gpawelski Posted April 18, 2013 Share Posted April 18, 2013 The latest thing in cancer treatment are so-called "targeted" therapies, the most prominent of which now are tyrosine kinase inhibitors (e.g. gefitinib, erlotinib, sunitinib, sorafenib). These drugs are very expensive and work most often modestly in a minority of cases. We are now beginning to be able to use molecular profiling to provide personalized treatment that offers hope of improved survival and less toxicity from therapy. And the ability to provide this molecular diagnostic test on a worldwide basis with rapid turnaround will be critical for further clinical research and application in the clinic. What were the data supporting the use of this testing? Prospective, randomized trials showing improved treatment outcomes in patients so tested? Nope. Prospective trials, showing survival advantages in patients with "positive" test results? Nope. Prospective trials, showing response advantages in patients with "positive" test results? Nope. Retrospective trials, showing both response and survival advantages in patients with "positive" test results, in thousands of patients, from multiple laboratories? Nope. Two entirely retrospective studies, from two Harvard-affiliated hospitals, showing response, but not survival, advantages with a grand total of 26 assay/treatment correlations? Yes. A subsequent study from another laboratory did not show correlations between gene mutations and patient survival. So, the clinical application of DNA content assays have been shown to correlate only with response and not survival, and only in a handful of patients, and only in entirely retrospective studies. What is going on here? From a scientific perspective, the principal reason why the war on cancer has largely failed is due to an almost obsessive and myopic focus on targeting cancer cells and tumors at the expense of addressing the underlying factors that cause cancer in the first place. Although the theory behind targeted therapy is appealing, the reality is more complex. For example, 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 shrink the tumor as expected. One approach to this problem is to functionally target multiple pathways in a cancer cell. Another challenge is to identify which of the targeted treatments will be effective (enzyme inhibitors, proteasome inhibitors, angiogenesis inhibitors, and monoclonal antibodies). Targeted therapy is still trial-and-error treatment. Medical research has focused a great deal on developing DNA (genomic) tests to identify gene expressions, amplifications and mutations relevant to cancer. The hope is that genetic information will enable researchers to better predict how you will respond to various treatment options. However, when it comes to predicting the best treatment, unlocking the complexities of your DNA is simply not the answer. In fact, a March 2010 study in the Journal of the National Cancer Institute looked at the value of a number of gene tests and concluded none of the studies showed “clear usefulness.” http://jnci.oxfordjournals.org/content/102/7/NP.1.full While genomic analysis can provide a veneer of information, unraveling the complexity of human tumor biology is beyond the scope of these analyses. Gene tests cannot capture the myriad of factors that ultimately determine how tumor cells will behave inside the body. Simply put, the human body is much more complex than the sum of its genes. For example: a flower seed may have the genetic instructions to become a rose. But, its genes will not necessarily determine its size, number of blooms, etc. These features are heavily influenced by non-genetic and environmental factors, such as the soil, nutrients, water, sun exposure, pathogens and the climate in which the seed is nurtured. No good gardener would attempt to tell you how your future bouquet will look by simply examining a packet of flower seeds. Similarly, no good doctor should attempt to choose drugs based solely on genomic analyses. Most physicians realize that genotype does not equal phenotype. By testing your tumor in its native state, “functional profiling” takes not just your genomic make-up into consideration, but your cells’ entire biology. Treatment based on genetic testing is still a guessing game. Selecting drugs and combinations through the functional profiling of a tumor sample can predict response to treatment. The functional profiling platform can explore multiple signaling pathways from the same test. It doesn't have to test for each and every signaling pathways there are. There are many pathways to altered cellular function. Testing for these pathways, those which identify DNA, or RNA sequences or expression of individual genes or proteins often examine only one component of a much larger, interactive process. In testing for all "known" mutations, if you miss just one, it may be the one that gets through. And it's not just only targeted drugs that may be effective as first-line treatment on your individual cancer cells. Cancers share pathways across tumor types. There really is no lung cancer chemos, or breast cancer chemos, or ovarian cancer chemos. There are chemos that are sensitive (effective) or there are chemos that are resistant (ineffective) to each and every "individual" cancer patient, not populations. There are chemos that share across tumor types. The functional profiling platform has the unique capacity to identify all of the operative mechanisms of response and resistance by gauging the result of drug exposure at its most important level: cell death. Finding what targeted therapies would work for what cancers is very difficult. A lot of trial-and-error goes along trying to find out. However, finding the right targeted therapies for the right "individual" cancer cells can be improved by cell-based assays, using functional profiling. Identifying DNA expression of individual proteins (that measure of RNA content, like Her2, EGFR, KRAS or ALK) often examine only one component of a much larger, interactive process. Gene (molecular) profiling measures the expression only in the "resting" state, prior to drug exposure. There is no single gene whose expression accurately predicts clinical outcome. Efforts to administer targeted therapies in randomly selected patients often will result in low response rates at significant toxicity and cost. Functional profiling measures proteins before and after drug exposure. It measures what happens at the end (the effects on the forest), rather than the status of the individual trees. Molecular profiling is far too limited in scope to encompass the vagaries and complexities of human cancer biology when it comes to drug selection. The endpoints of molecular profiling are gene expression. The endpoints of functional profiling are expression of cell death (both tumor cell death and tumor associated endothelial [capillary] cell death). In testing for all "known" mutations, if you miss just one, it may be the one that gets through. And it's not just only targeted drugs that may be effective as first-line treatment on your "individual" cancer cells. Cancers share pathways across tumor types. Targeted treatments take advantage of the biologic differences between cancer cells and healthy cells by "targeting" faulty genes or proteins that contribute to the growth and development of cancer. Many times these drugs are combined with chemotherapy, biologic therapy (immunotherapy), or other targeted treatments. Clinicians have learned that the same enzymes and pathways are involved in many types of cancer. However, understanding targeted treatments begins with understanding the cancer "cell." In order for cells to grow, divide, or die, they send and receive chemical messages. These messages are transmitted along specific pathways that involve various genes and proteins in the cell. 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. Targeted therapies are typically not very effective when used singularly or even in combination with conventional chemotherapies. The targets of many of these drugs are so narrow that cancer cells are likely to eventually find ways to bypass them. Physicians may have to combine several targeted treatments to try an achieve cures or durable responses for more complicated tumors like those that occur in the breast, colon and lung. These targeted therapies produce limited results because they can help a relatively small subgroup of cancer patients. But when they work, they produce very good responses. With targeted therapy, the trick is figuring out which patients will respond. Tests to pinpoint those patients cannot be accomplished with genetic testing. All the gene amplification studies, via genetic testing, tell us is whether or not the cancer cells are potentially susceptible to a mechanism/pathway of attack. They don't tell you if one drug is better or worse than another drug which may target a certain mechanism/pathway. Cell-based functional analysis can accomplish this. The cell is a system, an integrated, interacting network of genes, proteins and other cellular constituents that produce functions. You need to analyze the systems' response to drug treatments, not just one target or pathway, or even a few targets/pathways. Quote Link to comment Share on other sites More sharing options...
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