Natalie Beitel-White

Pancreatic cancer is a significant cause of cancer-related deaths in the United States with an abysmal five-year overall survival rate that is under 9%. Reasons for this mortality include the lack of late-stage treatment options and the immunosuppressive tumor microenvironment. Histotripsy is an ultrasound-guided, noninvasive, nonthermal tumor ablation therapy that mechanically lyses targeted cells. To study the effects of histotripsy on pancreatic cancer, we utilized an in vitro model of pancreatic adenocarcinoma and compared the release of potential antigens following histotripsy treatment to other ablation modalities. Histotripsy was found to release immune-stimulating molecules at magnitudes similar to other nonthermal ablation modalities and superior to thermal ablation modalities, which corresponded to increased innate immune system activation in vivo. In subsequent in vivo studies, murine Pan02 tumors were grown in mice and treated with histotripsy. Flow cytometry and rtPCR were used to determine changes in the tumor microenvironment over time compared to untreated animals. In mice with pancreatic tumors, we observed significantly increased tumor-progression-free and general survival, with increased activation of the innate immune system 24 h posttreatment and decreased tumor-associated immune cell populations within 14 days of treatment. This study demonstrates the feasibility of using histotripsy for pancreatic cancer ablation and provides mechanistic insight into the initial innate immune system activation following treatment. Further work is needed to establish the mechanisms behind the immunomodulation of the tumor microenvironment and immune effects.

Objective: Tissue electroporation is achieved by applying a series of electric pulses to destabilize cell membranes within the target tissue. The treatment volume is dictated by the electric field distribution, which depends on the pulse parameters and tissue type and can be readily predicted using numerical methods. These models require the relevant tissue properties to be known beforehand. This study aims to quantify electrical and thermal properties for three different tissue types relevant to current clinical electroporation. Methods: Pancreatic, brain, and liver tissue were harvested from pigs, then treated with IRE pulses in a parallel-plate configuration. Resulting current and temperature readings were used to calculate the conductivity and its temperature dependence for each tissue type. Finally, a computational model was constructed to examine the impact of differences between tissue types. Results: Baseline conductivity values (mean 0.11, 0.14, and 0.12 S/m) and temperature coefficients of conductivity (mean 2.0, 2.3, and 1.2 % per degree Celsius) were calculated for pancreas, brain, and liver, respectively. The accompanying computational models suggest field distribution and thermal damage volumes are dependent on tissue type. Conclusion: The three tissue types show similar electrical and thermal responses to IRE, though brain tissue exhibits the greatest differences. The results also show that tissue type plays a role in the expected ablation and thermal damage volumes. Significance: The conductivity and its changes due to heating are expected to have a marked impact on the ablation volume. Incorporating these tissue properties aids in the prediction and optimization of electroporation-based therapies.

Immunotherapies have demonstrated limited efficacy in pancreatic ductal adenocarcinoma (PDAC) patients despite their success in treating other tumor types. This limitation is largely due to the relatively immunosuppressive environment surrounding the tumor. A focal ablative technique called irreversible electroporation (IRE) has been shown to modulate this environment, enhancing the efficacy of immunotherapy. One enhancing factor related to improved prognosis is a decrease in regulatory T cells (T_reg). This decrease has been previously unpredictable for clinicians using IRE, who currently have limited real-time metrics for determining the activation of the patient’s immune response. Here, we report that larger overall changes in output current are correlated with larger decreases in T cell populations 24 hours post-treatment. This result suggests that clinicians can make real-time decisions regarding optimal follow-up therapy based on the range of output current delivered during treatment. This capability could maximize the immunomodulating effect of IRE in synergy with follow-up immunotherapy. Additionally, these results suggest that feedback from a preliminary IRE treatment of the local tumor may help inform clinicians regarding the timing and choice of subsequent therapies, such as resection, immunotherapy, chemotherapy, or follow-up thermal or non-thermal ablation.

Irreversible electroporation (IRE) is a cancer therapy that uses short, high-voltage electrical pulses to treat tumors. Due to its predominantly non-thermal mechanism and ability to ablate unresectable tumors, IRE has gained popularity in clinical treatments of both liver and pancreatic cancers. Existing computational models use electrical properties of animal tissue that are quantified a priori to predict the area of treatment in three dimensions. However, the changes in the electrical properties of human tissue during IRE treatment are so far unexplored. This work aims to improve models by characterizing the dynamic electrical behavior of human liver and pancreatic tissue. Fresh patient samples of each tissue type, both normal and tumor, were collected and IRE pulses were applied between two parallel metal plates at various voltages. The electrical conductivity was determined from the resistance using simple relations applicable to cylindrical samples. The results indicate that the percent change in conductivity during IRE treatments varies significantly with increasing electric field magnitudes. This percent change versus applied electric field behavior can be fit to a sigmoidal curve, as proposed in prior studies. The generic conductivity data from human patients from this work can be input to computational software using patient-specific geometry, giving clinicians a more accurate and personalized prediction of a given IRE treatment.