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Researchers refine methods of predicting outcome in pediatric cancer cases
By Lori Williams

Making the right prediction on how patients with cancer will respond to therapy takes on added significance when those patients are children.

Pediatric oncologists or cancer specialists don't want to order any treatment that may not be necessary because the potential harmful side effects of those therapies could crop up later in the lives of the youngsters they treat. Determining which children will do well without aggressive treatment and which children might perish if it is withheld is a daunting prospect. Recently, however, the solution is coming closer to reality because of work done on the genomics of malignant disease by researchers such as Ching Lau, MD, PhD, at Baylor College of Medicine.

Lau and his cancer genomics research team at Texas Children's Cancer Center are seeking to develop methods of predicting which brain tumors need more aggressive treatment than others.

"One of the major obstacles in treating brain tumors in children is that the brain is still undergoing rapid development and is vulnerable to toxicities from treatments such as radiation or chemotherapy," said Lau, an assistant professor of pediatrics at Baylor. "We are concerned about the potential impact of treatment on normal brain tissue."

Lau and his team are analyzing the genes specific to individual medulloblastoma tumors to determine which can predict the outcome. Medulloblastoma is the most common form of malignant brain tumor in children. If the genetic analysis of the tumor shows that the child likely will have a good outcome, then more aggressive treatment, such as radiation, could be reduced.

"But, unfortunately, in certain cases if you don't use very aggressive therapy up front, you lose the chance of curing the disease," said Lau. "Being able to make use of new genomic technologies to identify which children can be successfully treated while being spared long-term side effects of aggressive therapy, such as growth, hearing, cognitive and emotional problems, will be a real breakthrough."

This approach will help identify those tumors that are the most aggressive and require the more intense therapies.

"For some children, the price to pay in terms of toxicity may be high but may be necessary if we are to have a chance to save their lives," he said.

Lau's team was part of a national pilot study on genetic profiling of medulloblastoma. Their initial work was published in the journal Nature in January of this year. Efforts are now in progress to develop better ways to analyze medulloblastoma, as well as other brain tumors, such as ependymoma, and bone tumors.

Lau predicts that using information from the rapidly developing field of human genomics will eventually make the genetic profiling of all types of tumors possible.

"In the next 10-15 years, treatment for patients with cancer is going to be drastically different. Not only will we be able to predict correctly how a tumor will respond to treatment, but also how the therapy will affect the rest of the body, " he said. "If you're able to predict outcome, you can customize the treatment for each individual so that the patient will have the best chance of survival while experiencing the least amount of unnecessary side effects."

"The field of cancer genomics is new, but is developing very rapidly. The Human Genome Sequencing Project brought forward the information that made it possible to quickly analyze specific genes."

Lau and his team's first efforts centered on expression profiling, that is, obtaining a profile of all the genes expressed by a specific tumor. With this "molecular signature" of the tumor, the researchers then eliminated genes one by one to come up with a set of genes that they thought could predict outcome. Analyzing these genes, they were able to correctly predict the tumor's response to therapy in all 60 cases tested.

Lau said the next step will be to use another technique to analyze these tumors. Instead of looking at what genes are expressed or not expressed, as was the case in the first effort, this round will look at the structural alteration of the genome of these tumors.

"Previously, we were working with RNA. Now, we want to take a step backwards and work with DNA," Lau said. "In trying to select the genes from the expression profiling that best predicts outcome, we were confronted with too many candidates."

"So, now we are imposing more rigorous criteria in selecting these genes -- disregarding the expression," he said. "We're going to see if these genes are structurally altered because common sense would say if a gene is both structurally altered and abnormally expressed, there's a better chance it would play a role in controlling the biology of the tumor."

"Ten years ago, this was just a dream."

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