PERSONALIZED MEDICINE

Personalized Cancer Therapy - Profiling Genetic Changes

DNA is not the whole story

Pharmacogenomics can be defined as the study of how a person's genetic makeup determines response to a drug. Whether a medicine works well for you or whether it causes serious side effects, depends, to a certain extent, on your genes.

A challenge facing pharmacogenomic profiling in cancer cell lines is the number and complexity of interactions a drug has with biological molecules in the body. Variations in many different molecules may influence how someone responds to a medicine. Teasing out the genetic patterns associated with particular drug responses involves some intricate and time-consuming scientific detective work.

DNA is not the whole story. Genomics has provided sophisticated target therapies, but cellular pathways contain redundancies that can be activated in response to inhibition of one or another pathway, thus promoting emergence of resistant cells and clinical relapse.

Cancer cells utilize cross-talk and redundancy to circumvent targeted therapies. They back up, zig-zag and move in reverse, regardless of what the sign posts say. Using genomic signatures to predict response is like saying the Dr. Seuss and Shakespeare are truly the same because they use the same words.

The building blocks of human biology are carefully construed into the complexities that we recognize as human beings. However, appealing genotyping analysis may appear to those engaged in this field, it will be years before these profiles can approximate the vagaries of human cancer.

The endpoints genotyping analysis are gene expression, examining a single process (pathway) within the cell or a relatively small number of processes (pathways) to test for "theoretical" candidates for targeted therapy.

The endpoints of phenotyping analysis are expression of cell-death, both tumor cell-death and tumor associated endothelial (capillary) cell-death (tumor and vascular death), and examines not only for the presence of the molecular profile, but also for its functionality, the interaction with other genes, proteins and other processes occurring within the cell, and for its "actual" response to anti-cancer drugs (not theoretical susceptibility).

Phenotyping analysis measures biological signals rather than DNA indicators, provides clinically validated information and plays an important role in cancer drug selection. The data that support phenotyping analysis is demonstrably greater and more compelling than any data currently generated from genotyping analysis.

Phenotyping measures the response of the tumor cells to drug exposure. Following this exposure, it measures both cell metabolism and cell morphology. The integrated effect of the drugs on the whole cell, resulting in a cellular response to the drug, measuring the interaction of the entire genome. No matter which genes are being affected, it is measuring them through the surrogate of measuring if the cell is alive or dead.

We don't know how to handle one gene, never mind 20,000 genes. To put this in context, two percent of the human genome that codes for known proteins (the part that everyone currently studies) represents only 1/20 of the whole story.

A more highly productive direction would be to investigate the targeting agents in each individual patient's tissue culture, alone and in combination with other drugs, to guage the likelihood that the targeting will favorably influence each patient's outcome.

The need for phenotyping analysis has never been greater. As systems biologists point out, complexity is the hallmark of biological existence. Any attempts to oversimplify phenomena that cannot be simplified, have, and will continue to lead us in the wrong direction.

http://cancerfocus.org/forum/showthread.php?t=3666