Gene Expression Profile Predicts Leukemia Relapse After Treatment

NEW YORK (Reuters Health) - Differential expression of a relatively small number of genes is associated with resistance to the drugs commonly used to treat childhood acute lymphoblastic leukemia (ALL), investigators report in The New England Journal of Medicine for August 5th.

"Up until now, we've gotten an 80% cure rate for patients with ALL by a lot of smart empiricism," senior investigator Dr. William E. Evans told Reuters Health. "This new research represents one of several new strategies being used to bring modern technology of the human genome to bear on the last 20% of children who are not being cured."

"Essentially," he continued, "we took a genome-wide approach to ask the question, what are the differences in leukemia cells of patients whose cells are resistant to...drugs versus those that are sensitive?"

Dr. Evans, at St. Jude Children's Research Hospital in Memphis, Tennessee, and his team tested leukemia cells from 173 newly diagnosed children for sensitivity to vincristine, prednisolone, asparaginase, and daunorubicin. After a median follow-up of 4.2 years, 132 patients remained in continuous complete remission, 40 had relapsed, and one patient developed a second cancer.

The researchers then subjected the cells to microarray analysis to determine gene expression patterns that could be used to predict treatment outcome. From a set of 14,500 probes, they found 124 unique genes and 28 complementary DNA clones that were differentially expressed in sensitive and resistant cells, only three of which had been previously identified.

A high combined gene-expression score indicating resistance to all four drugs was associated with a significantly increased risk of relapse (p = 0.001).

In multivariate analysis that included patient age, ALL lineage and genetic subtype and white cell count at diagnosis, the hazard ratio for relapse was 3.0 for those with a combined drug-resistance gene-expression score of 5.58 or higher compared with those with a score of 4.7 or lower, which indicated sensitivity (p = 0.027).

"This indicates that the expression of genes associated with drug resistance has an independent influence on the outcome of treatment in ALL," the authors note.

Dr. Evans' group confirmed their results in an independent population of 98 ALL patients treated with the same medications. The multivariate analysis showed a high combined drug-resistance gene-expression score associated with a higher probability of relapse, hazard ratio of 11.85, compared with a low score (p = 0.019).

In the near future, Dr. Evans suggested, physicians may routinely perform gene expression profiling on patients newly diagnosed with ALL. "If a patient has a signature suggesting resistance to drug A, maybe we should focus on drugs B, C and D, and downplay drug A," he said.

In addition, "we've identified 152 potential new drug targets" that may be used to find new drugs to convert resistant leukemia cells to sensitive leukemia cells, he added.

These drugs "may not be anti-leukemic per se, but rather drugs to modulate sensitivity of leukemia cells to existing anti-leukemia drugs."

His group has placed this primary data in a publicly available database "so that anyone who wants to download and analyze it further can do that," he said. The URL is

These new findings suggest that "gene-expression profiles could be used to alter therapy instead of the more cumbersome method of in vitro sensitivity testing," Dr. Naomi J. Winick, at the University of Texas Southwestern Medical Center in Dallas, and her colleagues comment in a related editorial.

Dr. Winick's group also predicts that gene-expression patterns will help "stimulate the development of alternative treatment strategies, targeted to those with resistant disease identified at diagnosis."

Source: N Engl J Med 2004;351:533-542,601-603. [ Google search on this article ]

MeSH Headings: Behavioral Sciences : Cytological Techniques : Behavioral Disciplines and Activities : Drug and Narcotic Control : Drug Screening : Drug Screening Assays, Antitumor : Health Care Economics and Organizations : Evaluation Studies : Genetic Techniques : Health Occupations : Health Services Administration : Legislation : Legislation, Drug : Investigative Techniques : Organization and Administration : Pharmacy Administration : Quality of Health Care : Social Control, Formal : Social Sciences : Sociology : Technology : Technology, Industry, and Agriculture : Technology, Medical : Allied Health Occupations : Drug Approval : Health Care Quality, Access, and Evaluation : Health Care Evaluation Mechanisms : Gene Expression Profiling : Analytical, Diagnostic and Therapeutic Techniques and Equipment : Anthropology, Education, Sociology and Social Phenomena : Biological Sciences : Health Care : Psychiatry and Psychology : Technology, Food and Beverages

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