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Development of a highly pulmonary metastatic orthotopic renal cell carcinoma murine model.

ABSTRACT: The incidence of renal cell carcinoma (RCC) is high, and its outcomes remain poor. Mortality is attributable largely to metastatic disease and a dearth of effective therapeutic interventions. The lungs are the most common metastatic site. To elucidate the biological mechanisms underlying pulmonary metastasis and identify superior therapeutic strategies, we developed a novel and clinically relevant murine RCC model exhibiting enhanced pulmonary metastasis. Mice underwent intrarenal implantation using luciferase-expressing Renca, a murine renal adenocarcinoma cell line. Primary renal tumor progression and development of metastatic lung lesions were monitored in live mice using bioluminescent imaging, followed by post-mortem organ assessment. Cells were isolated from pulmonary metastases for reimplantation, followed by repeat monitoring and assessment. This process was repeated once more for a total of two in vivo passages to select for pulmonary metastatic Renca cell subpopulations. However, a single round of in vivo selection was sufficient to produce a near-maximally metastatic subpopulation. Relative to Renca cell-implanted mice, subpopulation-implanted mice exhibited shorter implantation-metastasis intervals (5 days), shorter implantation-moribundity intervals (sacrificed at 18.6±2.9 versus 22.3±1.1 days), a higher number of metastatic lung lesions at 23 days (183.9±39.0 versus 172.6±38.2) and poorer survival. Implantation of cells derived from the second round of in vivo selection produced no further significant differences in the above metrics. This model consistently and efficiently recapitulates RCC pulmonary metastasis while allowing in vivo monitoring of tumor progression, thereby facilitating elucidation of the molecular mechanisms underlying pulmonary metastasis and evaluation of therapeutic modalities.

SUBMITTER: Park JS

PROVIDER: S-EPMC8084570 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Accurate prediction of outcome for metastatic renal cell carcinoma (mRCC) patients receiving targeted therapy is essential. Most of the available models have been developed in patients treated with cytokines, while most of them are fairly complex, including at least five factors. We developed and externally validated a simple model for overall survival (OS) in mRCC. We also studied the recently validated International Database Consortium (IDC) model in our data sets.The development cohort included 170 mRCC patients treated with sunitinib. The final prognostic model was selected by uni- and multivariate Cox regression analyses. Risk groups were defined by the number of risk factors and by the 25th and 75th percentiles of the model's prognostic index distribution. The model was validated using an independent data set of 266 mRCC patients (validation cohort) treated with the same agent.Eastern Co-operative Oncology Group (ECOG) performance status (PS), time from diagnosis of RCC and number of metastatic sites were included in the final model. Median OS of patients with 1, 2 and 3 risk factors were: 24.7, 12.8 and 5.9 months, respectively, whereas median OS was not reached for patients with 0 risk factors. Concordance (C) index for internal validation was 0.712, whereas C-index for external validation was 0.634, due to differences in survival especially in poor-risk populations between the two cohorts. Predictive performance of the model was improved after recalibration. Application of the mRCC International Database Consortium (IDC) model resulted in a C-index of 0.574 in the development and 0.576 in the validation cohorts (lower than those recently reported for this model). Predictive ability was also improved after recalibration in this analysis. Risk stratification according to IDC model showed more similar outcomes across the development and validation cohorts compared with our model.Our model provides a simple prognostic tool in mRCC patients treated with a targeted agent. It had similar performance with the IDC model, which, however, produced more consistent survival results across the development and validation cohorts. The predictive ability of both models was lower than that suggested by internal validation (our model) or recent published data (IDC model), due to differences between observed and predicted survival among intermediate and poor-risk patients. Our results highlight the importance of external validation and the need for further refinement of existing prognostic models.

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Development of a highly pulmonary metastatic orthotopic renal cell carcinoma murine model.

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