Biomedical Engineering Reference
In-Depth Information
inflammatory events, including even autoimmune diseases. Furthermore, CRP is a
predictive marker of future risk of CVD. There is no defined clinical cutoff value,
but concentration ranges for risk prognosis are suggested: CRP concentrations
below 1 lg/ml mean low risk, concentrations in the range 1-3 lg/ml indicate
intermediate risk, and concentrations in the range 3-15 lg/ml show a high risk
[
103
]. Owing to the comparatively high concentrations in blood, CRP is one of the
most commonly used model analytes for testing and demonstrating the perfor-
mance of a biosensor. Therefore, numerous approaches with all kinds of transducer
principles and biosensor coatings have been reported. CRP biosensors were
recently reviewed in connection with other cardiac biomarkers, [
103
].
Furthermore, CRP was detected in human serum by means of TIRF using two
test formats, i.e., sandwich assay and binding inhibition assay. Samples were
diluted 1:100. The working range of the sandwich assay was 0.044-2.9 lg/ml
(detection limit 0.13 lg/ml), and the working range of the binding inhibition assay
was 0.13-22.9 lg/ml (detection limit 0.055 lg/ml). These values represent con-
centrations in undiluted serum, i.e., both methods allow the detection of CRP in
the low/intermediate risk range [
108
]. An impedimetric biosensor using a so-called
biogenic nanoporous silica membrane as a layer for each electrode was designed
for direct and label-free detection of CRP and another cardiovascular biomarker,
myeloperoxidase, in human serum. In human serum samples, for both proteins a
large dynamic range from 1 pg/ml to 1 lg/ml was obtained [
109
]. Admittedly, in
the case of CRP, quantification of concentrations below 1 lg/ml is usually not
required. However, in this case sample dilution for minimizing the potential risk of
nonspecific adsorption could be performed without further ado.
3.3 Detection of Cancer Biomarkers
3.3.1 Cancer Diagnostics
Besides CVD, cancer is globally a major cause of death [
110
]. There are more than
200 cancer-related diseases and all have one thing in common, i.e., an early
detection and classification is crucial for a positive outcome for the patients [
4
,
7
].
Since 1958, tumor staging has been standardized via the TNM system, which
based on information about tumor size or depth (T), lymph node spread (N), and
the presence or absence of metastases (M) [
3
,
111
]. This anatomical-based staging
system has increasingly been complemented by molecular markers to allow further
classification of the tumor into subsets, targeting improved diagnosis, prognosis, or
prediction of therapy [
3
]. This includes monitoring of cancer treatment or
remission cycles, which is easier to perform if serum biomarkers can be used
instead of tissue-related biomarkers [
1
,
13
].
In the case of cancer, efficient diagnosis demands the detection of more than
one single biomarker. Instead, a complete marker profile (''molecular signature'')
has to be determined, both on the genomic and on the proteomic level [
3
,
4
],
