Historical Models
Historical cancer disease models have relied on the use of large panels of unrelated cell-lines that have been isolated over many years from individual cancer patients who may differ genetically in hundreds of ways. This makes it very difficult to understand a drugs true mechanism; and therefore many secondary assays are required to build confidence in drug’s mode-of-action and utility in specific patient populations.
Click on the image to enlarge.
Other methods have been developed that do allow a specific disease-associated gene to be studied, but their applications are limited as they only ever approximate the real disease situation and often, do so in a manifestly non-relevant way to that seen in humans. For example:
- RNAi, can only partially remove a target gene’s activity; which in many cases will be insufficient to yield an effect on a cell. Moreover, RNAi cannot model gain-of-function mutations and is neither a stable nor specific.
- Ectopic gene over-expression systems completely fail to mimic the complex regulation and feedback loops that exist in the proper genomic context; and thus have a real danger of leading the researcher into studying a non-patient relevant genotype, phenotype or drug response.
In summary; these common older disease models, while they can be generated in high-throughput, can easily lead to misleading findings on the role of putative cancer genes and drugs that target them.
X-MAN Disease Models