Biomedical Engineering Reference
In-Depth Information
A major challenge of translating information from the research community into
useful biomarker targets and biomarker assays is that all too often publications
contain little or no validation data and shockingly sometimes no actual flow cytometry
data. Without the context of method validation, in particular, precision assessments, it
is not possible to establish if the changes in cellular subsets reported are valid or an
artifact of method variability. Even though pharmaceutical scientists will perform the
appropriate “Fit-for-Purpose” method validation prior to testing clinical specimens,
there is an associated risk when the initial decision to pursue a biomarker is based on
information generated with poorly validated methods [35]. Without a validated
method, it is not possible to know if the method is capable of distinguishing changes
that are statistically significant. Moreover, proper assay development and validation
of flow cytometric methods is more time consuming and expensive compared to the
more commonly used biomarker platforms such as immunoassays.
Another challenge is that with the exception of the major lymphocyte subsets
(T cells, CD4 T cells, CD8 T cells, NK cells, and B cells), there are no reference
intervals for the lymphocyte subsets commonly evaluated. Reference intervals can be
used to assess clinical improvement. For example, LDL cholesterol has been
established as a possible marker for cardiovascular risk. LDL levels can be monitored
both to assess medical treatment of atherosclerosis and to serve as an indicator of heart
attack or stroke risk; when values are within optimal range, treatment is considered
successful. Similarly in HIV, CD4 counts are routinely monitored to assess treatment
efficacy. With a validated method, it is possible to statistically determine if changes
are correlated with treatment; however, without reference values in healthy and
diseased populations, it is difficult to understand if the changes are clinically mean-
ingful. Analysis of the more exploratory PD biomarker data raises many questions
that contribute to the difficulty in interpreting the data. What does a change indicate?
What does the lack of a change indicate? How should this information affect decision
making in the clinical development of the compound?
Sampling is also a challenge when monitoring the cellular components of the
human immune system. By and large, sampling is limited to the peripheral blood that
is a more accessible, less invasive sampling site than the secondary lymphoid tissues
(bone marrow, lymph node, and spleen) or inflamed tissue (intestine, synovium)
where specific immune responses are generated. Testing is conducted under the
assumption that the peripheral blood represents a true snapshot of the immune
activation and inflammatory responses elsewhere. For example, B-cell depletion is
monitored in the periphery, yet the goal is to deplete the B-cell population in the lymph
nodes where most of the cells reside. Similarly, Treg cells act in tissues to control
established inflammation and it is unclear if their levels in the peripheral blood are
reflective of overall levels and activity.
Perhaps, the most challenging aspect of measuring cellular components of the
immune system is the lack of a consensus phenotype for most commonly evaluated
cell types [36]. In many studies where flow cytometric analysis was “limited” to four-
or five-color detection, CD4 and CD8 T-cell subsets were evaluated by two additional
parameters, CD45RA (or CD45RO) and CD62L or CD27 or CCR7 in order to identify
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ve and memory T cells. More recently, labs equipped with the newer instruments
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