (r = -0.84), and Ktrans on DCE-MRI (r = 0.71; p < 0.05 for all). The LS and SIR parameters had higher AUC values for distinguishing early-stage LF from both no fibrosis (0.94 and 0.93, respectively) and advanced-stage LF (0.95 and 0.87, respectively). The predictive model showed a slightly higher AUC value of 0.97 (0.90-0.99) than LS and SIR in distinguishing early-stage LF from no fibrosis (p > 0.05), a significantly higher AUC value of 0.98 (0.93-0.99) than the SIR in distinguishing early-stage from advanced-stage LF (p < 0.05). CONCLUSION: SWI, DCE-MRI, and MRE in particular showed improved performance for LF diagnosis and stage. The predictive model based on multiparametric MRI was found to further enhance diagnostic accuracy and could serve as an excellent imaging tool for staging LF.

Magnetic resonance elastography in a rabbit model of liver fibrosis: a 3-T longitudinal validation for clinical translation.

This study aimed to determine the relationships between magnetic resonance elastography (MRE) imaging biomarkers and the stages of liver fibrosis in a rabbit model of liver fibrosis, a longitudinal validation for clinical translation. Liver fibrosis was induced in 38 male New Zealand rabbits by weekly subcutaneous injections of 0.1 ml 50% carbon tetrachloride oily solution per kilogram of body weight for 4 to 10 weeks to produced varying degrees of liver fibrosis. The values for the liver stiffness (LS) MRE imaging biomarkers were measured at different stages of liver fibrosis. Masson trichrome staining of liver tissue was used to identify collagen tissue. Among the 38 rabbits, the histological studies showed liver fibrosis stage 1 (F1, n = 11), liver fibrosis stage 2 (F2, n = 8), liver fibrosis stage 3 (F3, n = 7), and liver fibrosis stage 4 (F4, liver cirrhosis, n = 12). Additional healthy rabbits served as controls (F0, n = 15). During liver fibrosis progression, the mean LS values increased during liver fibrosis progression. There were significant differences in LS values between (F0 and F1) and (F2 and F3), (F2 and F3) and (F4), and (F0 and F1) and (F4), which are three clinically relevant fibrosis groups. There was a high correlation between the LS values measured by MRE and the stages of liver fibrosis determined by histology (R2 = 0.67, P < 0.001). MRE imaging has the potential to serve as a noninvasive, unenhanced imaging technique for liver fibrosis diagnosis and staging.