I'd love to start a thread here with examples of successful biomarkers for either 1) human disease or 2) drug activity, and any supporting data in animal models.

[This may require some clarification on what we mean by "biomarker"... but perhaps that is a topic for another thread]

Anyone got any good examples?

pw_18 said:

I'd love to start a thread here with examples of successful biomarkers for either 1) human disease or 2) drug activity, and any supporting data in animal models. [This may require some clarification on what we mean by "biomarker"... but perhaps that is a topic for another thread] Anyone got any good examples?

This is what I found as the most generalized description for Biomarkers:
Substances sometimes found in an increased amount in the blood, other body fluids, or tissues and which can be used to indicate the presence of some types of cancer.
lymphomation.healthology.com/focus_article.asp
What do you exactly mean by successful?

Roshan,
Your general definition is a good start, but there's no reason to limit biomarkers to cancer, as opposed to other diseases. One way to think about a "successful" biomarker would be something that is elevated in blood in disease, and which can be lowered by drug treatment (e.g. C-reactive protein for heart disease).

Another way to look at it is to look at what biomarkers are affected by drug treatment, with or without the presence of disease (e.g. in normal animals/patients). This would be a so-called "surrogate marker" for drug activity, rather than one for disease state.

The key here, from a drug development point of view, is to find a biomarker of drug activity that can be measured BEFORE clinical efficacy is observed. This way, instead of running a long clinical trial, you could do a short one to make sure that your biomarker is affected by drug treatment, then dive in and do the whole clinical study with an efficacy endpoint.

Does that make a little more sense?

PW

At my last company we used a similar approach to screening herbal extracts prepared using different techniques to determine which ones would be the most effective. We used both actual animals and cell lines. For example, we looked for increases in Tumor Necrosis Factor in Mouse Macrophages treated with different immune system stimulants, changes in cortisol levels in mice treated with different adaptogens, neurotransmitter reuptake inhibition for Mood elevators etc...

It seems this approach could lead to some poor candidates being selected for futher analysis. Of course, any technique has signal/noise challenges.

Here's a silly example to make the point. Put a Morpholino oligo targeting TNF-alpha into a diseased cell. The level of TNF-alpha decreases, but that doesn't mean there is any change in disease state, just that you've suppressed translation of the marker.

Surely there are many compounds which change the state of putative biomarkers without having therapeutic value.