Biology Reference
In-Depth Information
BMT. However, this endeavor will be expensive and might include some
variation in collection and interpretation of clinical data. Such a multicenter
prospective trial validation is important because the algorithm should take
into account the variability between centers (center effect) and the indi-
vidual risks related to known risk factors, such as age, HLA match, donor
source (particularly cord blood), and conditioning regimen, including T-cell
depletion (
in vivo
or
in vitro
). The statistical model should use the methods
discussed above. Ideally, we will be able to develop a single national Clini-
cal Trial Network formula to predict a patient's risk for aGVHD, allowing for
innovative, cutting-edge personalized medicine. The ideal formula will be
as simple as possible. In the best-case scenario, a single marker at a single
time point and few transplantation risk factors (e.g., conditioning intensity,
cord blood source, and use of T-cell depletion) would be investigated. Next,
a trial of preemptive therapy for aGVHD using the formula would be initi-
ated. Therapeutic approaches for aGVHD have largely been limited to the
nonspecific targeting of effector cells. As a result, steroids remain the first-
line treatment for patients presenting with aGVHD symptoms. Biomarkers
represent promising targets for new therapeutics. In addition, we propose
that the discovery of aGVHD-specific drugs based on biomarkers will target
the appropriate effector T cells to both increase efficacy and lower toxicity.
This approach represents the first step in a continuum of research that is
expected to lead to the development of pharmacologic strategies to specifi-
cally treat GVHD. One direct outcome of this proposal will be the establish-
ment of clinical trials using both biomarkers for risk stratification and new
drugs for treatment in high-risk populations.
474
Conclusions
Proteomics is a revolutionary field that includes detection technologies for
proteins, molecules that are the most proximal to the real-time pathophysi-
ology of alloreactivity. In a short time, the use of proteomics has led to the
identification of novel mechanisms of allogeneic HSCT, which are unlikely
to have been discovered by traditional hypothesis-driven research. A prom-
ising proteomics approach is to use protein biomarkers in risk stratification
to better employ current disease treatment modalities. Furthermore, the
biomarker findings presented in this chapter offer the potential for explor-
ing targeted therapeutics. Unlike genes, protein levels may be influenced
by several post-transcriptional modifications and other factors, such as the
cytokine milieu. The principal barrier that must be circumvented is the vali-
dation of biomarker concentrations in various types of allo-HSCT settings
[e.g., conditioning intensity, donor sources (particularly cord blood), T-cell-
depleted grafts]. Achieving this aim will require a much larger validation
study, ideally in a multicenter prospective trial. Once an algorithm for each
setting is established, personalized medicine will be possible.
References
[1] Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred
definitions and conceptual framework. Clin Pharmacol Ther 2001;69:89-95.
[2] Mowat A, Socie G. Intestinal graft-vs.-host disease. In: Ferrara JLM, Cooke KR, Deeg HJ,
editors. Graft-vs-Host Disease. 3rd ed. New York: Dekker; 2004. p. 279-327.
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