New DNA chip method could improve cancer diagnosis

One of the biggest challenges in cancer treatment is choosing the right regimen for a given patient. Treatment strategies work differently for different tumors. In choosing effective treatments with minimal side effects, oncologists rely heavily on biopsy reports that diagnose the tumor type involved. However, even today, cancer diagnosis is done the old-fashioned way: by observing morphological changes in biopsies under the microscope. The method suffers from serious limitations because cancer cells that look similar under the microscope can follow different clinical courses and respond differently to therapy.

Now, in a new study reported in Friday's Science, a team of Whitehead-led researchers reports the first systematic and objective approach for identifying and classifying tumor types. This approach exploits the hot new technology of DNA microarrays--DNA chips that can analyze the activity of thousands of genes at a time--and could be used in the future to accurately diagnose cancer subtypes and also to predict clinical outcomes. Moving cancer diagnosis away from visually based systems to such molecular based systems is a major goal of the National Cancer Institute.

In the study, scientists used a DNA chip to examine gene activity in bone marrow samples from patients with two different types of acute leukemia--acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). Then, using a computer algorithm, also developed at the Whitehead, they identified signature patterns that could distinguish the two types. When they cross-checked the diagnoses made by the chip against known differences in the two types of leukemia, they found that the chip method could automatically discover the distinction between AML and ALL without previous knowledge of these classes.

"These results demonstrate the feasibility of cancer diagnosis based solely on gene expression and suggest a general strategy for discovering new subtypes of cancer, indepen

Contact: Seema Kumar
Whitehead Institute for Biomedical Research

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