A Molecularly Characterized Preclinical Platform of Subcutaneous Renal Cell Carcinoma (RCC) Patient-Derived Xenograft
Dennis Gürgen1, Michael Becker1, Mathias Dahlmann1
1Experimental Pharmacology and Oncology Berlin-Buch GmbH (EPO), Berlin, Germany.
Abstract:
Renal cell carcinoma (RCC) is a kidney cancer with an onset mainly during the sixth or seventh decade of the patient's life. Patients with advanced, metastasized RCC have a poor prognosis. The majority of patients develop treatment resistance towards Standard of Care (SoC) drugs within months. Tyrosine kinase inhibitors (TKIs) are the backbone of first-line therapy and have been partnered with an immune checkpoint inhibitor (ICI) recently. Despite the most recent progress, the development of novel therapies targeting acquired TKI resistance mechanisms in advanced and metastatic RCC remains a high medical need. Preclinical models with high translational relevance can significantly support the development of novel personalized therapies. It has been demonstrated that patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In the present project, we established and molecularly characterized a comprehensive panel of subcutaneous RCC PDX models with well-conserved molecular and pathological features over multiple passages. Drug screening towards four SoC drugs targeting the vascular endothelial growth factor (VEGF) and PI3K/mTOR pathway revealed individual and heterogeneous response profiles in those models, very similar to observations in patients. As unique features, our cohort includes PDX models from metastatic disease and multi-tumor regions from one patient, allowing extended studies on intra-tumor heterogeneity (ITH). The PDX models are further used as basis for developing corresponding in vitro cell culture models enabling advanced high-throughput drug screening in a personalized context. PDX models were subjected to next-generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in RCC. In summary, we report a newly established and molecularly characterized panel of RCC PDX models with high relevance for translational preclinical research.
Insights
We developed new kidney cancer models that mimic patient tumors to test new therapies. These models show varied responses to standard drugs, aiding personalized treatment development for advanced renal cell carcinoma (RCC).
Area of Science:
- Oncology
- Translational Research
- Cancer Modeling
Background:
- Advanced renal cell carcinoma (RCC) has a poor prognosis, with frequent resistance to standard therapies like tyrosine kinase inhibitors (TKIs).
- There is a critical need for novel therapies targeting TKI resistance mechanisms in metastatic RCC.
- Patient-derived xenograft (PDX) models are vital for preclinical evaluation of targeted therapies and combinations.
Purpose of the Study:
- To establish and molecularly characterize a panel of renal cell carcinoma (RCC) patient-derived xenograft (PDX) models.
- To assess the translational relevance of these PDX models for preclinical drug screening and personalized therapy development.
- To investigate intra-tumor heterogeneity (ITH) in RCC using PDX models from metastatic and multi-tumor regions.
Main Methods:
- Established and characterized subcutaneous RCC PDX models over multiple passages.
- Performed drug screening of four standard-of-care (SoC) drugs targeting VEGF and PI3K/mTOR pathways.
- Utilized next-generation sequencing (NGS) for molecular characterization, including mutational and gene expression analysis.
Main Results:
- The PDX models demonstrated well-conserved molecular and pathological features, mirroring patient heterogeneity in drug responses.
- Models derived from metastatic disease and multi-tumor regions allowed for studies on intra-tumor heterogeneity (ITH).
- Molecular characterization identified potential biomarkers and treatment targets for RCC.
Conclusions:
- A novel, molecularly characterized panel of RCC PDX models with high translational relevance has been established.
- These PDX models accurately reflect patient drug response heterogeneity, supporting personalized preclinical research.
- The models provide a foundation for developing in vitro models for high-throughput drug screening in a personalized context.
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