Patient-derived Orthotopic Xenograft Models for Human Urothelial Cell Carcinoma and Colorectal Cancer Tumor Growth...

Cancer patients have poor prognoses when lymph node (LN) involvement is present in both high-grade urothelial cell carcinoma (HG-UCC) of the bladder and colorectal cancer (CRC). More than 50% of patients with muscle-invasive UCC, despite curative therapy for clinically-localized disease, will develop metastases and die within 5 years, and metastatic CRC is a leading cause of cancer-related deaths in the US. Xenograft models that consistently mimic UCC and CRC metastasis seen in patients are needed. This study aims to generate patient-derived orthotopic xenograft (PDOX) models of UCC and CRC for primary tumor growth and spontaneous metastases under the influence of LN stromal cells mimicking the progression of human metastatic diseases for drug screening. Fresh UCC and CRC tumors were obtained from consented patients undergoing resection for HG-UCC and colorectal adenocarcinoma, respectively. Co-inoculated with LN stromal cell (LNSC) analog HK cells, luciferase-tagged UCC cells were intra-vesically (IB) instilled into female non-obese diabetic/severe combined immunodeficiency (NOD/SCID) mice, and CRC cells were intra-rectally (IR) injected into male NOD/SCID mice. Tumor growth and metastasis were monitored weekly using bioluminescence imaging (BLI). Upon sacrifice, primary tumors and mouse organs were harvested, weighed, and formalin-fixed for Hematoxylin and Eosin and immunohistochemistry staining. In our unique PDOX models, xenograft tumors resemble patient pre-implantation tumors. In the presence of HK cells, both models have high tumor implantation rates measured by BLI and tumor weights, 83.3% for UCC and 96.9% for CRC, and high distant organ metastasis rates (33.3% detected liver or lung metastasis for UCC and 53.1% for CRC). In addition, both models have zero mortality from the procedure. We have established unique, reproducible PDOX models for human HG-UCC and CRC, which allow for tumor formation, growth, and metastasis studies. With these models, testing of novel therapeutic drugs can be performed efficiently and in a clinically-mimetic manner.