news Classifying cancer with microarrays Despite the strides made in cancer research, the classification of the disease still depends primarily on the morphological appearance of tumors. However, this approach can be misleading because morphologically similar cancers may have very different pathologies. In addition, morphology does not always reveal differences in subgroups—an important step in finding the most effective treatment. Now, a solution is being offered by T. R. Golub, Eric S. Lander, and coworkers at the Whitehead Institute, the Massachusetts Institute of Technology,
Genes distinguishing acute myeloid leukemia (AML) from acute lymphoblastic leukemia (ALL). (Adapted with permission. Copyright 1999 American Association for the Advancement of Science.)
the Dana-Farber Cancer Institute, Harvard Medical School, the St. Jude Children’s Research Hospital, and Ohio State University. The researchers have developed a generic approach to cancer classification that uses DNA microarrays to monitor gene expression. Unlike previous microarray studies of cells, the researchers did not use homogeneous cell cultures but samples taken from 38 patients with several forms of acute leukemia. The researchers first developed a system for cancer classification by screening 6817 genes to find those that correlated with known morphological indicators of cancer. From the 1100 genes that had especially high correlation, they selected a subset of “informative genes” and used them to divide the samples into two categories. For each sample, a “predictive
All-in-one imaging and sensing Following chemical dynamics within living cells has greatly improved our understanding of how cells respond to various stimuli. Traditionally, such measurements have been performed either on bulk samples, which do not account for cell-tocell variation, or on individual cells, which is very time-consuming. David R. Walt and Karri L. Michael of Tufts University have developed a technique that combines the best of both worlds—the simultaneous analysis of multiple cells with single cell resolution. At the heart of their technique is a microarray sensor, which is capable of both imaging and chemical sensing. The sensor was created by immobilizing a thin, analyte-sensitive polymer layer on the end of an optical imaging fiber and coupling the fiber to an array detector (e.g., CCD camera). The researchers demonstrated how the sensor measures localized chemical dynamics in real time by monitoring the intracellular increase in pH that occurs when a sea urchin egg is fertilized. In this case, the imaging fiber was coated with a thin, pH-sensitive polymer layer. Using white-light imaging, they obtained morphological information, such as the egg’s size, shape, and location. By switching to fluorescence imaging, they monitored surface chemical events (e.g., release of H+) with 2- to 4-µm spatial resolution. The researchers also successfully measured responses from multiple cells distributed over tens of thousands of square micrometers. The microarray sensor technique has several advantages over existing methods, including the ability to make measurements under physiological conditions without penetrating the cell. In addition, the sensor does not require precise positioning and is flexible, allowing experiments to be perCombined imaging and chemical sensing technique. (Adapted with formed at a distance from the microscope and perhaps ultipermission. Copyright 1999 Academic Press.) mately in vivo. (Anal. Biochem. 1999, 273, 168–178)
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news Redesigning the electric cell strength”—a measure of confidence in the classification—was calculated. When a blind study was done, 36 of the 38 bone marrow samples could be classified as either acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) with high confidence, and these results agreed with independent diagnoses by physicians. Similar results were obtained when a mixture of bone marrow and blood samples was used. Interestingly, the results were not strongly dependent on the number of informative genes chosen. Sets of 10–200 genes yielded comparable results. However, the predictive strengths for samples obtained from one laboratory were consistently lower, and the researchers speculate that this was due to the use of a different sample preparation protocol. The researchers also devised an algorithm to “discover” classes of cancer. They clustered tumors using “selforganizing maps”—a technique that identifies centroids around which data tend to aggregate. When two classes were specified, the groupings corresponded closely to the ALL/AML division. To evaluate the method for cases in which the diagnoses cannot be confirmed easily, the researchers ran the clusters through the classification algorithm, reasoning that the predictive strengths would always be high if the clustering was accurate. Good results were obtained. In a more rigorous test, four classes were specified, yielding clusters that corresponded to four known clinical subgroups. After application of the classification algorithm, two of the clusters were collapsed, yielding three final groups. From these results, the researchers concluded that the clustering and classification steps can be used iteratively to determine classifications. The method even revealed one case in which cancer had been misdiagnosed in the clinic. (Science, 1999, 286, 531–537)
When it comes to analyzing a wide mass range of ions by MS, mass spectrometers with magnetic cells usually have an advantage over those with electric cells, such as the Paul trap. That is because in an electric cell the “crosstalk” between the high-frequency storage field and the detector electrodes makes wideband ion analysis difficult. M. Aliman and A. Glasmachers of the University of Wuppertal (Germany) introduce an electrical quadrupole ion trap with a redesigned Paul trap, which significantly reduces crosstalk. The new design allows even the weak signals of an ion-induced charge to be detected for use in Fourier transform MS. The new cell retains the end-cap geometry of the Paul trap, but it replaces the ring electrodes with a cylindrical series of electrodes (see figure). The resulting geometry is a cylinder with hyperbolic top and bottom. Compared with the Paul trap, the quadrupole field remains the same, but the crosstalk current plummets by a factor of 1/27. (A compensation technique balances out the remaining crosstalk, which allows a low-noise charge amplifier to be used with this new design.) The design was tested by collecting a single-shot frequency spectrum (calculated with a fast Fourier transform) of diethylether at 5 x 10–6 mbar and frequency and mass spectra of argon at 10–7 mbar. Moreover, because the massdependent frequencies of ion motion relative to the z axis are detected, the method is nondestructive. Thus, the authors were able to remeasure ions from a single ionization phase three times with an efficiency of 70%. The authors say that they plan to upgrade the new cell instrument and further test its capabilities. (J. Am. Soc. Mass Spectrom. 1999, 10, 1000–1007)
Ring out the old. (a) Paul ion trap and (b) new trap. (Adapted with permission. Copyright 1999 American Society for Mass Spectrometry.)
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