Gene Mutation Helps To Predict Drug Responsiveness In Cancer Patients

Gene Mutation Helps To Predict Drug Responsiveness In Cancer Patients?

Although the theory behind inhibitor targeted therapy is appealing, the reality is more complex. Cancer cells often have many mutations in many different pathways, so even if one route is shut down by a targeted treatment, the cancer cell may be able to use other routes.

In other words, cancer cells have "backup systems" that allow them to survive. The result is that the drug does not affect the tumor as expected. The cancer state is typically characterized by a signaling process that is unregulated and in a continuous state of activation.

In chemotherapy selection, molecular profiling examines a single process within the cell or a relatively small number of processes. All a gene mutation study can tell is whether or not the cells are potentially susceptible to a mechanism of attack. The aim is to tell if there is a theoretical predisposition to drug response.

It doesn't tell you the effectiveness of one drug (or combination) or any other drug which may target this in the individual. There are many mechanisms/pathways to altered cellular function.

Another more practical approach to this problem would be to target multiple pathways in a cancer cell. The challenge is to identify for which patients the targeted treatment will be effective (enzyme inhibitors, proteasome inhibitors, angiogenesis inhibitors, and monoclonal antibodies).

What is needed is to test the concept of targeted cancer drugs with biomarkers as pharmacodynamic endpoints, and with the ability to measure multiple parameters in cellular screens now in hand using flow cytometry. And actually test these targeted drugs against the fresh tumor specimen.

I believe functional profiling would be more beneficial. It measures what happens at the end, rather than the status of the individual mechanisms/pathways. It assesses the activity of a drug (or combinations) upon combined effect of all cellular processes, using combined metabolic and morphologic endpoints, at the cell population level, measuring the interaction of the entire genome.

No matter which mutation is being affected, functional profiling is measuring it through the surrogate of measuring if the cell is alive or dead. The key to understanding the genome is understanding how cells work. How is the cell being killed regardless of the mechanism/pathway.

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