Longitudinal Monitoring of Simulated Interstitial Fluid Pressure for Pancreatic Ductal Adenocarcinoma Patients Treated with Stereotactic Body Radiotherapy

A Comparative Analysis of Alpha and Beta Therapy in Prostate Cancer Using a 3D Image-Based Spatiotemporal Model

PURPOSE

In treating prostate cancer, distinguishing alpha and beta therapies is vital for efficient radiopharmaceutical delivery. Our study introduces a 3D image-based spatiotemporal computational model that utilizes MRI-derived images to evaluate the efficacy of 225Ac-PSMA and 177Lu-PSMA therapies. We examine the impact of tumor size, diffusion, interstitial fluid pressure (IFP), and interstitial fluid velocity (IFV) on the absorbed doses.

METHODS

An MRI-based geometric model of the tumor and its surrounding environment is initially developed. Subsequently, COMSOL Multiphysics software is utilized to solve convection-diffusion-reaction equations and conduct numerical analyses of blood pressure distribution. This computational methodology provides valuable insights into interstitial fluid patterns and the spatiotemporal distribution of extracellular and intracellular concentrations of 225Ac-PSMA and 177Lu-PSMA. In addition, our study investigates the impacts of increasing tumor size on absorbed doses and mechanisms involved in radiopharmaceutical transport and delivery.

RESULTS

Larger tumors have diminished absorbed doses, highlighting the need for customized treatments according to tumor size. Diffusion significantly influences the transport and delivery of radiopharmaceuticals. Additionally, alpha therapy was observed to consistently yield higher absorbed doses within the tumor than beta therapy.

CONCLUSIONS

This study reveals the complex interplay between radiopharmaceutical properties, the tumor microenvironment, and treatment outcomes. It highlights the potential of 225Ac-PSMA in prostate cancer treatment, advocating for personalized treatment strategies tailored to the specific characteristics of each patient and their tumor.

Transcytosis-Triggering Nanoparticles for Overcoming Stromal Barriers and Reversing Immunosuppression in Pancreatic Cancer Combinatorial Therapy

In pancreatic ductal adenocarcinoma (PDAC), stromal cells and matrix proteins form a dense physical barrier that, while preventing the outward spread of tumor cells, also limits the penetration of drugs and CD8+ T cells inward. Additionally, the overactivated TGF-β/SMAD signaling pathway further promotes matrix proliferation and immune suppression. Therefore, crossing the stromal barrier while preserving the integrity of the stroma, releasing drugs intratumorally, remodeling the stroma, and activating the immune system is a promising drug delivery strategy. In this work, a type of enamine N-oxides modified nanoparticle was prepared, with stearic acid-modified gemcitabine prodrug (GemC18) and pSMAD2/3 inhibitor galunisertib encapsulated. The peripheral enamine N-oxides can trigger transcytosis and then respond to hypoxia and acidic microenvironments, turning the surface charge of the nanoparticles to a positive charge and enhancing penetration. The released galunisertib inhibits the TGF-β/SMAD signaling pathway, reshapes the matrix, activates antitumor immunity, and combines with gemcitabine (Gem) to kill tumor cells.

Recent advances in drug delivery and targeting for the treatment of pancreatic cancer

Despite significant treatment efforts, pancreatic ductal adenocarcinoma (PDAC), the deadliest solid tumor, is still incurable in the preclinical stages due to multifacet stroma, dense desmoplasia, and immune regression. Additionally, tumor heterogeneity and metabolic changes are linked to low grade clinical translational outcomes, which has prompted the investigation of the mechanisms underlying chemoresistance and the creation of effective treatment approaches by selectively targeting genetic pathways. Since targeting upstream molecules in first-line oncogenic signaling pathways typically has little clinical impact, downstream signaling pathways have instead been targeted in both preclinical and clinical studies. In this review, we discuss how the complexity of various tumor microenvironment (TME) components and the oncogenic signaling pathways that they are connected to actively contribute to the development and spread of PDAC, as well as the ways that recent therapeutic approaches have been targeted to restore it. We also illustrate how many endogenous stimuli-responsive linker-based nanocarriers have recently been developed for the specific targeting of distinct oncogenes and their downstream signaling cascades as well as their ongoing clinical trials. We also discuss the present challenges, prospects, and difficulties in the development of first-line oncogene-targeting medicines for the treatment of pancreatic cancer patients.

Characterization of Microvascular Invasion in Hepatocellular Carcinoma Using Computational Modeling of Interstitial Fluid Pressure and Velocity

BACKGROUND

Most solid tumors show increased interstitial fluid pressure (IFP), and this increased IFP is an obstacle to treatment. A noninvasive model for measuring IFP in hepatocellular carcinoma (HCC) is an unresolved issue.

PURPOSE

To develop a noninvasive model to measure IFP and interstitial fluid velocity (IFV) in HCC and to characterize the microvascular invasion (MVI) status by using this model.

STUDY TYPE

Retrospective.

POPULATION

A total of 97 HCC patients (mean age 57.6 ± 10.9 years, 77.3% males), 53 of them with MVI and 44 of them without MVI.

FIELD STRENGTH/SEQUENCE

A 3-T, three-dimensional spoiled gradient-recalled echo.

ASSESSMENT

MVI was defined as microscopic vascular invasion of small vessels within the peritumoral liver tissue. The volumes of interest (VOIs) were manually delineated and enclosed the tumor lesion and healthy liver parenchyma, respectively. The extended Tofts model (ETM) was used to estimate permeability parameters from all the VOIs. Subsequently, the continuity partial differential equation (PDE) was implemented and IFP and IFV were acquired.

STATISTICAL TESTS

Wilcoxon signed-ranks tests, histogram analysis, Mann-Whitney U test, Fisher's exact test, least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC), Youden index, DeLong test, and Benjamini-Hochberg correction. A P value <0.05 was considered statistically significant.

RESULTS

The HCC lesions exhibited elevated IFP and reduced IFV. There were no significant differences in any measured demographic and clinical features between the MVI-positive and MVI-negative groups, except for tumor size. Nine IFP histogram analysis-derived parameters and seven IFV histogram analysis-derived parameters could be used to characterize the MVI status. LASSO regression selected five features: IFP maximum, IFP 10th percentile, IFP 90th percentile, IFV SD, and IFV 10th percentile. The combination of these features showed the highest AUC (0.781) and specificity (77.3%).

DATA CONCLUSION

A noninvasive IFP and IFV measurement model for HCC was developed. Specific IFP- and IFV-derived parameters exhibited significant association with the MVI status.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 2.