Cancer Model Database

Testing your compound in a disease-relevant environment saves substantial time and money on the path to the clinic. Using our cancer model database (i.e., the Tumor Model Compendium), you can create a more targeted study design from the start by selecting the most appropriate tumor model for your preclinical program. By searching for specific histology or molecular properties our cancer model database can help you select the most relevant model for your research needs.

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Micropathology of breast tumor model, to represent the tumor models available in Charles River’s Cancer Model Database.

The Right Tumor Model Speeds Entrance to the Clinic

How can our cancer model database improve your drug discovery?

Julia Schueler, Research Director for Discovery Services, explains how her team used the cancer model database to select the most relevant models for the well-known target EGFR to showcase the feasibility of the selection in the different drug development platforms, including 2D in vitro cell line screening, 3D ex vivo colony assays, and in vivo efficacy tests. Watch the video to see how the cancer model database can support your in vitro, in vivo, and ex vivo studies.


Initial Tumor Model Selection

Allowing you to search by features of interest, our cancer model database facilitates model selection, whether it be for cell line screening, 3D culture assays, or an in vivo study. Search parameters include histologies, gene expression, copy number variation, and whole exome sequencing data, or a combination search across molecular properties. You can even do a combination search across several properties (e.g., mutation and gene expression).

  • Gene expression determined by Affymetrix® Human Genome U133 Plus 2.0 Array
  • RNA-seq data (gene expression, mRNA mutations, fusions, HLA predictions)
  • Whole exome mutations determined by next generation sequencing
  • Gene copy number variations determined by Affymetrix® Genome-Wide Human SNP Array 6.0

Visualize and analyze data per molecular features or tumor types and download the data to your computer for further analysis.

You can then verify protein expression using our tissue microarray services, which quickly detect antigens across a broad panel of tumors via immunohistochemistry.


In Vitro-Aided Tumor Model Selection

Seen as the industry standard for early toxicity and patient identification, in vitro oncology is a critical means of testing the efficacy of compounds in a rapid, reliable, and cost-effective way. Simplifying and speeding what can be an otherwise time-consuming process, Charles River’s unique cancer model database is a valuable resource for oncology researchers as they enter the critical in vitro stages of their work.

Using data from the compendium, we can select the best in vitro model to test your compound from our selection of 2D in vitro assays and 3D ex vivo assays. A 3D tumor colonogenic assay pilot study can add value by allowing you to evaluate known responders and known non-responders and screen numerous models in a cost-effective way.

In vitro assays for tumor model selection in oncology research

In Vivo Discovery

Before moving into full-scale in vivo models, in vivo proof-of-concept, mini-screens, and single mouse trials can be useful.

  • Proof-of-concept studies can be used for models with highest expression of target
  • Mini screen is used for screening efficacy and can be useful for testing combination regimens
  • Single mouse trial format addresses the need for more cost-effective compound testing in larger, more diverse tumor populations that can be targeted using our vast portfolio of highly characterized models

Our cancer model data and pre-selection process ensure you have selected the most relevant model for full-scale in vivo efficacy models. The cancer model database includes tumor models from a wide range of tumor subtypes, including patient-derived xenografts (PDX), cell line-derived xenografts (CDX), and mouse syngeneic models.

You can view our models and data across a range of different histotypes that closely mimic the required cancer of your drug development.

Screenshot from the tumor model database.

 

Our integrated approach using in vitro 2D, ex vivo 3D, in vivo models, and bioinformatics data facilitates drug development and accelerates your oncology research.

Login to access Charles River's Cancer Model Database; search parameters include tumor histology, mRNA expression level, gene copy number alteration, and whole exome sequencing mutation profiles. Search criteria can be used individually and in combination. The wealth of information we have collected on each PDX model guides our suggestions as to which PDX models are suited best to help you to reach your research goals.