Testing cancers for prognosis


I am more optimistic about what genetic testing might mean for patients who have been diagnosed with cancer. The more we learn about the genes that control cancer cell growth, the better able we will be to predict which cancers will grow fast and which will not. We'll also be better placed to distinguish pseudodisease from aggressive cancer. And we'll be better able to predict the host response and tailor therapy to the specific disease.

Recently, for example, researchers examined some 5,000 genes in each of 78 early breast cancer cases. Because these specimens had been collected years earlier, the researchers knew which breast cancers ultimately went on to produce distant metastases (that is, which ones were aggressive). They found that a molecular profile of 70 genes could accurately predict which cancers were aggressive and which were not. When they tested their approach on a new set of 19 cancers, moreover, it did wonders.

This is a tremendous step forward. I don't want to downplay the significance of findings such as these. Genetic testing of early cancer will help us predict which cancers need aggressive treatment, which ones need standard treatment, and which ones can be watched.

But it will never be perfect. Tumor markers and genes can provide probabilities, but not definitive answers. Consider the research I just described. If the molecular profile diagnosed a cancer as aggressive, 70% of times it was right but 30% of times it was wrong. And if the profile diagnosed a cancer as not aggressive, 90% of the time it was right and 10% of times wrong.

Even with the most complete information, the "right answer" may not be obvious. "You have a . cm growth that, based on its gene expression profile, has just one 10% chance of metastasizing within the next five years." That's important information. But now what should you do?

RESEARCH THAT REALLY Must be DONE

Maybe we are planning on cancer the wrong manner. Medicine's approach to date has focused on finding cancer as early as possible and acting as quickly as possible. But you now know there's a price for getting too far in front of the game: the price of unnecessary worry, unnecessary treatment, finding too much cancer, disagreement about who has cancer, and distraction from more pressing concerns.

Cancer is a dynamic process in which many things must go wrong. It may be imagined as a cascade of events, in which numerous opportunities exist to stop the process.

The process starts when a cell experiences some genetic damage: a DNA mutation. In fact, this sort of damage is believed to be a very common occurrence. Most the time, the mutation is repaired but sometimes it's not. Then when there is a second mutation and another repair failure, the cell may become irrevocably damaged. Most of the time these atypical cells self-destruct or are recognized by the body's defense system but sometimes they start to replicate and go unchecked.

As collections of abnormal cells form, the host's immune response is usually activated but again, sometimes it's not. So while we all have DNA mutations, only a few of us die from cancer. One step does not necessarily lead to another.

Yet we often act as if it does. Our current approach to cancer diagnosis and intervention seems to assume that the process proceeds in lockstep. Pathologists are asked to create a judgment based on a few cells, a judgment that may initiate a chain of aggressive reactions.

But the pathologist is trying to predict the appearance of a dynamic process (spreading throughout the body, ending in death) based on a static observation (the look of cells under the microscope) early in the process. What we really need to learn more about is the dynamics of early cancer. A few of the genetic testing of the cancers themselves can help move us in this direction. But using genetic testing also calls for a heretical approach: waiting and simply watching.

We know that some abnormalities that meet the cellular definition of cancer won't progress and that some small abnormalities on a scan today may not be there tomorrow. The best way to sort these cases out may be to do research on a more dynamic diagnostic process one that involves repeated measurements over time.

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This article was sent to us by: Fiona Landman at 08152010

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