WEDNESDAY, March 14 (HealthDay News) -- By analyzing gene mutations in patients with acute myeloid leukemia, researchers were able to more accurately predict which ones had the best chances of going into remission, and which ones would respond well to standard treatments or needed more aggressive treatment.

Doctors from Memorial Sloan-Kettering Cancer Center in New York City analyzed 18 genes from about 500 patients with acute myeloid leukemia (AML). AML is a cancer of the bone marrow, or the soft tissue that forms blood cells.

The patients had previously taken part in a clinical trial for a chemotherapy drug, daunorubicin, and researchers knew how everyone had fared in that study.

In the new analysis, the scientists used the latest gene-sequencing technology to determine what mutations were present in the cancer cells of the patients, and whether the presence of those mutations predicted how well people did.

They found that certain combinations of mutations were associated with both better or worse chances of survival, and that those genetic predictors could be used to determine whether patients would respond to the standard dose of daunorubicin or whether they should receive a higher, more aggressive dose of the drug.

Currently, some cancer hospitals already do a limited genetic analysis in leukemia patients to look for three mutations that are associated with a low or high risk of relapse, experts explained.

But about 60 percent of people fall into the intermediate category, said senior study author Dr. Ross Levine, an associate member in the Human Oncology and Pathogenesis Program at Sloan-Kettering. That leaves oncologists with a lot of uncertainty about how aggressively to treat those patients and what to tell them about their prognosis.

"If you know patients have a high chance of cure, you would pursue a standard therapeutic route," Levine said. "If you have a patient with a low chance of cure, you might consider more aggressive or investigational therapies."

Using the information from the more extensive analysis, about half of the patients who were in the intermediate risk could be put into a low- or high-risk category, Levine said.

"What we found was by studying the DNA of patients with leukemia and classifying all 500 patients, you could identify a set of mutations, which allows us to more accurately separate those at high risk of relapse, at intermediate risk of relapse and at low risk of relapse," Levine said. "Specifically, risk stratification with more extensive mutational profiling better predicts outcome than current classification schema."

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