Biomarkers Found That Predict Lung Cancer Patient Response To Therapy
Researchers at UCLA’s Jonsson Cancer Center have discovered biomarkers that predict which patients with advanced non-small cell lung cancer will respond to a combination treatment of the anti-inflammatory drug Celebrex and the growth factor receptor blocker Tarceva.
This entry was posted on Thursday, January 31st, 2008 at 8:51 am and is filed under Research, Non-Small-Cell. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.
At 10:50 pm on February 24th, 2008 Gregory D. Pawelski said:
Predicting Lung Cancer Patient Response To Therapy
The drug discovery model over the last few years has been limited to one gene (or protein), one target, one drug. 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.
Genetic profiles are able to help doctors determine which patients will probably develop cancer, and those who will most likely relapse. However, it cannot be suitable for specific treatments for “individual” patients.
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. Targeting one pathway may not be as effective as targeting multiple pathways in a cancer cell.
Another challenge is to identify for which patients the targeted treatment will be effective. Tumors can become resistant to a targeted treatment, or the drug no longer works, even if it has previously been effective in shrinking a tumor. Drugs are combined with existing ones to target the tumor more effectively. Most cancers cannot be effectively treated with targeted drugs alone.
The cell “function” methodology, which exists today and is not hampered by the problems associated with gene expression tests. That is because they measure the net effect of all processes within the cancer, acting with and against each other in real time, and it tests living cells actually exposed to drugs and drug combinations of interest.
The key to understanding the genome is understanding how cells work. The ultimate driver is a “functional” assay (is the cell being killed regardless of the mechanism) as opposed to a “target” assay (does the cell express a particular target that the drug is supposed to be attacking). While a “target” assay tells you whether or not to give “one” drug, a “functional” assay can find other compounds and combinations and can recommend them from the one assay.
The core of the functional assay is the cell, composed of hundreds of complex molecules that regulate the pathways necessary for vital cellular functions. If a “targeted” drug could perturb any one of these pathways, it is important to examine the effects of the drug within the context of the cell. Both genomics and proteomics can identify potential new therapeutic targets, but these targets require the determination of cellular endpoints.
Cell-based “functional” assays are being used for screening compounds for efficacy and biosafety. The ability to track the behavior of cancer cells permits data gathering on functional behavior not available in any other kind of assay.
Source: Cell Function Analysis
At 2:31 am on May 23rd, 2008 vit said:
The drug discovery model over the last few years has been limited to one gene (or protein), one target, one drug. 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.
http://avemar.world-cancer.net