Comparative Study of the Effects of Ferrochelatase-siRNA Transfection Mediated by Ultrasound Microbubbles and Polyethyleneimine in Combination with Low-dose ALA to Enhance PpIX Accumulation in Human Endometrial Cancer Xenograft Nude Mice Models

Metabolomic Detection Between Pancreatic Cancer and Liver Metastasis Nude Mouse Models Constructed by Using the PANC1-KAI1/CD82 Cell Line

Background: Pancreatic cancer (PC) has a poor prognosis and is prone to liver metastasis. The KAI1/CD₈₂ gene inhibits PC metastasis. This study aimed to explore differential metabolites and enrich the pathways in serum samples between PC and liver metastasis nude mouse models stably expressing KAI1/CD₈₂. Methods: KAI1/CD₈₂-PLV-EF1α-MCS-IRES-Puro vector and PANC1 cell line stably expressing KAI1/CD₈₂ were constructed for the first time. This cell line was used to construct 3 PC nude mouse models and 3 liver metastasis nude mouse models. The different metabolites and Kyoto encyclopedia of genes and genomes (KEGG) and human metabolome database (HMDB) enrichment pathways were analyzed using the serum samples of the 2 groups of nude mouse models on the basis of untargeted ultra-performance liquid chromatography-tandem mass spectrometry platform. Results: KAI1/CD₈₂-PLV-EF1α-MCS-IRES-Puro vector and PANC1 cell line stably expressing KAI1/CD₈₂ were constructed successfully, and all nude mouse models survived and developed cancers. Among the 1233 metabolites detected, 18 metabolites (9 upregulated and 9 downregulated) showed differences. In agreement with the literature data, the most significant differences between both groups were found in the levels of bile acids (taurocholic acid, chenodeoxycholic acid), glycine, prostaglandin E2, vitamin D, guanosine monophosphate, and inosine. Bile recreation, primary bile acid biosynthesis, and purine metabolism KEGG pathways and a series of HMDB pathways (P < .05) contained differential metabolites that may be associated with liver metastasis from PC. However, the importance of these metabolites on PC liver metastases remains to be elucidated. Conclusions: Our findings suggested that the metabolomic approach may be a useful method to detect potential biomarkers in PC.

Imaging of Preclinical Endometrial Cancer Models for Monitoring Tumor Progression and Response to Targeted Therapy

Endometrial cancer is the most common gynecologic malignancy in industrialized countries. Most patients are cured by surgery; however, about 15% of the patients develop recurrence with limited treatment options. Patient-derived tumor xenograft (PDX) mouse models represent useful tools for preclinical evaluation of new therapies and biomarker identification. Preclinical imaging by magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), single-photon emission computed tomography (SPECT) and optical imaging during disease progression enables visualization and quantification of functional tumor characteristics, which may serve as imaging biomarkers guiding targeted therapies. A critical question, however, is whether the in vivo model systems mimic the disease setting in patients to such an extent that the imaging biomarkers may be translatable to the clinic. The primary objective of this review is to give an overview of current and novel preclinical imaging methods relevant for endometrial cancer animal models. Furthermore, we highlight how these advanced imaging methods depict pathogenic mechanisms important for tumor progression that represent potential targets for treatment in endometrial cancer.