Myeloid Leukemia

238 Kohlmann et al.
the integrity of the starting RNA, efficiency of first-strand cDNA synthesis, and/
or IVT of cRNA. As recommended by the manufacturer, there is no single threshold
cutoff to assess sample quality. Routinely, most users refer to a threshold
ratio of less than 3.0 for the most common tissues.
9. As a simple means to relate signal values between arrays, a set of 100 maintenance
genes is represented on recent expression microarrays (probe set identifiers
from 200000_s_at to 200099_s_at). These normalization controls were
originally identified from a data set of HG-U95Av2 hybridizations representing
a large number of different tissues and cell lines. The data on these probe sets
shared the common characteristic of consistently being called present (P) while
exhibiting relatively low signal variation over different sample types (23). Therefore,
when scaling data between the HG-U133A and B arrays, an algorithm
against these normalization controls, which are represented on both arrays, avoids
a skewing of the data and provides an improved alternative tool to global scaling.
Specific mask files for these probe sets are available from the manufacturer
(www.affymetrix.com). Scaling factors, i.e., the multiplication factor applied to
each signal value on an array, will vary across different samples, and there are no
set guidelines for any particular sample type. However, if they differ by too much
within a set of experiments, this indicates wide variation in the underlying image
files, and therefore the analyzed data should be treated with caution.
5. Commentary
The introduction of microarray technology has been a major step towards
the comprehensive biological characterization of various diseases, and clearly
will allow the identification of yet unknown subentities and even new entities.
In particular, it has become clear that distinct cytogenetically defined subtypes
in AML carry highly specific gene expression profiles, which can be used to
identify these subtypes based on microarray analyses with very high accuracy
(24–27). Therefore, it is expected that the routine application of microarrays
will significantly improve molecular diagnostics in leukemia and will provide
deep insights into the pathogenetic alterations of malignant and nonmalignant
hematopoietic cells. In addition, these comprehensive data are anticipated to
allow the identification of prognostically relevant markers as well as diseasespecific
markers that can be applied for programs of monitoring minimal
residual disease. Of highest clinical relevance is the capability of microarray
approaches to identify pathogenetically essential structures and alterations that
can be targeted by future drugs, which hopefully will lead to improved management
of these diseases. The accurate diagnosis and subclassification of leukemias
is currently based on a comprehensive combination of various methods,
including cytomorphology, cytochemistry, multiparameter immunophenotyping,
cytogenetics, fluorescence in situ hybridization, and quantitative
and non-quantitative molecular genetics, which are costly, time-consuming,