Particles and Prejudice: Nanomedicine Approaches to Reducing Health Disparities in Endometrial Cancer

Abstract

Endometrial cancer is the most common gynecological malignancy worldwide and unfortunately has a much higher mortality rate in Black women compared with White women. Many potential factors contribute to these mortality rates, including the underlying effects of systemic and interpersonal racism. Furthermore, other trends in medicine have potential links to these rates including participation in clinical trials, hormone therapy, and pre‐existing health conditions. Addressing the high incidence and disparate mortality rates in endometrial cancer requires novel methods, such as nanoparticle‐based therapeutics. These therapeutics have been growing in increasing prevalence in pre‐clinical development and have far‐reaching implications in cancer therapy. The rigor of pre‐clinical studies is enhanced by the likeness of the model to the human body. In systems for 3D cell culture, for example, the extracellular matrix mimics the tumor more closely. The increasing emphasis on precision medicine can be applied to cancer using nanoparticle‐based methods and applied to pre‐clinical models by using patient‐derived model data. This review highlights the intersections of nanomedicine, precision medicine, and racial disparities within endometrial cancer and provides insights into reducing health disparities using recent scientific advances on the nanoscale.

Engineering a three-dimensional multilayer multicellular model of endometrial cancer for high throughput drug screening and novel treatment methods

“…Specifically, we evaluated the influence of the concentration of Col I, fibrinogen and a synthetic polymer PEGDA (10% w/v) or GelMA (7% w/v) in the bottom hydrogel layer; and Col IV, fibronectin, laminin and a PEGDA (10% w/v) or GelMA (7% w/v) in the top hydrogel layer. From the experimental results, we generated multivariant models of microvessel length, endometrial invasion depth, endothelial cell coverage, and endometrial cancer coverage, with predicted vs. observed R 2 values of 0.89, 0.89, 0.70, and 0.83, respectively, and Q 2 values ≥0.50 suggesting that the number of model terms adequately fit the model. The R 2 -adjusted values, though slightly lower, remain robust and underline the model’s reliability.…”

“…From the experimental results, we generated multivariant models of microvessel length, endometrial invasion depth, endothelial cell coverage, and endometrial cancer coverage, with predicted vs. observed R 2 values of 0.89, 0.89, 0.70, and 0.83, respectively, and Q 2 values ≥0.50 suggesting that the number of model terms adequately fit the model. The R 2 -adjusted values, though slightly lower, remain robust and underline the model’s reliability. Finally, the G-efficiency of the model was 51.32%.…”

“…23 In our studies, the 2D IC 50 values do not support the known Paclitaxel sensitivity of the cell lines, however, the 3D models align with previous findings which show the 3D model better predicts the in vivo behavior. 39…”

“…23 In our studies, the 2D IC50 values do not support the known Paclitaxel sensitivity of the cell lines, however, the 3D models align with previous findings which show the 3D model better predicts the in vivo behavior. 39 In addition to cell viability, we assessed cancer invasion and microvessel length, to provide a broader evaluation of metastatic behavior. Interestingly, our findings revealed that Paclitaxel treatment had a more pronounced effect on KLE invasion compared to KLE cell viability.…”

“…Endometrial cancer, the most common gynecological cancer in developed countries and the sixth most common type of cancer worldwide, presents a significant healthcare challenge. 1,2 In 2023, 66,200 women were diagnosed with this disease and over 13,000 women died from endometrial cancer in the United States alone. 3 While early-stage endometrial cancer can be effectively treated with surgery, chemotherapy, and radiation, advanced stages often have poor prognoses, with a five year survival rate under 20%, primarily due to metastasis.…”